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NIGERIAN JOURNAL

OF

SOIL SCIENCE

VOLUME 22 (1)

2012

ISSN – 1597 – 4488

Published by the Soil Science Society of Nigeria.

FUNDED BY EDUCATION TRUST FUND

NIGERIAN JOURNAL OF SOIL SCIENCE

Members of the Editorial Board

Editor-in-Chief Prof. S. O. Ojeniyi

Deputy, Editor-in-Chief Prof. T. A. Okusami

Deputy, Editor-in-Chief Prof. D. O. Asawalam

Editor Dr. J. A. Odofin

Business Manager Prof. Akin Olayinka

Other Members Prof. U. C. Amalu

Dr. (Mrs.) F. I. Oluwatoyinbo

Prof. J. D. Kwari

Prof. A. S. Fasina

Editorial Assistants/ICT Prof. L. B. Taiwo

Dr. B. S. Ewulo

Ayo Ojeniyi

Officers of the Soil Science Society of Nigeria 2010-2012

President Prof. V. O. Chude

Vice President Prof. O. O. Agbede

General Secretary Prof. J. A. Adediran

Assistant General Secretary Prof. D. O. Asawalam

Treasurer Prof. B. A. Raji

Financial Secretary Prof. M. A. N. Anikwe

Editor-in-Chief Prof. S. O. Ojeniyi

Business Manager Prof. Akin Olayinka

Ex-officio Members Prof. I. E. Esu

Mr. C. O. Ezendu

Dr. (Mrs.) O. T. Ande

The Soil Science Society of Nigeria, founded in 1968, is a registered member of the

International Union of Soil Science.

The Society is responsible for the publication of the Nigerian Journal of Soil Science.

Membership of the Society is open to all persons (ordinary), institutions, private firms and

companies (Corporate) and Students interested in Soil Science.

Application forms and subscription for membership can be obtained from the Treasurer;

Prof. B. A. Raji, c/o Department of Soil Science, Ahmadu Bello University, Zaria, Nigeria.

Make all cheques payable to Soil Science Society of Nigeria. Purchase and payment for

journal should be directed to Business Manager at Department of Soil Science, Obafemi

Awolowo University, Ile – Ife, Osun State. Manuscripts should be sent to: The Editor-in-

Chief, Prof. S. O. Ojeniyi, Nigerian Journal of Soil Science, Department of Crop, Soil and

Pest Management, Federal University of Technology, Akure, Nigeria.

The Journal is Abstracted in: African Journal on line (ajoi) http//www.inasp.infolajoi.

ii

GUIDE TO CONTRIBUTORS

Contributors are invited from all parts of the world in any field of Soil Science and

should be original works which have not been published, accepted or submitted for

publication in any other journal.

Manuscripts should be written and typeset (in Ms Word) in English, typed in

quarto-size paper, double spaced and with wide margins. Three copies, the original and

two carbon copies should be sent to the Editor-in-Chief. In addition, diskette of the

accepted paper in MS Word will be required.

The major headings to use when preparing the manuscript should be Abstract,

Introduction, Materials and Methods, Results, Discussion, (or Results and Discussion) and

Acknowledgement, if any. Abstracts should be fully intelligible without reference to the

body of text and should not exceed 300 words. Sub-headings should be in italics.

Title headings and sub-headings should be concise and should be typed in small

letters. Titles should be followed by name(s) of author(s) and institutions. Tables should be

numbered in Arabic numerals and titles in small letters. Vertical lines should be avoided

and horizontal lines kept to a minimum,.

All lettering on diagrams and figures must be of good quality. Insert tables and

figures at appropriate places in text.

Reference should be arranged in alphabetical order of authors’ names at the end of

the paper. Each should be given in the following form: author’s name, year of publication,

title of paper, title of journal in full, volume number, first and last page e.g.

Braimah, A.K. (2000): Land evaluation for sorghum. Nigerian Journal of Soil

Science 12:4-11.

Kilmer V. J. (1990). Handbook of Soils and Climate in Agriculture. CRC Press,

Boca Ratio. In the text, reference should be given by the name of the author followed by the

year of publication in brackets. The letters, a, b, etc. should be used to distinguish between

papers published by the same author in a single year.

Authors are advised to consult latest issue of Nigerian Journal of Soil Science.

As a result of high cost of printing, the cost of publications of articles is borne by

contributors.

iii

NIGERIAN JOURNAL OF SOIL SCIENCE

VOLUME 22 (1), 2011

TABLE OF CONTENTS

Officers of the Soil Science Society of Nigeria/Subscription……………………….......... ii

Guide to Contributors……………………………………………………………............ iii

Table of Contents…………………………………………………………………............ iv

Acknowledgement………………………………………………………………….......... vi

Land Suitability Evaluation for Maize (Zea Mays) Cultivation in a Humid Tropical

Area of South Eastern Nigeria by Udoh, B. T and Ogunkunle, A. O. ..............................

1

Characterization and Classification of Soils of Ideato North Local Government Area by Onyekanne, C. F., Akamigbo, F. O. R. and Nnaji, G. U. .......................................

11

Degradation Effect of Palm Oil Mill Effluent (POME) on Physical and Chemical

Properties of the Soils of Uga, South Eastern Nigeria by Patience. O. Umeugochukwu,

Victor O. Chude and Ezeaku, P.............................................................................................

18

Impact of Soil Erosion on Land Degradation in Uga Southeastern Nigeria by O. P

Umeugochukwu, P. I. Ezeaku, V. O Chude, and G. U. Nnaji........................................

26

Characterization of Phosphorus Status in Soils of the Guinea Savanna Zone of

Nigeria by S.O. Amhakhian and I.O.Osemwota...................................................................

37

Physical and Chemical Properties of Soils in Kogi State, Guinea Savanna of Nigeria

by S.O. Amhakhian and I.O. Osemwota................................................................................

44

Oyster Shell Compost Effect on some Physical and Chemical Properties of an Inland

Valley Soil by Eneje, R.C. and Ukut, Asuama N...................................................

53

Effects of Rice Mill Waste and Poultry Manure on some Soil Chemical Properties

and Growth and Yield of Maize (Zea mays L.) by Eneje, R.C., and Uzoukwu, I. ..........

59

Assessment of some Soil Fertility Characteristics of Abakaliki Urban Flood Plains of

South-East Nigeria, for Sustainable Crop Production by Ogbodo, E.N. ..................

65

Effect of Tillage and Crop Residue on Soil Chemical Properties and Rice Yields on an

Acid Ultisol at Abakaliki Southeastern Nigeria by Ogbodo, E.N. and P.A.

Nnabude................................................................................................................................

73

Effect of Tillage and Crop Residue on Soil Physical Properties and Rice Yields on an

Acid Ultisol at Abakaliki Southeastern Nigeria by Ogbodo, E.N. and P.A.

Nnabude................................................................................................................................

86

iv

Soil Fertility Evaluation of Selected Aquic Haplustalfs in Ebonyi State, Southeast Nigeria by Ogbodo, E. N. and G. O. Chukwu......................................................................

97

Growth and Yield of Okra and Tomato as Affected by Pig Dung and other Manures Issue for Economic Consideration in Benue State by Olatunji, O and V.U. Oboh......................................................................................................................................

103

Effect of NPK and Poultry Manure on Cowpea and Soil Nutrient Composition by Olatunji, O., S. A. Ayuba, B.C. Anjembe and S. O. Ojeniyi...................................................

108

Suitability of Extractants for the Determination of Available Sulphur for Groundnut Production in Some Soils of Benue State, Nigeria by Bemgba Anjembe and M.T Adetunji....................................................................................................................................

114

Evaluation of Nutrient Restorative Ability of some Selected Crop and Soil Management Practices in Makurdi, Southern Guinea Savanna, Nigeria by Agber, P.I. and M.E. Obi............................................................................................................................

122

Shear Strength and Compaction Characteristics of Termite Mound Soil (TMS) by Manuwa, S.I. and Olawolu, O.E...........................................................................................

128

Testing the Goodness of Fit of Infiltration Models for Soils Formed on Coastal Plain Sands in Akwa Ibom State, Southeastern Nigeria by Ogban, P. I., Obi, J. C., Anwanane, N. B., Edet, R. U., and Okon, N. E..........................................................................................

134

Contaminant Limit (C/P Index) of Heavy Metals in Spent Oil Contaminated Soil Bioremediated With Legume Plants and Organic Nutrient by Udom B.E., Ano A. O. and Chukwu L. I. ..................................................................................................................

141

Characterization, Classification and Management of Olokoro Soils Umuahia, Abia State Nigeria for Increased Dioscorea dumetorum Yields. Onyekwere, I.N., Nwosu, P O., Ezenwa, M . I. S. and Odofin, A. J. ..................................................................................

150

Rheological Properties of Soil Groups in Central South-Eastern Nigeria in Relation to other Physical Properties by E.U. Onweremadu, B.N. Ndukwu, G.E. Osuji and M.A. Okon.........................................................................................................................................

158

Responses of Melon (Collocynthis citrullus ) and Soil Chemical Properties to Different N - Sources In Ado – Ekiti, Southwestern Nigeria by B. Osundare...................................

162

Assessment of Degradation Status of SoilS in Selected Areas of Benue State Southern Guinea Savanna of Nigeria by A.O. Adaikwu, M.E. Obi and A. Ali ..................................

198

Effects of Land Use Types on Soil Quality in A Southern Guinea Savanah, Nasarawa State of Nigeria by Amana, S. M; Jayeoba, O. J and Agbede, O. O. ....................................

178

Soil Properties and Response of Yam to Ash Application at Akure, Nigeria by Kayode, B.O., Ojeniyi, S. O and Odedina, S. A.…………………………………………..

183

Use of Agricultural Wastes for Improving Soil Crop Nutrients and Growth of Cocoa Seedlings by Akanni, D.; Odedina, S.A and Ojeniyi, S. O……………………….................

187

v

ACKNOWLEDGEMENT

The Editor-in-Chief acknowledges the contributions of the following colleagues,

researchers and scientists who reviewed papers submitted to the Nigerian Journal of Soil

Science.

Prof. M. T. Adetunji - UNAAB

Prof. F. K. Salako – UNAAB

Dr. J. K. Adesodun - UNAAB

Dr. J. O. Azeez - UNAAB

Dr. G. A. Ajiboye – UNAAB

Prof. O. O. Ajayi – FUTA

Prof. M. A. K. Smith – FUTA

Dr. S. O. Agele – FUTA

Prof. M. O. Alatise – FUTA

Dr. O. P. Aiyelari – FUTA

Prof. L. L. Lajide – FUTA

Dr. Ayodele Ajayi – FUTA

Dr. B. S. Ewulo – FUTA

Dr. M. A. Awodun – FUTA

Prof. A. O. Ogunkunle – UI

Dr. S. O. Oshunsanya – UI

Prof. A. S. Fasina – UNAAD

Dr. B. Osundare – UNAAD

Dr. O. J. Ayodele – UNAAD

Dr. L. B. Taiwo – IART Ibadan

Prof. T. Ibia – Uni Uyo

Dr. P. Ogban – Uni Uyo

Prof. O.O. Agbede – Nasarawa S. U.

Prof. V.O. Chude – NPFS Abuja

Prof. A. Olayinka – OAU

Prof. J. A. Adediran – IART Ibadan

Prof. O. Osonubi – UI

Dr. A. J. Odofin – FUT Minna

vi

LAND SUITABILITY EVALUATION FOR MAIZE (ZEA MAYS) CULTIVATION IN A

HUMID TROPICAL AREA OF SOUTH EASTERN NIGERIA

Udoh, B. T1* and Ogunkunle, A. O.2

1Department of Soil Science, University of Uyo, Uyo Akwa Ibom State, Nigeria

E-mail:[email protected]

GSM: 08032630790

*Corresponding Author 2Department of Agronomy, University of Ibadan, Nigeria

ABSTRACT

The land of Akwa Ibom State of Nigeria, under the humid tropical climate, was evaluated for

maize (Zea mays) cultivation by the FAO system. Data were obtained by field soil survey from

29 pedons in four major land types, covering about 40% of the state’s land mass. The result

showed that although certain land qualities/characteristics (e.g. mean annual temperature,

relative humility, topography, soil depth and total nitrogen), were optimum for maize cultivation,

there was no S1 (highly suitable) land for maize cultivation in the area. When assessed by the

non-parametric method (potentially), 76% of the pedons were moderately suitable (S2), 14%

were marginal (S3) and 10% were not suitable (N) for maize cultivation. But currently, 62% of

the pedons were marginal (S3) while 38% were not suitable (N). However, by the parametric

method (potentially and currently), there was neither S1 nor S2 land for maize cultivation in the

area. Potentially 93% of the pedons were marginally suitable (S3) while 7% were not suitable

(N); whereas currently 59% were marginal while 41% were not suitable. The most severe

constraints to maize cultivation in the area were climate (excessive annual rainfall) and soil

fertility (low exchangeable K).

INTRODUCTION

Maize (Zea mays), is the most efficient plant

for capturing the energy of the sun and

converting it to food. Maize provides a major

source of calories not only for humans but also

for animals in Nigeria as well as other parts of

the world. Use of maize for direct human

consumption as roasted cob, breakfast cereal,

pudding, soup, fermented paste, couscous, etc.,

has remained stable at about 100 million tones

per annum since 1988. About three quarters of

maize is transformed into meat, milk, eggs and

other animals products (Idem and

Showemimo, 2004). Thus, maize more than

any other crop offers the promise of meeting

Africa’s food needs in this millennium.

Climate and soil are the main environmental

factors that determine crops yields (Udoh et

al., 2006). Although maize is found to grow

throughout Nigeria under a wide range of

agro-climatic conditions, three broad agro-

ecological zones can be distinguished for

maize production. These are the forest, the

moist (or Guinea) savanna and the

forest/savanna transition zone (Idem and

SHowemimo, 2004). The Guinea savanna is

the most important maize growing zone in

1

Idoh and Ogunkunle NJSS/22(1)/2012

Nigeria. High insolation during the brief maize

growing season, relatively high rainfall

amount, high radiation, long dry season which

limits the incidence of pests and diseases, and

low night temperature characteristic of the

Northern Guinea Savanna, make this zone the

most favourable ecology for maize, provided

adverse soil conditions do not limit

production. This indicates that climate is the

most important factor in maize cultivation in

Nigeria.

In farming, risk is minimized by matching the

requirements of land use to land qualities. This

is the role of land evaluation and it implies a

process of prediction (Alves and Nortcliff,

2000). Application of the FAO Framework for

Land Evaluation (FAO, 1976), can identify the

most limiting land qualities and provide a

good basis for advising farmers on appropriate

management practice, for optimum production

in a particular agroecological zone (Chinene,

1992). Therefore, the present study was

designed to assess the potentials and

limitations of some climatic factors and soil

properties in the suitability of the land of

Akwa Ibom State, Southeastern Nigeria, for

maize cultivation under the humid tropical

climate.

MATERIALS AND METHODS

The study was carried out in Akwa Ibom State

located in the extreme south eastern Nigeria. It

lies within latitudes 4030’ and 5030’ N and

longitudes 7030’ and 8020’E. It covers an area

of 8,412Km2.

The climate is humid tropical with annual

rainfall varying from 3,000mm along the coast

to about 2250 mm at the extreme north, with 1

– 3 dry months in the year. Mean annual

temperature varies between 26 and 280C while

the relative humidity is 75 – 80%. The natural

vegetation comprises the lowland rainforest,

mangrove forest and coastal vegetation

(SLAK, 1989). The soils are formed mainly

from coastal plain sands and alluvial rich

sediments.

Field Survey

Four of the mapping units (M.Us) of Akwa

Ibom State soil map, called land types (LTs),

each covering 581 – 858km2, were selected for

the study. They were Essene, Etinan, Uyo and

Alluvial (LTs, I, II, III and IV, respectively).

Two study sites were located in each of the

M.Us. Soil identification was carried out by

detailed (rigid grid) soil survey of each study

site. Soil properties examined included colour,

texture, consistence, drainage, effective soil

depth, presence or absence of plinthite or

concretions and presence or absence of

mottles. Similar soils with respect to the above

properties were grouped into mapping units

which were represented by a standard profile

pit. The pits were described according to the

FAO (1990) guidelines, soil samples were

collected from each horizon in each soil

profile pit for laboratory analysis.

Laboratory Analysis and Soil Classification

Laboratory analyses of soil samples were

carried out using appropriate standard

procedures (Udo and Ogunwale, 1986; IITA,

1979; 1981). From the results of the laboratory

analysis and field morphological properties,

the 29 pedons encountered in the study area

were classified, following the USDA Soil

Taxonomy (Soil Survey Staff, 1999), from the

order level to subgroups and correlated with

FAO/UNESCO Legend (FAO, 1990).

Land Evaluation

The suitability of the 29 pedons for maize

cultivation was evaluated both by the

conventional (non-parametric) (FAO, 1976)

and the parametric method (Ogunkunle, 1993,

Udo et al., 2006).

For the non-parametric evaluation, pedons

were first placed in suitability classes by

matching their characteristics (Table 1) with

the established requirements (Table 2). The

final (aggregate) suitability class in Table 4 is

that indicated by the most limiting

characteristics of the pedon.

2

Land suitability for maize

For the parametric method each limiting

characteristic was rated (Table 3). The index

of productivity (IP) for each pedon was

calculated using the equation:

IP = A x B x C x…x F

100 100 100

Where: A is the overall lowest characteristic

rating and B, C…F are the lowest

characteristic ratings for each land quality

group (Udoh et al., 2006).

Both the potential index of productivity (IPP)

and current or actual index of productivity

(IPc) were calculated for each pedon using the

established class scores in Table 2. In each

pedon only one member of each of the five

land quality groups (climate (c); topography

(t); wetness (w); soil physical characteristics

(s) and soil fertility (f), was used in the

calculation because there are usually strong

correlation among members of the same group

(e.g. texture and structure in group ‘s’)

(Ogunkunle, 1993).

The basic difference between IPP and IPC, is

that while calculating IPP, exchangeable K,

available phosphorus and total nitrogen which

are easily altered, are not part of the ‘f’ group.

Whereas in calculating IPc, properties that are

easily altered, listed above, are taken into

consideration as well as the requirements for

potential fertility, i.e. those ‘f’ group members

which are not easily altered, e.g. cation

exchange capacity (CEC), base saturation, pH

and organic matter content.

RESULTS AND DISCUSSION

Land Qualities/Characteristics of the Study

Area and Land Use Requirements for

Maize Cultivation

The determination of land suitability classes,

using the FAO framework (1976), involves the

matching of land qualities/characteristics with

the land use requirements. The five land

quality groups used in this study are shown in

Table 1, and the land requirements for the four

suitability classes (S1, S2, S3 and N) for maize

cultivation, are shown in Table 2.

Climate (c)

Climatic parameters considered were annual

rainfall, length of dry season, mean annual

temperature and relative humidity. In Akwa

Ibom State, annual rainfall is a limiting factor

to maize cultivation. The result of matching

the land characteristics (Table 1) with the

requirements for maize cultivation (Table 2)

rated the land as being only 60% suitable for

maize cultivation as shown by the first seven

of the 29 pedons, presented in Table 3. This is

because annual rainfall amount (2,100mm) is

excessively higher than the requirement –

850mm (Sys, 1985).

Length of dry season (3 months or 90 days) is

good but is sub optimal (95%), compared to

the requirement (150 days). However, the

mean annual temperature and relative

humidity (Table 3) are optimum (rated 100%)

for maize cultivation.

3


Table 1: Land qualities/characteristics of pedons from the study sites ----Climate (c) --------- Topog

(t)

Weth

(w)

Soil physical charact

(s)

…………………………………….….. Soil fertility

(f)

………………..………………….

LTa PNb RFc

(mm)

LDSd

(mon)

MTe

(0C)

RHf

(%)

Slope

(%)

Drainage Soil Dept

(Cm)

Coarse frag.

(Vol.%)

Tc Ex

Ca

Ex

Mg

Ex

K

CEC K

Mole

Frac

Mg:

K

B/s

(%)

Total

N

Org.

C

Avail P

Mgkg-1

pH

(KCI)

….(Cmol kg-1)... …..gkg1….

I 1 2100 3 26.8 79 0-2 Good >200 NIL SL .009 0.23 0.012 5.94 .002 2.0 12.6 0.36 1.8 9.2 4.2 2 2100 3 26.8 79 2-6 Good >200 NIL SL .12 .016 .010 5.83 .002 1.6 12.4 0.38 2.1 2.7 4.1

3 2100 3 26.8 79 6-13 Poor 73 NIL SL .06 .014 .013 6.28 .002 1.1 12.0 0.35 1.8 4.0 4.3

4 2100 3 26.8 79 2-6 Good >200 NIL SL .04 .011 .030 5.25 .006 0.4 9.9 0.69 2.8 20.7 4.2 5 2100 3 26.8 79 2-6 Good >200 NIL SL .08 .021 .006 5.41 .001 3.5 15.6 0.57 3.2 43.7 4.4

6 2100 3 26.8 79 6-13 Good >200 NIL SL .07 .029 .008 7.0 .001 3.63 8.5 0.82 4.0 11.0 4.1

7 2100 3 26.8 79 0-2 Modr >200 NIL SCL .28 .130 .019 6.85 .003 6.8 24.0 0.84 6.7 63.0 4.1 II 8 2100 3 26.8 79 0-2 Good >200 NIL SL .15 .030 .010 5.0 .002 3.0 23.0 0.30 1.2 46.7 4.3

9 2100 3 26.8 79 2-6 Good >200 NIL SCL .15 .013 .010 5.23 .002 1.3 7.7 0.48 2.4 58.1 4.0

10 2100 3 26.8 79 6-13 Poor >200 NIL S .05 .015 .013 2.6 .005 1.2 26.0 0.23 0.6 5.3 4.4 11 2100 3 26.8 79 0-2 Good >200 NIL LS .09 .024 .035 6.62 .005 0.7 23.1 0.58 1.2 60.0 4.0

12 2100 3 26.8 79 2-6 Modr 173 NIL S .15 .050 .051 12.7 .004 1.0 40.5 0.36 1.3 39.3 4.1

III 13 2100 3 26.8 79 0-2 Good >200 NIL SL .03 .070 .003 1.06 .003 2.3 9.3 0.40 2.5 6.8 4.0 14 2100 3 26.8 79 13-25 Good >200 NIL SCL .02 .009 .002 2.2 .002 2.25 6.3 0.51 2.2 2.0 4.0

15 2100 3 26.8 79 6-13 Good >200 NIL LS .02 .007 .004 8.5 .004 0.23 17.0 0.42 2.0 16.1 4.0


18 2100 3 26.8 79 13-25 Good >200 NIL LS .05 .013 .001 7.05 .001 1.3 11.5 0.50 1.3 3.0 4.0

19 2100 3 26.8 79 2-6 Modr 105 NIL LS .12 .020 .012 3.6 .003 1.7 28.3 0.60 2.2 5.5 4.2

IV 20 2100 3 26.8 79 0-2 Good >200 NIL LS .05 .013 .02 11 .002 0.65 12.6 0.72 2.8 64.6 3.9

21 2100 3 26.8 79 2-6 Good >200 NIL SL .07 .030 .008 4.2 .002 3.75 14.1 0.44 2.0 71.4 4.1


24 2100 3 26.8 79 2-6 Good >200 NIL SCL .08 .025 .012 5.0 .002 2.1 9.5 0.45 1.6 35.2 4.1

25 2100 3 26.8 79 6-13 Good >200 NIL SL .01 .030 .010 7.6 .001 3.0 20.0 0.38 1.6 40.3 4.1 26 2100 3 26.8 79 2-6 Good <200 NIL LS .15 .067 .012 7.4 .002 5.6 29.0 0.68 2.7 87.0 4.5

27 2100 3 26.8 79 0-2 Good 134 + 25 SCL .09 .040 .010 7.0 .001 4.0 13.6 0.30 1.1 3.6 4.0

28 2100 3 26.8 79 6-13 Imp. . 125 + 25 SCL .11 .053 .011 6.5 .002 4.8 15.1 0.51 3.0 7.2 3.9 29 2100 3 26.8 79 0-2 v. POOR 15 NIL C .020 .800 .020 6.2 .003 40.0 45.0 0.51 2.6 22.0 3.9

a = Land type; b=Pedon no.; c= Rainfall; d=Length of dry season; e=Mean temperature; f=Relative humidity; g=Topography;

h=wetness; i = Textural class; j = Base Saturation; Ex=exchangeable

4


Table 2: Land Use Requirements*for Maize

Ratings (%) According to Severity of Limitations

Land Quality and Characteristics 100 – 95 (SI)

94 – 85 (S2)

84 – 40 (S3)

39 – 20 (NI)

19-0 (N2)

1. Climate (c): Annual rainfall (mm)

850 – 1250

850 – 750 1250-1600

750 – 600 1600-1800

600 – 500 >1800

- -

Length of dry season (days) 150 – 220 130 – 150 110 – 130 90 – 110 Mean annual maximum temp. (0C) 22 – 26 22 – 18

26 – 32 18 – 16 32+

36-30

Relative humidity (%) 50 – 80 50 -42 >80 2 Topography (t):

Slope (%) 0-2 0 – 4

2 – 4 4 – 8

4 – 8 8 – 16

8 – 16 16 – 30

>30 – 50

Wetness (w)*: Flooding Drainage

FO Good

Moderate Moderate

F1 Good

Aeric Poor

Poor Drainable

Soil Physical Characteristics (s): Texture / structure+

CL, L

SL, LS

LCS

CS, S

S

Coarse fragments (Vol.%), 0-10cm <3 3 – 15 15 – 35 35 – 55 - Fertility (f):

Cation exchange capacity (cmol.kg-1 clay) Base saturation (%) pH* organic carbon (%), 0 -15cm

<24 <50 5.5-7.0 >2

16 – 24 35 – 50 5.5-7.0 1.2 -2

<16(-) 20 – 35 5.0-8.0 0.8 -1.2

<16(+) <20 5.0-8.0 <0.8

- - - -

Av. P. (mg.kg-1) Total N. (%) Extr. K (cmol.kg-1)

>22 >0.15 >0.05

13-22 0.10-15 0.3 -0.5

7.13 0.08-01 0.2-0.3

3 -7 0.04-0.08 0.1-0.2

>3 >0.4 >0.1

Key: FO: No Flooding; F1: Seasonal flooded, CL: Clay loam; SL: Sandy Loam; LS: Loamy Sand, LCS: Loamy Coarse Sand; SCL: Sandy Clay Loam; S: Sand. Source: *Modified from Sys (1985).

5


Topography and Soil Wetness (t and w)

The topography of Akwa Ibom State is

generally suitable for maize cultivation.

However, only eight (28%) of the 29 pedons

evaluated were optimum (slope = 0 – 4%) for

maize cultivation, 19 pedons (65%), were

rated as good (95%) to moderate (85%) while

two (or 7%) of the pedons were rated marginal

(60%) for maize cultivation.

In terms of soil wetness (drainage), 21 (or

72%) of the 29 pedons were rated as optimum

for maize cultivation, four pedons (or 14%)

were good to moderate; three pedons (or 10%)

were marginal; while one pedon (or 3%) was

not suitable for maize cultivation.

Soil Physical Characteristics (s)

Soil physical characteristics evaluated were

texture/structure, volume of coarse fragments

and soil depth. Matching the land qualities

(Table 1) with the requirements for maize

cultivation (Table 2), the land of Akwa Ibom

is optimum for maize cultivation in terms of

volume of coarse fragments and soil depth.

Only two (or 7%) of the 29 pedons (pedons 27

and 28) in terms of volume of coarse

fragments and 3 and 29 in terms of soil depth,

respectively (Table 1), were sub-optimal or not

suitable for maize cultivation.

However, soil texture is generally sub-

optimum for maize cultivation in the study

area. Whereas soil texture for optimum maize

performance is clay loam or loam (Sys, 1985),

most soils – 19 (or 66%) of the 29 pedons

were sandy loam or loamy sand and were rated

moderately (85%) suitable. Seven pedons

(24%) were sandy clay loam, rated as nearly

optimal (95% suitable); while three pedons

(10%) were sand and rated as not suitable for

maize cultivation.

Soil Fertility (f)

Both the potential and current soil fertility

were assessed. Under potential fertility are

chemical properties which are not easily

altered. These include cation exchange

capacity (CEC), base saturation and organic

matter content which was optimum (>2%) or

nearly so (0.8 – 1.2%) (Table 1). In almost all

the pedons, CEC and base saturation imposed

serious limitations on the suitability of the

soils for maize. Most of the soils were

marginal for maize cultivation in terms of

CEC (< 16cmolkg-1) and base saturation (<

20%) (Sys, 1985).

Current (or actual) soil fertility refers to

chemical fertility when properties that are

easily altered (exchangeable K, total N and

available P) are taken into consideration as

well as the requirements for potential fertility

already listed above (Ogunkunle, 1993).

The result of matching the land

qualities/characteristics (Table 1) with the

requirements for maize (Table 2) showed that

exchangeable K is one of the most serious

constraints to maize cultivation in Akwa Ibom.

Ninety percent of the soils are marginal and

10% are not suitable for maize cultivation (K

<0.02 cmolkg-1) (Enwezor et al., 1989,

Oluwatosin, 1991). Available P is optimum

(>22mg/kg) for over 50% of the soils, about

10% of the pedons were sub-optimum – 85%

suitable, while 40% of the pedons ranged from

marginal to not suitable due to available P

deficiency.

In terms of total nitrogen, about 90% of the

study area was optimum for maize cultivation

(total N > 0.15%) (Enwezor et al., 1989); 7%

of the soils were marginal while 3% was not

suitable for maize cultivation due to N

deficiency.

Land Suitability Classes in the Study Area

In Table 3 are the individual scores of the land

characteristics (seven of the 29 pedons

evaluated are presented here). This is the result

of matching the land qualities (Table 1) with

the land requirements (Table 2). Table 4 shows

a summary of the suitability aggregate scores

and suitability classifications under the

potential and current evaluation by the

parametric and non-parametric methods, for all

the 29 pedons identified in the study area.

6


Table3: Suitability Class Scores of some of the pedons in the study area

Pedon

1

Pedon

2

Pedon

3

Pedon

4

Pedon

5

Pedon

6

Pedon

7

Climate (C)

Annual rainfall

Length of dry season

Mean annual temperature

Relative humidity

S3(60)

S1(95)

S1(100)

S1(100)

S3(60)

S1(95)

S1(100)

S1(100)

S3(60)

S1(95)

S1(100)

S1(100)

S3(60)

S1(95)

S1(100)

S1(100)

S3(60)

S1(95)

S1(100)

S1(100)

S3(60)

S1(95)

S1(100)

S1(100)

S3(60)

S1(95)

S1(100)

S1(100)

Topography (t):

Slope (%)

S1(100)

S1(100)

S2(85)

S1(95)

S1(95)

S2(85)

S1(100)

Wetness (w):

Drainage

S1(100)

S1(100)

S3(60)

S1(100)

S1(100)

S1(100)

S2(85)

Soil physical characteristics(s)

Texture and structure

Volume of coarse fragments

Soil depth

S2(85)

S1(100)

S1 (100)

S2(85)

S1(100)

S1 (100)

S2(85)

S1(100)

S1 (100)

S2(85)

S1(100)

S1 (100)

S2(85)

S1(100)

S1 (100)

S2(85)

S1(100)

S1 (100)

S2(95)

S1(100)

S1 (100)

Soil fertility (f):

Cation exchange capacity

Base saturation

Organic matter content

Exchangeable K

Available phosphorus

Total nitrogen

S3 (60)

S3 (60)

S1(95)

S3 (40)

S2 (85)

S1(100)

S3 (60)

S3 (60)

S1(100)

S3 (40)

N1 (20)

S1(60)

S3 (60)

S3 (60)

S1(100)

S3 (40)

N1 (20)

S3(60)

S3 (60)

S3 (60)

S1(100)

S3 (40)

S1 (100)

S1(100)

S3 (60)

S3 (60)

S1(100)

S3 (40)

S2 (100)

S1(100)

S3 (60)

S3 (60)

S1(100)

S3 (40)

S2 (85)

S1(100)

S3 (60)

S3 (85)

S1(100)

S3 (40)

S1 (100)

S1(100)

Aggregate suitability+:

Potential

Actual (current)

S3 (43)

S3 (29)

S3(42)

N2(14)

S3 (31)

N2(10)

S3(42)

S3(28)

S3(42)

S3(28)

S3(40)

S3(26)

S3(40)

S3(28)

+: Aggregate suitability class scores: 100-75 = S1, 74 – 50 = S2; 49 – 25=S3, 24-15 = N1; 0 = 12.

7


Table 4: Suitability aggregate scores and suitability classifications of pedons for maize,

indicating limiting characteristics

Pedon

Potential Current

Parametric1 Non-Parametric1 Parametric1 Non-Parametric2

1 S3 (43) S2cf S3(29) S3f

2 S3 (42) S2cf N2(14) N1f

3 S3 (31) S2cwf N2(10) N1f

4 S3 (42) S2cf S3(28) S3f

5 S3 (40) S2cf S3(28) S3f

6 S3 (40) S2cf S3(26) S3f

7 S3 (40) S2cf S3(28) S3f

8 S3 (45) S2cf S3(30) S3f

9 S3 (42) S2cf S3(28) S3f

10 N2 (11) N1s N2(11) N1s

11 S3 (42) S3cf S3(28) S3f

12 S3 (28) N1s N2(13) N1s

13 S3 (29) S3f N2(14) N1f

14 N1 (23) S3f N2 (13) N1f

15 S3 (40) S2cf S3(28) N1f

16 S3 (42) S2cf S3(28) S3f

17 S3 (40) S2cf S3(26) N1f

18 S3 (33) S2cft N2(11)) N1f

19 N1 (22) S3f N1 (23) S3f

20 S3 (42) S2cf S3(28) S3f

21 S3 (42) S2cf S3(28) S3f

22 S3 (42) S2cf S3(28) S3f

23 S3 (40) S2cf S3(28) S3f

24 S3 (44) S2cf S3(26) S3f

25 S3 (42) S2cf S3(29) S3f

26 S3 (42) S2cf N1(14) S3f

27 S3 (43) S2cf S3(24) N1f

28 S3 (26) S2cf N1(14) S3f

29 N2 (9) N1sw N2(6) N1sw

1: Aggregate suitability class scores: 100-75 = S1; 74 – 50 = S2; 49 – 25 = S3; 24 – 15 = N1;

14 – 0 = N2.

2: C = Climatic limitation; f = Fertility limitation; w = wetness limitation; S=Soil physical

characteristic limitation.

Parametric Evaluation The result in Table 4 shows that by the parametric method, potentially, up to 86% (25 out of 29 pedons) of the soils in the study area is only marginally (S3) suitable while 14% (pedons 10, 14, 19 and 29; Table 4), are not suitable (N) for maize cultivation. However, currently (by the same parametric method), up to 41% (12 out of 29) of the pedons are not

suitable (N) while 59% (17 out of 29) of the pedons are only marginally suitable (S3) for maize cultivation. Non-Parametric Evaluation By the non-parametric evaluation, the area is shown to be more favourable to maize cultivation than the parametric method. However, none of the soils is in optimum (S1)

8


condition for maize cultivation. Potentially, 76% (22 out of 29) of the pedons were moderately suitable (S2), 14% (4 out of 29 pedons) were marginal (S3); while 10% (pedons 10, 12 and 29; Table 4) were not suitable (N1 or N2) for maize cultivation. However, currently (by the non-parametric method), the situation is not as favourable as there was neither SI nor S2 land class for maize. About 62% (18 out of 29) of the pedons were only marginally suitable (S3) while 38% (11 out of 29) of the pedons were not suitable (N1 or N2) for maize cultivation. Major Limitations to Land Suitability for Maize The above analysis has shown that in Akwa Ibom State two of the five land qualities – topography (slope) and wetness (drainage) are optimum or nearly so for maize cultivation. Also mean annual temperature and relative humidity as aspects of climate are optimum for maize cultivation in the State. Furthermore, soil depth and volume of coarse fragments under soil physical characteristics are optimum for maize cultivation in the State. One of the most serious limiting characteristics to maize cultivation in the State is annual rainfall. The annual rainfall amount in the area of study is up to 2100 mm (Table 1) which is in excess of 850 – 1250 mm recommended as the optimum requirement for maize cultivation (Sys, 1985). This has rendered the entire State marginal for maize cultivation. Soil texture is another serious limitation to maize cultivation in the State. For optimum performance of maize crop, clay loam or loam texture is required (Sys, 1985). But in the area of the study, most of the pedons have sandy loam or loamy sand texture. Although the limitation is not very severe, it is of a general nature thereby rendering the entire area sub-optimal for maize cultivation. Furthermore, soil fertility is another land quality that severely limits maize production in the State. Both the potential fertility (e.g. CEC and base saturation), and current fertility,

particularly exchangeable K are serious constraints to maize cultivation in the State. Exchangeable K is generally below the critical level (0.2cmol/kg-1) (Enwezor, et al., 1989) in the entire State thereby rendering the land marginal for maize cultivation. With heavy rainfall and coarse soil texture – having poor nutrient holding capacity, as expressed by low CEC, the rate of leaching is high. This explains the low exchangeable bases, particularly K observed in these soils. Climate (excessive annual rainfall) is also a serious constraint to maize cultivation in the State because excessive moisture would encourage incidence of pests and diseases as well as hamper grain maturity and ripening. CONCLUSION The result of the study shows that inspite of the optimal or near optimal mean annual temperature, relative humidity, soil drainage and depth and total nitrogen, there is no highly suitable (S1) land for maize in the State. The State is mostly moderately to marginally suitable for maize. The most severe limitations to maize cultivation in the State are excessive annual rainfall, soil texture and chemical fertility – particularly CEC, base saturation and exchangeable K. In order to raise the productivity of the land to optimum for maize cultivation, management techniques to be adopted should enhance the nutrient and moisture holding capacity of the soil. Application of organic fertilizers/materials would enhance land productivity. Finally, in order to avoid yield reduction arising from incidence of pests and diseases, as a result of excessive rainfall during the growing season, appropriate drainage facilities should be put in place to take care of the excessive moisture and check the rising water table, while provision of irrigation facilities would make dry season farming possible. This would ensure optimum land productivity as a result of high insolation, relatively dry environment and therefore a favourable ecology for maize production.

9


REFERENCES Alves, H. M. R. and Nortcliff S., 2000.

Assessing potential production of maize using simulation models for land evaluation in Brazil. Soil Use and Management, 16:49 – 55.

Chinene, V. R. N. 1992. Land evaluation using

the FAO Framework: An example from Zambia. Soil Use and Management, 8:130 – 139.

Enwezor, W. O., Udo, E. J. Usoroh, N. J.,

Ayotade, K. A., Adepetu, J. A.. Chude, V. O. and Udegbe, C. I. 1989. Fertilizer Use and Management Practices for Crops in Nigeria (eds), FMAWRRD, Lagos, 163pp.

FAO, 1976. A Framework for Land

Evaluation. FAO Soils Bull, 32: FAO, Rome, 87pp.

FAO. 1990. Guidelines for Soil Desriptions,

3rd Ed., FAO, Rome. FAO-UNESCO-ISRIC. 1990. Soil Map of the

World. Revised Legend Reprinted with Corrections. World Soil Resources Report. 60, FAO, Rome, 119p.

Idem, N. U. A. & Showeminmo, F. A. (eds)

2004. Cereal Crops of Nigeria: Principles of Production and Utilization, IAR, ABU, Zaria, xxii 337

IITA, (International Institute of Tropical

Agriculture). 1979. Selected Methods for Soil and Plant Analysis. IITA Manual Series, I, IITA, Ibadan, Nigeria, 60pp.

IITA, 1981. Automated and Semi-automated Methods for Soil and plant Analysis. Manual Series No.7, IITA, Ibadan, 33p.

Ogunkunle, A. O. 1993. Soil in Land

suitability evaluation: An example with oil palm in Nigeria. Soil Use and Management, 9(1): 35 – 40.

Oluwatosin, G. A. 1991. Land evaluation for

maize production in the basement complex area of the savanna zone of Western Nigeria. Ph.D. Thesis. Department of Agronomy, Univ. of Ibadan, Ibadan.

SLAK (Soil and Land Use Survey of Akwa

Ibom State). 1989. Technical Report. Govt. Printers, Uyo, 602pp.

Soil Survey Staff. 1999. Soil Taxonomy; a

basic system of soil classification for making and interpreting soil surveys. USDA Agric. Handbook. No. 436, Second edition. U. S. Govt. Printing Office, Washington D. C. 868pp.

Sys, C. 1985. Land Evaluation. Part I, II, III.

247pp. Publication No. 7 of the General Administration of Cooperation Development. Place de Champs de Mars 5, boite 57, 1050 Bruxelles.

Udo, E. J. and Ogunwale, J. A. 1986.

Laboratory Manual for the Analysis of Soil Plant and Water Samples. Dept. of Agronomy, Univ. of Ibadan, Nigeria.

Udoh, B. T., Ogunkunle, A. O. and Olaleye,

A. O. 2006. Land Suitability evaluation for banana/plantain (Musa spp.) cultivation in Akwa Ibom State of Nigeria. Journal of Research in Agriculture, 3(3): 1-6.

10


CHARACTERIZATION AND CLASSIFICATION OF SOILS OF

IDEATO NORTH LOCAL GOVERNMENT AREA.

ONYEKANNE, C. F., AKAMIGBO, F. O. R. AND NNAJI, G. U1

Department of Soil Science, University of Nigeria, Nsukka. 1coressponding author - [email protected]

ABSTRACT

The soils of Ideato North local government Area in Imo State, Nigeria were mapped,

characterized and classified in order to provide information necessary for good land use

planning. Topographic map was used for the reconnaissance survey of the area and nine villages

within the local government area were selected for the study. They were Urualla, Akpulu,

Ndiuche, Ndiadimoha, Obodoukwu, Akokwa, Ndiawa, Umualoma and Osina, Nine profile pits

were dug and a total of 47 samples were collected from these locations. Selected soil physical

and chemical properties were determined. Soil textural classes identified in the area were sandy

loam, loamy sand, sand, sandy clay loam, and sandy clay. However dominant soil texture is

sandy clay loam. The soils were extremely acidic to strongly acidic ranging from pH of 4.0-5.4.

The base saturation of the soils ranged from low to moderate with values ranging from 9.48-

58.50 %. The CEC was generally low ranging from 4.00-18.00cmol./kg soil. The exchangeable

bases were low. The soils were classified as Arenic kandiudults, Plinthic kandiudults, Arenic

kandiudults, Aquic kandiudults, Arenic kandiudults, Arenic kandiudults, Typic kandiudults,

plinthic kandiudults, Arenic kandiudults for Urualla, Akpulu, Ndiuche, Ndiadimoha,

Obodoukwu, Akokwa, Ndiawa, Umualoma and Osina profiles respectively. Application of

mineral and organic fertilizers, liming and good management practices are necessary for

maximum productivity of these soils.

INTRODUCTION

Soils are very important natural resource. They

are the bases for most development projects it

is the foundation material for houses, roads

and buildings. They also, serve as purification

system for septic tank effluent, media for

establishment of lawn and the growth of

shrubs and garden. In order to ensure that the

soil is put to the most appropriate and

sustainable use there is every need for

characterization and classification of the soil.

Soil survey paves a way to soil

characterization, classification and evaluation.

Soil characterization, soil classification and

soil mapping, provide a powerful resource for

the benefit of mankind especially in the area of

food security and environmental sustainability

(Esu, 2004). Soil classification is the

systematic arrangement of soil into groups or

categories on the basis of their characteristics.

Soil characterization studies are major

building block for understanding the soil,

classifying it and getting the best

11

Onyekanne, Akamigbo and Nnaji NJSS/22(1)/2012

understanding of the environment. Soil

characterization provides the information for

our understanding of the physical, chemical,

mineralogical and microbiological properties

of soil. Each soil, based on its characteristics

has a predictable response to management or

any kind of manipulation (Ogunkule, 2004).

A sustainable land management system is the

one that does not degrade the soil or

significantly contaminate the environment

while providing necessary support to human

life (Greenland, 1994) and can only be

recommended after characterization,

classification and evaluation of the soil. There

is dearth of information on soils of Ideato

North Local government area in these regards.

Therefore, the objective of this study is to

characterize and classify the soils of Ideato

North Local Government Area of Imo State.


Description of the study area

The study area falls within the humid tropical

zone. Jungerius, (1964) noted that the area has

uniformly high temperature and a seasonal

distribution of precipitation with humidity

being generally high except during the

desiccating weather of harmatan. Two major

seasons are the wet and dry seasons with the

former lasting for eight months (March –

October) and latter for four months (November

– February). Total annual rainfall ranges from

1,500 – 1800mm while the maximum

temperature ranges from 290C to 330C and

minimum temperature ranges from 20.80C to

22.80C

Field work The field work commenced on 29th July, 2010

and the following materials were used; spade,

machete, hoes, pike axe, sampling bags,

masking tape, permanent marker, digital

camera, munsell colour chart, hand-held global

positioning system tool (GPS), measuring

tapes, 4 pegs, dilute hydrochloric acid, (HCl).

A reconnaissance survey of the area was

carried out and with the aid of topographic

map and nine villages were chosen for the

study. They are Urualla, Akpulu, Ndiuche,

Ndiadimoha, Obodoukwu, Akokwa, Ndiawa,

Umualoma and Osina, all in Ideato North

Local Government Area of Imo State, South

Eastern Nigeria. The villages traversed the

entire local government area. From the field

assessment of auger soil samples one profile

pit was prepared and studied in each village. A

total of nine profile pits were studied. The

profiles were described following the guide

lines outlined in USDA-SCS (1974). Also, the

soils were classified according to the

comprehensive soil classification system (Soil

Taxonomy).

Laboratory analysis

Soil samples were air dried and sieved with

2mm sieve. Particle size analysis was

determined by Bouyoucos hydrometer method.

The pH was determined using glass electrode

digital consort pH meter. Organic carbon

content was determined by the wet dichromate

method and organic matter was calculated by

multiplying organic carbon with 1.724. Cation

exchange capacity (CEC) was determined by

using ammonium acetate method, calcium and

magnesium were determined by the

complexometric titration method. Sodium and

potassium were determined in the 1N

ammonium acetate leachate using the flame

photometer. Exchangeable hydrogen and

aluminum were determined by the titrimetric

method using 1N KCl extract. Percentage base

saturation was calculated as follow- total

exchangeable bases/CEC X 100. Available

Phosphorous was determined by the Bray II

Method. Total N was determined by the

kjeldahl wet oxidation method. Boron was

determined by Carmine method. Lead was

determined by calorimetric determination

using Sulphide method. Iron was determined

by calorimetric determination using

12

Characterization and classification of Ideato soils

Orthorphenanthroline. Cadmium was also

determined using spectrophotometer


Soil physical properties.

The physical properties of soils are presented

in Tables 1-3. Most of the soils are dominated

by sand fraction, with sand content being

higher than 50% in all soil horizons. The sand

content decreased down the profile for most

profiles. The texture of the soils falls within

these textural classes – sand, sandy clay loam,

sandy loam, sandy clay and loamy sand.

Generally, the texture of the soil did not

change for a relatively short time (Brady and

Weil, 1999) hence the parent material from

which soils form has significant influence on

soil texture (Nnaji et al., 2002). The soils of

the study area might have developed from

sandstone and quartzite parent material. Such

parent materials are capable of impacting

coarse texture to the soil. High and intense

rainfall experienced in the area might have

resulted in clay illuviation down the profile.

Table 1: Particle size distribution of soils from Urualla, Akpulu and Ndiuche

Profiles depth Clay

(%)

Silt

(%)

Fine sand

(%)

Coarse

sand (%)

Total sand

(%)

Texture

P1

Urualla 0 – 15

12.76

8.56

25.12

53.56

78.68

sandy loam

15 – 70 5.76 4.56 36.12 53.56 89.68 loamy sand

70 – 90 5.76 2.56 20.88 70.80 91.68 Sand

90 – 160 17.76 6.56 27.38 48.30 75.68 sandy loam

160 – 180 11.76 8.56 28.62 51.06 79.68 sandy loam

P2

Akpulu 0 – 20

17.76

10.56

32.56

38.82

71.68

sandy loam

20 – 50 25.76 8.56 30.50 35.18 65.68 sandy clay loam

50 – 10 25.76 18.56 17.16 38.52 55.68 sandy clay loam

100 – 120 25.76 8.56 20.18 45.50 65.68 sandy clay loam

P3

Ndiuche 0 – 20

5.76

4.56

29.08

60.60

89.68

loamy sand

20 – 49 13.76 2.56 39.04 44.64 83.68 loamy sand

49 – 90 25.76 2.56 24.06 47.62 71.68 sandy clay loam

90 – 140 25.76 2.56 28.32 43.36 71.68 sandy clay loam

140 – 190 29.76 6.56 18.52 45.16 63.68 sandy clay loam

13


Table 2: Particle size distribution of soil Ndiadimoha, Obodoukwu and Akokwa Profiles depth (cm) Clay

(%)

Silt

(%)

Fine sand

(%)

Coarse sand

(%)

Total sand

(%)

Texture

P4

Ndiadimoha 0 – 20

20 – 50

50 – 70

70 – 100

100 – 140

140 – 180

5.76

11.76

11.76

35.76

41.76

35.76

8.56

12.56

12.56

8.56

6.56

14.56

74.40

63.46

64.44

48.1

42.68

41.80

11.28

12.22

11.24

7.58

9.00

7.88

85.68

75.68

75.68

55.68

51.68

49.68

loamy sand

sandy loam

sandy loam

sandy clay

sandy clay

sandy clay loam

P5

Obodoukwu 0 – 20

20 – 30

30 – 65

65 – 80

80 – 130

130 – 200

25.76

33.76

21.76

25.76

27.76

29.76

11.28

11.28

5.28

5.28

7.28

5.28

15.40

11.24

11.22

12.42

9.92

12.24

47.56

43.70

61.74

60.54

55.04

52.72

62.96

54.96

72.96

72.96

64.96

64.96

sandy clay loam

sandy clay loam

sandy clay loam

sandy clay loam

sandy clay loam

sandy clay loam

P6

Akokwa 0 – 25

25 – 80

80 – 120

120 – 155

155 – 200

15.76

9.76

21.76

21.76

17.76

5.28

11.28

3.28

3.28

3.28

6.66

14.46

11.72

15.48

17.96

72.30

64.50

63.24

59.48

61.00

78.96

78.96

74.96

74.96

78.96

sandy loan

sandy loam

sandy clay loam

sandy clay loam

sandy loam

Table 3: Particle size distribution for soils from Ndiawa, Umualoma and Osina Profile depth Clay

(%)

Silt

(%)

Fine sand

(%)

Coarse sand

(%)

Total sand

(%)

Texture

p7

Ndiawa 0 – 18

11.76

13.28

64.60

10.36

74.96

sandy loam

18 – 40 11.76 17.28 63.80 7.16 70.96 sandy loam

40 – 80 11.76 13.28 67.74 7.22 74.96 sandy loam

80 – 110 19.76 9.28 67.82 3.14 70.96 sandy clay loam

110 – 143 25.76 19.28 48.42 6.54 54.96 sandy clay loam

143 – 186 29.76 5.28 53.72 11.24 64.96 sandy clay loam

p8

Umualoma 0 – 20

9.76

15.28

65.62

9.34

74.96

sandy loam

20 – 40 25.76 9.28 53.62 11.34 64.96 sandy clay loam

40 – 90 35.76 9.28 46.18 8.78 54.96 sand clay

90 – 140 43.76 5.28 40.92 10.04 50.96 sandy clay

140 – 180 37.76 7.28 48.88 6.08 54.96 sandy clay

p9

Osina 0 – 23

13.76

7.28

16.50

62.46

78.96

sandy loam

23 – 49 29.76 5.28 15.64 49.32 64.96 sand clay loam

49 – 85 31.76 11.28 13.44 43.52 56.96 sand clay loam

85 – 120 29.76 5.28 24.14 40.82 64.96 sand clay loam

120 – 200 33.76 11.28 18.56 36.40 54.96 sand clay loam

Soil Chemical Properties The chemical properties of the soils are given

in Tables 4, 5 and 6. The soils were acidic with

pH ranging from 4.0-5.4. The high acidic

nature of the soils may be due to high intensity

rainfall in the area, which leaches basic cations

down the profile. Enwezor et al (1981) stated

that leaching of Ca and Mg is largely

14


responsible for development of acidity. Also,

soil acidity may also be due to Al saturation of

the exchange complex as observed by Ekpete,

(1972).

The phosphorus content of the representative

pedon is low at the epipedon and decreases

down the depth except for few cases where it

is totally lacking. Generally, the low

phosphorus content of the soils may be due to

high soil acidity (Uzoho et al., 2004). Also,

Kubrin et al. (2000) noted that deficiency of

phosphorus may occur in soils due to the

strong adsorption of this nutrient by the soil

colloids. The organic matter content of the

soils ranged from 0.28-4.48% and is high in

the epipedons and decreases down the depth,

though in some cases decreases in irregular

manner (Tables 4, 5 and 6). However, for

tropical soils, the organic matter content of the

representative pedons were low except for few

layers with medium to high content of organic

carbon matter.

Exchangeable bases were either low or very

low and total nitrogen content of the soils

were very low; CEC was high in few profiles

and low in most profiles. The low CEC and

exchangeable content of the soils could be

attributed to high rate of weathering and

leaching of the basic cations in these soils as a

result of high temperature and rainfall

associated with humid tropical climate.

Akamigbo and Asadu (1986) noted that low

CEC could be as a result of high rainfall; clay

type and content as well as previous land use.

Classification of soils of the study area

The soils are Ultisols with kandic diagnostic

horizon; that is with accumulation of low

activity clay in the subsurface horizon. Soils

from Akpulu and Umualoma contain

plinththite, a highly weathered mixture of

sesquioxides of iron and aluminum with quartz

and other diluents that occur as red mottles

that changes irreversibly to hardpan upon

alternate wetting and drying (Brady and Weil,

1999). Soils from Ndiadimoha showed some

characteristics associated with wetness and

most soils showed evidence of plowing/mixed

horizon.

Table 4: Chemical characteristics of soils of the study area Urualla, Akpulu and Ndiuche Profile

No.

Exchangeable base Exchangeable acidity

Cmol/kg Soil Cmol/kg

Soil

Depth

Cm

pH

H2O

pH

KCl

Ca Na K Mg Al3+ H+ TN

(%)

OM

(%)

Avail.

P(mg/kg)

B CEC

(cmol/kg)

%

BS

Profile 1 0-15 4.8 3.9 1.4 0.08 0.06 0.40 Nil 0.80 0.100 1.93 7.09 1.19 6.4 30.31

15-70 4.7 3.3 0.4 0.11 0.02 0.20 Nil 1.60 0.030 0.96 1.12 1.19 6.8 10.74

Urualla 70-90 4.8 3.3 0.4 0.08 0.04 0.20 Nil 1.20 0.014 0.34 0.75 2.38 6.4 11.25

90-160 4.5 3.2 1.6 0.11 0.05 1.40 0.40 1.20 0.014 1.24 0.37 2.38 6.4 49.38

160-180 4.4 3.3 0.4 0.08 0.03 1.80 1.20 1.20 0.014 0.67 Nil 1.19 7.2 32.08

Profile 2 0-20 4.4 3.3 1.0 0.11 0.05 0.80 0.40 2.00 0.080 2.48 2.34 1.19 10.0 19.60

20-50 4.4 3.4 0.6 0.11 0.04 0.40 0.40 1.20 0.030 2.00 0.37 1.19 11.6 9.91

Akpulu 50-100 4.3 3.5 0.4 0.08 0.06 0.60 0.40 0.80 0.040 1.24 Nil 1.19 7.20 13.05

100-120 4.5 3.5 0.6 0.08 0.05 0.40 0.40 1.20 0.030 0.48 Nil 1.19 8.40 13.42

Profile 3 0-20 4.2 3.3 0.8 0.08 0.05 1.60 0.40 0.80 0.060 1.10 2.61 trace 4.80 52.71

20-49 4.3 3.2 0.4 0.11 0.04 1.40 0.80 0.80 0.030 1.17 Nil trace 6.80 28.68

Ndiuche 49-90 4.2 3.4 0.4 0.08 0.05 0.20 0.80 1.60 0.014 0.97 Nil 2.38 9.20 20.98

90-140 4.2 3.3 0.8 0.08 0.04 Nil 0.40 2.40 0.014 0.63 3.73 trace 4.80 19.17

140-190 4.1 3.3 0.8 0.08 0.03 Nil 0.40 0.80 0.014 0.48 0.37 trace 9.60 9.48

TN = total Nitrogen, OM=organic matter, BS = base saturation

15


Table 5: Chemical characteristics of soils from Ndiadimoha, Obodoukwu and Akokwa Profile

No. Exchangeable base Exchangeable acidity

Cmol/kg Soil Cmol/kg Soil

Depth

Cm

pH

H2O

pH

KCl


(%)

OM

(%)

Avail.

P(mg/kg)

B

CEC

(cmol/kg)

%

BS

Profile 4 0-20 4.0 3.2

0.4 0.11 0.05 1.00 Nil 1.20 0.070 1.03 1.87 trace 8.00 19.50

20-50 4.1 3.2 1.0 0.08 0.03 0.80 0.40 0.80 0.040 0.90 Nil trace 6.00 31.83

Ndiadim 50-70 4.3 3.2 1.0 0.08 0.02 0.40 0.80 1.20 0.040 0.28 Nil 1.19 6.00 25.00

Oha 70-100 4.3 3.2 1.2 0.11 0.05 0.60 3.20 1.20 0.030 0.84 Nil 1.19 10.4 18.85

100-140 4.2 3.2 1.6 0.08 0.04 0.80 2.80 1.20 0.030 1.93 Nil trace 10.0 25.20

140-180 4.4 3.2 1.0 0.11 0.04 0.40 2.40 0.80 0.040 0.34 Nil trace 10.4 14.90

Profile 5 0-20 4.5 3.8 1.8 0.08 0.03 1.00 Nil 2.80 0.100 3.80 2.60 2.38 10.8 26.94

20-30 4.2 3.4 1.2 0.08 0.01 1.80 0.80 1.20 0.040 4.48 0.37 1.19 18.0 17.17

Obodo 30-65 4.4 3.5 1.0 0.08 0.02 3.98 0.40 0.80 0.040 4.31 0.75 4.75 10.0 58.80

Ukwu 65-80 4.5 3.5 1.2 0.08 0.02 2.80 0.40 1.60 0.040 2.90 0.37 3.56 12.0 34.17

80-130 4.5 3.4 1.0 0.11 0.01 1.20 0.80 1.20 0.040 1.72 0.37 1.19 12.0 19.33

130-200 4.4 3.4 1.6 0.08 0.01 1.00 0.80 0.80 0.030 1.03 Nil trace 10.0 26.90

Profile 6 0-25 4.5 3.6 1.4 0.08 0.02 0.60 Nil 1.60 0.060 2 .14 4.48 2.38 5.60 37.50

25-80 4.6 3.4 1.0 0.08 0.01 0.40 0.40 1.60 0.030 1.45 0.37 1.19 8.00 18.63

Akokwa 80-120 4.6 3.3 0.8 0.08 0.008 1.40 2.00 Nil 0.014 0.89 0.37 3.56 4.00 57.20

120-155 4.6 3.4 0.6 0.05 0.003 1.60 0.80 1.20 0.014 0.67 3.73 1.19 7.20 31.29

155-200 4.6 3.3 0.8 0.08 0.01 0.60 1.20 0.80 0.014 0.33 0.37 trace 4.80 31.04

Table 6: Chemical Characteristics of soils from Ndiawa, Umualoma and Osina Profile

No. Exchangeable base Exchangeable acidity

Cmol/kg Soil Cmol/kg Soil

Depth

Cm

pH

H2O

pH

KCl


(%)

OM

(%)

Avail.

P(mg/kg)

B

CEC

(cmol/kg)

%

BS

Profile 7 0-18 4.9 4.2 2.0 0.11 0.05 0.80 0.40 3.20 0.100 1.31 1.87 1.19 5.20 56.92

18-40 5.1 3.9 1.8 0.08 0.03 0.40 0.40 1.60 0.040 1.02 0.37 1.19 6.00 38.50

Ndiawa 40-80 4.9 3.6 1.8 0.08 0.03 1.00 0.40 1.20 0.040 1.10 Nil 1.19 7.20 40.42

80-110 4.3 3.2 1.2 0.08 0.03 0.80 1.20 0.80 0.040 0.28 Nil 1.19 6.40 32.97

110-143 4.6 3.1 1.8 0.11 0.06 1.00 6.00 0.40 0.040 0.41 0.75 3.56 13.2 22.50

143-186 4.9 2.9 2.0 0.08 0.07 0.40 4.40 0.40 0.030 0.33 0.37 1.19 17.2 14.83

Profile 8 0-20 4.8 3.5 0.6 0.11 0.06 1.00 0.40 1.60 0.070 0.97 1.87 2.37 4.80 36.88

20-40 4.7 3.1 1.8 0.08 0.04 0.40 1.60 0.80 0.040 0.55 2.61 2.37 8.00 29.00

Umualoma 40-90 5.1 3.4 2.0 0.08 0.03 1.60 1.80 0.40 0.020 0.28 0.37 trace 13.2 28.11

90-140 5.4 3.4 2.2 0.08 0.04 1.40 1.20 0.40 0.020 0.62 Nil 1.19 14.0 26.57

140-180 5.2 3.3 2.6 0.11 0.03 1.60 1.40 0.20 0.030 0.67 Nil 1.19 10.8 40.19

Profile 9 0-23 4.2 3.2 1.0 0.08 0.02 0.60 0.60 1.20 0.060 1.90 2.61 1.19 5.20 32.69

23-49 4.4 3.4 0.8 0.08 0.01 1.40 0.40 1.60 0.040 1.20 0.37 1.19 7.30 31.36

Osina 49-85 4.3 3.6 0.4 0.11 0.01 1.00 0.80 1.10 0.014 0.69 Nil 1.19 4.00 38.00

85-120 4.1 3.2 1.6 0.08 0.02 0.60 0.80 1.20 0.014 0.53 Nil 1.19 6.00 38.33

120-200 4.3 3.2 0.4 0.11 0.02 1.20 0.80 1.20 0.014 0.29 0.37 1.19 4.10 42.20

CONCLUSION

Most soils of Ideato North in Imo state Eastern

part of Nigeria are highly weathered Ultisols,

acidic, and low in most nutrient elements.

However, with adequate management

practices such as application of organic and

inorganic fertilizers, liming and inoculation of

some nitrogen fixing organisms and

earthworm, they may become very productive.

16


REFERENCES

Akamigbo, F. O. R and Asadu, C.L. A

(1986).The influence of Soil Parameter

in selected area of Anambra state

Nigeria. Nigeria Journal of Soil

Science

Brady, N. C. and Weil, R.R. (1999). The

Nature and Properties of Soil.

Macmillan Publishers, New York. Pp

77.

Ekpete, D.M. 1972. Assessment of Lime

Requirement of Eastern Nigeria Soils.

Soil Science 113: 363 – 372.

Enwezor, W. O., E. J. Udo and R. A. Sobulo

(1981). Fertility status and the

productivity of the acid sands P. 56 –

73: In Acid Sand of South Eastern

Nigeria. Soil Science Society of

Nigeria Special Publ. Monograph.1.

Esu, I. E. (2004). Soil Characterization and

Mapping for Food Security and

Sustainable in Nigeria. In Proceeding

of the 29th Annual Conference of the

Soil Science Society of Nigeria. pp 9-

12

Esu I.E. (2004). Soil Characterization and

Mapping for food Security and

Sustainable Environment in Nigeria: In

Proceeding of the 29th Annual

Conference of the soil Science Society

of Nigeria. Pp 10-17

Greenland, D J. (1994) Soil Science and

Sustainable Land Management. In:

Syres, J.K and D.L.Rimmer (Ed) Soil

Science and Sustainable Land

Management in the Tropics. CAB

International, 1-15

Jungerius, P. D. (1964). The Soil of Eastern

Nigeria Publication.

Jubrin, J. M., Chude , V. O., Host, W. J., I Y.

Amagu (2000) The response of 10

leguminous cover crop and mage

native and applied phosphate.

Proceeding 26th Annual Conf Soil Sc.

Society of Nigeria. Nigeria

Nnaji, G. U., Asadu, C. L. A and Mbagwu, J.

S. C. (2002). Evaluation of the physic-

chemical properties of soils under

selected agricultural land utilization

types. Agro-Science Journal of

Tropical Agriculture, Food,

Environment and Extension. 3:27-33.

Ogunkunle, A.O. (2004). Soil Survey and

Sustainable Land Management: In

Proceedings of 29th Annual Conference

of The Soil Science Society of Nigeria.

Pp19-24.

USDA-SCS. (1974). Definition and

Abbreviations for Soil Description.

West Technical Service Center, Port

land, Oregun, USA.

Uzoho, B.U and N. N .O. T. (2004).

Phosphorus Adsorption characteristics

of Selected South Eastern Nigeria

Soils: In proceeding of the 29th Annual

conference of the Soil Science Society

of Nigeria pg 121 – 131.

17


DEGRADATION EFFECT OF PALM OIL MILL EFFLUENT (POME) ON PHYSICAL

AND CHEMICAL PROPERTIES OF THE SOILS OF UGA,

SOUTH EASTERN NIGERIA.

PATIENCE. O. UMEUGOCHUKWU1, VICTOR O. CHUDE2 AND EZEAKU P.1

1Department of Soil Science University of Nigeria, Nsukka. 2National Programme for Food Security (NPFS)

Email: [email protected], [email protected], [email protected]

08033945009, 07066725984

ABSTRACT This study investigated the impact of long term application of palm oil waste on physical and

chemical properties of a sandy Ultisols (Arenic Kandiustult) in Uga, Nigeria. Soil samples were

collected from the surface (0-10cm) and subsurface (15-25cm) of palm oil polluted site. Another

surface (0-10) and subsurface (15-25) samples were collected 15 meters away in the palm oil

unpolluted (control site). Core samples were from both soils. All the samples were analyzed for

selected physical and chemical properties. The result showed that both soils were loamy sand but

varied in the other physical properties as bulk density and total porosity. The two soils were

strongly acidic, but had more carbon, nitrogen and phosphorus in the palm oil polluted soils than

in the unpolluted soils. The result indicated that the area affected with the palm oil mill effluent

(POME) had more nutrient status but reduced plant growth due to clogging of water and

restricted aeration. The other forms of land degradation identified in the area were erosion,

deforestation, bush burning, and sand quarrying. Efforts at combating land degradation by the

Uga indigenes in order to protect their land from environmental devastation should be

intensified. Knowledge of the component and proper disposition of these pollutants should be

made known to the people of Uga.

Keywords: Keywords: Degradation; Palm oil mill effluent; food security; Environmental

hazards

INTRODUCTION Palm oil processing is carried out in mills where oil is extracted from palm fruits. Large quantities of water are used during the extraction of crude palm oil from the fresh fruits and about 50% of the water results in palm oil mill effluents (POME). It is estimated that for 1 tonne of crude palm oil produced, 5-7.5 tonnes of water will end up as POME (Ahmed et al., 2003). It has been observed that most of the POME produced by the small scale traditional operators in Uga undergo no

treatment and is discharged into the agricultural land that is used for arable farming (Umeugochukwu, 2001). This effluent is a serious land and aquatic pollutant when discharged immediately into the environment. Besides the presence of lipids and volatile compounds, the inhibitory effects of POME on living tissues, could also be due to presence of water-soluble phenolic compounds (Radzia 2001; Perez et al., 1992).

18

Effect of palm oil effluent on soils

mailto:[email protected]

Soil is a fundamental base for agricultural production system and therefore deserves to be seriously conserved. The relationship between the cropland degradation and food production deserves to be looked at very well. Land degradation problem is a serious problem confronting the people of Uga, in Anambra State. Land degradation is the diminution of soils current or potential capacity to produce food, feed and fiber as a result of one or more degradative processes. Understanding soil degradation, causes and processes are essential for better management of the soil. The importance of maintaining or improving the soil physical and chemical properties in agriculture has been reported by many researchers. Lal and Greenland (1977) stated that the development of stable and viable system of soil management in tropical region with a harsh climate or environment must be based on a thorough understanding of the soil physical and chemical condition, if it were to be meaningful. Ahn (1974) considered that the physics of the soil was as important as its chemistry and that any chemical shortcoming might be made good simply by adding the necessary fertilizer; but no amount of nutrient would make up for poor soil physical properties. Soil structural conditions are important if, for example, yield responses of agricultural crops to fertilizer inputs are to be optimized (Smith et al, 1989). POME is the most polluted organic residue generated from palm oil. It is composed of high organic content. Untreated POME contains high concentration of free fatty acids, proteins and plant tissues but it is non toxic (Ngan et al., 1996). It has a high biological oxygen demand BOD which makes it more polluting than other domestic sewage (Okwute et al, 2007). Palm oil mill effluents had been discovered by the people of Malaysia as better organic compost for agricultural production than chemical fertilizer after treatment to remove the oil in the effluent ( APOC, 2004). The situation at Uga is contrary as no plant was found growing on the area where the effluents were disposed. This study is to

investigate the effect of POME on soil physical and chemical properties and suggest a better way of disposing the effluent to enhance food production and security.

MATERIAL AND METHODS The area under investigation is located within longitude70 4’E and latitude 63 56’N. It is about 32km south of Awka, Anambra state capital. The study area falls within humid tropical zone. The two major seasons in the area are wet and dry season with the former lasting for 8 months (April- October) and the latter for 4 months (November-March). The average annual rainfall is 1485.2mm with maximum temperature of 350 C. The temperature is generally high and rarely falls to 210 C throughout the year. The mean annual temperature ranges from 270C-350C (Badiane, 2009). The relative humidity ranges from 40%-92%. The vegetation of the area is rain forest with mainly grassland and savannah vegetation. The dominant land uses are cereal and arable cropping systems. The soils are classified as an ultisol (Arenic Kandiustult) bases on USDA soil classification system (Umeugochukwu, 2010). Soils of areas affected with palm oil effluents and another area not affected by the effluent were collected and analyzed.

Soil sampling method Soil sampling: Soils of the two sites (polluted and unpolluted) were collected from 0-15 and 15-25cm depth. For purposes of analysis, the surface samples were composite separately from the sub surface samples. Undisturbed core samples were collected from the surface (0-10cm) and subsurface (15-25cm) of palm oil polluted and unpolluted site. The unpolluted samples were collected 15 meters away from the palm oil polluted site and all were analyzed for selected physical and chemical.

Laboratory Analysis Methods The samples were taken to the laboratory in well labeled polyethene bags. They were air

19

Umeugochukwu, Chude and Ezeaku NJSS/22(1)/2012

dried and sieved to pass through 2mm sieve. The fine earth fraction was analyzed for the following physical and chemical properties; physical properties selected include: Particle size distribution- Sand, Silt and Clay; Bulk Density, Porosity. Chemical properties were pH, Organic Carbon, Total Nitrogen, Available P, C.E.C, and Exchangeable Cations (Ca2+, Mg2+84 , Na+ and K+85). Particle size analysis was determined by Gee and Bauder (1986) method. The textural classes were determined from the USDA soil textural triangle. Bulk density was obtained by the method of Blake and Hartge (1986). Total Porosity was calculated from the values of the bulk density using the method described by Vomicil (1965). Soil pH was obtained in 1:25 soil/water extract of the composite samples according to Mclean (1982) method. Available P was determined by the Bray 2 extract Olsen and Sommers (1982). Cation Exchange Capacity (CEC) was determined by the NH4OAC displacement method and exchangeable acidity by titrimetric method after extraction with 1.0N KCl (McLean, 1982). Total exchangeable bases (Ca2+, Mg2+, Na+ and K+92 ) were determined using 1N NH4OAC extrantant method ( Thomas, 1982), where Ca2+ and Mg2+ 93 were obtained on an Atomic Absorption Spectrometer; Na+ and K+ 94 by flame photometer. Base saturation was calculated from TEB/CEC x 100, where TEB = total exchangeable bases. Soil organic carbon (OC) was determined by Nelson and Sommer (1982) method. Soil organic matter was obtained by multiplying percentage carbon by 1.724. Total nitrogen was determined by the macro-Kjeldhal method of Bremmer and Mulvaney, (1982).

Statistical Analysis The statistical analysis consists of descriptive statistics and paired sample T-test. Descriptive statistics shows the means of the chemical and physical properties of the different soils (polluted and unpolluted soils.) The paired t-test compared the differences in mean among the two sites.


Impact of the POME on the Soil. Preliminary observation shows that pollution of the soil with palm oil waste and other domestic wastes was prominent in the study area. It affected land use in terms of plant growth. There was little or no plant seen growing on the area polluted with POME even though it contained more nutrients than the unpolluted site. There was more siltation on the polluted site which was as a result of clogging of the pore sizes which of course restricted aeration. The lack of air in these area as predicted could possibly result to lack of plant growth despite the nutrients contained in the POME. The impact of this pollution is mostly felt in wet season when it forms a suitable breeding ground for most vectors of diseases.

Physical properties The particle size distribution results in table 1 indicated that the fine earth fractions were dominated mainly by sand followed by clay and silt in both soils. The textural classification of the two soils was loamy sand. The mean values of the clay (11.0%), total sand (81.5), and coarse sand (32.0) collected from both soils indicated that the highest values were obtained from the unpolluted soils. The polluted soil had higher mean silt content of (7.5) than the unpolluted soil of (1.5). The top soil of the polluted site recorded more sand fraction than its sub layer which is the same trend with the unpolluted site. The subsurface layers in both soils had more clay content. Their clay mean values were 11.0 and 12.5 in the polluted and the unpolluted soils respectively. The trend of the silt content varied. It was more in the top soil of the polluted site than the unpolluted site (Table 1).

Bulk Density, Total Porosity and Pore size distribution: The bulk density values were obtained from both top and sub soils of the two soils. The bulk density value obtained from the top soil of the polluted site ( 1.2 g/cm3) was lower than that of the top soil of the unpolluted soil (1.4 g/cm3). The bulk densities and total porosity, values averaged

20


1.2 g/cm3, 52%, 35%, 17% respectively and the unpolluted soil values were 1.45 g/cm3, 45%, 35%, 10% respectively. The mean bulk density of the polluted soil is lower than the mean bulk density of the unpolluted soil Table 2. The polluted soil with lower bulk density recorded higher total porosity than the unpolluted soil with higher bulk density.

Chemical properties The soil pH was generally low. It ranged from 4.8-4.9 H20 for all the soils. The mean value of the pH for the two soils was the same (4.3) (table 3). The soils were extremely acidic. There was no significant difference in the pH of the two soils. The mean values of soil organic matter (1.82%) was higher in the palm oil polluted soil than in the unpolluted soil (0.86%). The values increased with depth in the palm oil polluted soil and decreased with depth in the unpolluted soil (Table 1). The topsoil of the palm oil polluted soil had 1.72% and 1.93% organic matter in the sub layer while the unpolluted soil had 0.97% in the topsoil and 0.76% in the subsurface. The differences in mean was significant (P>0.05). the values of the polluted soil and the unpolluted soils were statistically different. The two soils had high amounts of available phosphorus. The mean values of the two soils were 62ppm and 56ppm for polluted and unpolluted soils respectively. The polluted had more P than the unpolluted soil. There was no difference in the trend of distribution of phosphorus in the top soil and the sub soil of the polluted and unpolluted soils. There was no significant difference in the available phosphorus of the two soils. The mean values of the ACEC and ECEC in the polluted soil was 1.15, 2.3 and 1.47,2.5 in the unpolluted sample respectively. The differences were not significant at P>0.05. The base saturation had mean value of 73% in the polluted soil than in the unpolluted soil (57%). The exchangeable acidity mean value for the both soils was of the same value (2.0).

For both soils in the polluted and unpolluted sites, mean exchangeable Na was 0.15meq/100g and 0.10meq/100g, 0.45 meq/100g and 0.35 meq/100g of K, 0.5 meq/100g and 0.4 of Ca, in polluted and unpolluted soils respectively. Mg had mean value of 0.3 in both soils. Na, K and Ca had higher mean values in the polluted soils than in the unpolluted soils.

DISCUSSION The relatively high sand content in the area is the reflection of the effect of the sandy parent material. The dominance of sand size particles would have emanated from the presence of such particles in the parent material of the soils. The parent materials of the soils of eastern Nigeria have been noted to influence the texture of the soils derived from them (Akamigbo and Asadu cited in Asadu and Agudosi (1994). The relatively higher clay content in the subsurface layers in each site may have resulted from the process of eluviation from the upper horizons. The low clay content observed in the upper layers of these soils may further indicate the degree of weathering and leaching that the soil has undergone (Asadu et al; 2008). The higher silt content observed in the upper layer of the polluted soils may be due to the effect of palm oil mill effluent. This can be attributed to reduced floatation of silt particles in runoff and hence reduced carting away of silt particles by overland flow. However the soils of these areas are inherently low in silt content (Akamigbo, 1984) essentially due to low content of these particles in the original parent material. A test of mean difference carried out to compare the mean values of the particles size analysis data between the two soils, however showed that the mean clay, silt and sand contents were significantly different at P>0.05. Thus the palm oil mill effluent (POME) influenced the particle size distribution in the soil significantly. Salimon (2007) noted that the impact of POME on the physical properties of soil depends on the method of application.

21


POME retards growth of cowpea at the early stage, enhances nodulation when applied in a controlled manner and inhibits nodulation when applied in a large quantity. He also noted that it can be used as organic fertilizer material to improve degraded sandy and low organic matter soils. The lower bulk density in the palm oil polluted soil can be attributed to the accumulation of palm oil effluent in this soil. The bulk density value was lowest on top of the polluted site showing that the effect is more at the zone of application. As you go down the sub layers, the effect reduced. Palm oil mill effluent contains a lot of organic materials of low bulk density (Harrison, 1995) and so impacts this property to the soil. There was increase in the values of the bulk density down the layers both in the polluted and the unpolluted soils. Increase in total porosity is often correlated with decrease in bulk density. This was observed in the samples of the polluted and unpolluted soils where the mean total porosity was lower in the polluted soil than the unpolluted soil. The paired t-test showed significant difference in the samples from polluted and unpolluted soils. The mean t-test of porosity was significantly higher in the unpolluted soil than in the polluted soil at P>0.05. It has been reported that when raw POME is discharged, the pH is acidic (Hemming, 1977) but seems to gradually increase to alkaline as biodegradation takes place. Soil acidity is one of the principal factors affecting nutrient availability, therefore availability of major nutrients (N,P,K) cannot effectively promote high yields of crops if soil pH is not correct. The uniformity in the soil pH indicated that the POME had started undergoing degradation. The low pH noticed in the POME could be as a result of presence of phenolic acids and oxidation of the organic acid compounds (Nwoko, 2010). The higher values of organic matter in the polluted soil confirms the report of ( Falodun et al, (2010). He observed that POME contains

relatively high amount of plant nutrients. This may also be due the accumulation of the effluent on the soil. This is the reason POME can be used for growing crop and amending soil fertility depletion. Nwoko (2010) reported that POME amended plots gave higher maize height that significantly differed from that of control. Similarly, POME application with resultant positive yields may be attributed to the ability of the pome to stimulate the activity of micro organism in the subsisting soil/plant environment. The available phosphorus is more in the polluted soil than in the unpolluted soil. The palm oil mill effluent affected the availability of phosphorus in the polluted soil. The higher mean value of phosphorus in the polluted soil is in line with the work of Haun (1987) which suggest possibly high absorption in the soil or a possible precipitation of phosphate. He also said that there is a good evidence that suggests that phosphorus is the dominant element controlling carbon and Nitrogen immobilization. The uniformity in the pH reflected in the available P as acid soils tend to fix phosphorus. According to Rhodes (1982) CEC usually expressed in meq/100g is a measure of quantity of readily exchangeable cations neutralizing negative charges in the soil. The high values of the CEC in the POME showed that the soil is enriched with the following exchangeable bases: Ca, Mg, Na and K due to the presence of POME in the soils. Increase in CEC could be attributed to increase in pH dependent charges as well as addition of organic matter from the effluent as observed by Okwute (2007). The CEC and the exchangeable acidity had no difference in the two soil but the base saturation showed significant difference at p>0.05 in the two soils. The base saturation average value of more than 50% confirms the reason the soil is fertile. The higher value of B.S in the polluted soil is an evidence of higher fertility than the unpolluted soils.

22


CONCLUSION The first impression that could be got from POME soil environment was that of bareness and a wasted land. The absence of vegetation was not surprising since the POME soil’s ability to retain water could cause clogging of soil pores and hence water logging of the soil (Chan et al, 1980). Excess water in the soil restricts micro-organisms and their activities by preventing oxygen movement into and

through the soil in sufficient quality to meet the oxygen demand of the organism. From the data generated in the study, it is obvious that the physical and chemical properties of the POME soils is different from that of the non POME. Since the POME has been shown to be acidic in nature, it is advisable to be treated before application to the soil. Proper use of POME could lead to improved soil fertility and soil structure.

Table 1: The selected physical properties of the polluted and unpolluted soils Designation Depth

(cm)

Clay

(%)

Silt

(%)

T.sand

(%)

F.S C.S B.D T.P T.C

Polluted Soil Top polluted 0-10 10 8 82 48 36 1.2 54 Loamy

Sub polluted 15-15 12 7 81 40 28 1.3 50 Sand

Unpolluted Soil Top unpolluted 0-1 11 1 88 44 36 1.4 47 Loamy

Sub unpolluted 15-25 14 2 84 40 32 1.5 43 Sand

Table 1.2: The chemical properties of the polluted and unpolluted soils. Depth

(Cm)

pH C

(g/kg)

O.M

(g/kg)

N

(g/kg)

Av.P

(mg/kg)

Exchangeable Bases

(cmol/kg)

C.E.C

(cmol/kg)

B.S

(%)

Exch.

Acidity

(cmol/kg)

Na+ K+ Ca2+ Mg2+ ACEC ECEC AL3+ H+

Polluted soil

0-10 4.9 1.12 1.72 0.08 62 0.02 0.06 0.6 0.4 1.3 2.66 83 0.2 0.1

15-25 4.9 1.00 1.93 0.06 62 0.01 0.03 0.4 0.2 1.0 1.94 64 0.2 0.1

Unpolluted soil

0-10 4.8 0.57 0.97 0.09 56 0.01 0.04 0.4 0.3 1.05 2.10 75 0.2 0.1

15-25 4.8 0.44 0.76 0.05 56 0.01 0.03 0.4 0.3 1.9 2.94 39 0.2 0.1

Table 2: Mean value and T value/significant levels of soil physical properties of polluted

and unpolluted soils in Uga.

Parameter Mean Std. Dev. Std. Error M.D T-Value

Clay P1

P2

T. Sand P1

P2

C.S P1

P2

Silt P1

P2

11.0

12.50

81.50

86.00

32.00

34.00

7.50

1.5

1.41

2.12

0.71

2.83

5.66

2.83

0.71

0.71

1.00

1.50

0.50

2.83

4.00

2.00

0.50

0.50

-1.50

-4.50

-2.00

6.00

-3.00

-3.00

-1.00

6.00

B.D P1

P2

T.P P1

P2

1.25

1.45

52.00

45.00

7.07

7.07

2.83

2.83

5.00

5.00

2.00

2.00

Legend: T. Sand = total sand, C.S = coarese sand, B.D = Bulk Density, T.P = Total porosity.

23


Table 3: Mean value and T value/significant levels of soil chemical properties of polluted and unpolluted soils in Uga. Parameter Mean Std. Dev. Std. Error M.D T-Level -Value/sig pH P1 P2 Carbon P1 P2 Av.p P1 P2 Exch. Mg P1 P2 Nitrogen P1 P2 Org. M P1 P2 Exch. Ca P1 P2 Exc. Na P1 P2 B.S P1 P2

4.9 4.8 1.06 0.51 62.00 56.00 3.00 3.00 0.07 0.07 1.82 0.86 5.00 4.00 0.015 0.010 73.50 57.00

0.00 0.00 8.48 9.19 0.141 0.00 0.11 0.23 0.12 0.12 1.41 0.00 0.005 0.000 10.97 20.70

0.00

6.00 6.50

1.00 0.00 0.05 0.11 0.06 0.06 1.00 0.00 0.002 0.000 5.48 10.39

0.55

5.55

0.00

0.96

1.00

0.005

16.50

111.00

0.00

0.00

7.918

1.00

1.732

3.362

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field textures in a humid tropical environment.’ Soil Survey and land Evaluation, Vol. 4

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Asadu C.L.A, and Agudosi, H.C (1994). A

comparative study of soils inside and outside ogbunike cave in Eastern Nigeria; Discovery and Innovation Vol.6 no 4. Pp367-371.

Asadu, C.L.A, Ucheonye-Oliobi, B. and

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Nigeria: Impact on soil morphological and physical properties, outlook on Agriculture Vol 37, No 1.Pp 63-69.

Bremmer, J.M and C.S. Mulvaney, (1982).

Total N,P.895-926. In Page et al (eds) Methods of Soil Analysis. Part 2. 2nd ed. Agron. Monog. 9 ASA and SSSA, Madison WI.

Chan, K.W, Watson, I., Lim, K.C (1980). Use

of Palm oil waste material for increased production. Paper presented at the Conference on Soil Science and agricultural development in Malaysia, Kuala Lumpur.

Falodun E.J, Osaigbovo A.U and Remison

S.U. (2010). Effect of Palm oil mill Effluent and NPK15:15:15 fertilizer on the growth and yield of soya bean.

Gee, G.W and Bauder, J.W (1986). Particle

size Analysis.P.383-411. In: Klute, A (ed). Methods of Soil Analysis part 2, 2nd ed Agronomy Monograph No 9,ASA and SSSA, Madison, WI.

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Haun, K.C. (1987). Trials on long term effect of application of POME in soil properties, oil palm nutrition and yield. In; proceedings of the international oil palm, palm oil conferences (eds) 575-598.

Lal, R,and Greenland, D.J. (1977). Soil

Physical properties and Crop Production in the tropics, John Wiley, New York, pp 7-9.

Mclean, E.O (1982). Soil pH and Lime

Requirement. P. 199-224. In: Page et al (eds) Method of Soil Analysis part 2. Chemical and microbial properties. 2nd 288 ed. Agron. Monog. 9 ASA and SSSA, Madison WI.

Nelson, D.W., and Sommers, L.E (1982).

Total Carbon, organic carbon and organic matter, in page, et al ed, method of soil Analysis, part 2, 2nd 291 ed Agronomy Monograph No 9,ASA and SSSA, Madison, WI, pp 539-579.

Ngan, M.A, Zajima, Y. Asahi M.,and Junit H

(1996). A novel treatment process for palm oil mill effluent. PORIM TECHNOLOGY, October 1996.

Nwoko, C.O (2010). Evaluation of Palm oil

mill effluent to maize (Zea mays. L) crop: yields, tissue nutrient content and residual soil chemical properties, Australian Journal of Crop Science.

Okwute, O.L and Isu, N.R (2007). Impact

analysis of palm oil mill effluent in aerobic bacterial density and ammonium oxidizers in a dump site in Anyamgba, Kogi State. African Journal of Biotechnology Vol 6 (2) pp 116-119.

Olsen, S.R and Sommers, (1982). Phosphorus.

P 403-434. In page et al (eds), method of soil Analysis, part 2, 2nd ed Agronomy Monograph No 9,ASA and SSSA, Madison, WI.

Perez J, de la Rubia T, Moreno J, Martinez J

(1992) Phenolic content and antibacterial activity of olive oil waste

waters. Enviro. Toxicology Chem. 11: 489-495.

Radziah O (2001) Alleviation of Phytotoxicity

of Raw POME by microorganism retrieved Sept, 2005, fromwww.agri.upm.edu.my/agrosearch/v3n2/irpa3.htm

Rhodes, J.O. (1982). CEC in A.L page R.H

Miller and D.R keeney (eds) methods of soil analysis, part 2, Chemical and microbial properties. Madison Wisconsin: pp 149-157.

Salimon, B.O, (2007). ‘The effect of palm oil

mill effluent (POME) on soil properties, growth, Nodulation and yield of cowpea (Vigna Unguiculata) in palm oil producing zone of Nigeria’ paper presented at the annual meeting of the Soil and Water Conservation Society, Saddlebrook Resort, Tampa, Florida <Not Available>. 2010-06-04 from http://www.allacademic.com/meta/p174308_index.html

Smith, S. R, Hail, J. E, and Hadley, P. (1989).

Composting Sewage sludge wastes in relation to their suitability for use as fertilizer material for vegetable crop production. International Symposium of Compost Recycling of wastes, 4-7 October, Athens.

Thomas, G.W. (1982). Exchangeable cations,

Pp 159-165. In page et al (eds) Method of soil Analysis, part 2, 2nd ed Agronomy Monograph No 9,ASA and SSSA, Madison, WI

Umeugochukwu, O.P and Akamigbo, F.O.R.

(2010). Soil Degradation as a prelude to Land degradation and Environmental Reserves in Uga, Aguata L.G.A of Anambra State. Nigeria. Proceedings of the 44th annual conference of Agricultural Society of Nigeria, ‘LAUTECH,ogbomosho, 2010’ pp1390-1393.

Vomicil, J. A. (1965). Porosity, In Black, C.A

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25


IMPACT OF SOIL EROSION ON LAND DEGRADATION IN UGA

SOUTHEASTERN NIGERIA

*O. P UMEUGOCHUKWU1, P. I. EZEAKU1, V. O CHUDE2, and G. U. NNAJI1 1 Department of Soil Science, University of Nigeria, Nsukka.

2National Programme for Food Security (NPFS)

*Corresponding author: [email protected], [email protected]

ABSTRACT

This study was to investigate the causes and hazard of soil erosion in Uga, Anambra State as the

area is always having the problem of erosion. This study was carried out in some selected

erosion sites in Uga. The study investigated the impact of soil erosion on land degradation and its

environmental hazards in Uga Southeastern Nigeria. Two profile pits were prepared, one on

severely degraded (eroded) sites and the other on less severely degraded (eroded) sites. They

were morphologically described and sampled. Surface soil samples were collected from the

erosion sites that were controlled at the depth of (0-25cm) and (25-50cm) to check the effect of

the control on the soils. Some physical and chemical properties of the soil were determined.

Morphologically, the soils were deep and well drained with no concretions or mottles. The

colour variations ranged from brown (7.5YR 4/4) to dark reddish brown 7.5 R 3/3 for the profile

pits. The soils varied in texture from fine loamy sand to sandy clay loam. The structures varied

from hard to weak coarse crumb to friable. The Bulk Density values (B.D) were relatively high

1.4g/cm2 – 1.6g/cm3. The infiltration was rapid ranging from 10cm – 150cm/2. Chemically they

were strongly acidic and low in nutrient status. The pH was low between 3-9-5.1. Nitrogen

ranged from 0.01 – 0.12%. Erosion affected significantly the phosphorus, pH and Al3+ Heavy

metals values were low. Other forms of land degradation identified in the area were bush

burning, sand quarrying, deforestation etc. Management practices such as use of organic

amendments, minimum tillage and crop rotation could help in the conservation of the soils and

ensure food security for further generations.

Keywords: Degradation, erosion, food security, hazards, sustainability.

INTRODUCTION

Soil degradation is the temporary or permanent

lowering of the productive capacity of the soil.

Soil erosion process is a serious problem

confronting Uga people in Anambra State. Soil

erosion by water is a major type of soil

degradation, not just in Nigeria but in the

tropics. It occurs most often as a result of human

activities like deforestation, overgrazing,

building orientations and/or natural activities

like soil types, topography, climate etc. The

major causes of land degradation are as a

result of land misuse and poor land

management practices. Land degradation

which has been defined as the loss of utility or

potential utility of land or the decline in soil

quality caused through misuse by humans

(Barrow, 1992) is posing more threat to our

future than military aggression.

26

Impact of soil erosion on land


The impact of environmental problems in

Anambra State is very severe and needs

adequate attention (Akamigbo, 1996). They

have soil types and climate which accelerate

erosion processes. Erosion may dissect the

land by forming deep gullies. The scenario is

typical in Nanka and Ekwulobia of Anambra

state. (Akamigbo, 1996). Gully erosion not

only reduces the land area for agricultural

purposes but also threatens the buildings of the

inhabitants of the area where it occurs. In

Anambra state, studies by the task force on

soil erosion control revealed that 10% of the

land area is occupied by gully erosion of all

types. This must have increased by now. Soil

erosion affects agriculture by selective

removal of plant nutrient and removal of

organic matter by wind or water.

Efforts made in the past to combat the

problem even by the state government and the

village people could not make much meaning.

The erosion sites are still on the increase. The

investigation carried out in the study area

revealed that the most severe site studied

started developing like six years back.

There is need not only to investigate the causes

of the problems of land degradation but also to

investigate the effect of soil erosion on

agricultural production and make

recommendations on how to ameliorate them

in order to secure food and sustain the

environment. This study is aimed at examining

the nutrient status of the severely eroded, less

severely eroded sites and also the controlled

site.


Study Site.

This study was conducted on two different

types of erosion sites. One site was located on

erosion site that was very severely eroded and

the second site was on a less severely eroded

site. Surface samples were collected from an

erosion site that has been controlled. The area

is located between latitude 50 56’N and 50 57’N

and between longitude 70 4’E and 70 06'E. The

area falls within the humid tropical zone of

southeastern Nigeria with average annual

rainfall of about 1485mm and mean annual

temperature that ranges from 27 to 350C and

rarely falls to 210C throughout the year. The

relative humidity ranges from 40 to 92%

(Badiane 2009). The vegetation of the area is

rainforest with mainly grasslands. The natural

vegetation of the area consists mainly of

secondary forest. The major land use types in

the study area are arable crop production, cash

crop production and non agricultural uses such

as residential, commercial and local roads.

Two profile pits were sited. One pit each on

the severely eroded site and less severely

eroded site respectively. Auger samples were

collected at the depth of 0 - 25cm and 25 -

50cm depth to check the effect of the control

measures on the soil, physical and chemical

properties. Core samples were collected from

around the profile pits for physical property

analysis.

Laboratory Analysis

The samples were air dried and sieved to pass

through 2mm sieve. The fine earth fraction

was analyzed for the following parameters.

Particle size analysis was carried out by

hydrometer method.

The textural classes were determined from the

USDA soil textural triangle. Bulk density was

obtained by CORE method. Total Porosity was

calculated from the values of the bulk density

using the method described by Vomicil

(1965). Soil pH was obtained in 1:25

soil/water extract of the composite samples

according to Mclean (1965) method.

Available P was determined by the Bray 2

extract. Cation Exchange Capacity (CEC) was

determined by the NH4OAC displacement

method and exchangeable acidity by titrimetric

method after extraction with 1.0N KCl

(McLean, 1965). Total exchangeable bases

(Ca2+, Mg2+, Na+ and K+) were determined

using 1N NH4OAC extractant method, where

Ca2+ and Mg2+ were obtained on an Atomic

Absorption Spectrometer; Na+ and K+ by

flame photometer. Base saturation was

27

Umeugochukwu, Chude and Nnaji NJSS/22(1)/2012

calculated from TEB/CEC x 100, where TEB

= total exchangeable bases. Soil organic

carbon (OC) was determined by dichromate

method. Soil organic matter was obtained by

multiplying percentage carbon by 1.724. Total

nitrogen was determined by the macro-

Kjeldhal method (Bremmer 1965).

Infiltration rates were determined in the field

using the double ring cylinder infiltrometer

method. Heavy metals Pb, Zn, Cu and Fe were

also determined. The determination was done

on the top layers of each site since that is

where the concentrations of the heavy metals

are more and the surface sample is where

arable farming is done. The concentration of

individual metals was measured with atomic

absorption spectrometer (AAS) after wet

digestion with HNO3 for Pb and a mixture of

HNO3 and HCL for iron (Bruce and White

side, 1984).

Statistical Analysis

The statistical analysis consists of descriptive

statistics and ANOVA with Duncan multiple

range test. Descriptive statistics show the

means of the chemical properties of different

eroded soil (severely eroded, less severely

eroded and eroded but controlled soil). The

ANOVA compared the differences in mean

among the three sites.

RESULTS AND DISCUSION

Causes of Soil Erosion in the Area.

When a man tries to modify the land for his

own use, he changes and upsets the natural

balance thereby resulting to erosion. One of

the major causes of erosion in this place is

indiscriminate building orientation which is a

result of land tenure system. Land tenure

system is a system of land ownership by

individual which means that people are forced

to use the land to build based on the shape of

their land and not based on whether it will

cause erosion. Other causes identified were

indiscriminate removal of vegetative cover.

Akamigbo (1986) said that major factors of

soil erosion in Anambra state are bush burning

together with indiscriminate removal of

vegetative cover. The people are involved in

bush burning, overgrazing, deforestation,

quarrying of sand and intensive cropping. This

is to combat the teeming population density of

about 1500-2200 which is too much for an

area of 1sqkm. The soil type of the area which

is sandy soil derived from sand stone parent

materials and the climate of the area explains

why the area is prone to erosion. The

topography of the area is another reason why

the study area had erosion. The entire area is

located on a slope. The people irrespective of

the slope still carry out their continuous

cropping on the land. Akamigbo (1996)

observed that 75% of gullies in Anambra State

had their origin in poorly executed civil works

with direct or indirect concentrated runoff.

This is similar to the case of the eroded but

controlled site that was examined. Agricultural

methods of controlling erosion should be

encouraged as it enhances soil structure and

also more sustainable

Soil Morphology.

The erosion had minimal effect on the

morphology of the soils. The soils were

derived from sandstones and are generally

deep and well drained. The colour variation

ranging from deep brown (7.5YR 4/4) dry to

dark reddish brown (7.5 R 2/2) on the top soils

and orange (2.5YR 6/6) in the sub layers in the

severely eroded sites. In the less severely

eroded site the colour ranged from dark

reddish brown (7.5YR 3/3) in the top soil to

reddish brown (10R 4/4) in the sub soil. The

difference in colours of top soil and sub soil in

the two sites was as a result of erosion that has

washed off some soil particles. The structures

of the severely eroded site ranged from

medium crumb structure at the top layer to

strong moderate sub-angular blocky structure

in the sub layer. The less severely eroded site

had weak coarse crumb on the top layer and

strong moderate sub angular blocky in the sub

layers. The structures of the sub layers were

virtually the same but that of the top soils were

different because erosion has affected it. The

major differences were due to slope of the area

which was 12% and 2% in the severely and

28


less severely eroded soil. Akamigbo (1986)

noted that erosion deposits detached soils in

the lower area. The consistency was generally

non sticky to friable in the top layers and

sticky to plastic in the sub layers.

Physical Properties

Particle Size Distribution.

The particle size distribution indicated that the

two profile pits and the auger samples have

fine sand dominant over coarse sand. Textural

classifications are Sandy clay loam, Sandy

loam, and Loamy sand. This could be

attributed to the type of parent material of the

area (Akamigbo and Asadu, 1983). The clay

content of the soils ranged from 8% to 34%

(Table 1). The upper horizons had lower clay

content which could be attributed to the runoff

of the surface caused by high rainfall and

slope. The coarse sand was decreasing with

depth at 50cm in the first profile but was not

so in the other samples. This could be

attributed to the nature of lithology of the

parent material. The samples have low silt

content indicating the extent of weathering

(Akamigbo, 1984). They also have higher

quantity of fine sand which is due to the age of

those areas as attested by their weathering

index f.s/c.s (fine sand/coarse

sand=73/16=4.56). In AP of UG/02 profiles,

the fine sand ranges from 40-73 while the

coarse sand ranges from 14-36 and it is

decreasing with depth. The findings further

confirm the observation of Obi and Asiegbu

(1980) that the low clay and silt content of

surface soil horizons in this area were

attributed to the high detachability and

transportability of these lighter soil materials.

The low content of silt and clay is essentially

due to the low content of these properties in

their parent materials (Akamigbo and Asadu,

1983)

Bulk Density and total porosity The bulk density values are relatively high. It

ranged from 1.2g/cm3-1.6g/cm3. The value

obtained from the top soils of the severely

eroded soil was (1.4 g/cm3) lower than the

bulk density values of the top soil of less

severely eroded site (1.6g/cm3). This could be

due to agricultural activities going on at the

less severely eroded site and again as a result

of soil and structure degradation. Mbagwu et

al (1985) observed that high B.D which tends

to loosen the structures is as a result of soil and

structure degradation. The top soil of severely

eroded soil had more O.M and so the reason

for lower B.D because O.M has the tendency

of reducing B.D. Increases in total porosity are

often correlated with decreased bulk density.

This was observed in these samples. The total

porosities of the samples are moderate ranging

between 39% and 54% and the values

decreased with depth due to little compaction

by overburden pressure of the materials on the

surface. The pore space in UG/02 of 39% is

less than that in UG/01 of 54%. This could be

attributed to the resultant effect of intensive

cultivation which leads to compaction.

Compaction reduces the pore spaces and void

spaces making it difficult for water to enter the

soil or for plant to grow resulting to erosion.

Infiltration Rates.

The infiltration rates are rapid and moderately

high in the two pedons investigated ranging

from 60cm/hr to 150cm/hr (Table 1) in the two

pedons. In all, the steady states were reached

in about one hour. In the two cases, the

infiltration rates decreased with time. The

infiltration rates, as a function of time is an

indication of the observed textural pattern of

the soil encountered. The infiltration rates are

moderate to high, which could be as a result of

the nature of the parent materials, which is

sandstone.

Chemical Properties

Table 2 shows that all the chemical properties

were generally low in both sites and even in

the auger samples. The values obtained from

the less severely eroded site were higher than

the ones obtained from the severely eroded site

indicating that erosion has really affected the

site more than the other.

Soil pH

The soil pH was generally extremely low

ranged from extremely acidic to strongly

29


acidic for both the less severely eroded site

and the eroded but controlled site with their

values ranging from 3.9-5.1 in the both sites.

The pH in the severely eroded site is extremely

acidic with the values ranging from 4.0 - 4.1.

The pH values in the less severely eroded site

and the eroded but controlled site are lower

than that in the severely eroded site showing

that they are less acidic than the severely

eroded site. The acidic level of the severely

eroded soil is significantly greater than the

acidic levels of the eroded but controlled and

less severely eroded soil (Table 3). The high

acidic level of the less severely eroded soil

than that of the eroded but controlled soil

could be attributed to farming activities, since

there is bound to be addition of inorganic

fertilizers. The high acidity in the eroded sites

could also be in accordance with the findings

by Akamigbo and Igwe (1990) that high

acidity is recorded in many eroded soils which

facilitates erosion process because the basic

elements which usually influence aggregation

are lost when soil reaction is in the strongly to

extremely acidity of these soils. This could be

responsible for high aluminum saturation and

very low calcium and magnesium content of

the soils (Table 2). There is equally significant

difference in the aluminum and hydrogen

content of these soils (Table 3). The

implication is that it will take a longer time to

increase the pH if a crop that is not tolerant to

low pH is to be planted there. The control also

helped in increasing the pH of the area.

The Organic Carbon and Total Nitrogen

The organic carbon was higher especially in

the top layer of the severely eroded soil than in

the less severely eroded site. It ranged from

very low to high in all. The values ranged from

0.21% - 2.01% in the severely eroded site and

0.37 – 1.16% in the less severely eroded site. It

was decreasing with depth except in the less

severely eroded site, where may be illuviation

or leaching has taken place. The rainfall

intensity and cultivation have contributed to

leaching of the organic carbon deeper to the

last layer where the plants cannot access it.

The Ap horizon of the severely eroded site

recorded higher organic carbon because the

place was left fallow since erosion was almost

claiming the place and accumulation of plant

debris increased organic matter content.

Morgan (1979), regarded soils with less than

2% organic matter as erodible. The severely

eroded site had more than 2% organic content

on its top layer yet more severely eroded. This

indicates that organic matter is not the only

factor that determines erodibility. The reason

for this very site being much eroded could be

majorly due to slope of 12%, the soil type and

the farming activities going on there.

Total nitrogen values ranged from very low to

moderately low in the two soils. The values

ranged from 0.01 – 0.12%. The highest value

was recorded in the severely eroded soil. The

values were decreasing with depth due to

mineralization by high temperature and

leaching since nitrogen is soluble. No

significant difference between the less

severely eroded soil and eroded but controlled

soil because of the parent material of the area

is same. This is so because the effect of the

erosion on the control site is more on

recovering the lost nutrients. There is the

tendency that it will increase with time when it

must have been fully recovered.

Exchangeable Bases, Exchangeable Acidity,

C.E.C and Base Saturation.

For both soils, the severely eroded, less

severely eroded and eroded but controlled

sites, the exchangeable bases were generally

low. Na ranged from 0.01- 0.03meq/100g of

soil, K ranged from 0.01-0.12meq/100g of

soil, Ca ranged from 0.1- 1.6meq/100g of soil,

and Mg ranged from 0.2- 1.0meq/100g of soil.

The eroded but controlled site recorded higher

Mg2+ content than the rest of the soils. This

could be the effect of the control given to the

place. The low levels of this could be

attributed to the texture and structure together

with the environment of the study area. The

control reduced the erodibility of the bases.

Low exchangeable bases in erosion prone area

have been confirmed by Mbagwu (1986). The

exchangeable acidity is low ranging from 0.1 -

0.4 cmol/kg the values could be due to parent

30


material of the area. The effective cation

exchange capacity (ECEC) and apparent

cation exchange capacity (ACEC) of the

studied soils are very low and may be due to

clay composition of the area. Kang and Juo

(1981) referred to such soils as low activity

clay soils (LAC).

The percentage base saturation values are

generally low to high and ranged from 14%-

73%. The high base saturation values of the

soils could be attributed to properties inherited

from the local parent material. Akamigbo and

Asadu (1986) showed that parent materials

have a strong influence on total exchangeable

bases and total acidity of soils.

Available Phosphorus.

The values of available P from severely eroded

site ranged from 34-53mg/kg and 42-87mg/kg

in the less severely eroded soil. The values are

moderate to high which could be attributed to

the element being present in the parent

material. The high values could be attributed

to the result of inorganic fertilization by

farmers in the less severely eroded and organic

deposits in the severely eroded sites. The

profile at the less severely eroded site had

significantly higher phosphorus than the others

probably due to fertilizations. However,

available phosphorus is usually low in high

acid soils which tend to fix phosphorus by

forming insoluble aluminum phosphate

(Unamba – Opara, 1990).

Heavy Metals.

Lead was only identified in the severely

eroded site and the value was 8.89ppm with

AAS. The value is below hazardous level. Iron

value was 11.7ppm for both the severely and

less severely eroded site. The type of iron

analyzed was Fe2+. Zinc value was 5.2ppm in

the severely eroded site and 4.16ppm in the

less severely eroded site and 5.85ppm in the

eroded but controlled site. Copper value in the

severely eroded site was 1.64ppm and

0.82ppm in the less severely eroded site (Table

2). There was no cadmium identified in the

area. Heavy metal components of the samples

were low and these values may be influenced

by the content in parent material as well as the

human activities of the area. The highest

concentration of these metals (Pb, Fe, Zn, Cu,

Cd) are recorded in the Ap horizon of the

UG/01 pedon. The higher values of these

metals in the area could be attributed to the

higher organic matter content of that area:

because Wild (1996) said that organic matter

absorbs cadmium, copper, and lead but more

of lead and copper than cadmium which is

evident in the study area. Soil pH generally

plays an important role in the availability of

metals, toxicity and leaching capability to

surroundings (Chimuka et al 2005). Heavy

metals are mostly more soluble and leached in

acidic soils.

Erosion Control Measures

So far efforts are in progress to see that the

area is rescued from the incidience of erosion

hazards. Local materials like bamboo trees,

elephant grasses (Pennisetum purpurem ),

diversion ditches and sand bags are used to

construct barriers in the area prone to erosion.

Government efforts through the Task Force on

soil Erosion Control have contributed to

erosion control by constructing culverts and

other measures to see that erosion is combated

some sites have been controlled before but due

to the type of soil and topography of the area

aided by anthropogenic activities of man in the

area, the gully is increasing despite all the

efforts to control it.

CONCLUSION

Erosion was identified as the major land

degradation problem in Uga town of Anambra

State. There are differences in physical and

chemical properties and also the heavy metal

in the soils of severe degradation and less

severe degradation. The soils of severe erosion

recorded higher values of exchangeable

acidity, %clay, %silt, heavy metals than the

site with less severe erosion. The bulk density

is lower than that of the less severe

degradation. It must be borne in mind that the

soils are naturally poor in chemical attributes

and degradation of land is prominent in Uga

31


and the degradation potentials are high loss of

nutrients, poor structures e.t.c. If nothing is

done to it now, one day the whole land may be

lost to erosion. To ensure continuous usage of

the land and at the same time derive maximum

returns from the land and preserve it for future

use, sound conservation measures are very

essential. So every Uga indigene should be

encouraged to participate in the restoration of

the land to avoid these stated hazards.

RECOMMENDATIONS

Government and the village should enact a law

that will mandate the indigenes to use the

correct building orientation to build houses

and also stop quarrying of sands.

Rural Policy on agricultural land uses should

be made and enforced so that there would be

reduced misuse of the land.

Creation of awareness through mass education

about the soils of the area will help to let the

people know the implications of using it

wrongly.

Soil conservation should be made a

multidisciplinary course involving every

discipline

Conservation team should form a monitoring

team that will be visiting all corners of the

town and report any case that needs urgent

attention. Defaulters of conservation rules

should be sanctioned. An effective engineering

construction must be preceded by appropriate

environmental impact assessment studies. The

existing gullies should be reforested.

32


Table 1. Physical properties of representative profiles and auger samples

Horizon Depth

(cm)

Clay

(%)

Silt

(%)

Total

sand

(%)

Fine

Sand

Coarse

Sand

Textural

classe

Infiltration Rates

Severely

eroded

Less Severely

eroded

B.D

g/cm3

T.P

(%)

Time

(min)

IR Time

(min)

IR

Severely Eroded soil 2 150 3 100

Ap 0-24 16 7 77 41 36 SL 3 100 2 150

AB 24-42 26 1 73 57 16 SCL 2 150 3 100

Bt1 42-69 26 3 71 55 16 SCL 3 100 4 75 1.2 54

Bt2 69-128 34 1 65 51 14 SCL 2 150 5 60

Bt3 128-165 34 3 63 47 15 SCL 2 150 4 75

Less Severely Eroded soils 2 150 4 75

Ap 0-13 8 3 89 73 16 Sand 4 75 4 75

AB 13-67 11 2 87 57 30 LS 4 75 4 75 1.6 39

Bt1 67-120 12 1 87 55 32 SL 4 75

Bt2 120-200 17 1 82 52 29 SC 3 100

Eroded but controlled soils 5 60

A1 0-25 12 1 87 58 29 LS 3 100

A2 25-50 14 1 85 53 31 LS 5 60

5 60

5 60

5 60

5 60

Legend: A1 and A2: Auger point controlled sites, SL: Sandy loam, IR Infiltration Rates

SCL: Sandy clay loam, LS: loamy sand, SC: Sandy Clay B.D, Bulk Density, T.P, Total porosity.

33


Table 2. The Chemical properties of the representative profiles and auger samples and the heavy metal contents

Hori Depth

(Cm) Ph C

(g/kg)

N

(g/kg)

Av.P

(mg/kg)

Exchangeable Bases

(Cmol/Kg)

C.E.C

(Cmol/kg)

B.S

(%)

Exch, acidity

(Cmol/Kg)

Na+ K+ Ca2+ Mg2+ ACEC ECEC AL3+ H+ Pb Fe Zn Cu Cd

Severely Eroded Soil

Ap 0-24 4.0 2.01 0.12 53 0.01 0.06 1.6 0.4 2.8 5.4 73 0.3 0.2 8.89 11.7 5.2 1.64 trce

AB 24-42 4.0 0.87 0.07 37 0.01 0.03 0.4 0.2 2.2 3.44 29 0.2 0.4

Bt1 42-69 4.0 0.50 0.04 39 0.01 0.03 trace 0.2 1.7 2.54 14 0.2 0.4

Bt2 69-128 4.1 0.25 0.02 47 0.01 0.01 trace 0.6 1.8 2.92 33 0.1 0.4

Bt3 128-

165

4.1 0.21 0.01 41 0.01 0.03 trace 0.2 1.2 1.84 20 0.2 0.2

Less severely eroded soil

Ap 0-13 4.2 1.08 0.09 87 0.01 0.12 0.2 0.4 1.8 2.83 40 0.1 0.2 trace 11.70 4.16 0.82 trace

AB 13-67 3.9 0.62 0.05 59 0.02 0.03 0.2 0.2 1.8 2.62 24 0.2 0.2

Bt1 67-

120

4.1 0.37 0.03 42 0.01 0.03 0.4 0.2 2.0 3.04 32 0.1 0.3

Bt2 120-

200

4.0 1.16 0.01 76 0.01 0.02 0.4 0.2 1,5 2.43 42 0.1 0.2

Eroded but controlled soil

A1 0-25 5.1 0.87 0.08 51 0.01 0.06 0.4 1.0 1.9 3.57 32 0.1 0.1 trace 5.85 5.85 1.23 trace

A2 25-50 4.5 0.62 0.05 42 0.01 0.04 0.1 0.2 1.6 2.25 22 0.1 0.2

34


Table 3: Statistical table showing the F-values and significant values of the chemical

properties analyzed.

Variable F-Value Eroded but

controlled

Less severely

eroded

Severely eroded

pH 15.444** 4.80a 4.05b 4.04b

Carbon 0.009NS 0.745 0.768 0.808

Nitrogen 0.001NS 0.45 0.45 0.052

Phosphorus 3.525* 46.50b 66.00a 43.40b

Sodium 0.845NS 0.01 0.125 0.01

Potassium 0.437NS 0.05 0.05 0.032

Calcium 0.081NS 0.250 0.30 0.40

Magnesium 1.417NS 0.60 0.25 0.32

ACEC 0.206NS 1.750 1.775 1.940

ECEC 0.272NS 2.91 2.73 3.23

B.S 0.141NS 27.00 34.50 28.04

Al3+ 2.876* 0.100 0.125 0.200

H+ 3.092* 0.150 0.225 0.320

Legend: * and ** = P< 0.05 and 0.01 percent significant levels, NS= not significant,n=2,4,5

for eroded but controlled, less severely eroded and severely eroded respectively. D.f=1.

REFERENCES Akamigbo, F.O.R and Asadu, C.L.A, 1983.

The accuracy of field textures in a

humid tropical environment. Soil

Survey and land Evaluation 4(3); 63-

70.

Akamigbo, F.O.R and Asadu, C.L.A. 1986.

The influence of toposequence some

soil parameters in selected areas of

Anambra state, South-Eastern Nigeria.

J. of Soil Science 6: pp 35-46.

Akamigbo, F. O. R 1984. The accuracy of

field textures in the humid tropical

environment. Soil Survey and Land

Evaluation, 4(3) 63-70.

Akamigbo (1986) Guide on erosion control.

Star printing publishing co; Uwani Enugu

1:21pp

Akamigbo, F.O.R 1996. Major Environmental

problems and their impacts in Anambra

State. An invited paper presented at the

1st stakeholder workshop on

Anambra State environmental action

plan, Ikenga, Hotel, Awka, Anambra

State. Organized by Santon

Consultants, Lagos.

Badiane A. 2009. Executive Summary of

Structure Plans For Awka, Onitsha And

Nnewi And Environs 2009-2027. United

Nations Human Settlements Programme

publications can be obtained from un-

habitat Regional Information Offices or

directly from Nairobi Kenya.

http://www.unhabitat.org/pmss/getElec

tronicVersion.asp?nr=2684&alt =1

Barrow, C. J. 1992. Land Degradation.

Cambridge Univ. Press, New York.

Bouyoucos, C. J. 1951. Direction for making

mechanical analysis by the hydrometer

method. Soil Sci. 42; 25-229.

Bray, R. H. and L. T Kurtz 1945.

Determination of total organic

carbon and available forms of

phosphorus in soils. Soil Sci. 59; 39-

45.

Bremmer, J.M 1965; Total Nitrogen in C.A.

Black methods of soil analysis, part I. Am Soc. Argron.9; 1149-2278.

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http://www.unhabitat.org/pmss/getElectronicVersion.asp?nr=2684&alt =1

http://www.unhabitat.org/pmss/getElectronicVersion.asp?nr=2684&alt =1

Bruce, A M and Whiteside, P. J 1984.

Introduction to Atomic Absorption

Spectrophotometer, 3rd ed, Pye Unicam

limited, England. 150pp.

FAO 1977. Guidelines on profile description

Rome.

Jackson, M. C. 1958: Soils Chemical

Analysis. An advance Course

University of Wisconsin, U. S. A.

Kang, B. T. and Juo, A.S.P. 1981.

Management of low acidity clay (LAC)

soils in tropical Africa for food crop

production workshop, Kigali, Kwanza.

June 2nd -12th.

Mbagwu, J.S.C 1986. Effects of soil erosion

on the productivity of agricultural

lands in Humid tropics Beitrage trop.

Landwritch.Verterinarmeat.24:H.2 161

-175

Mclean, E. O. 1965. Aluminum. Methods of

Soil analysis part 2. Ed. C. A. Black.

Am. Soc. of Agronomy.

Morgan, R.P.C 1979. Tropic in applied

Geography. Soil erosion.Longman

Group ltd, London pp.39-41.

Obi, M. E. and Asiegbu, J. O. 1980. The

physical properties of some eroded

soils of south-eastern Nigeria’, Soil

Science, Vol 130, pp 39 – 48.

Soil Survey Staff, 2010 Keys to Soil

Taxanomy. United States Department

of Agriculture (USDA), 9th ed. P 263-

285.

Unamba-Opara, I. 1990, 1988. Lecture

discussion Department of Soil Science,

University of Nigeria, Nsukka.

Vomicil, T. A. 1965. Porosity. In C. A. Black

(ed.), Methods of Soil Analysis Part 1.

American Soc. of Agron. 9:299-314.

Walkley, A. and I. A. Black 1934.

Determination of organic carbon in

soil. Soil Sci 7; 29-38.

Wild, A. A 1996. Soils and the environmental:

An introduction. Cambridge

University press U.K.

36


CHARACTERIZATION OF PHOSPHORUS STATUS IN SOILS OF THE GUINEA

SAVANNA ZONE OF NIGERIA.

S.O. AMHAKHIAN1 AND I.O.OSEMWOTA2 1Department of Soil and Environmental Management, Kogi State University,

Anyigba. Kogi State

08064469673: email [email protected] 2Department of Soil Science, Ambrose Alli University, Ekpoma, Edo State

ABSTRACT This study was undertaken in Kogi State of Nigeria to determine: the various phosphorus forms in the soils; Twenty composite surface soil samples (0-15cm depth) drawn from two distinct geological formations (Cretaceous sediments and Basement complex) were used for the study. These soils were collected from different sites with varying cropping history. The soils were analysed for physical and chemical properties. Total and organic P were determined by standard laboratory procedure while inorganic P forms by fractionation. Available p ranged from 1.57 to 23.52mg/kg with a mean of 7.58mg/kg while Organic P content ranged from 18.94 to 171.00mg/kg and from 24.31 to 485.93mg/kg with means of 56.56 and 134. 94.mg/kg for Cretaceous Sediments and Basement complex Soils, respectively. Total P content ranged from 28.94 to 320mg/kg with mean of 188.36mg/kg. Eighty five percent of the soils were deficient in available Bray P1 extractable P based on established critical level of 15mg/kgP for Nigerian soils. Total P and organic P were a bit high in these soils and were in the following order: Ca-P>Fe-P> Saloid-P>A1-P. INTRODUCTION Phosphorus is one of the major elements and it is second in importance to nitrogen in terms of nutrient requirement for increased crop production in most tropical soils. Phosphorus determination is an important factor to be considered in the evaluation of soil fertility. The quantity and relative distribution of various forms of P are of great importance to soil genesis and fertility studies. Enwezor and Moore (1966) worked on some savanna and forest soils and provided the first phosphorus fractionation of Nigerian soils using Change and Jackson’s procedure. They found that over half of the extractable phosphorus was present as iron phosphorus, the remainder being made up of approximately equal quantities of aluminum and calcium phosphates. Klleinman et al. (1999), noted that the distribution of P

was closely related to the pedogenetic evolution of soils with the more matured soil having low P status. They observed that the distribution of the active fraction (Al-P, Fe-P and Ca-P) and their abundance in soil are dependent on pH, the solubility product of the different phosphate, the cations present and the degree of weathering.

Loganathan and Sutton (1987) and Ibia and Udo (1993) in their work reported the influence of parent material on the forms and distribution of P in southern Nigeria and concluded that soils formed on coastal plain sands and sandstones parent materials were more weathered than those on alluvium, beach sands and shale parent materials. Udo (1985) observed a wide variation in the abundance of

37

Amhakhian and Osemwota NJSS/22(1)/2012

total P ranging from 68 mgkg - 1 in some acid coastal plain sands to over 2000mgkg-1 in soils derived from basaltic rocks and detail deposits. Also Uzu et al. (1985), Udo and Dambo (1987), Loganathan and Sutton (1987) and Ibia and Udo (1993) found that the relative abundance of the active inorganic P fractions decreased in the order Fe-P> AI-> Ca – P in most Nigeria Soils. There is paucity of information as regards P status in soils of Guinea Savanna of Kogi State. Hence, the first objective of this study was to study the distribution of phosphorus status in some soils of guinea savanna of Kogi State of Northern Nigeria and the second objective was to determine the various forms of P in the soils of the area under study,.

MATERIAL AND METHODS The study area, Kogi State, lies between latitude 50 151 to 70 451 North and Longitude 50 451 and 80 451 east of the equator. Twenty surface soil samples (0-15cm) were collected from pre-classified sites. The twenty composite soil samples were used for the physical and chemical properties (routine analysis) determination and the contents of various forms of phosphors in the soils. Total P was extracted by the perchloric acid digestion method (Jackson, 1994) and the organic form by the ignition method as described by Legg and Black (1955). Inorganic P was sequentially fractionated using the procedure outlined by Chang and Jackson (1957) as modified by IMPHOS (1980) to exclude the occluded and reductant-soluble forms. Available P was extracted with acid fluoride using the Bray P-1 and Bray P-2 method (Bray and Kurtz, 1945). Phosphorus in each extract was determined colorimetrically by the blue colour method of Murphy and Riley (1962). RESULTS AND DISCUSSION Forms and Distribution of P. The results of phosphorus distribution in soils of Guinea savanna of Kogi State are shown in Table 1. Available Phosphorus The content ranged from 1.57 to 23.52 mg/kg with an average of 7.58 mg/kg. Based on the critical level of 15mg/kg, 85 percent of the soils were deficient in available phosphorus

(table 1). Available phosphorus was generally low, thus indicating the poor phosphorus fertility of the guinea savanna soils. Apart from soils of Ganaja, Eni (Ogori-Mangogo), Abejukolo and Idah all other soils were generally below the critical level of 15mg/kg established for Nigerian Soils. Effective cation exchange capacity and pH were positively and significantly correlated with available P with “r” values of 0.551* and 0.452*, respectively (Table 2). Available P and Saloid P were positively and significantly correlated with “r” value of 0.992***. Organic Phosphorus. This varied within each geological formation and between the geological formations based on their parent materials. The mean values of organic phosphorus forms were calculated to be 76.94. Organic P constituted between 87 to 93% of the total phosphorus, the least content was obtained in Ikanekpo (18.94 mg/kg P) while the highest organic P in soils formed on the Basement complex was obtained from Eni (485.50 mg/kg P). Effective cation exchange capacity and pH were positively and significantly correlated with organic P (Table 2). Total Phosphorus. In Table 1 total phosphorus contents of the soils were generally low indicating the poor phosphorus fertility of the soils. Generally total P content ranged from 28.94 to 320 mg/kg P with a mean of 188.36 mg/kg P. The low phosphorus content of some tropical soils has been attributed to low apatite content of the soil forming minerals (Guzel and Ibrika, 1994). Parent rocks of the soils studied consisted mainly of schists, granite gneisis and sandstones, all of which have low apatite inclusion; parent material may also offer an explanation for the observed differences in total P values between the soils since matured soils possess low P values (Enwezor, 1977), the low P content of these savanna soils, in addition to the low apatite content, may be due to their maturity. Inorganic Phosphorus. The distributions of various forms of inorganic phosphorus in the soils studied are shown in Table1. The content of Al-P was low; it varied from 0.06 to 0.60 mg/kg P in the soils with a mean of 0.18mg/kg. Al-P was positively and

38

Phosphorus status in soil

significantly correlated with clay (r = 0.534*). Saloid P (part of total active P) was generally low, it ranged from 0.06 to 44.28 mg/kg P with a mean of 3.39mg/kg P. Saloid P contributed little to total P and was positively and significantly correlated with pH and ECEC (r = 0.505* and0.668** respectively). The Fe–P content was higher than that of Al–P in all the soils. Fe–P content ranged from 0.06 to 33.25 with a mean of 3.94mg/kg P. Fe-P was positively and significantly correlated with clay and Fe2O3 contents (r = 0.833** and 0.487* respectively). The higher amount of Fe-P of all the other active fractions is expected since the soils were essentially slightly acidic. Ca-P content was generally low, except in soils of Ikanekpo, Idah, Ofunene, Ihima and Ehika as would be expected in soils of the savanna regions. Ca–P content was higher than Fe-P and Al-P. The low amount of Ca-P found in these soils may be due to possible conversion of Al-P and Fe-P in the acidic to slightly matured soils of these ecological zones. The preferential formation of Ca-P relative to Al-P neutral in acidic soils has been reported by Lindsay and Moreno (1960). The contribution of this fraction to total extractable inorganic P ranged from 0.66 to 25.27 mg/kg P with a mean of 6.71mg/kg in the soil. Ca-P was positively and significantly correlated with clay (r = 0.534*). Occluded Fe and Al-P content of the soils ranged from 0.13 to 8.11 with a mean of 1.31. It contributed very little to total P. It was positively and significantly correlated with clay and Fe2O3 with “r” values of 0.685** and 0.596**, respectively. Reductant P content for the soils ranged from 0.19 to 9.71 mg/kg P with means of 0.50mg/kg P. It was positively and significantly correlated with organic matter and Fe2O3 (r = 0.531* and 0.527*, respectively). Although residual P formed a dominant proportion of inorganic P, it was still very low. The low fraction of residual P in some soils may be attributed to lack of factor

responsible for retaining P in the non-extractable form. The relative amounts of inorganic P fractions had been used to assess the extent of pedogenetic processes. On the Chang and Jackson (1958) scale, the observed distributions of the inorganic P forms indicated that all the soils were moderately weathered and are capable of fixing reasonable proportion of the existing small amounts of the native soil phosphorus in relatively unavailable form. The Ca-P was more in amount than Fe-P, which in turn were greater than Saloid P, occluded P and Al-P. The abundance were in the following order: Ca-P = Fe-P > Saloid-P > Occluded Fe > Al-P. This sequence of abundance of the inorganic fraction was also observed by Uzu et al., (1975). Correlation coefficients among the phosphorus forms and between soils physio-chemical properties are shown in Table3. Saloid P. was positively and significantly correlated with active-P, Organic-P and available-P (r = 0.537*, 0.794** and 0.992***, respectively). Fe-P was positively and significantly correlated with active-P and reductant-P (r = 0.681* and 0.862** respectively). Ca-P had a positive and significant correlation with active-P (r = 0.615**). Active-P was also positively and significantly correlated with reductant-P, organic-P and available-P (Table3). CONCLUSION The result shows that soils in guinea savanna of Kogi State differ in their phosphorus status in relation to the parent materials. Various P forms correlated with available P indices. 85% of the soil in the zone were deficient in available P. This means that the area will require P fertilizer for cropping, thus justifying the need for routine soil test for P in order to achieve fertilizer best practice for crop production.

39


Table 1 Phosphorus forms in Soils of Kogi State. S/N Location Saloid P Al – P Fe – P Ca – P Active – P Red –P Occlu. Occlu

P Fe&AlP

Res. P

Org. P Total P Avail Bray

P1Extra Table

1. Anyigba 0.46 0.13 1.13 1.58 2.87 0.53 0.53 0.26 293.46 53.91 351.10 2.86

2. Abejukolo 7.19 0.13 4.85 0.85 13.02 0.59 0.59 2.30 65.18 171.00 244.90 20.42

3. Ajaka 0.39 0.06 1.33 1.98 3.76 0.71 0.71 0.26 241.76 61.06 307.16 9.00

4. Ikanekpo 1.32 0.13 1.59 16.49 19.53 0.66 0.66 0.59 278.30 18.94 316.70 10.01

5. Umomi 0.52 0.26 0.06 1.12 1.96 0.39 0.39 0.13 310.09 63.41 386.46 8.00

6. Ochaja 0.52 0.13 1.79 0.79 3.23 0.39 0.39 0.19 230.44 36.39 270.12 7.57

7. Idah 1.71 0.33 33.25 22.30 57.57 0.73 0.73 8.11 44.77 48.02 157.5 19.00

8. Odenyi 0.39 0.06 2.19 3.63 6.93 0.66 0.66 1.32 164.84 104.32 277.02 3.50

9. Okpo 0.19 0.19 1.59 2.64 4.61 0.53 0.53 1.25 472.11 24.09 502.40 9.29

10. Kontokarfi 1.10 0.13 1.46 3.72 6.41 0.62 0.62 1.20 297.93 30.06 335.12 6.24

11. Ofunene 0.33 0.13 1.59 25.27 27.32 0.79 0.79 0.59 50.95 81.29 108.61 2.86

12. Obehira 2.17 0.19 1.66 0.85 4.87 0.19 0.19 0.13 31.38 52.62 87.52 3.14

13. Ihima 0.39 0.13 2.19 22.57 25.28 0.53 0.53 0.13 99.73 51.58 176.86 2.21

14. Ishanlu 0.39 0.13 2.32 8.64 11.48 0.66 0.66 0.92 18.81 63.85 95.33 3.00

15. Ayetorogbede 0.72 0.13 3.12 0.66 4.63 0.53 0.53 0.06 07.14 24.31 98.94 10.36

16. Mopa-Moro 0.06 0.19 3.15 1.45 5.15 0.19 0.19 0.26 33.39 86.37 125.52 5.14

17. Ganaja 5.08 0.13 4.98 1.32 11.51 0.99 0.99 4.75 86.28 320.05 418.56 17

18. Ofere 0.33 0.60 4.65 2.04 7.68 0.73 0.73 0.72 48.88 81.57 140.19 1.57

19. Eni(OgoriMangogo) 44.28 0.14 3.12 1.05 48.59 0.86 0.86 1.45 102.99 485.93 595.54 23.52

20. Ehika 0.65 0.23 2.31 15.25 18.44 0.95 0.95 1.12 58.59 101.85 180.30 2.16

40


Table 2: Correlation Coefficient between P Forms and Soil Physcio-chemical Properties Total P Org P Sal. P Ca-P Al-P Fe-P Occ.Fe&A

l-P

Act. P Red. P Bray P1-

P

Clay -0.145 -0.044 -0.211 0.290 0.534* 0.830** 0.685** 0.545* 0.139 -0.044

Silt -0.335 0.323 0.296 0.128 0.144 0.285 0.185 0.397 0.810 0.323

pH -0.314 0.452* 0.505* -0.256 0.103 -0.153 0.007 0.111 0.036 0.452*

OM -0.380 0.375 0.185 0.188 0.202 0.325 0.385 0.373 0.531* 0.375

Al2O3 -0.122 -0.247 -0.194 0.333 -.089 0.367 0.266 0.229 -0.181 -0.247

Fe2O3 -0.081 0.271 0.167 0.001 0.380 0.487* 0.596** 0.335 0.527* 0.271

ECEC -0.196 0.551* 0.668** 0.342 0.185 0.142 0.079 0.685** 0.268 0.551*

* = Significant at 5% level of probability.

** = Significantly at 1% level of probability.

Table 3: Correlation Coefficient among forms of Phosphorus. Saloid-P Al-P Fe-P Ca-P Act-P Occl-P Red-P Total-P Organ-P Avail-P Resid.P

Saloid-P - - 0.095 0.004 - 0.187 0.537* 0.304 0.304 0.029 0.794** 0.992*** -0.130

Al-P - 0.351 0.033 0.126 0.044 0.147 - 0.309 - 0.0650 - 0.085 -0.209

Fe-P - 0.388 0.681** 0.186 0.862** - 0.176 - 0.172 0.033 -0.297

Ca-P - 0.615** 0.325 0.246 - 0.108 - 0.079 -0.165 -0.243

Act-P - 0.462 0.589* - 0.125 0.543* 0.568* -0.358

Occl-P - 0.467 0.168 0.523* 0.292 -0.187

Red-P - 0.0661 0.410 0.087 -0.325

Total-P - - 0.065 0.059 0.393

Organ-P - 0.748** -0.341

Avail-P - -0.083

Residual-P -

* = Significantly at 5% level of probability.

** = Significantly at 1% level of probability.

*** = Significantly at 0.1% level of probability.

41


Table 4 Physico-chemical properties of soils used for study Location % % % Textural

Class

pH(H2O) g/kg g/kg Mg/kg

Cmol/kg

Al203 Fe203

Kg

Clay Silt Sand OM N Ca Mg Na K H+ AL ECEC

Anyigba

Abejukolo

Ajaka

Ikanekpo

Umomi

Ochaja

Idah

Odenyi

Okpo

Kotokarfi

Ofunene

Obehira

3.40

4.40

4.40

3.40

2.40

3.40

15.40

5.40

4.40

3.50

9.40

2.40

6.50

4.50

3.50

4.00

3.50

3.00

10.50

14.50

6.50

4.40

5.00

6.50

90.10

90.10

92.10

92.10

94.10

93.66

74.10

80.10

89.10

92.10

85.60

91.10

Sand

Sand

Sand

Sand

Sand

Sand

Sandy Loam

Sandy Loam

Sandy Loam

Sand

Loamy Sand

Sand

5.88

5.45

4.63

6.00

5.35

6.42

5.34

6.30

6.62

5.01

5.60

6.90

17.20

13.20

4.90

5.50

3.30

7.10

2.50

12.20

15.00

6.10

11.80

6.70

6.20

5.60

2.00

2.00

1.00

2.20

6.60

5.20

66.60

3.00

6.00

4.00

5.51

0.54

1.28

0.54

0.55

7.73

24.50

12.8

0.92

1.32

0.54

0.54

4.08

2.72

1.92

4.16

2.72

2.40

6.96

5.66

5.04

2.72

10.16

2.96

2.00

0.56

1.20

1.84

1.52

1.08

3.44

1.60

1.76

0.56

3.52

2.24

2.84

0.84

0.66

0.78

0.84

0.72

0.91

0.84

0.97

0.84

0.66

0.84

0.35

0.84

0.08

0.05

0.15

0.11

0.54

0.17

0.19

0.84

0.13

0.19

0.20

0.50

0.30

0.60

0.20

0.60

0.50

0.20

0.60

0.50

0.30

0.70

0.20

0.50

0.40

0.20

0.60

0.10

0.30

0.50

0.40

0.80

0.20

0.70

7.63

5.99

4.56

7.66

5.54

4.88

12.65

8.92

9.96

6.27

14.98

7.64

45.50

34.00

25.60

36.70

31.00

43.50

52.00

23.70

34.50

46.60

32.50

49.00

6.50

2.50

1.50

7.50

6.00

2.65

26.50

11.00

16.50

18.00

5.50

4.10

Ihima

Ishanlu

Ayetorogbede

Mopa-Moro

Ganaja

Ofere

Eni

Ehika

3.40

3.40

3.90

6.90

3.90

5.90

1.90

3.10

84.50

5.50

9.00

10.00

6.00

10.00

12.00

6.80

48.10

91.10

87.10

83.10

90.10

84.10

86.10

90.10

Loamy Sand

Sand

Loamy Sand

Sandy loam

Sand

Loamy Sand

Loamy Sand

Sand

5.40

5.60

5.50

5.99

6.69

5.89

7.32

6.25

11.70

13.20

2.60

12.20

18.80

14.50

18.20

31.70

5.00

6.00

5.00

6.00

6.00

1.00

1.30

6.90

0.54

10.95

1.60

0.54

7.07

10.31

11.21

11.95

13.81

5.04

3.60

5.28

8.64

10.40

19.38

8.64

4.96

2.24

0.64

2.08

0.32

3.30

5.40

0.32

0.97

0.48

0.84

0.84

0.78

0.84

0.91

0.77

0.14

0.17

0.45

0.33

0.30

0.18

1.14

0.20

0.30

0.20

0.46

0.80

0.70

2.20

0.30

0.20

0.90

0.50

0.50

0.30

0.20

0.20

0.40

0.60

21.11

8.63

6.44

9.64

7.14

15.19

27.57

7.39

45.00

21.20

37.00

16.00

74.50

18.50

24.00

37.50

3.20

2.50

14.50

7.50

23.20

21.50

17.90

21.30

42


REFERENCES

Agbenin, J.O. and Agboola, A.A. (1986). Phosphorus Sorption by Three Cultivated Savanna Alfisols as Influenced by pH. Fertilizer. 37-42.

Bray, R.H. and Kurtz, L.T., 1945.

Determination of total, organic and available forms of phosphorus in soils. Soil Sci., 591: 39-45.

Chang, S.G. and Jackson, M.L., 1957.

Fractionation of phosphorus. Soil Sci., 84: 133-144.

Enwezor, W.O. and Moore, A.W. (1966).

Phosphorus Status of Nigerian Soils Science 102(5) 31 312-328.

Enwezor, W.O., 1977. Soil testing for

phosphorus in some Nigerian soils. 3. Forms of phosphorus in soils of southeastern Nigeria and their relationship to plant available phosphorus. Soil., 124: 27-33.

Guzel, N.N and Ibrika, H. (1994). Distribution

Fractionation of soil phosphorus in

particle size separation in soils of Western Turkey. Communication Soil

science and Plant Analysis. 25 (17 & 18) 2945-2958.

IMPHOS, 1980. Phosphorus in tropical soils:

assessing deficiency levels and phosphorus requirements. Scientific Publ. No. 2., World phosphate Institute, Paris.

Ibia, T. O. and Udo, E. J. 1993. Phosphorus

forms and fixation capacity of representative soils in Akwa Ibom State of Nigeria. Geoderma. 58: 95-106.

Jackson, M.L., 1964. Soil Chemical Analysis.

Prentice Hall, Englewood Cliffs, NY, 498 pp. Juo, A.S.R. and Ellis, B.G., 1968. Chemical and physical properties of iron and aluminum phosphates and their relationship to phosphorus availability. Soil Sci. Soc. Am. Proc., 32: 216-221.

Kleinman, P.J..A; Bryant, R.B. and Rad, W.S.

(1999). Development of Pedotransfer Functions to quantity Phosphorus Saturation of Agricultural Soil. Journal of Environmental Quality. 28: 2026-2030.

Legg, J.O. and Black, C.A., 1955.

Determination of organic phosphorus in soils. 11: Ignition method. Soil Sci. Soc Am. Proc., 19: 139-142.

Lindsay, W.L. and Moreno, E.C (1960).

Phosphate phase equilibria in soils. Soil Science Society of America proceedings. 24: 177-182.

Loganathan, P. and Sutton, P.M., 1987.

Phosphorus fractions and availability in soils formed on Different ecological deposits in the Niger Delta area of Nigeria. Soil Sci., 143: 16-25.

Murphy, J. and Riley, J.P., 1962. A modified

single solution method for the determination of phosphorus in natural waters. Anal. Chim. Acta., 27: 31-36.

Udo, E.J. 1985. Phosphorus status in major

Nigeria soils. In: Soil Testing, Soil Tilth and Post Clearing Land Degradation in the Humid Tropics. Proceedings of International Society of Soil Science (Commission IV and VI). Soil Science Society of Nigeria, Ibadan. Pp 90-103.

Udo, E.J. and Dambo, V.I., 1979. Phosphorus

status of the Nigerian Coastal Plain sands. J. Agric. Sci., 93: 281-289.

Udo, E.J. and Ogunwale, J.A., 1977.

Phosphorus fractions in selected Nigerian Soils. Soil Sci. Soc. Am. J., 41: 1146.

Uzu, F.O., Juo, A.S.R. and Fayemi, A.A.A.,

1975. Forms of phosphorus in some important agricultural soils of Nigeria. Soil Sci., 120: 212-218.

43


PHYSICAL AND CHEMICAL PROPERTIES OF SOILS IN KOGI STATE,

GUINEA SAVANNA ZONE OF NIGERIA

S.O. AMHAKHIAN1 AND I.O. OSEMWOTA2 1Soil and Environmental Management Department, Kogi State University, Anyigba

2Soil Science Department, Ambrose Alli University, Ekpoma, Edo State

ABSTRACT

This experiment was conducted in Kogi State. Twenty composite surface soil samples (0.15cm

depth) drawn from two distinct geological formations (Cretaceous sediments and Basement

complex) were used for study. These soils were collected from different sites with varying

cropping history. Particle size analysis of the soils used indicated a high proportion of sand, the

texture of the soils ranged from sand to loamy sand. All the soils used had very low organic

matter contents. Available P ranged from 1.57 to 23.52mg/kg with a mean of 7.58mg/kg while

organic P content ranged from 18.94 to 171.00mg/kg and from 24.31 to 485.93mg/kg with

means of 56.56 and 134.94mg/kg for Cretaceous Sediments and Basement complex soils

respectively. Total P content ranged from 28.94 to 320mg/kg with a mean of 188 36mg/kg.

Eighty five percent of the soils were deficient in available Bray P1 extractable P based on

established critical level of 15mg/kg P for Nigerian soils. Total P and organic P were a bit high

in these soils. Residual P was more in abundance of all the inorganic fractions. The levels of

micronutrients in most of the soils used were moderately high.

INTRODUCTION The study area which is Kogi State, lies

between latitutde 50 151 to 70 451 N and

longitude 50 451 and 80 451 East of the equator.

The mean annual rainfall ranges from

1.560mm at Kabba in West to 1.808mm at

Anyigba in the East. The dry season generally

extends from November to March. During this

period, rainfall drops drastically to less than

12.0 mm in any of the months. The

temperature shows some variation throughout

the years. Average monthly temperature varies

from 17oC to 36.2oC. The state has two main

vegetations; the forest savanna mosaic zone

and the southern guinea zone. The State has

two main geological formations; they are the

Basement complex rocks to the west while the

other half is on Cretaceous sediments, to the

North of the confluence and east of River

Niger. The state is known for cultivation of

arable crops such as yam, cassava, maize,

groundnut cowpea, but its soils like the most

soils in north central agricultural zone of

Nigeria have high erodibility, are structurally

weak, coarse textured with low organic matter

status. Specifically there is dearth of

information on the physical and chemical

properties of the soils in different agro-

ecological zones of Kogi State, specifically

with reerence to availability of phosphorus and

micro-nutrients, which are known to limit

performance of arable crops and are often not

supplied by chemical fertilizer. The objective

of this work is to evaluate the chemical

properties of soils in different locations of

Kogi State of Nigeria.

44

Properties of soil in Kogi State

MATERIALS AND METHODS Twenty surface soil samples (0-15cm) were collected from pre-classified sites (FDALR 1985). A composite surface soil sample constituted ten cores taken randomly from each of the sampling sites with the aid of auger and mixed into a bag. Two composite samples were taken from places indicated in Table 1. Samples were air dried, crushed with the aid of wooden roller and sieved through 2mm sieve and stored in plastic container with covers. Particle size was determined by hydrometer method. Soil pH was measured in a soil: water ratio of 1:1 with the aid of glass electrode pH meter, organic matter was determined by wet dichromate acid oxidation method, exchangeable bases (Ca, Mg, K and Na) were extracted with 1N NH4OAC buffered at pH7. The Ca and Mg were determined using atomic absorption spectro photometer, K and Na were read on flame photometer, exchangeable acidity was extracted with 1N KCL (Thomas, 1982) and determined by fitration with 0.05N NaOH using phenolphthalein as indicator. Nitrogen was determined by Macro Kjedahl method, effective cation exchange capacity (ECEC) was calculated by the summation of exchangeable bases (Ca, Mg. K and Na) and exchange acidity (Carter, 1993). Percentage

base saturation (PBS) was calculated by multiplying total exchangeable bases by 100 and dividing by ECEC. Extractable micronutrients (Mn, Fe, Zn and CU) were determined by double acid method. Dithionate extractable Fe and Al (Free Fe and Al oxides soils) were determined by method of Mehra and Jackson (1960). Total phsphorus was determined by perchloric acid (HCLO4) digestion method and organic phosphorus was determined by ignition method. Available P was estimated by Bray P-1 method.

RESULTS AND DISCUSSION Properties of the Experimental Soils: The physical and chemical properties of the soils used for the experiments are showed in Table 2 while the mean, range and coefficient of variation values of the properties are presented in Table 3. The micronutrient contents are shown in table 4. The texture of the two geological formations:- Basement complex soils and Cretaceous sediments ranged from sand to loamy sand. The clay, silt and sand contents ranged from 19.00 to 154.00g/kg, 30.00 to 145.00g/kg and 741.00 to 941.00g/kg with a mean of 45.00, 68.00 and 835.00g/kg respectively. They also have co-efficient of variations of 64.50g/kg, 46.70g/kg and 5.70g/kg, respectively (Table 3).

Table 1: Land use and Soil classification of sampling and experimental soils S/N Sampling

locations

Coordinates Land use Soil taxonomy

(USDA)

1 Anyigba 7o30’N/7o09’E Oil palm, cassava, mango, maize, yams and cashew

Typic Tropustult

2 Abejukolo 7o40’N/7o16’E Shrub, melon, oranges and groundnut Typic Hyplustult 3 Ajaka 7o09’N/6o49’E Bambara nut, tomatoes and yam Arenic paleustult 4 Ikanekpo 7o22’N/7o36’E Oil palm, yam and cassava Psammentic Haplustalf 5 Umomi 7o19’N/7o00’E Cashew, oranges, cassava and oil palm Rhodic Eutrustox 6 Ochaja 7o25’N/7o14’E Cashew, oranges, mango, coffee and cassava Typic Tropustult 7 Idah 7o06’N/6o43’E Pepper, cassava, yam and rice Typic Tropaqualf 8 Odenyi 7o47’N/7o02’E Sugarcane, cassava and mango Typic Hapludult 9 Okpo 7o12’N/7o31’E Cassava, oil palm and yam Arenic Paleustult 10 Kontokarfi 8o05’N/6o48’E Cashew, cassava and mango Typic Hapludult 11 Ofunene 7o27’N/6o40’E Grasses, cassava and yam Aquic Kandiustalf 12 Obehira 7o30’N/6o11’E Yam, cassava and melon Typic Haplustalf 13 Ihima 7o36’N/6o12’E Tomatoes, maize and oranges Typic Paleustalf 14 Ishanlu 8o16’N/5o48’E Cassava, maize and oranges Aquic Tropopsamment 15 Ayetoro-gbede 7o58’N/5o59’E Iroko tree, yams, and maize Kandic Ustropept 16 Mopa-Moro 8o05’N/5o54’E Fallow land consisting mainly of grasses Typic Haplaquept 17 Ganaja 7o46’N/6o44’E Cassava, maize and cashew Rhodic Ustropept 18 Ofere 7o25’N/5o46’E Yam, cassava, maize and iroko trees Typic Plinthustalf 19 Eni 7o26’N/6o10’E Cassava, yam and oranges Typic Haplaquepts 20 Ehika 7o40’N/6o25’E Cassava and maize Typic Haplustalf

Source: 1: Kogi State Agricultural Development Project Zonal Office Anyigba


2: College of Agriculture, Kabba, Kogi State.

The pH of the soils ranged from slightly

alkaline (7.32) to strongly acidic (5.01) in

reaction with a mean of 5.9 and coefficient of

variation (CV) of 11.35%. Kontokarfi location

recorded the lowest pH (5.01) while Eni

(Ogori Mangogo) the highest pH (7.32). The

pH was positively and significantly correlated

with Ca (r = 0.65**), ECEC (r = 0.584*) and

Mn (r = 0.510*). It was negatively and

significantly correlated with Bo (r = 0.567*).

The pH of most agriculture soils in the tropics

has been reported to range from 5.0 to 6.8

(Udo and Dambo, 1979). Organic matter

content ranged from 3.3g/kg to 31.7g/kg with

a mean of 13.8g/kg and coefficient of variation

of 51.77%. These values of organic matter are

low when compared to values reported by

Enwezor et al. (1990). The critical level of

organic matter for optimum crop production

was given as 30g/kg (Agboola and Corey,

1972). The low value of organic matter

coupled with the sandy texture of the soil

would encourage a rapid leaching of cations

into the subsoil from the surface soils. The

soils were therefore low in ECEC and tended

to be low in available P and total nitrogen.

This is in agreement with earlier evaluation of

Balasubramanian, et al. (1984). Organic matter

was positively and significantly correlated

with Ca, Bo, extractable Mn and Cu with (r)

values of 0.644**, 0.681** 0.581** and

0.578* respectively. It was also negatively and

significantly correlated with Mg and

extractable Mn with (r) values of -0.644* and -

0.404* respectively (Table 5). Total nitrogen

content of both soils (Basement complex soil

and Cretaceous sediments) was low. Total

nitrogen content was below the critical level of

1.50g/kg for optimum maize production in

Nigeria (Agboola and Corey, 1972). The total

nitrogen content ranged from 0.01 to 1.20g/kg

with a mean of 0.06g/kg and co-efficient of

variation of 383.67% (Table 3). The soils are

deficient in total nitrogen. It has been

documented that temperature and moisture

have profound effects on nitrogen availability

through their effect on nitrogen mineralization,

transformation and movement (Adepetu and

Corey, 1985). Total nitrogen content of the

soil, was positively and significantly correlated

with ECEC, Mn and Fe with r values of

0.410*, 0.416* and 0.525* respectively. It was

negatively and significantly correlated with Ca

(r = -0.554*). Exchangeable calcium ranged

from 1.92 to 19.34 cmol/kg with a mean of

6.39 cmol/kg and a coefficient of variation of

70.52%. Exchangebale calcium was the

principal saturating cation being the mostly

abundant exchange cation in these soils and

occupied an average of 75% of the exchange

site. The critical level of exchangeable Ca was

given as 2.6 cmol/kg (Agboola and Corey,

1972). Based on this level, 20% of the soils are

deficient in exchangeable Ca Exchangeable Ca

was positively and significantly correlated

with ECEC, Al2O3. Zn and Mn contents with r

values of 0.836**, 0.475*, 0.585* and 0.508*

respectively. It was also negatively and

significatly correlated with Al2O3 content with

(r) values of -0.475* (Table 5).

Exchangeable sodium content of the soils

ranged from 0.48 to 0.94 cmol/kg with a mean

of 0.81 cmol/kg and conefficient of variationof

14.04% (Table 3). Exchangeable Na was

positively and significantly correlated with

copper contents with ‘r’ value 0.578*. It was

also negatively and significantly correlated

with Mo content with ‘r’ values of -0.495*

(table 3). Exchangeable magnesium content of

the soils ranged from 0.32 to 5.44 cmol/kg

with a mean of 2.03 cmol/kg and coefficient of

variationof 71.77% (Table 3). Exchangeable

Mg was positively and significantly correlated

with ECEC, Zn. Zn, Mn and Cu with ‘r’ values

of 0.449*, 0.553*, 0.451* and 0.460*,

45

46


respectively (Table 5). Exchangeable

potassium content of the soils ranged from

0.05 – 0.84 with a mean of 0.34 cmol/kg

(Table 2). It had a coefficient of variation of

90.35%. Exchangeable K was positively and

significantly correlated with ECEC and Zn

with ‘r’ values of 0.499* and 0.716**

respectively. It was also negatively and

significantly correlated with Bo, and Fe with

‘r’ values of -0.642** and -0.479**

respectively. The critical level of exchangeable

K for most crops was given as 0.20 cmol/kg.

Based on the value, 60% of the soils were

deficient in exchangeable K. The

exchangeable bases were in order to

abundance in the soils studied. They were of

the order Ca > Mg > Na > K. The soil

exchangeable acidity comprises of

exchangeable H+ and exchangeable Al3+,

exchangeable H+ ranged from 0.20 to 0.80

cmol/kg with a mean of 0.41 cmol/kg and

coefficient of variation of 48.07% (Table 3).

Exchangeable H+ was positively and

significantly correlated with Mn (r = 0.485*).

It was negatively and significantly correlated

with Zn and Cu contents (r = -0.557* and -

0.630* respectively. Exchangeable Al3+ values

ranged from 0.10 to 0.90 cmol/kg with a mean

of 0.45 cmol/kg. Effective cation exchange

capacity (ECEC) ranged from 4.56 to 27.57

cmol/kg with a mean of 12.85 cmol/kg and a

coefficient of variation of 58.28% (Table 3).

47


Table 2: Physico-Chemical properties of soils used for study Fe203

Location

% % % Textural

Class

pH(H2O) g/kg g/kg Mg/kg

Cmol/kg

Al203 Kg

Clay Silt Sand OM N Ca Mg Na K H+ Al ECEC

Anyigba

Abejukolo

Ajaka

Ikanekpo

Umomi

Ochaja

Idah

Odenyi

Okpo

Kotokarfi

Ofunene

Obehira

3.40

4.40

4.40

3.40

2.40

3.40

15.40

5.40

4.40

3.50

9.40

2.40

6.50

4.50

3.50

4.00

3.50

3.00

10.50

14.50

6.50

4.40

5.00

6.50

90.10

90.10

92.10

92.10

94.10

93.66

74.10

80.10

89.10

92.10

85.60

91.10

Sand

Sand

Sand

Sand

Sand

Sand

Sandy Loam Loamy Sandy

Loam Sand

Sand

Loamy Sand

Sand

5.88

5.45

4.63

6.00

5.35

6.42

5.34

6. 30

6.62

5.01

5.60

6.90

17.20

13.20

4.90

5.50

3.30

7.10

2.50

12.20

15.00

6.10

11.80

6.70

6.20

5.60

2.00

2.00

1.00

2.20

6.60

5.20

66.60

3.00

6.00

4.00

5.51

0.54

1.28

0.54

0.55

7.73

24.50

12.8

0.92

1.32

0.54

0.54

4.08

2.72

1.92

4.16

2.72

2.40

6.96

5.66

5.04

2.72

10.16

2.96

2.00

0.56

1.20

1.84

1.52

1.08

3.44

1.60

1.76

0.56

3.52

2.24

2.84

0.84

0.66

0.78

0.84

0.72

0.91

0.84

0.97

0.84

0.66

0.84

0.35

0.84

0.08

0.05

0.15

0.11

0.54

0.17

0.19

0.84

0.13

0.19

0.20

0.50

0.30

0.60

0.20

0.60

0.50

0.20

0.60

0.50

0.30

0.70

0.20

0.50

0.40

0.20

0.60

0.10

0.30

0.50

0.40

0.80

0.20

0.70

7.63

5.99

4.56

7.66

5.54

4.88

12.65

8.92

9.96

6.27

14.98

7.64

45.50

34.00

25.60

36.70

31.00

43.50

52.00

23.70

34.50

46.60

32.50

49.00

6.50

2.50

1.50

7.50

6.00

2.65

26.50

11.00

16.50

18.00

5.50

4.10

Ihima

Ishanlu

Ayetorogbede

Mopa-Moro

Ganaja

Ofere

Eni

Ehika

3.40

3.40

3.90

6.90

3.90

5.90

1.90

3.10

84.50

5.50

9.00

10.00

6.00

10.00

12.00

6.80

48.10

91.10

87.10

83.10

90.10

84.10

86.10

90.10

Loamy Sand

Sand

Loamy Sand

Sandy loam

Sand

Loamy Sand

Loamy Sand

Sand

5.40

5.60

5.50

5.99

6.69

5.89

7.32

6.25

11.70

13.20

2.60

12.20

18.80

14.50

18.20

31.70

5.00

6.00

5.00

6.00

6.00

1.00

1.30

6.90

0.54

10.95

1.60

0.54

7.07

10.31

11.21

11.95

13.81

5.04

3.60

5.28

8.64

10.40

19.38

8.64

4.96

2.24

0.64

2.08

0.32

3.30

5.40

0.32

0.97

0.48

0.84

0.84

0.78

0.84

0.91

0.77

0.14

0.17

0.45

0.33

0.30

0.18

1.14

0.20

0.30

0.20

0.46

0.80

0.70

2.20

0.30

0.20

0.90

0.50

0.50

0.30

0.20

0.20

0.40

0.60

21.11

8.63

6.44

9.64

7.14

15.19

27.57

7.39

45.00

21.20

37.00

16.00

74.50

18.50

24.00

37.50

3.20

2.50

14.50

7.50

23.20

21.50

17.90

21.30

48


Table 3: Correlation coefficient matrix of the relationships among soil variables Clay %silt %sand pH Om N pH Ca Mg Na K H Al ECEC Al2O3 Fe2O3 Mo Bo Zn Mn Fe

%Clay 0.25 -0.118 0.246 0.200 0.023 0.510* 0.050 0.234 0.065 0.030 0.097 0.329 0.118 0.152 0.322 -0.209 0.109 0.109 0.152 0.959*** -0.359

%Silt -0.007 0.269 0.397 0.041 0.433 0.209 0.159 0.201 0.200 0.180 0.179 0.637** 0.224 0.230 -0.517* -0.224 0.224 0.632*** 0.220 0.123 %sand 0.001 0.383 0.044 0.588* -0.522 0.201 0.378 0.149 0.054 0.080 -0.490 0.057 -0.334 0.476* 0.040 -0.039 0.479** 0.078 0.135

P%om 0.283 0.260 0.117 0.650** 0.178 0.238 0.108 0.279 0.230 0.584* -0.088 0.039 -0.004 .0567* 0.298 0.510* 0.078 0.017

N 0.076 0.532 0.644** 0.644* 0.151 0.231 0.175 0.082 0.227 -0.328 0.394 -0.404* 0.681** -0.066 0.581** -0.019 0.578* P -0.161 0.554* -0.036 0.338 0.097 0.211 0.226 0.410* -0.025 0.525* 0.416* 0.332 0.076 0.416** 0.525* -0.190

Ca 0.303 0.215 0.021 0.271 0.235 0.234 0.064 0.226 -0.124 0.045 0.080 0.495** -0.508 0.525* -0.315

Mg 0.363 0.274 0.307 0.278 0.014 0.836** 0.475* 0.241 -0.508* -0.330 0.585* 0.508* 0.025 0.253 Na 0.266 0.149 0.253 0.026 0.449* -0.041 0.686 -0.230 -0.050 0.553* 0.451* 0.246 0.460*

K 0.344 0.213 0.252 0.361 0.258 -0.094 -0.495* -0.139 0.203 0.031 0.006 0.578*

H 0.077 0.299 0.499* 0.078 0.479* -0.157 0.642* 0.716*** 0.221 0.159 0.078 Al 0.170 -0.243 0.740 -0.073 0.087 0.174 -0.557* 0.485* 0.475* 0.630*

ECEC 0.132 0.227 -0.350 0.179 -0.089 0.233 0.154 0.118 0.193

Al2O3 0.155 0.169 -0.315 -0.241 0.667* 0.475* 0.057 0.499* Fe2O3 -0.224 0.206 0.303 -0.080 0.554** 0.156 -0.339

Exch. 0.989*** 0.118 0.096 -0.376 -0.024 -0.054

Mo 0.149 -0.001 0.131 -0.251 -0.079 Exch.

Bo -0.385* 0.174 0.089 -0.198

Exch. Zn

Exch. 0.321 0.479** 0.509* Mn

Exch.

Fe 0.321* -0.078 Exch

Ca

0.301

*, ** and *** Significant at 5%, 1% and 0.1% level of probability.

49


The ECEC was positively and significantly

correlated with extractable Zn, Mn and Cu (r =

0.667**, 0.475* and 0.499* respectively).

However, ECEC had a non significant

negative correlation with Mo and Bo (r =

0.315 and -0.241 respectively) Available

phosphorus content ranged from 1.57 to 23.52

mg/kg with an average of 7.58 mg/kg. Based

on the critical level of 15 mg/kg, 85 percent of

the soils were deficient in avaialable P.

Available P had a very low coefficient of

variability of 7.15%. Available phosphorus

was generally low, thus indicating the poor

phosphorus fertility of the guinea savanna

soils. Apart from soils of Ganaja, Eni (Ogori-

Mangogo), Abejukolo and Idah all other soils

were generally below the critical level of

15mg/kg established for Nigerian Soils.

Effective cation exchange capacity and pH

were positively and significantly correlated

with available P with ‘r’ values of 0.551* and

0.452*, respectively (Table 3). Organic

phosphorus varied within each geological

formation and between the geological

formations based on their parent materials.

The mean values of organic phosphorus forms

were least in soils formed on Cretaceous

sediments when compared to that of the

Basement complex. The content of organic P

of Cretaceous sediments ranged from 18.94 to

171.00 mg/kg P with a mean of 56.56 mg/kg P

while that of the Basement complex soils

ranged between 24.31 to 485.93 mg/kg P with

a mean of 134.94 mg/kg P. Organic P

constituted between 87 to 93% of the total

phosphorus, the least content was obtained in

Ikanekpo (18.94 mg/kg P) while the highest

organic P in soils formed on the Basement

complex was obtained from Eni (485.50

mg/kg P). Total phosphorus contents of the

soils were generally low indicating the poor

phosporus fertility of the soils. Generally total

P content ranged from 87.52 to 595.79 mg/kg

P with a mean of 258.79 mg/kg P. The low

phosphorus content of some tropical soils has

been attributed to low apatite content of the

soil forming minerals. Parent rocks of the soils

studied consisted mainly of schists, granites,

granite gneisis and sandstones, all of which

have low apatite inclusive parent material.

This may also offer an explanation for the

observed differences in total P values between

the soils. Variation in total P in respect of

parent material has been demonstrated by

Rhodes (1977); Matured soils possess low P

values. The low P content of these savanna

soils, in addition to the low apatite content,

may be due to their maturity. Extractable Zn,

Mn, Fe, Cu, Bo and Mo ranged from 1.93 to

19.03, 6.69 to 26.95, 6.54 to 19.65, 1.91 to

3.98, 0.67 to 8.57 and 10.13 to 43.60 mg/kh

with a mean of 5.07, 16.02, 14.28, 2.71, 4.50

and 24.41mg/kg respectively (Table 4). They

had coefficient of variation of 72.00%,

39.73%, 25.08%, 21.03%, 48.08% and

86.23%, respectively. In terms of

micronutrients abundance in the soils, they

were in the following order: Mo > Mn > Fe >

Zn > Bo > Cu. Copper was sufficient in the

soils when compared to the critical level of 2 –

3mg/kg with the exception of Ehika soils

(Typic haplustalf) which was lower than

2.00mg/kg. With a critical level of 5.0mg/kg

for extractable Fe, the soils are said to be

adequate since all the soils used for the studies

were above critical level of 5.00mg/kg; except

Ayetorogbede (Kandic ustropept) in the

basement complex soil, the soils were

sufficient in available Zn (Table 4). The

contents of free Fe2O3 and Al2O3 ranged from

0.25 to 2.65%, 1.600 to 5.20% with a mean of

1.17 and 3.33%, respectively, (Table 2).

50


Table 4: Extractable micronutrient contents of soils studied

S/N Location Mo Bo Zn Cu Mn Fe

Mg/kg

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

27.86

35.94

43.60

29.62

120.10

112.34

25.96

19.96

40.66

36.36

26.98

18.03

18.48

10.13

12.19

12.72

15.98

16.43

28.25

36.65

8.06

2.69

3.02

7.69

3.70

3.53

6.55

4.37

7.36

4.03

3.51

5.04

4.37

8.57

3.03

4.70

4.37

0.67

1.68

2.89

2.30

7.27

4.44

3.60

6.01

2.87

4.86

4.02

3.71

7.27

5.12

6.01

5.96

5.23

1.93

3.29

3.34

2.87

19.03

2.34

20.52

8.31

6.82

6.69

12.01

8.70

20.00

23.44

26.95

8.31

14.14

12.01

13.34

20.65

18.12

16.62

19.48

20.97

25.50

16.48

17.71

17.17

17.05

13.95

15.07

12.78

12.76

10.28

6.54

17.17

16.08

15.07

15.71

7.97

18.59

19.65

18.15

12.19

21.19

17.51

2.40

2.49

3.27

3.24

3.28

2.18

2.16

2.03

2.29

2.55

2.20

3.28

3.18

2.99

3.09

3.27

2.18

3.22

3.98

1.19

Table 5: Mean, range values and coefficient of variability of the physical and chemical

properties of soil studied

Properties Range

(%)

Mean

(%)

CV

(%)

pH (H2O)

Organic matter (g/kg)

Total N (g/kg)

P (mg/kg)

Ca (cmol/kg)

Mg (cmol/kg)

Na (cmol/kg)

K (cmol/kg)

H (cmol/kg)

Al3+ (cmol/kg)

ECEC (cmol/kg)

Fe2O3 (%)

Al2O3 (%)

Clay (g/kg)

Silt (g/kg)

Sand (g/kg)

5.01 – 7.32

03.3 – 31.7

0.01 -1.20

0.54 – 24.80

1.92 – 19.34

0.32 – 5.44

0.48 - 0.94

0.05 – 0.84

0.20 – 0.80

0.10 – 0.90

4.56- 27.57

0.25 – 2.65

1.60 – 5.20

19.00 – 154.00

30.00 – 145.00

741.00 – 941.00

5.91

13.8

00.6

5.95

6.39

2.03

0.81

0.34

0.41

0.45

12.85

1.17

3.33

45.50

68.90

835.10

11.35

51.77

383.67

116.42

70.52

71.77

14.04

90.35

48.07

51.71

58.28

64.54

31.59

64.51

46.70

5.70

51


CONCLUSION Particle size analysis of the soils used

indicated a high proportion of sand, the texture

of the soils ranged from sand to loamy sand.

Since these soils were coarse grain in nature,

they may likely have low water and nutrient

retention capacities. All the soils used had very

low organic matter contents. The low organic

matter content might be due to rapid

mineralization of organic matter. Soils with

less than 2% organic matter are erodible. The

low level of organic matter content may

probably be responsible for the low ECEC and

nitrogen content of these soils. The levels of

micronutrients in most of the soils used were

moderately high. Organic matter was

positively and significantly correlated with Bo,

extractable Mn and Cu with “r” values of

0.681**, 0.578* respectively. Total P content

of the soils on average basis appeared to be

higher than what was reported for some native

rangeland soils of Northern Nigeria.

REFERENCE

Adepetu, J.A. and Corey, R.B. (1985).

Changes in N and P availability

fraction in Iwo soils from Nigeria,

under intensive cultivation. Plant and

Soil. 46: 309-316 Fertilize.

Agboola, A.A. and Corey, R.B. (1972). Soil

test calibration for N.P.K. for maize in

the soils derived from metamorphic

and igneous rocks of Western State of

Nigeria. Journal of West Africa Science

Association, 19(2): 93-100. Resources

6: (1) 65.

Balasubramanian, V., Nnadi, L.A. and

Mokwunye, A.U. (1984). Fertilizing

Sole crop maize for high yields.

Samaru Miscellaneous paper. 76, 14.

Cater, M.R. (1993). Soil Sampling and

Methods of Analysis. Lewis

Publishers. London. Page 23.

Enwezor, W.O.; Ohira, A.C., Opuwaribo,

E.E. and Udo, E.J (1990). A review of

fertilizer use on crops in southeastern

zones of Nigeria. In literature review

on soil fertility investigation in

Nigeria: pp 49-100.

FDALR (1985). Soil Map of Nigeria Federal

Department of Agricultural Land

Resources. Gee, G.W. and Bauder,

J.W. (1986). In Particle Size Analysis

Part 1. Physical and Microbiological

methods Second edition. Agronomy.

Series No 9. Soil Science Society of

America. America Society of

Agronomy. Madison, Wiscoson,

U.S.A.

Mehra, J. And Jackson, M.L. (1960). Iron

oxide removal from soils and clay by a

Dithioriate citrate system. Buffered

with sodium carbonate Clay Mineral.

7: 317-327.

Rhodes, ER. (1977). Phosphorus in Serra

Leone soils. Trop. Agric. (Trinidad).

54: 77-85.

Thomas, G.W. (1982). Exchangeable cation.

In A 1 page R.H. Moller and

D.R/Keeney (eds); methods of soil

analysis part 2 Second Edition.

America Society of Agronomy,

Madison pp. 157-164.

Udo, E.J. and Dambo, V.I. 1979. Phosphorus

status of the Nigeria coastal plain

sands. Journal of Agricultural Science,

(Cambridge) 93: 281-289.

52


OYSTER SHELL COMPOST EFFECT ON SOME PHYSICAL AND CHEMICAL

PROPERTIES OF AN INLAND VALLEY SOIL

ENEJE, ROSETA C.1 AND UKUT, ASUAMA N.1 1Department of Soil Science and Agro-climatology, Michael Okpara University of Agriculture

Umudike, Nigeria. Email: [email protected]

ABSTRACT An experiment was conducted in the Soil Science laboratory of Michael Okpara University of Agriculture, Umudike to investiage the effect of oyster shell composted with goat and poultry droppings on some physical and chemical properties of an inland valley soil. The experiment was 4X3 factorial in completely randomized design. Soil samples were collected from 0-30cm depth. The treatments applied were compost of combinations of goat (G) droppings, poultry (P) droppings and oyster shell (OY) (G+P+OY, P+OY, G+OY, G+P) and the amendment rates were 0%, 10% and 20% respectively. Each treatment was replicated three times. The results show that the application of the manure composts improved soil pH, ECEC, available phosphorus, total nitrogen organic carbon, exchangeable acidity, and aggregate stability of the soil. The improvements in soil properties were relative to the rate of application of these amendments and sampling duration, G+P+OY treatments influenced total nitrogen, ECEC, available P most while P+OY was most effective on aggregate stability, exchangeable calcium and pH of the soil. Keywords: Oyster shell, goat dung, aggregate stability, manure compost, ECEC INTRODUCTION Soils and their potentials differ appreciably from location to location depending on the nature of the parent material and other environmental factors. Adequate knowledge of their characteristics is needed before proper management practices can be applied to ensure sustainable productivity. In Nigeria, the pressure from a rapidly expanding population and the concomitant increasing demand for food necessitate a rational exploitation of the limited land resources for the production of more food. Soils in waterlogged environment are part of the land resources that can be made available for such a purpose. Research reports indicate that waterlogged soils, because of their fluctuating water tables and periodical flooding, in most cases show fluctuation in their acidity level (Udo, 2001). Soil pH is

regarded as a very important property since it influences such properties as the degree of base saturation and control the availability of all plant nutrients. Thus in soils with low pH, iron, aluminum and manganese are present in their toxic levels while other basic cations like calcium and potassium are fixed in the soil. However, according to Mullins, (2002) livestock manure contains nutrient elements that can enhance the chemical and physical properties of soils and support crop production. These amendments do not drastically alter soil chemical properties over a short term, but promote and build up organic matter, thereby improving soil physical properties; they also improve soil tilth and water holding capacity through improved soil structure, biological activity and aggregate

53

Eneje and Ukut NJSS/22(1)/2012

stability. In addition, Sobulo and Jayeola (1977), reported that organic amendments incorporated into the soil, greatly improved texture, loosened heavy/compacted soils and bound together light textured ones making the soil more friable, warmer, more retentive of moisture and more congenial to plant in every way. It is therefore important to investigate the possibility of using organic amendments under the prevailing structurally and chemically limiting conditions of waterlogged soils to increase the potentials of this scarce resource (land) for crop production. The objectives of the study therefore, are to; (i) determine the effect of organic

amendments on the physico-chemical properties of waterlogged soils;

(ii) provide information on interactive effects of organic amendments on soil fertility and structural stability of waterlogged soils.

MATERIALS AND METHODS Study site The soil sample used for the experiment was collected from an inland valley created by Ibakwa River, after the Ibakwa Military Barracks in Abak Local Government Area of Akwa Ibom State. This area lies between latitutes 4o33’N and 5030’N and longitude 7035’E and 8025’E and is characterized by heavy rainfall (2500-4000mm), high relative humidity (79%) and heavy cloud cover. The temperature of the area is generally high and changes slightly during the year (UNIUYO Consult Limited, 2002). The area is located within the South-South geo-political zone (Niger Delta Region) of Nigeria. Sample Collection and Preparation The soil samples were collected with soil auger to a depth of 0-30cm, air-dried and sieved using 2mm mesh. Oyster is a sea food with the fleshy part eaten as meat and the shells are discarded in dumping sites near market places in Uyo Local Government Area of Akwa Ibom State. The oyster shells were collected dried, ground and sieved through a 2mm mesh. Poultry and goat droppings were collected from the University Livestock Farm,

air-dried, crushed and passed through 2mm mesh. Incubation and Composting of Material The organic materials were mixed in the ratio of 1:1 in the following manner; Poultry dropping + Goat dropping + Oyster shell (P+G+OY) or (OYM) Poultry dropping + Oyster shell (P+OY) Goat dropping + Oyster shell (G+OY) Goat dropping + poultry dropping (G+P) The mixed organic materials were incubated under shade for 10 days. During this period of incubation, adequate moisture and aeration were ensured by the addition of water and turning with a stick every two days to encourage microbial activities. At the end of the incubation period, these organic materials were used as soil amendment. Incorporation of Amendment The composted materials were mixed with the soil samples in 8-litre capacity buckets perforated at the bottom. The treatment rates were 0kg, 0.2kg and 0.4kg per 2kg of soil equivalent to 0%, 10% and 20% respectively. The treatment soils were watered at two-week intervals and samples taken at 2, 4 and 6 weeks. All the treatments were replicated three times. Soil Analysis The soil pH was determined in 1:2.5 soils to water ratio using pH meter (Mclean, 1965), the organic carbon was determined using the Walkley and Black (1934) dichromate wet oxidation method as modified by Piper (1942). Total nitrogen (N) was determined using the macro Kjeldahl method described by Jackson (1958) while available phosphorus (P) was determined using Bray II method as described by Bray and Kurtz (1945). The available phosphorus in the soil extract was determined colorimetrically using molybdate blue colour method of Murphy and Riley (1962). Exchangeable acidity was determined by the method of Mclean (1965). Exchangeable K, Ca, Mg and Na were determined by extracting soil samples in 1N NH4OAc. Effective cation exchangeable capacity was computed as the

54

Effect of oyster compost on soil

sum of exchangeable properties and percent base saturation (BS %) computed as: % BS = Ca + Mg + k + Na x 100 ECEC 1 Aggregate stability was determined using the mean weight diameter method as described by Kamper (1965). Bulk density was determined usig the core method, while particle size distribution was determined using the method of Bouyoucos (1962). Data Analysis Data were analyzed using the analysis of variance (ANOVA) as outlined by Steel and Torrie (1980) using a 4 x 3 factorial in CRD. The factors were; factor A = Type of

amendment (G+P+OY, P+0Y, G+OY and G+D) factor B = Amendment rates (0%, 10% and 20%). The Fisher’s Least Significant difference (FLSD) as 5% probability level was used to separate the means. RESULT AND DISCUSSION The properties of the soil used are shown in Table 1. The soil used was a slightly acidic clay loam with medium organic carbon, low exchangeable cation content and high availale P. The oyster shell had high neutralizing equivalent value (CaCO3 = 116) suggesting that it is a good liming material. The Mg content of poultry dropping was very low (0.46%), but highest in the oyster shell (2.71%), while K and Na were low in all the materials.

Table 1: Physico-chemical properties of soil studies Characteristics Value Sand (%) Silt (%) Clay (%) Textural class pH H2O (1:2.5) Calcium (cmol/kg) Magnesium (cmol/kg) Potassium (cmol/kg) Sodim (cmol/kg) Exchangeable acidity (cmol/kg) Organic carbon (g/kg) Total Nitrogen (%) Effective cation exchange capacity (ECEC) cmol/kg) Available phosphorus (mg/kg) % Base saturation

68.52 5.17 26.31 Sandy clay loam 5.27 6.52 2.13 0.16 0.08 0.99 13.17 0.04 9.88 23.34 89

Table 2: Characteristics of materials used for composting Properties Materials Poultry Manure Goat Dropping Oyster Shell

Available phosphorus (ppm) Calcium (cmol/kg) Magnesium (cmol/kg) Potassium (cmol/kg) Sodium (cmol/kg) Nitrogen (%) CaCO3 equivalent

0.18 1.25 0.46 0.37 0.09 1.35

-

0.72 0.97 1.03 0.29 0.07 1.25

-

0.06 37.3 2.71 0.01 0.01

- 116

The effects of the composts on the Mean

Weight Diameter (MWD) of the soil show that

aggregate stability (AS) increased as the

compost rate increased and with the duration

55


of incubation. The values were highest with

OY+P treatment and least in the control soil

(Table 3). The effects of treatment, rate and

treatment and rate interaction effects

(P<0.001) on aggregate stability, were

significant at all sampling times. The increase

can be attributed partly to improvements in

organic carbon content. Mullins (2002)

observed that the incorporation of organic

residue increased organic carbon and its

various fractions which contribute to the

formation and stabilization of soil aggregates.

In addition, Mbagwu and Piccolo (1990)

reported that organic manure application

improved the degree of soil aggregation and

aggregate stability. In this study, compost-

treated soils performed better than the control

in affecting the physicochemical properties

studied. The G+P+OY treatment was most

effective in improving the exchangeable

cations and ECEC with the largest increase

obtained at the sixth week of improving the

exchangeable cations and ECEC with the

largest increase obtained at the sixth week of

sampling, with highest rate of compost

application. The improvement in ECEC is

attributable to the decomposition of organic

matter contained in the composts. Base

saturation increased with G+OY treatment in

line with the liming ability of oyster shell.

Exchangeable calcium was high in the material

which explains the significant increase in

treated soils compared to the control. Edem et

al (1998) and Mullins, (2002) had reported

increases in exchangeable magnesium,

calcium and potassium content of soil, with

application of poultry and goat manures which

is enhanced by the addition of oyster shell.

Therefore, the results from this study confirm

these observations and agree that organic

manure with oyster shell has positive effect on

soil exchangeable properties.

56


Table 3: Physico-chemical properties of compost amended soils at different sampling ‘times Rate OC

(%)

Total N

(%)

Avail. P

PPM

Soil activity

Exchangeable cations (Cmol/kg) BS(%) AS

H2O CaCl2 Ca Mg Na K EA ECEC

Two Weeks

Control (0%)

Oym(10%)

G+P(10%) Oy+p(10%)

Oy+g(10)

Oym(20%) G+P(20%)

Oy+p(20%)

Oy+g(20%) FLSD(0.05)T

FLSD(0.05)R

FLSD(0.05)TR

1.03

1.61

1.56 1.86

1.82

1.92 1.69

1.62

1.53 0.136

0.118

0.237

0.04

0.07

0.06 0.09

0.08

0.08 0.29

0.07

0.07 0.01

ns

ns

0.24

0.29

0.26 0.39

0.58

0.26 0.39

0.61

0.45 0.052

0.045

0.091

6.54

7.53

7.62 7.64

6.83

7.72 7.63

7.54

7.77 0.309

0.268

0.536

4.25

6.96

6.64 6.80

6.17

7.00 6.75

6.47

6.78 0.237

0.205

0.411

6.48

25.36

37.12 28.81

15.44

38.64 33.92

21.12

42.40 8.16

7.07

14.13

2.10

5.17

9.36 7.52

4.35

9.69 7.35

6.42

9.57 2.581

2.235

4.47

0.05

0.07

0.06 0.07

0.07

0.07 0.07

0.09

0.07 0.006

0.005

0.010

0.13

0.20

0.09 0.16

0.29

0.11 0.21

0.35

0.23 0.021

0.018

0.037

0.96

1.36

2.15 1.60

1.16

1.56 1.68

1.52

1.32 0.255

0.221

0.441

9.72

28.08

48.79 38.15

21.31

50.07 43.23

29.50

53.60 10.09

8.74

17.48

90.12

94.95

94.74 95.74

94.28

96.09 96.11

94.83

97.48 1.04

0.90

1.80

0.25

0.72

0.40 0.84

0.33

0.44 0.87

0.36

0.81 0.015

0.014

0.027

Four weeks

Control (0%)

Oym(10%) G+P(10%)

Oy+p(10%)

Oy+g(10) Oym(20%)

G+P(20%) Oy+p(20%)

Oy+g(20%)

FLSD(0.05)T FLSD(0.05)R

FLSD(0.05)TR

1.03

1.65 1.60

1.95

1.83 1.97

1.73 1.58

1.66

0.144 0.124

0.249

0.04

0.07 0.07

0.37

0.08 0.08

0.09 0.07

0.08

0.129 0.112

0.224

0.24

0.29 0.26

0.39

0.58 0.26

0.39 0.45

0.61

0.05 0.05

0.09

6.54

7.54 7.64

7.66

6.83 7.74

7.65 7.79

7.54

0.309 0.268

0.535

4.25

6.98 6.65

6.82

6.18 6.98

6.77 6.90

6.48

0.241 0.209

0.418

6.48

25.59 37.18

28.86

15.45 38.76

33.98 43.21

21.13

8.20 7.10

14.2

2.10

5.22 9.37

7.54

4.36 9.70

7.36 9.59

6.44

2.577 2.232

4.463

0.05

0.07 0.07

0.08

0.08 0.08

0.08 0.08

0.08

0.007 0.006

0.011

0.13

0.21 0.13

0.18

0.31 0.17

0.25 0.26

0.37

0.025 0.022

0.044

0.96

1.40 2.19

1.65

1.19 1.60

1.25 1.36

1.55

0.375 0.325

0.649

9.72

28.27 48.94

38.31

21.39 26.31

43.38 50.52

29.56

9.17 7.94

15.89

91.12

95.16 94.96

95.64

94.28 96.04

96.01 97.46

94.83

1.01 0.87

1.75

0.40

0.76 0.50

0.88

0.40 0.55

0.89 0.94

0.43

0.019 0.017

0.034

Six Weeks

Control (0%)

Oym(10%)

G+P(10%) Oy+p(10%)

Oy+g(10)

Oym(20%) G+P(20%)

Oy+p(20%)

Oy+g(20%) FLSD(0.05)T

FLSD(0.05)R

FLSD(0.05)TR

1.03

1.71

1.57 2.06

1.85

2.01 1.78

1.67

1.60 0.151

0.131

0.262

0.40

0.08

0.08 0.11

0.07

0.08 0.09

0.08

0.08 0.012

0.009

0.019

0.24

0.30

0.26 0.39

0.58

0.27 0.39

0.61

0.45 0.052

0.045

0.089

6.54

7.57

7.65 7.73

6.84

7.75 7.67

7.55

7.79 0.301

0.260

0.521

4.25

7.01

6.68 6.85

6.49

7.17 6.78

6.50

6.93 0.245

0.212

0.424

6.48

25.59

37.23 28.93

15.50

39.22 34.04

21.18

43.21 8.32

7.20

14.41

2.10

5.26

9.38 7.77

4.38

9.74 7.41

6.49

9.62 2.55

2.21

4.43

0.05

0.08

0.07 0.08

0.08

0.08 0.09

0.08

0.08 0.005

0.004

0.009

0.13

0.25

0.13 0.22

0.28

0.17 0.26

0.30

0.24 0.05

0.044

0.089

0.96

1.42

2.22 1.67

1.22

1.62 1.74

1.57

1.35 0.261

0.226

0.453

9.92

29.10

49.18 38.68

22.38

50.83 43.52

29.62

54.51 10.27

8.89

17.78

90.12

95.21

95.63 94.24

94.24

96.01 94.71

94.71

97.45 0.571

0.494

0.988

0.52

0.76

0.56 0.92

0.46

0.62 0.96

0.53

0.95 0.202

0.017

0.034

The composted materials affected total N,

avaialble P percent, organic carbon and soil

acidity, and there were increases in the

strength of relationships between these

properties with time. The trend of effect of the

treatment on total N, available P and percent

organic carbon relative to the control,

irrespective of application rate, indicates that

the improvements were highest with the

combinations of G+P+OY. The pH (H2O) of

the treated soil was raised from moderately

acidic to neutral (7.54) which showed that the

composts were effective in eliminating the soil

acidity, with highest value obtained at the sixth

week. Mullins (2002) had attributed these

changes to the neutralizing effect of oyster

shell and poultry droppings stressing that the

liming effect is due to calcium carbonate in

poultry feed. Generally, the relationship

between selected properties with the compost

type and rate of application indicated that the

rate and type of compost amended soil was

responsible for only about 38% and 17% of Na

and organic carbon after two weeks of

incubation. However, after four to six weeks

of compost incorporation with the soil, this

effect on available P was diminished by half

while the exchangeable Na became higher.

This study has shown that composted organic

materials from poultry manure, goat manure

and oyster shell improved the pH, CEC,

available P, total N, organic carbon,

exchangeable acidity and aggregate stability of

57


soil from an inland valley. The improvements

increased with the rate of the amendments and

sampling time. Specifically, the G+P+OY

treatment influenced total N, cation exchange

capacity and available P the most, while P+OY

treatment was most effective in improving

aggregate stability, pH, and exchangeable

calcium content of the soil.

REFERENCES Bouyoucos, G.J. (1962): Hydrometer Method

Improved for making Particle Size

Analysis of Soils, Soil Science Society

America Proc. Vol. 26, 464-465.

Bray, R.H. and Kurtz, L.T. (1945):

Determination of total organic and

available Phosphorus in the soil. Soil

Science 59: 39-45.

Edem, S.O Effiong, G.S and Umoh, G.A.

(1998): The Wetlands of Akwa Ibom

State Utilization and present Land Use

Practices. Nigerian Journal of

Agricultural Technology 7: 13-24.

Jackson, M.L. (1958): Aggregate Stability. In:

method of Soil Analysis (ed). C.D.

Black Agron; No. 9, American Society

Agron, Madison.

Kemper, W.D. (1965): Aggregate stability: In

Method of Soil analysis (ed) C.D.

Black. Agron. No. 9 American Society

of Agron. Madison.

Murphy, J. and Riley, (1962): A modified

simple solution method for the

determination of phosphorus in Natural

waters Anal. Chimi Acta 27: 31-36.

McLean, I.O. (1965): Aluminium in L.A.

Black (ed) Methods of Soil Analysis.

Part II Am. Soc. Agron. Madison N1pp

976-985.

Mbagwu, J.S.C. and Piccolo, A. (1990): Effect

of Humic Substances and Surfactants

on the Stability of Soil Aggregates.

Soil Science, Vol. 6 pp. 10.

Mullins, G.L. (2002): Poultry Litter as a

Fertilizer and Soil Amendment;

Agriculture and Natural Resource.

Virginia Tech. Organic Research-

http;/www.organic-research.com/2002.

Piper, C.S. (1942): Soil and Plant Analysis.

Intern Science Publication Inc. NY. Pp

368. Steel, R.G.D. and Torrie, J.H.

(1980). Principles and procedures of

statistics: A biometrical approach (2nd

Ed. M.C. Graw Hill, New York) Pp

257-259.

Sobulo, R.A., and Jayeola, E.K. (1977):

Influence of soil organic matter on

plant nutrition in Western Nigeria.

Ecprint, “Soil Organic Matter Studies”.

Intern Atomic Energy. Vienna pp 105-

115.

Udo, E.J. (2001). Nutrient status and

agricultural potentials of wetland soils

In: Proceedings 27th Annual

Conference of Soil Science Society of

Nigeria, Calabar: 1-10.

Uniuyo Consult Limited (2002). Soil

Potentials of Akwa Ibom State: Soils of

the Coastal Zone Akwa Ibom. Nigeria.

Pp. 3-97.

Walkley A. and Black I.A. (1934). An

examination of the different methods

for determining soil organic matter and

proposed modification of the chromic

and digestion method. Soil Science 37:

29-338.

58


EFFECTS OF RICE MILL WASTE AND POULTRY MANURE ON SOME

SOIL CHEMICAL PROPERTIES AND GROWTH AND YIELD OF MAIZE

ENEJE, R.C.1, AND UZOUKWU, I.1 1Department of Soil Science and Agro-climatology, Michael Okpara University of Agriculture

Umudike, Nigeria, Email: [email protected]

ABSTRACT

An experiment was conducted at the Michael Okpara University of Agriculture, Umudike

Western Farm, to investigate the effect of rice mill waste and poultry manure on some soil

chemical properties and growth and yield of maize (Zae mays L.). The study was laid out in a

randomized complete block design (RCBD) with three replicates. Soil amendments were applied

at the rates of 0, 2, 4 and 8 t/ ha-. The results showed that the addition of the organic materials

improved the soil chemical properties with the poultry manure alone giving the highest value for

all the parameters analyzed, which included soil pH, available phosphorus and organic carbon.

However, total nitrogen was highest when the mixture of rice mill waste and poultry manure was

applied. Growth and yield parameters of maize were significantly increased by the application of

the organic materials. Rate of application at the different times was statistically significant, in

affecting all the chemical characteristics of the soil, and the growth and yield parameters

investigated.

Keywords: Maize yield, organic carbon, soil pH, available P, rice mill waste.

INTRODUCTION The soil is the most important source of wealth

of any agrarian state, when a soil is cultivated

continuously its productivity gradually

decreases, due to depletion of organic matter

which is believed to be a reservoir of plant

nutrients.

Soil fertility is dynamic as it is subject to the

influence of climate and cultural practices

(Allison and Moodie, 2004). Nowadays,

mineral fertilizers are the major soil

amendments used for the maintenance of soil

fertility. The use of mineral fertilizers and

some bad farming practices, such as burning

have greatly contributed to the reduction in the

organic matter content of soils. Besides, the

physical, chemical, and biological properties

of soils are adversely affected. For this reason,

issues of agricultural sustainability and

environmental hazard minimization should be

addressed simultaneously. The application of

organic source of nutrient such as animal

manure, crop residues, sewage sludge, city

refuse, and compost manure to soils is a

current environment and agricultural practice

for maintaining soil and supplying plant

nutrient (Francis et al, 1990).

It is evident that soils under cultivation are

gradually depleted in organic matter and the

methods of farming commonly practiced are

neither maintaining the content of organic

matter nor the productivity of the soil.

Therefore, different types of experiments on

the use of organic sources of nutrients such as

animal manure, crop residues, sewage sludge,

59

Eneje and Uzoukwu NJSS/22(1)/2012

city refuse and compost manures have been

reported. However, information on the extent

of nutrient release, when combinations of

organic matter sources are used as

amendments for certain crops are not

adequate. This had become a necessity today

where emphasis is on agricultural

sustainability and food security, especially in

the tropics and subtropics. Therefore, the aim

of this work is to assess the effect of different

rates of application of rice mill waste and

poultry manure on the growth and yield of

maize.

MATERIALS AND METHOD

Experimental Site The experiment was conducted at Michael

Okpara University of Agriculture Research

Farm in Umudike (Longitude 070 33`E,

Latitude 050 29’N, altitude 122m). The climate

is essentially tropical humid climate; the area

has a total rainfall of 2177mm per annum,

annual average temperature of about 26oC.

The rainfall pattern is bimodal; a long wet

season from April to July is interrupted by a

short “August brake” followed by another

short rainy season from September to October

or early November. Dry season stretches from

early November to March. (Speccini et al,

2001). Stumps in the field were removed using

cutlass, before harrowing and ploughing with

tractor then the plots were demarcated into

beds of plot sizes 3m x 2.5m, with furrow size

of 0.5m.

Experimental Layout The total experimental area was 336.6m2, four

rates of rice-mill waste (RMW), poultry

manure (PM) and an equal mixture of rice-mill

waste and poultry manure (RMW+PM),

namely 0, 2 tons, 4 tons and 8 tons per hectare

were applied to the demarcated plots in a

sandy loam soil. The experimental design was

a randomized complete block design (RCBD)

with three replicates.

Planting and Weeding

The maize variety used was Oba super 2

planted at a spacing of 1m by 1m, with two

seeds sown per hole, giving a population of

20,000 maize plants per hectare. Weeding was

done manually at four weeks after planting.

Collection and Preparation of Soil Sample Soil samples were collected at one month and

two months after amendment application using

a soil auger at 0 to 15 cm depth in each plot.

The soil samples were air dried at room

temperature for 3 days and sieved through a 2

mm sieve. The samples were then analysed for

physical and chemical parameters.

The soil pH was determined in 1:2.5 soils to

water ratio using pH meter (Maclean, 1965),

the organic carbon was determined using

dichromate wet oxidation method (Walkley

and Black, 1934) as modified by Piper (1942).

Total nitrogen was determined using the macro

Kjaldahl method described by Jackson (1958),

while available phosphorus was determined

using Bray II method as described by Bray and

Kurtz (1945).

Collection of growth and yield Data Data were collected on height and stem

diameter of maize at 2 and 6 weeks after

planting. Also at harvest data were collected

on cob length and weight of 100 seeds.

Data Analysis All the data were subjected to analysis of

variance (ANOVA) as outlined by Steel and

Torrie (1980). Treatment means were

compared, using the Fisher’s Least Significant

Difference (FLSD) at 5% probability.

60

Effect of rice waste and manure on soil


Table 1:Physical and chemical properties of soil samples used for the study before cropping

Characteristics Value

Sand %

Silt %

Clay%

Textural class

pH H2O (1:2.5)

pH CaCl2 (1:2.5)

Total N (%)

K (cmol/kg)

OM (%)

OC (%)

Avail. P. (mg/kg)

Mg (cmol/kg)

Ca (cmol/kg)

Na (cmol/kg)

85.00

20.00

15.00

Sandy loam

5.25

4.73

0.098

0.194

14.44

8.30

20.23

1.82

2.53

0.106

Table 2: Chemical properties of organic amendments used for the study

Properties Poultry manure (PM) Rice mill waste (RMW)

Avail. P (ppm)

Ca2+ (cmol/kg)

Mg2+ (cmol/kg)

K+ (cmol/kg)

Na+ (cmol/kg)

Nitrogen (%)

0.78

1.26

0.43

0.29

0.81

1.05

0.29

2.10

1.02

0.47

0.22

0.671

Table 3: Organic manure effect on soil chemical properties at one month after manure

application Rates OC(%) Total N(%) pH(H2O) Avail. P(mg/kg)

PM+RW PM RW PM+RW PM RW PM+RW PM RW PM+RW PM RW

0t/ha

2t/ha

4t/ha

8t/ha

8.48

19.05

23.68

26.49

8.48

19.95

25.10

28.26

8.48

15.77

16.23

16.96

0.127

0.182

0.202

0.227

0.127

0.178

0.183

0.203

0.127

0.177

0.172

0.177

5.77

5.91

6.08

7.02

5.77

5.99

6.45

7.34

5.77

6.26

6.12

6.3

25.50

30.51

33.42

41.39

25.50

33.93

43.12

70.41

25.50

25.56

30.50

35.69

SED T=0.174

SED R=0201 SEDIR=0.348

SED T=0.0025

SED R=0.0029 SED TR=0.005

SEDT=NS

SEDR = 0.240

SEDT=0.648

SEDR=0.749 SEDTR=1.296

Two months after manure application in the field

Rates OC(%) Total N(%) pH(H2O) Avail. P(mg/kg)

PM+RW PM RW PM+RW PM RW PM+RW PM RW PM+RW PM RW 0t/ha

2t/ha

4t/ha 8t/ha

9.33

20.70

23.48 20.16

9.33

25.04

27.1 23.16

9.33

26.83

29.15 24.44

0.140

0.248

0.200 0.195

0.140

0.263

0.220 0.204

0.140

0.282

0.237 0.215

5.193

6.233

6.490 5.877

5.193

6.487

6.903 6.460

5.193

7.177

7.437 6.583

23.57

36.90

44.90 28.99

23.57

48.84

56.86 37.86

23.57

56.21

78.50 39.81

SED T=0.334

SED R=0.289 SEDIR=0.578

SED T=0.0046

SED R=0.00403 SED TR=0.00806

SEDT=0.0595

SED R=0.0515 SEDR = 0.103

SEDT=1.144

SEDR=0.9991 SEDTR=1.982

61


The results above show that the application of

organic amendments increased the pH level of

the soil, because the amendments were

effective in reducing the soil acidity. The pH

increased as the rate of amendment and

sampling duration increased with the highest

value obtained at the rate of 8 t/ ha- and two

months sampling time. The result also showed

that the application of poultry manure alone

gave the highest pH value, onemonth after

application. However the reverse was the case

after two months when rice mill waste alone

gave the highest pH values (Table 3). The

ANOVA showed that the treatment (PM +

RW, PM, RMW), at the different application

rates (2, 4 and 8 t/ ha- significantly (P<0.001),

affected soil pH after two months of sampling.

Similarly, type and rates of organic manure

significantly affected the carbon and nitrogen

status of the soil. This observation agrees with

the report of Nwadialo (1991), that increasing

rates of poultry manure resulted in increasing

values of exchangeable bases. In addition, Obi

and Ebo (1995) reported a significant increase

in soil organic matter content (p=0.05) with

the application of poultry manure. This effect

of poultry manure irrespective of the

application rate on carbon content, and total

nitrogen in 20 cm sampling depth compared to

the other manure suggests that the poultry

manure is superior to other organic manure

with respect to nitrogen and phosphorus. This

further corroborates the observation of Darra

and Ussaman (1998), that organic manure is an

excellent soil amendment, providing both

organic matter and nitrogen, even though the

effects of organic manure, especially poultry

droppings on soil chemical properties and crop

yield depends on the type of feed the animal

consume, type of bedding materials used (if

any) and the state in which the manure is

applied i.e. a solid or liquid form. Moreso, the

effects of organic manure is also attributable to

the reactions initiated in the soil on its

application as reported by Heck (2001).

Animal and green manure are relatively bulky

materials, which are added mainly to improve

the physical structures of the soil, to replenish

and keep up its humus status, to maintain the

optimum condition for the activities of soil

micro-organisms and replenish part of the

plant nutrients removed by crops or other wise

lost through leaching and soil erosion.

Generally, the high response of crops to

poultry manure compared to the other

amendments is attributed to both the inherent

nutrient content of poultry manure, and the

effect of the manure on soil physical

properties, such as improvement of

aggregation, porosity and aggregation stability

(Musgrave, 1995). This advantage is also

attributed to the ease of decomposition of

poultry manure and subsequent mineralization

compared to the other amendments. The ease

of mineralization of poultry manure makes it

preferable to crop residues in situations where

plant nutrients are deficient and requires

immediate replenishment (Dara and Ussaman,

1998). This observation also explains the

higher effect of single application of poultry

manure on stem height and diameter of maize

crop as indicated in Table 4. However, the sole

effect of rice mill waste was enhanced by

admixture of poultry manure because crop

residues such as rice mill waste, maize husk,

groundnut husk, are abundant sources of

organic carbon, although, slow in

decomposition and release of plant nutrients,

(Eneje, et al, 2007).

62


Table 4: Effect of organic manure on growth and yield of maize at sampling times

Plant height after two weeks Plant height after six weeks

Treatments 0t/ha 2t/ha 4t/ha 8t/ha 0t/ha 2t/ha 4t/ha 8t/ha

PM+RW

PM

RW

3.2

3.2

3.2

6.8

6.0

4.2

8.0

9.13

5.0

12.0

10.0

7.0

6.0

6.0

6.0

20

23

10.5

21.1

26.1

13.2

52.0

40.0

25.0

SED T = 0.0136

SED R = 0.01571

SED TR = 0.0277

SED T = 0.0471

SED R = 0.0544

SED TR = 0.0943

Cob length at harvest 100 Seed weight at harvest

Treatments 0t/ha 2t/ha 4t/ha 8t/ha 0t/ha 2t/ha 4t/ha 8t/ha

PM+RW

PM

RW

4.468

4.468

4.468

5.767

6.100

5.633

6.067

8.822

5.933

12.667

13.433

10.733

15.24

15.24

15.24

21.37

23.15

19.31

27.92

31.97

25.95

32.01

35.05

23.76

SED T = 0.1562

SED R = 0.1803

SED TR = 0.3123

SED T = 0.357

SED R = 0.412

SED TR = 0.713

In this study, PM also gave the highest value for 100 seed weight and the effect increased with increasing rate of application (Table 4), suggesting a linear relationship between maize seed weight and increasing rate of PM. This obervation agrees with that of Reeds et al (2002), who reported shoot dry matter increase of about 7% in maize when N rate was increased from 0 to 200 kg ha-1. Moreover, Ma et al (2004), reported a linear increase in the weight of 1000 grains in varieties of maize used for trial and attributed this to increases in nitrogen which plays very important roles in several physiological processes in plants. The effect of the ricemill waste on the growth parameters can be explained by the observation of Rajcan (1999), that the RW was carbonaceous, and when applied to the soil, does not decompose with ease, and this normally results in low rates of mineralization. However, the poor performance of maize in terms of growth and yield parameters can be attributed to loss of carbon in the form of CO2. CONCLUSION AND RECOMMENDATION The results of this study have shown that the addition of organic materials, such as poultry manure and rice mill waste solely or in combination improved the chemical properties of the soil. The improvement relative to control increased as the rate of application and sampling duration increased. The organic materials also improved plant height and yield of maize. The use of rice mill waste in

combination with poultry manure is recommended for improvement of soil pH to the optimum value required by most tropical crops, especially maize. Furthermore, though the combinations of the organic manure supply practically all the elements of fertility which crops require, it is not in adequate proportion. Therefore proper organic manuring requires admixtures of the sole manures that will encourage maximum microbial activity to enhance the release of soil nutrients in available forms and reduce nutrient loss through fixation or downward movement in the soil. Generally, the best soil amendment is the mixture of poultry manure and rice mill wastes. Additions of woody materials such as wheat straw, sawdust, rice husk, wood shavings etc, should be accompanied by addition of nitrogen sources, to minimize the fast decomposition of soil organic matter. REFERENCES Allison, L.E. and Moodie, M.O. (2004),

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63


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Heck, A.F. (2001), Conservation and

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Ma, B.L., Dwyer, L.M. and Gregeriah, E.G.

(1991). Soil nitrogen amendment effects on nitrogen uptake and grain yield of maize. Agron. J. 9: 650-656.

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Piper, C.S. (1942). Soil and Plant Analysis. Int. Sci. Publ. Inc. N.Y. p. 368. Steel, R.C.D. and Torrie, J.H. (1980).

Principles and Procedures of Statistic: A Biometric Approach. 2nd ed.,

McGraw-Hill Book Company, Inc. N.Y. Toronto, London.

Maclean, I.O. (1965). Aluminum. In: Black C.

A. (ed.) Methods of Soil Analysis. (Part II) Am. Soc. Agron. Madison, WI, 976-998.

Reed, A.J., Singletaery G.W., Schussler, J.K.,

Willianson O.R. and Christy A.C. (2002). Shading effects on dry matter and nitrogen partitioning, kernel number and yield of maize crops. Soil Science. 28:819-825.

Robbins, C.W., Freeborn, L.L. and

Westernman, O.T. (2000). Organic phosphorus source affects calcareous soil phosphorus and organic carbon J. Environ Qual. 29: 973-978.

Rajcan, I. and Tollen, M. (1999). Source: Sink

ratio and leaf sensescense in maize I: Organic. Matter accumulation and partitioning during grain filling. Field Crops Research, Amsterdam, 60 (2) 245 – 253.

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J.S.C. and Piccolo, A. (2001). Carbohydrates in water-stable aggregates and particle size fractions of forest and cultivated soils in two contrasting tropical ecosystems. Biogeochemistry, 53:1-22.

Tejada, M. and Gonzalez, J.C. (2001). Waste

management. American Society of Agronomy. U.S.A.

Lannoji, M., Whalen, J.K. and Change C.

(2001). Phosphorus accumulation in cultivated soil from long-term annual application of cattle feedlot manure J. Environ. Qual. 30: 229-237.

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examination of the Degtjareff methods for determining soil organic matter and proposed modification of the chromic acid digestion method. Soil Science 37: 29-38.

64


ASSESSMENT OF SOME SOIL FERTILITY CHARACTERISTICS OF ABAKALIKI

URBAN FLOOD PLAINS OF SOUTH-EAST NIGERIA, FOR SUSTAINABLE CROP

PRODUCTION

OGBODO, E.N. Department of Soil Science and Environmental Management,

Faculty of Agriculture and Natural Resources Management, Ebonyi State University, P.M.B. 053

Abakaliki, Nigeria.

ABSTRACT

There is lack of adequate information on the fertility status of the soils of Abakaliki urban flood

plains. Farming activities have therefore been carried out on the surrounding uplands only. This

study was therefore conducted in 2009 rainy season, to evaluate the fertility status of the flood

plains and compare it with the fertility of the uplands with a view to making recommendations

for sustainable agricultural production. Soil samples were obtained from the Iyiudene floodplain,

Iyiokwu floodplain, Ebonyi river basin and the surrounding upland and subjected to physical and

chemical analysis. The soil texture ranged from loam in the upland areas to clay loam in the

flood plains and the river basin. Soil bulk density of the upland soils was significantly higher

than the flood plains. The bulk density of the flood plains was respectively suitable for crop

production. The soil water holding capacity of the upland was rather too low, whereas the

floodplains had adequate water holding capacity for crop production purposes. The soil organic

matter was generally low for both the upland and the flood plains. However, the floodplains and

the river basin soils contained significantly (p<0.05) higher organic matter than the upland. The

upland soil was very acidic whereas the soils of the floodplains were acidic. The available

phosphorus was low, however, the floodplains had significantly (p<0.05) higher soil available P

than the upland. Total N, soil pH and exchangeable acidity were significantly (p<0.05) higher in

the upland soils than in the soils of the floodplains whereas the floodplains had significantly

(p<0.05) higher exchangeable Ca, Mg, Na, CEC and base saturation. The overall soil fertility

status of the floodplains was therefore superior to the upland soils.

Key words: Soil Fertility, Soil Characteristics, Urban Floodplains, Sustainable Crop Production,

Southeastern Nigeria

*Corresponding author. Tel.: +234 8037465495; e-mail:[email protected]

INTRODUCTION

In most derived savannah like in Abakaliki,

streams channels do not accommodate stream

flow at certain periods of the raining season.

Most of the year, the water levels maybe well

below the stream bank height, but at certain

periods heavy rains can deliver more water

than the stream can carry. Such excess water

that overflow stream banks and covers

adjacent land is considered as flood. The

changes in land use associated with urban

development affect flooding in the study area

65

Ogbodo NJSS/22(1)/2012


in many ways – removing vegetation and soil,

grading the land surface, constructing road

networks and building of houses increase

runoff to stream from rainfall. As a result, the

peak discharge, volume and frequency of

floods increase in nearby steams. Changes to

stream channels during urban development can

limit the capacity of these streams to convey

flood waters (Sauer et al., 1992). Intensity of

rainfall in short period in the study area during

raining seasons also leads to extremely high

runoffs, reduced infiltration and eventual flood

resulting from the impervious layer, high bulk

density and crusting (FDALR, 1985). Many

human activities increase the severity and

frequency of the floods including dumping of

domestic wastes into the streams which leads

to channel suffocation by these wastes

resulting into channel interference.

Under normal condition, floods are mitigated

by flood plains lowland that is periodically

inundated during normal flood. These

floodplains are usually very fertile, flat and

easily farmed. In most of the developed world,

floodplains are widely farmed, and cleared of

vegetation. Farmers go to flooded areas for

their activities because flooded areas are

usually very fertile for farming; there is

availability of water and nutrient for crop

growth in these areas. Flooded areas support

variety of ecosystem; different species of crop

grow in flooded areas (floodplains). However,

reports on the effect of flooding on soil

properties of the Abakaliki flood plains are

rather few, necessitating this study; to evaluate

the effect of flooding on the soil properties and

compare the nutrient content of the flooded

plains with that of adjacent arable land with

the intention of ascertaining whether the

floodplains could be put to agricultural uses.


Study Area

The study area is Abakaliki municipality

which lies within latitude 16o 04’N and

longitude 18o 65’E, south east of Nigeria. It

has a bimodal rainfall pattern from April to

November. The total amount of rainfall

recorded within this period range from 1,900-

2,600mm annually while the maximum mean

daily temperature hovers around 27-31oC

through the year. The mean relative humidity

is 65-80%. The soil classification is Ultisol,

which is hydromorphic, of shale parent

material with underlying impervious layer at

about 40cm depth. It is characterized by

rampant flooding and water logging which is a

precipitate of poor drainage resulting from the

impervious layer, high soil bulk density and

crusting (FDALR, 1985), and recently by poor

urban settlement and human activities. The

flooding is experienced about the peaks of the

rainy season (July and September) and covers

the basins and floodplains around the middle

and lower courses of the river and the streams.

Field Method

A reconnaissance survey was carried out on

the study area, traversed by two streams called

lyiudene and Iyiokwu. The streams flow

through an undulating course with the main

sources at Mgbabor and Nkaliki respectively,

with other tributaries and terminating at where

they converge and empty into Ebonyi River.

Random method was used to collect soil

samples from the study area. Ten auger

samples were collected from each sampling

area at 0-20cm depth at the middle and lower

courses of the streams at both East and west

sides of the banks. Core samples were also

collected respectively from the same areas, for

determination of bulk density and total

porosity, while six other auger samples were

collected at 0-10cm depth from the respective

sampling areas for determination of soil

moisture holding capacity. The auger samples

were stored in labeled polythene bags. They

were dried under shade for three days,

crushed, sieved with a 2mm sieve and taken to

the laboratory for the determination of particle

size distribution and chemical properties.

Laboratory Methods

Particle size distribution was determined using

hydrometer method. Available water at field

capacity by the method of Klute (1986) and

bulk density by Blake and Hartge (1986).

66

Soil fertility characteristics of Abakaliki plains


Total porosity was calculated from the bulk

density values assuming a particle density of

1.65gcm-3. Soil pH was determined using glass

electrode pH meter in water using 1:2:5 soil;

water ratios. Total nitrogen was determined

using macro – kjeldahl methods. Available

phosphorus was determined using Bray 11

methods. Organic carbon was measured by the

Walkey – Black procedure. Exchangeable

bases (K, Ca, Mg and Na) and Exchangeable

acidity (H+ and Al+) were determined as

described by Tel and Rao (1982). Cation

exchange capacity was determined by the

summation of exchangeable bases (K, Ca, Mg

and Na) and exchangeable acidity (H+ and

AL3+) by IITA (1979).

Data obtained were analyzed using one tailed

analysis of variance (ANOVA).

RESULT

Soil particle size distribution

Table 1 shows the particle size distribution of

the soils. The upland had higher values of sand

fraction than the flooded areas, whereas the

floodplains had higher values of silt, and clay

fractions compared to the arable land. The

textural class of the soils ranged from clay

loam for both flood plains and the river basin

to loam for the upland.

Table 1: Particle size distribution of the soils.

Treatment % Sand % Silt % Clay Textural class

Iyiudene

floodplain

36.40 36.80 26.80 Clay loam

Iyiokwu floodplain 32.40 36.80 30.80 Clay loam

Ebonyi River basin 32.40 34.80 32.80 Clay loam

Upland 44.40 34.80 20.80 Loam

Soil Physical Properties

The physical properties of the soil are

presented in Table 2. The bulk density values

for the floodplains and the river basin were

significantly lower than that of the upland,

whereas the soil densities of the floodplains

were statistically comparable with the river

basin soil. The soil total porosity of the

Iyiokwu and Iyiudene flood plains and the

Ebonyi river basin were correspondingly

higher than the soil total porosity of the

upland, owing to the lower soil density of the

areas. It was also observed that the soil water

retention capacity was higher with the

floodplains and the Ebonyi river basin than the

upland. The soils of the Iyiudene flood plain

and Ebonyi river basin areas also had higher

moisture retention capacity than the Iyiokwu

floodplain.

Table 2: Some Soil Physical Properties of the Soils. Treatment Bulk Density

(kg) Percentage Moisture

Retention Porosity

(%) Iyiudene floodplain 1.20 22.48 54.5 Iyiokwu floodplain 1.30 19.34 51.1 Ebonyi river basin 1.24 24.78 53.3 Upland 1.61 9.88 39.2 FLSD (0.05) 0.13 2.89 3.92

Chemical Properties of the Soil

Soil pH, Organic matter, N and P

Table 3 shows the soils chemical properties.

The result shows that the floodplains and the

river basin had higher pH values than the

upland. The pH values of the Iyiudene

floodplain and the Ebonyi river basin were

also significantly (p<0.05) higher than the pH

values of the Iyiokwu floodplain and the

upland. Soil pH was also significantly

67

(p<0.05) higher with the Iyiudene floodplain

than the Ebonyi river basin, whereas the pH of

the upland and the Iyiokwu floodplain were

comparable. The floodplains and the river

basin soils had significantly (p<0.05) higher

organic matter levels than the upland, whereas

the Ebonyi river basin had significantly

(p<0.05) higher organic matter levels

compared to the organic matter levels of the

Iyiudene and Iyiokwu floodplains. The upland

soils had significant (p<0.05) higher N values

than the floodplains and the river basin. The

result also indicated that the floodplains and

the river basin had significantly (p<0.05)

higher values of available phosphorus than the

upland.

Table 3. The Soil Chemical Properties Treatment Organic

matter

Ph Nitrogen Available

Phosphorus

K Ca Mg Na ECEC Exchangeable

Acidity

Base

Saturation

(%) (H2O) (%) (PPM) (Cmol/Kg) (%)

Iyiudene floodplain 2.93 6.15 0.13 28.20 0.15 11.20 5.20 0.09 18.72 2.08 88.89

Iyiokwu floodplain 3.11 5.39 0.12 29.20 0.13 10.40 5.60 0.09 18.18 1.96 89.22

Ebonyi river basin 2.65 5.95 0.13 34.80 0.13 12.00 5.20 0.13 19.67 2.16 88.76

Upland 2.06 4.38 0.15 18.50 0.17 8.40 3.60 0.04 15.09 2.88 80.91

FLSD (0.05) 0.14 10 0.02 4.40 0.03 0.170 0.11 0.02 0.53 0.63 1.40

Exchangeable Bases

The floodplains and the river basin had

significantly (p<0.05) higher soil

exchangeable Ca, Mg and Na content

compared to the upland, whereas significantly

(p<0.05) higher levels of exchangeable K was

detected on the upland than the Iyiudene

floodplain, Iyiokwu floodplain and the Ebonyi

river basin. The soil of the Iyiokwu floodplain

also had significantly (p<0.05) higher Mg

content than the Iyiudene floodplain and the

soil of the Ebonyi river basin, whereas the

Ebonyi river basin contained significantly

(p<0.05) higher exchangeable Na than the

Iyiudene and Iyiokwu floodplains.

Exchangeable Acidity, Effective Cation

Exchange Capacity and Base Saturation

The upland had significantly (p<0.05) higher

exchangeable acidity values compared to the

floodplains, whereas soil cation exchange

capacity was significantly (p<0.05) higher in

the soils of the Iyiudene, Iyiokwu floodplains

and Ebonyi river basin than the upland. The

soils of the Ebonyi river basin also had

significantly higher CEC than the Iyiudene and

Iyiokwu floodplains Base saturation was

significantly (p<0.05) higher in the floodplains

and river basins than the upland, whereas the

floodplains and the river basin had comparable

levels of base saturation.

DISCUSSION

The upland had higher percentage of sand

fraction. Ordinarily, soil textural composition

rarely changes, but in this case it was believed

that the different land uses; the arable

cultivated upland and flooded fallow lowland

over a long time could have led to the

transportation of dislodged lighter soil

particles (silt and clay) to the lower plains

where they accumulated on the topsoil

influencing the texture of the top soil layer.

Anikwe et al. (1999) had observed changes in

soil properties owing to changing land uses in

Abakaliki area.

The higher soil bulk density of the upland was

anticipated. The soil of the study area had been

noted by many researchers to have high bulk

density and to suffer from compaction

problems (FDALR, 1985). This situation was

however ameliorated by the flooding on the

flood plains and the river basin. The runoff

from the upland and flooding from the river

and streams deposited layers of alluvial

materials on the floodplains and the river basin

which had not yet consolidated unlike the soils

of the upland. However, the decayed organic

residue of the vegetation of the floodplains and

the basin areas produced higher levels of

organic matter which reduced the soil density.

The organic matter acting as the soil binding

materials created higher soil porosity and

68


reduced soil density. The low level of moisture

retention in the upland was rather very severe,

and could constitute a serious impediment to

crop production. The soil cultivation practices

normally distort the continuity of pores leading

to increased water runoff and reduced water

infiltration. It was believed that the improved

soil water retention of the flooded lands was

an attribute of reduced density, improved

porosity and higher organic matter content,

and reduced water runoff compared to the

cultivated upland. These properties reflect

improved soil structure for the floodplains and

the river basin.

The higher levels of organic matter detected

on the flood plains and river basin soils were

attributable to the accumulation of residues of

the fallow vegetation over a long term and the

deposits brought by the flood water. The

clearing and cultivation of the upland led to

organic residue decomposition and loss of

organic materials to seasonal water runoff and

erosion. The soil of the study area is however

noted to have low organic matter levels

(Asadu and Akamigbo, 1990) which

drastically affected the organic matter status of

the soils generally.

The various soil areas are rather acidic.

Several researchers had earlier reported that

the soils of the area are acidic and of low

fertility (Ogbodo and Nnabude, 2004). The

low organic matter levels of the soil were

assumed to have contributed in part to the low

soil pH. The higher pH values of the

floodplains were attributed to the higher Ca

and Mg levels. These elements naturally

displaced H+ ion from the exchange complex

into the soil solution, where they are leached.

This situation is even more intensive under

strongly acidic soil conditions as obtained in

the study area.

The lower N values of the floodplains could be

as a result of losses of N through various

sources. Nitrogen being a very mobile

element, is prone to be lost easily through

leaching and percolation under flooded

situation, and volatilization once the flood

water recedes. This could account for a

reasonable depletion of the element in the

floodplains, which could adversely affect crop

production. Nelson and Terry (1996) observed

drastic loss of soil nitrogen after flooding. The

low total N of the floodplains also conforms to

the observations of Valiela and Teal (1974)

that estuarine wetlands tend to have N

limitations.

The significantly higher soil available P on the

flooded soils was understandable. This is

because the easiest way to increase soil P is to

improve soil moisture content. Nathan (2002)

also observed that flooding generally increases

the availability of P to crops. The higher pH of

the flood plain and the river basin soils could

also have encouraged the solubilization of

organic P which might have led to the release

of inorganic P bound in soil minerals. The

decay and mineralization of the vegetation

residues could have in turn led to the release of

organic P in residues in the floodplain areas.

Ukpong (2006) reported high available P

levels in the Creek / Calabar River swamps.

The generally low level of available P

indicates that P may be chemically bound as

phosphates of Fe and Al owing to the observed

high acidity of the soils of the study area. This

observation is in agreement with the findings

of Ibia and Udo (1993).

Significantly higher soil Ca, Mg and Na levels

were observed in the flooded soils than the

unflooded upland. Some of these elements

could have been eroded from the upland

during runoff and deposited on the floodplains

by the flood water. On the other hand nutrient

mining by crops could have contributed to the

reduction of these elements in the upland. The

release of the organic forms of Ca and Mg

from the organic matter increased their levels

in the flooded soils which had higher organic

matter deposits. In addition, the higher soil

moisture of the flooded soils could have

assisted the release of the inorganic Ca and Mg

from the soil minerals. The levels of soil K

content varied among the floodplains. The

69


inconsistency of the soil K content among the

study areas could be as a result of the variation

in soil minerals and constituents amongst the

different sites of the study area. The higher

exchangeable K found in the upland than the

floodplain soils could be attributed to small

content in the organic matter and the flood

water supply. There could also have been

losses of K through leaching and percolation

in the floodplains. Higher rates of K losses

have been reported to occur in Wetlands

(IFPRI, 1999), whereas Ambeager (2006)

reported losses of K through erosion and

leaching. The soil Na content was higher on

the flooded areas than the Na content of the

upland. Naturally flood water carries along

salts which are deposited on the soil as the

flood water recedes, and as evaporation takes

place leaving salt crusts and crystals. This

situation was adduced for the higher Na

content of the flood plains and the river basin

areas.

Exchangeable acidity was significantly

(p<0.05) higher in the upland than the

floodplains and river basin. The levels of

exchangeable acidity of the study soils were

such that could cause serious problems to crop

production. The variability in soil cation

exchange capacity was in response to variation

in vegetation residue type and soil organic

matter levels. Organic matter is the store of

essential elements, hence the higher the soil

organic matter levels, the higher the soil CEC

and buffer capacity. The transportation of

elements, in the flood water and runoff from

the streams and arable land increased the

element contents of the river flood plains and

the basin thus increasing their CEC. Percent

base saturation was high in both upland and

the floodplains. Base situation was above 50%

in all the cases which forms the separating

index between fertile soils and less fertile

soils. This was surprising considering the low

CEC of the soils in the study area.

Some important soil chemical characteristics

that influence the rating of soils suitability for

crop production include pH, organic matter

total N, available P, and exchangeable bases

and physical properties including texture,

structure, temperature, bulk density, porosity,

moisture and drainage. The soils have

particularly low organic matter content.

However, the observed higher organic matter

values of the flood plains reflect higher

productivity and reduced decomposition and

mineralization rates in wetland environments.

Kyuma (1985) and Patrick (1990) reported that

such situations result in accumulation of

organic matter.

Based on the result of the soil chemical

analysis, it is apparent that the soils are

generally acidic, low in organic matter, total

N, available P and cation exchange. According

to the ratings capacity of Landon (1984) and

Enwezor et al. (1988), the soils are low in

fertility and cannot sustain optimum crop

production.

For improved crop yields on short term basis,

mineral fertilizers are recommended as a stop-

gap to promote higher crop yields. However,

for a long-term sustainable crop production,

soil fertility restoration measures affordable

for farmers should be adopted. Among these

measures are the use of organic manure and

burnt rice husk which is abundant in the area

to improve the soils physical and chemical

constraints. Alternatively, green maturing

practices (e.g. groundnut and other non-food

legumes) should be introduced as a very

economic measure for soil fertility

improvement and regeneration. This measure,

according to Yadav et al. (2001), increases

crop yields by 20-30%, improves soil chemical

N and P by 25%, restores natural fertility and

stimulates plant growth.

CONCLUSION

The result of this study confirms that the soils

of Abakaliki; the study area, has low fertility

and suffers major productivity constraints. The

inhabitants engage the upland soils in crop

production, predominantly root crops and

grain crops, while the flood plains had been

abandoned over the years as unsuitable for

70


agricultural purposes. There has been recent

rapid urbanization of the area, which has led to

the flood plains being choked with houses

aggravating the flooding problem. This study

has revealed that the flood plains are even of

higher fertility than the uplands, and could be

put to better crop production activities.

However, in order to ensure optimum crop

production, there is the need to alleviate the

inherent fertility constraints of the soils. The

use of organic residues to solve the soils

physical and chemical constraints is

recommended, to improve the fertility and

crop yields. The inhabitants could utilize this

ameliorative measure to produce rice in the

flood plains during the rainy seasons.

REFERENCES

Ambeager, A., 2006. Soil fertility and plant nutrition in the tropics and subtropics IFAV IPI. Pp. 96.

Anikwe, M.A.N., C.I. Okonkwo and N.L.

Aniekwe, 1999. Effect of Changing Land use in selected soil properties in Abakaliki Agroecoloigcal Zone South-East Nigeria. Environmental Education and Information 18, pp. 79-89.

Asadu, O.L.A. and F.O.R. Akamigbo, 1990.

Relative contribution of organic matter and Clay fractions to Cation Exchange Capacity of Soils in Southeastern Nigeria. Samaru Journal of Agricultural Research 7:17 - 23.

Blake, G.R. and K.H. Hartge, 1986. Bulk

density. In: methods of soil analysis, part 1. Physical and Mineralogical methods. A. Klute (ed) American Society of Agronomy, Madison, WI USA: 365-375.

Enwezor, W.O., A.C. Ohiri, E.E. Opuwaribo

and E.J. Udo, 1988. A review of soil fertilizer use of crops in Southeastern zone of Nigeria. Fertilizer procurement and Distribution Department, Lagos, Nigeria.

Federal Department of Agriculture Land

Resources (FDALR), 1985. Agriculture Land Resources Technical Bulletin. Vol 5.

IFPRI, 1999. Nurturing the soil in Sub-saharan

Africa. International Food Policy Research Institue. A 2020 vision for Food, Agriculture and the Environment.

IITA, 1979. Selected Methods for Soil and

Plant Analysis. Manual series No. 1 International Institution of Tropical Agriculture, Ibadan, Nigeria.

Klute, A. 1986. Water Retention: Laboratory

Methods. In: Klute, A. (ed). Methods of Soil Analysis, Part I: Physical and Mineralogical Methods, 2nd ed. ASA, SSSA, Madison USA: 635-660.

Landon, J.R., 1984. Booker Tropical Manual.

A handbook for soil Survey and agricultural land evaluation in the tropics and subtropics. Booker Agricultural International Ltd. UK.

Nathan S., 2002. Effect of soil flooding on

phosphorus reactions. Crop, soil and Environmental sciences Department. 115 plant science Bldg; University of Arkansas, Fayetteville, AR 72701.

Nelson S.D. and R.E. Terry, 1996. The effects

of soil physical Properties and irrigation method on denitrification. Soil science vol. 161 No. 4, Lippibcott Williams and Wilkins press, Baltimore. Pp. 242-249.

Ogbodo, E.N. and P.A. Nnabude 2004.

Evaluation of the performance of three varieties of upland Rice in degraded acid soil at abakaliki, Ebonyi State. Journal of Technology and Education in Nigeria. Vol. 9(1) 2004 1 – 7.

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Sauer, V.I.B., W.O. Thomas, V.A. Sticker and

K.V. Wilson, 1992. Flood

characterization of urban watershed in

The United States “U.S Geological

survey water-supply paper 2007, pp.

63.

Tel, D. and F. Rao, 1982. Automated and

semi-auto-mated methods for soil and

plant analysis, IITA manual series No.

17:15-25.

Valiela, L. and J.M. Teal, 1974. Nutrient

limitation in salt marsh vegetation. In:

Vegetation Reimold, R. J and W.H

Queen (Eds) Ecology of halophytes.

Academic press, New York, pp. 547-

563.

Yadav, A.K.; S.R. Chaudhari and M.R.

Motsara, 2001. Recent Advances in Biofertilizer Technology. Society for Promotion and Utilization of Resources and Technology, pp. 526.

72


EFFECT OF TILLAGE AND CROP RESIDUE ON SOIL CHEMICAL PROPERTIES

AND RICE YIELDS ON AN ACID ULTISOL AT ABAKALIKI SOUTHEASTERN

NIGERIA

OGBODO, E.N1. AND P.A. NNABUDE2 1Department of Soil Science and Environmental Management, Faculty of Agriculture and

Natural Resources Management, Ebonyi State University, P.M.B. 053 Abakaliki, Nigeria. 2Department of Applied Biological Sciences, Nnamdi Azikiwe University, Awka, Nigeria.

ABSTRACT

A study was conducted in 2008 and 2009 rainy seasons, to evaluate the possibility of alleviating

the degraded soil conditions at Abakaliki. The measures employed were combination(s) of

different tillage methods [ No-Tillage (NT), Hoe Tillage (HT), Ploughing (PL) and Ploughing

and Harrowing (PH)] and crop residues [No Residue (NR), Rice Straw (RS), Burnt Rice Straw

(BRS) and Legume Residue (LR)] treatments. Improved rice cultivars (ITA 257, Ex-China and

ITA 315) were the test crops. The design of the experiment was a 4 x 4 x 3 factorial in a

randomized complete block design replicated three times. Data on soil chemical properties, rice

growth and yield were collected and subjected to statistical analysis. The results obtained showed

that soil organic matter, pH, available P, exchangeable K, Ca, Mg and CEC significantly

(p<0.05) improved in the plots that received crop residue across the four tillage methods

compared to where crop residues were not applied. The soil chemical properties were also

significantly (p<0.05) superior with the application of BRS across the four tillage methods

compared to the application of the other residue treatments. Rice growth and grain yield were

significantly (p<0.05) higher on the plots that received the combination of the different tillage

methods and crop residues respectively than the combination of the different tillage methods

without crop residues. There were grain yield increases of 1.47, 1.21 and 1.20 t/ha in the first

year and 2.05, 1.64 and 1.53 t/ha in the second year with the application of NT+BRS, NT+RS

and NT+LR respectively compared to the application of NT+NR. The application of HT+BRS,

HT+RS and HT+LR brought about significant (p<0.05) grain yield increases of 1.65, 1.20 and

1.16 t/ha and 2.67, 2.45 and 2.42 t/ha in the first year and second year respectively. Grain yield

significantly (p<0.05) increased by 1.91, 1.68 and 1.62 t/ha in the first year and 2.44, 1.95 and

1.91 t/ha in the second year respectively as a result of PL+BRS, PL+RS and PL+LR treatments

compared to PL+NR. PH+BRS, PH+RS and PH+LR treatments led to significant (p<0.05) grain

yield increases of 2.55, 1.54 and 1.52 t/ha respectively in the first year and 2.74, 1.72 and 1.71

t/ha respectively in the second year compared to the application of PH+NR treatment. The ITA

315 and Ex-China produced 0.55 and 0.47 t/ha, and 0.62 and 0.50 t/ha significantly (p<0.05)

higher grains than ITA 257 in the first and second years respectively. The highest grain yield of

4.87 t/ha in the study was obtained from ITA 315 grown on soil that received PH+BRS

treatment.

Key words: Tillage and Crop Residue, Soil Chemical Properties, Rice Yields, Acid Ultisol,

Southeastern Nigeria

Ogbodo and Nnabude NJSS/22(1)/2012


INTRODUCTION

Most tropical soils are known to suffer

structural and fertility constraints. The soils of

the Abakaliki Agro-ecological zone of

southeastern Nigeria, which falls under the

tropical environment, have specifically been

reported by several researchers to be very

acidic, low in organic matter content and that

consequently the soils have low levels of

exchangeable bases, cation exchange capacity

and buffer capacity (Enwezor et al., 1985;

FDALR, 1985 and Asadu and Akamigbo,

1990). The soils are therefore of low fertility

leading to low crop productivity. The use of

minimum tillage and crop residue has been

advanced as minimumpart of the measures that

could be used to manage the soil productivity

problems and increase the yield of crops.

Rice production in Abakaliki area has been

severely affected by the degraded soil

conditions. The average yield of 2.5 t/ha

normally obtained from the area is rather low

compared to yields from other rice producing

areas of the world. Efforts had been made to

resolve the productivity constrains of the soil

through the use of different tillage methods, or

various organic manure sources and

management methods (Nnabude and Mbagwu,

1999; Ogbodo, 2004; Ogbodo, 2005ab;

Ogbodo, 2009 and Ogbodo, 2010).

The present study is a combination of different

tillage methods and crop residue sources to

resolve the soil and crop productivity problems

in the study area, using improved rice cultivars

as the test crop.


The experiments were carried out in the 2008

and 2009 rainy seasons at the Research and

Teaching Farm of the Faculty of Agriculture,

Ebonyi State University, Abakaliki. The area

is located within longitude 080 03/ E and

latitude 060 25/ N in the derived savanna zone

of Nigeria. The mean monthly temperatures

ranged between 24 0C and 28 0C. The rainfall

pattern was bimodal, with peaks in the months

of July and September. Annual amounts of

rainfall ranged between 1800 and 2000 mm.

Rainfall stabilized around May and stopped

around October, leaving a dry period between

November and April during the study seasons.

The soil is hydromorphic and has an

isohypothermic soil temperature regime and

belongs to the order ultisol derived from shale

and classified as typic haplustult (FDALR,

1985). The description of the surface soil

physical and chemical characteristics is shown

in Table 1. The experimental site was

previously used for rice cultivation, before it

was used for the experiment.

Table 1: Pre-Planting Soil Texture and Chemical Properties

Soil Texture Sand (%) Silt (%) Clay (%) Textural Class Chemical Properties pH (H2O) Organic Matter (%) Total N (%) Available P (gm/kg) K (cmol(+)kg) Ca (cmol(+)kg) Mg (cmol(+)kg) CEC (cmol(+)kg)

44.80 34.40 20.80 Sandy Clay Loam 4.80 2.00 0.12 6.00 0.19 2.10 2.20 4.60

73

Effect of tillage and crop residue on ultisol


Experimental Design and Field Layout

The experimental design used was 4 x 3 x 4

split-split plot factorial in a Randomized

Complete Block Design. The area of land

used for the experiment measured 769.5 m2.

Each replicate measured 256.5 m2 and

comprised of four tillage methods, three rice

cultivars and four crop residue sources. There

were three blocks within each tillage treatment

(made up of twelve treatment units) measuring

54 m2. Each block comprised of 4 treatment

units, each measuring 16 m2. The replicates

and tillage methods were separated by one

another by 1m alleys respectively, whereas the

individual plots were separated by 0.5 m

alleys.

Treatments

Tillage methods were the main treatment, the

rice cultivars were the sub treatment whereas

crop residues were the sub-sub treatment. Each

treatment was replicated three times. The

tillage methods were: No – tillage (NT), Hoe –

tillage (HT), Ploughing (PL) and Ploughing

and harrowing (PH). The three rice cultivars

were ITA 315, Ex-china and ITA 257, whereas

the crop residue treatments were no residue

(NR), Rice Straw (RS), Burnt Rice Straw

(BRS) and legume residue (LR). The dry rice

straw was from the previous year’s harvest,

whereas Centrocema pubensis was harvested

from the ones growing widely in the

surrounding bush. The improved rice cultivars

used for the trials were foundation seeds

sourced from the International Institute of

Tropical Agriculture (IITA), Ibadan, Nigeria.

Treatment Applications

The ploughing was carried out once for the PL

plots, while the PH plots were ploughed once

and harrowed twice. For the HT plots, the

vegetation was slashed with a matchet and

removed, while the soil was tilled manually

with a hoe. A non-selective herbicide,

glyphosate (360g a.i) was sprayed on the

vegetation on the NT plots at the rate of 5

liters per hectare two weeks before sowing the

seed. The crop residues were applied as

surface mulch on the appropriate plots. 5 ton

per hectare (t/ha) equivalent of dry rice straw,

freshly harvested Centrosema pubensis and

burnt rice straw were applied on the

appropriate plots respectively. For the NR

plots, no crop residue was applied while the

existing plant residues were removed. The rice

seeds were directly seeded by dibbling; using

sticks to create opening and the seeds covered

after sowing. Three seeds were planted per hill

at a spacing of 25 cm x 25 cm, and later

thinned down to two seedlings per stand at 21

days after planting (DAP), giving a plant

population of 320,000 stands per hectare.

Cultural Practices

Fertilizer was applied at the rate of 40 kg P /

ha as single super phosphate, 40 kg K / ha as

muriate of potash and 80 kg N / ha as urea to

all the plots. One third of the N fertilizer was

applied alongside the P and K basally before

residue application; 4 days before planting the

seeds, whereas the remaining two thirds of N

were applied at 75 DAP.

Data Collection

Six soil auger samples were randomly

collected from the experimental area at 0-20

cm depth for pre-planting soil analysis. At the

end of each season’s experiments, six auger

samples were taken from each plot, mixed and

a sub-sample taken for post harvest chemical

analysis. Plant height and tiller number were

measured at 75 DAP. Plant height was taken

as the height from the base of the plant and the

tip of the tallest tiller using a meter rule. At

dry maturity, the rice panicles were harvested

from a net plot of 2 m x 2 m in the middle of

each plot, dried, threshed and the grain yield

data adjusted to 14% moisture, and converted

to t/ha.

Laboratory Methods

The pre-planting composite soil sample (taken

at 0 – 20cm depth) was analyzed in the

laboratory for the texture and chemical

properties. The soil particle size distribution

was determined by the hydrometer method

74

75


(Gee and Bouder 1986). The post harvest soil

samples taken from each plot were subjected

to chemical analysis. Total nitrogen was

determined by the Macro Kjeldahl method

(Bouycous, 1951). Available P was

determined using Bray II method as outlined

in Page et al. (1982). Organic carbon was

determined by the Walkley and Black method

(Nelson and Sommers, 1982). Soil pH (2:1 in

water) was determined by the glass electrode

pH meter (Maclean, 1982). Exchangeable

bases were extracted using the ammonium

acetate method (Tel and Rao, 1982)

DATA ANALYSIS

Analysis of variance and mean separation was

done using least significant difference test for

P≤0.05 procedure as described by SAS (2006).

RESULTS

Soil chemical properties The effect of tillage methods and crop residue

treatments on soil chemical properties are

presented in Tables 2a – b. Significantly

(p<0.05) higher organic matter levels were

detected on the rice straw and legume residue

treated plots than on the no-residue and burnt

rice straw treated plots across the four tillage

methods. Application of the various crop

residues raised the soil pH levels across the

four tillage methods compared to where the

soil was not treated with crop residue. Treating

the soil with burnt rice straw significantly

(p<0.05) increased soil pH compared to the

other residue treatments across the tillage

methods.

Significantly (p<0.05) higher N, P, K, Ca and

Mg levels were also detected on the soils

treated with crop residue than where crop

residue treatment was not applied across the

four tillage methods. The concentrations of

exchangeable Ca and Mg were significantly

(p<0.05) higher on the soils that received burnt

rice straw treatment across the four tillage

methods than where the soil was treated with

rice straw and legume residue across the

tillage treatments.

The soils that received tillage and crop residue

treatments had significantly (p<0.05) higher

cation exchange capacity than the soils that

were treated with the various tillage methods

but without crop residue application. The soils

that specifically received burnt rice straw

treatment across the various tillage treatments

had significantly (p<0.05) higher cation

exchange capacity compared to the ones that

were treated with rice straw or legume residue

across the four tillage methods.

76


Table 2a: Effect of Tillage and Crop Residue on Organic Matter, pH, Total Nitrogen and Available Phosphorus

T

a

b

l

e

2

.

NT = No-Tillage; HT= Hoe Tillage; PL = Ploughing; PH = Ploughing and Harrowing; NR = No Residue; RS = Rice Straw;

BRS = Burnt Rice Straw and LR = Legume Residue

First Year

Residue

Type

Organic Matter

(%)

pH

(H20)

Total Nitrogen

(%)

Available Phosphorus

(mg/ gm)

NT HT PL PH NT HT PL PH NT HT PL PH NT HT PL PH

NR 2.00 1.00 2.00 2.02 4.80 4.70 4.70 4.50 0.12 0.12 0.11 0.14 6.00 5.80 5.50 6.60

RS 2.90 2.00 2.94 2.93 5.70 5.70 5.90 5.10 0.22 0.20 0.26 0.20 11.70 10.80 11.40 10.10

BRS 2.46 1.21 2.22 2.20 6.40 6.40 6.30 6.40 0.25 0.20 0.20 0.20 10.70 11.40 11.70 10.10

LR 2.87 2.00 2.63 2.62 5.70 5.80 5.70 5.60 0.22 0.22 0.24 0.21 9.50 8.10 9.70 8.50

LSD(0.05) 0.40 0.65 0.09 2.53

Second Year

Residue

Type

Organic Matter

(%)

pH

(H20)

Total Nitrogen

(%)


(mg/ gm)


NR 2.03 0.95 2.08 2.06 4.40 4.00 4.50 4.70 0.17 0.12 0.15 0.16 5.50 5.10 4.80 8.20

RS 2.99 2.00 2.92 2.94 5.60 5.80 6.00 5.40 0.24 0.19 0.22 0.23 11.20 11.00 10.20 11.10

BRS 2.36 1.26 2.00 2.20 6.90 6.30 6.60 6.60 0.24 0.22 0.24 0.24 10.60 10.10 11.00 10.10

LR 2.97 1.98 2.82 2.82 5.40 5.70 5.70 6.20 0.27 0.25 0.25 0.24 7.90 9.00 8.00 10.70

LSD(0.05) 0.36 0.68 0.06 2.26

77


Table 2b. Effect of Tillage and Crop Residue on Exchangeable K, Ca, Mg and Soil CEC

N

T

= No-Tillage; HT= Hoe Tillage; PL = Ploughing; PH = Ploughing and Harrowing; NR = No Residue; RS = Rice Straw;

BRS = Burnt Rice Straw and LR = Legume Residue

First Year

Residue

Type

Exchangeable K

(Cmol / kg)

Exchangeable Ca

(Cmol / kg)

Exchangeable Mg

(Cmol / kg)

Soil CEC

(Cmol / kg)


NR 0.19 0.15 0.16 0.17 2.10 1.10 2.00 2.10 2.20 1.00 2.10 2.10 4.49 2.25 4.26 4.37

RS 0.43 0.34 0.51 0.50 4.10 3.70 4.80 4.60 4.00 2.50 4.10 4.40 8.53 6.54 9.41 9.50

BRS 0.45 0.42 0.46 0.48 6.00 5.70 6.00 4.10 5.20 3.90 5.60 5.80 11.65 10.02 12.06 10.38

LR 0.37 0.30 0.46 0.47 4.10 4.40 4.70 4.80 3.30 3.00 3.50 3.60 7.77 7.70 8.66 8.87

LSD (0.05) 0.18 1.06 1.10 2.43

Second Year

Residue

Type

Exchangeable K

(Cmol / kg)

Exchangeable Ca

(Cmol / kg)

Exchangeable Mg

(Cmol / kg)

Soil CEC

(Cmol / kg)


NR 0.17 0.16 0.19 0.17 2.40 2.20 2.30 2.30 2.20 1.90 2.20 2.20 4.77 4.26 4.69 4.67

RS 0.45 0.34 0.42 0.40 4.40 4.10 4.90 4.80 4.20 3.20 4.00 4.90 9.05 7.64 9.32 10.10

BRS 0.46 0.47 0.47 0.40 6.70 6.30 5.80 6.30 5.80 4.90 5.60 5.60 12.96 11.67 11.87 12.30

LR 0.34 0.30 0.40 0.42 4.00 3.80 4.40 4.80 3.90 3.20 3.80 3.60 8.24 7.30 8.60 8.82

LSD (0.05) 0.17 1.02 1.08 2.38

78


Rice Crop Growth The growth response of the rice cultivars to

soil tillage and crop residue treatments are

shown in Tables 3 and 4. Generally rice

growth was significantly (p<0.05) better on the

soil treated with the combination of crop

residues and tillage method than on the soil

tilled or untilled without crop residue

treatment for the two years study. The growth

of the crops was superior on tilled soil treated

with crop residue than on the tilled soil

without crop residue treatment. Growth was

also superior on the untilled plots with crop

residue treatment than untilled plots without

residue treatment. The three rice varieties were

significantly (p<0.05) taller when the soil was

treated with crop residue than where the soil

had no crop residue treatment across the four

tillage methods. Ploughing, ploughing and

harrowing the soil with crop residue

significantly (p<0.05) increased plant height

than when the soil was not tilled, or hoe –

tilled with or without crop residue treatment.

There were no significant differences in plant

heights of the three varieties when under the

same treatments. Tillering was significantly

(p<0.05) higher in ITA 315 and Ex-china than

in ITA 257. The three varieties produced

significantly (p<0.05) higher number of tillers

when the soil was tilled and treated with crop

residue than when not; and when the soil was

untilled with crop reissue treatment than when

not. Ploughing, ploughing and harrowing the

soil with crop residue treatment significantly

(p<0.05) increased tillering compared to where

the soil was not tilled or hoe-tilled with or

without crop residue treatment. Tillerings of

the three varieties were statistically

comparable when the soil received rice straw,

legume residue and burnt rice husk treatments

across the four tillage methods.

Specifically, the influence of the No-tillage

method and residue treatment on the tillering

of the three varieties for the two years was in

the order: NT+BRS = NT+RS = NT+LR >

NT+NR. The application of Hoe-tillage

method and residue treatments to the soil led

to significant differences in tillering of the

three varieties in the order HT+BRS = HT +

RS = HT+LR > HT+NR in the first year, and

HT + BRS>HT+RS = HT+LR> HT+NR in the

second year. When the soil was treated with

ploughing and crop residue the rice tillering

was in the order: PR > PL + RS > PL +LRI>

PL+NR whereas in the second year it was in

the order: PL+BRS>PL+LR>PL+RS>PL+NR.

The influence of ploughing and harrowing

with crop residue treatments on the rice

tillering showed that in the first year

PH+RS>PH+BRS>PH+LR>PH+NR in the

first year, while in the second year the tillering

was in the order PH + BRS = PH + LR = PH +

LR > PH + NR.

The pooled result of the influence of the

various tillage and different residue treatments

on the tillering ability of the three varieties

was in the order ITA 315 > Ex-China>ITA

257 in the first year and ITA 315 = Ex-China

> ITA 257 in the second year.

The combination of the No-tillage and the

different crop residues did not produce

significant differences in plant height in both

years of the study. Plant height was however

significantly (p<0.05) higher where HT+BRS

treatment was applied compared to HT+NR

treatment in both years of the study. For

ploughing and crop residue combinations, the

rice plants were significantly (p<0.05) taller

where PL+BRS was applied to the soil

compared to the application of PL+NR in the

first year, while heights were comparable

among the plants on soils treated with

ploughing and the different crop residues in

the second year. The rice crops were taller on

soils treated with PH+BRS in the first year,

whereas in the second year, the rice plants

were taller on soils treated with PH+BRS and

PH+RS compared to the plants grown on soil

treated with PH+NR.

79


Table 3. Effect of tillage and crop residue on rice plant height

First Year Second Year

Rice Varieties Rice Varieties

Tillage and Residue ITA 257 Ex-China ITA 315 Mean ITA 257 Ex-China ITA 315 Mean

NT+NR 52.53 42.33 55.67 50.18 42.23 47.33 45.67 45.10

NT+RS 45.67 52.33 55.33 51.11 47.67 52.33 56.67 52.22

NT+BRS 49.33 56.67 66.67 57.56 54.33 60.00 61.33 58.55

NT+LR 47.33 54.33 50.67 50.78 50.00 61.33 62.00 57.78

HT+NR 47.33 49.33 52.33 50.60 45.67 47.33 47.67 46.89

HT+RS 56.33 59.00 62.33 59.22 55.33 56.00 66.00 59.11

HT+BRS 52.67 63.33 74.33 63.44 56.67 64.67 69.33 63.56

HT+LR 50.67 60.67 62.00 57.78 50.33 61.33 68.00 59.89

PL+NR 52.33 52.33 50.55 51.74 49.67 52.67 52.33 51.56

PL+RS 54.33 60.00 61.33 58.55 55.33 66.00 71.00 64.11

PL+BRS 56.33 64.67 73.00 64.67 60.00 66.00 72.67 65.67

PL+LR 52.33 60.00 69.67 60.67 56.33 63.00 68.67 62.67

PH+NR 54.33 55.33 56.00 54.22 50.67 52.67 56.00 53.11

PH+RS 61.33 63.00 68.67 64.33 66.00 68.67 74.67 69.78

PH+BRS 66.00 71.00 72.67 69.89 71.00 78.67 84.67 78.21

PH+LR 61.00 66.00 68.67 65.22 64.33 69.33 70.67 68.11

Mean 53.74 58.98 62.50 54.70 60.46 64.21

FLSD (0.05)

Tillage and residue 4.12 6.15

Varieties 5.00 9.26

NT+NR = No-Tillage + No Residue; NT+RS = No-Tillage + Rice Straw; NT+BRS = No-Tillage+ Burnt Rice Straw;

NT+LR = No-Tillage + Legume Residue; HT+NR = Hoe Tillage + No Residue; HT+RS = Hoe Tillage + Rice Straw

HT+BRS = Hoe Tillage + Burnt Rice Straw; HT+LR = Hoe Tillage + Legume Residue; PL+NR = Ploughing + No

Residue; PL+RS = Ploughing + Rice Straw; PL+BRS = Ploughing + Burnt Rice Straw; PL+LR = Ploughing +

Legume Residue; PH+NR = Ploughing and Harrowing + No Residue; PH+RS = Ploughing and Harrowing + Rice

Straw; PH+BRS = Ploughing and Harrowing + Burnt Rice Straw; PH+LR = Ploughing and Harrowing + Legume

Residue

Table 4. Effect of tillage and crop residue on number of rice tillers First Year Second Year Tillage and Residue Rice Varieties Rice Varieties ITA 257 Ex-China ITA 315 Mean ITA 257 Ex-China ITA 315 Mean

NT+NR 4.00 11.00 11.00 9.00 6.00 8.00 8.00 9.00 NT+RS 6.00 14.00 13.00 12.00 11.00 12.00 12.00 11.00 NT+BRS 7.00 15.00 16.00 13.00 10.00 13.00 13.00 12.00 NT+LR 7.00 15.00 17.00 14.00 8.00 12.00 11.00 11.00 HT+NR 6.00 11.00 15.00 11.00 7.00 11.00 12.00 10.00 HT+RS 12.00 14.00 16.00 14.00 12.00 15.00 17.00 15.00 HT+BRS 10.00 16.00 17.00 14.00 13.00 21.00 18.00 17.00 HT+LR 11.00 10.00 13.00 13.00 12.00 17.00 14.00 14.00 PL+NR 10.00 10.00 13.00 11.00 10.00 12.00 13.00 12.00 PL+RS 15.00 19.00 16.00 17.00 14.00 19.00 18.00 17.00 PL+BRS 16.00 18.00 20.00 18.00 12.00 15.00 17.00 15.00 PL+LR 14.00 16.00 15.00 15.00 13.00 15.00 18.00 15.00 PH+NR 12.00 15.00 14.00 14.00 14.00 14.00 15.00 14.00 PH+AS 15.00 18.00 20.00 18.00 19.00 18.00 16.00 18.00 PH+BRS 13.00 19.00 18.00 17.00 14.00 18.00 20.00 17.00 PH+LR 14.00 15.00 19.00 16.00 15.00 18.00 20.00 18.00 Mean 10.00 16.00 16.00 12.00 15.00 15.00 LSD (0.05) Tillage and residue 2.71 2.00 Varieties 2.75 3.00

NT+NR = No-Tillage + No Residue; NT+RS = No-Tillage + Rice Straw; NT+BRS = No-Tillage+ Burnt Rice

Straw;





80


Rice grain yield

The effect of tillage and crop residue treatment

on rice grain yield is presented in Table 5.

Generally, there was significant increase in

grain yield for the three varieties when the soil

was tilled and treated with crop residue than

when the soil was not tilled and without crop

residue treatment. Grain yield was also

significantly (p<0.05) higher when the soil

was tilled and treated with crop residue than

when tilled without crop residue treatment.

Grain yield was also significantly (p<0.05)

higher when the soil was treated with crop

residue than when not across the four tillage

methods. Ploughing, ploughing and harrowing

the soil with crop residue treatment led to

significantly (p<0.05) higher grain yield than

when the soil was not tilled or hoe-tilled, with

or without crop residue treatments. The

combination of burnt rice straw and ploughing,

and burnt rice straw and ploughing and

harrowing operations led to significantly

(p<0.05) higher grain yield than when the soil

was not tilled or hoe-tilled with residue

treatment. Generally, grain yield of ITA 315

and Ex-China were significantly (p<0.05)

higher than grain yield of ITA 257. The

highest grain yield of 4.87 t/ha was obtained

from ITA 315 when the soil received

combination of ploughing and harrowing with

burnt rice straw treatment.

Specifically, the influence of the different

tillage methods and crop residue treatments on

the grain yields of the three rice varieties

showed that under No tillage methods and

residue management, grain yields were

significantly higher in the order NT + BRS =

NT + RS = NT+LR>NT+NR in the first year

and NT+BRS > NT+RS= NT+LR> NT+NR in

the second year, whereas under Hoe-tillage

and crop residue combination treatments the

order was: HT + BRS > HT + RS = HT + LR

>HT+NR in the first year and HT + BRS = HT

+ RS = HT+LR>HT+NR in the second year.

The order of influence of ploughing and

residue combination treatments on grain yield

was in the order: PL+BRS = PL + LR = PL +

RS>PL+NR in the first year, and PL + BRS >

PL + RS=PL+LR>PL+NR in the second year,

while the order of influence for applying

ploughing and harrowing with crop residue

treatment to the soil on rice grain yield was

PH+BRS>PH+RS=PH+LR>PH+NR in both

years of the study.

The pooled result of the yield response of the

different varieties to the treatments were in the

order ITA 315 =Ex-China >ITA 257.

Quantitatively, grain yield significantly

increased by 147, 1.21 and 1.20 t/ha as a result

of the application of NTBRS, NT+LR and

NT+RS in the first year compared to NT+ NR

treatment. In the second year, there were 2.05,

1.64 and 1.53 t/ha significantly higher grain

yields as a result of the application of NT +

PRS, NT + LR and NT + RS treatments

compared to NT + NR, whereas NT+BRS also

led to 0.52 and 0.41 t/ha significantly (p<0.05)

higher grain yield than NT+ RS and NT + LR.

When the soil was tilled with hoe and treated

with crop residues, significantly (p<0.05)

higher grain yields of 1.65, 1.20 and 1.16 t/ha

were obtained by the application of HT+BRS,

HT+LR and HT+RS than HT+NR treatment,

while grain yield significantly increased by

0.45 and 0.49 t/ha as a result of the application

of HT + BRS compared to HT + LR and HT +

RS respectively. In the second year, HT +

BRS, HT + LR and HT + RS treatments

brought about 2.67, 2.45 and 2.42 t/ha

significantly (p<0.05) higher grain yields

compared to the application of HT+ NR.

Ploughing the soil and applying crop residues

brought about significant grain yield increases

of 1.91, 1.68 and 1.62 t/ha as a result of

PL+BRS, PL+LR and PL+RS treatments

respectively, compared to PL+NR in the first

year. In the second year subjecting the soil to

PL+BRS, PL+LR and PL+RS treatments

significantly increased grain yield by 2.44,

1.95 and 1.91 t/ha respectively compared to

PL+NR, whereas PL+BRS also significantly

improved grain yield by 0.53 and 0.49 t/ha

compared to PL+RS and PL+LR respectively.

When the soil was ploughed and harrowed,

and treated with the different crop residues,

81


significantly (p<0.05) higher grain yields of

2.55, 1.54, 1.52 t/ha were obtained as a result

of PH+BRS, PH+LR and PH+RS respectively

compared to PH+NR in the first year.

PH+BRS treatment also increased grain yield

by 1.03 and 1.01 t/ha compared to treating the

soil with PH+RS and PH+LR respectively.

The Second year result showed that applying

PH+BRS, PH+RS and PH+LR to the soil

significantly increased rice grain yields by

2.74, 1.72 and 1.71 t/ha respectively than

PH+NR treatment, whereas PH+BRS also

brought about 1.03 and 1.02 t/ha significantly

higher grains than treating the soil with

PH+LR and PH+RS respectively.

The variety effect on grain yield valued across

tillage methods and residue managements

showed that in the first year, ITA 315 and Ex-

China had 0.55 and 0.47 t/ha significantly

higher grain yields respectively than ITA 257,

while in the second year ITA 315 and Ex-

China had 0.62 and 0.50 t/ha significantly

higher grain yield than ITA 257. There were

no significant differences in the grain yields of

ITA 315 and Ex-China owing to variety effect

in the two years.

Table 5. Effect of tillage and crop residue on rice grain yield First Year Second Year

Tillage and Residue Rice Varieties Rice Varieties

ITA 257 Ex-China ITA 315 Mean ITA 257 Ex-China ITA 315 Mean

NT+NR 0.40 0.55 0.60 0.52 0.46 0.45 0.50 0.47

NT+RS 1.65 1.75 1.77 1.72 1.87 2.00 2.13 2.00

NT+BRS 1.75 2.23 2.00 1.99 2.40 2.53 2.63 2.52

NT+LR 1.70 1.75 1.75 1.73 2.00 2.10 2.23 2.11

HT+NR 0.50 0.68 0.67 0.62 0.60 0.67 0.68 0.65

HT+RS 1.68 1.80 1.85 1.78 2.40 3.30 3.53 3.07

HT+BRS 1.95 2.40 2.46 2.74 2.67 3.63 3.67 3.32

HT+LR 1.67 1.80 1.98 1.82 2.46 3.34 3.50 3.10

PL+NR 0.80 1.27 2.00 1.36 0.94 1.18 1.10 1.07

PL++RS 2.46 3.38 3.10 2.98 2.60 3.00 3.34 2.98

PL+BRS 2.60 3.58 3.63 3.27 3.00 3.62 3.92 3.51

PL+LR 2.59 3.34 3.20 3.04 2.68 3.10 3.28 3.02

PH+NR 1.42 1.69 1.87 1.66 1.28 1.77 1.83 1.63

PH+RS 2.68 3.34 3.53 3.18 2.83 3.56 3.67 3.35

PH+BRS 3.34 4.62 4.66 4.21 3.63 4.60 4.87 4.37

PH+LR 2.64 3.30 3.67 3.20 2.77 3.62 3.64 3.34

Mean 1.87 2.34 2.42 2.16 2.66 2.78

FLSD (0.05)

Tillage and residue 0.42 0.40

Varieties 0.43 0.45

NT+NR = No-Tillage + No Residue; NT+RS = No-Tillage + Rice Straw; NT+BRS = No-Tillage+ Burnt Rice

Straw;





Straw; PH+BRS = Ploughing and Harrowing + Burnt Rice Straw; PH+LR = Ploughing and Harrowing + Legume

Residue

DISCUSSION

The higher organic matter levels on the

surfaces of residue treated plots were a product

of the decomposed crop residue. The hoe-tilled

soil had lower organic matter level than the

soils with the other tillage methods with or

without residue treatment because of the

removal of the existing vegetation during land

clearing. The lower organic matter on the

burnt rice straw treated soils occurred because

much of the organic carbon was lost during

burning. The reduction in the acidity of residue

treated soils was more of a result of organic

matter level than the effect of tillage. The

significantly higher pH of the burnt rice straw

treated soils was also specifically because of

82


the influence of Ca and Mg which are the

major constituents of the burnt rice straw, and

which had liming effect on the soil acidity.

These elements displaced H ions in the

exchange site which were leached down the

soil profile, hence reducing the H ion

concentration of the soil. Biederbeck et al.

(1980) also reported that organic residue

particularly the burnt type had liming effect on

the soil. The improvement in soil chemistry in

the study was very encouraging considering

the poor fertility status of the soil reported

earlier (FDALR, 1985) and the pre-planting

chemical properties of the study site.

The differences in the basic cations between

where residues were applied compared to

where there was no residue application across

the tillage methods was accounted for by the

release of the organic elements in the residues

after decomposition and mineralization. This

might have been made possible by the

increased activities of microbes which must

also have increased in population due to the

conducive environment for their survival

provided by the residue mulch. The lower

acidity on the residue treated soil also

encouraged the mineralization and release of

these elements. The organic residue might also

have increased soil moisture levels and hence

the solubilization and increased organic P

availability. Blevins et al. (1983) equally

reported that the behaviour of P is governed by

soil water, which improves phosphorus

availability in the soil.

The higher organic matter levels equally led to

the increase in the soil nutrient elements and

CEC because of the ones released from the

organic matter reserve . Organic matter is

known to be the natural reserve of the organic

nutrients. The higher pH values on residue

treated soils also encouraged the release of

these elements in the soil exchange complex.

Asadu and Akamigbo (1990) reported that

reduced acidity would encourage the

solubilization and release of the inorganic

forms of nutrient elements into the soil. It is

the reduction in the soils acidity and increased

organic matter and accumulation of nutrients

that brought about higher soil cation exchange

capacity observed in the residue treated plots

in the study.

The improved soil chemical properties under

residue treatment made nutrients more

available for plant growth whether the soil was

tilled or not tilled. The higher levels of these

nutrient elements increased crop productivity .

The reduced acidity under crop residue

treatment made more nutrients available and

reduced the availability of trace elements that

could have hampered crop growth . Also,

improved soil structure and moisture under the

tilled and residue treatment conditions made

mobility of nutrient and gaseous exchange

easier leading to improved nutrient availability

and uptake by plants for growth .

The improved soil chemical properties

resulting from the treatment including reduced

acidity and higher soil organic matter and

availability of nutrients raised the soil fertility

status leading to significant increase in grain

yield. This was accentuated by the

improvement in grain yield tonnage harvested

per hectare among the three varieties. The

highest grain of 4.47 t/ha obtained in the study

is a great improvement in the average yield of

2.5 – 3.5 t/ha reported in earlier studies in the

area ( Ogbodo and Nnabude, 2004; Ogbodo et

al., 2009; Ogbodo, 2010). The reduced acidity

of the plots treated with BRS across the tillage

methods led to increased release of nutrient

into the soil and subsequent uptake by plants

for superior growth and yield compared to the

other treatments. The soil physical

environmental conditions provided by tillage

also improved mobility of nutrients and root

penetration to access the nutrients and water.

The superior plant size particularly the higher

tillering of the plants where the soil was tilled

and treated with crop residue enhanced the

photosynthetic efficiency of the plants, leading

to improved grain yield. The significantly

higher grain yield obtained in ITA 315 and Ex-

China plots across the whole tillage and crop

83


residue treatments was a product of variety

effect. Ogbodo and Nnabude (2004) had

reported significantly higher yield of ITA 315

and Ex-China compared to ITA 257 which

they attributed to the adaptability of the two

varieties to the inherent environmental

conditions of the study area.

CONCLUSION

The results of the study indicated that it is

possible to bring about improvements in the

fertility status of the soils of Abakaliki area

with adequate tillage and crop residue

management. These combination treatments

provided conducive soil environment for

nutrient availability and uptake by plant for

growth and yield. The treatment combination

of tillage and burnt rice straw provided

particularly superior improvement in soil

chemical properties, because the residue ash

neutralized the soil acidity to a great extent as

well as provided other nutrient needed by the

rice crop for growth and yield, compared to

the other residue sources. Ploughing and

harrowing the soil and treating with burnt rice

straw proved the most adequate measure in the

study to combat the soils chemical constraints.

It is apparent from the study that for a better

improvement in rice grain yield in the study

area that farmers are encouraged to plough and

harrow their soils, and treat with burnt rice

straw.

REFERENCES

Biederbeck, V. O; C. A. Campbell, K. E.

Bowren, M. Skitzer, and R. N. Melver

(1980). Effect of Burning Cereal Straw

on Soil Properties and Grain Yields in

Baskatchewan. Soil Sci. Soc. Amer J.

44: 103 – 111.

Blevins R. L.; G. W. Thomas, M. S. Smith, W.

W. Fyre and P. L. Cornelus (1983).

Changes in Soil Properties after 10

years continuous no tillage and

conventionally tilled corn. Soil tillage

Research: 135 – 146.

Bouyoucus, G.M., (1951). A recalibration of

hydrometer for making mechanical

analysis of soils, Agronomy Journal,

34:434-436.

Federal Department of Agricultural Land

Resources (FDALR), (1985).

Agricultural Land Resources Technical

Bulletin. Vol 5.

Gee, G.W. and J.W. Bauder, 1986. Particles

size analysis. In: Methods of Soil

analysis part 1. A. Klute (ed) Am. Soc.

Agron. Madision 101 USA: 38 - 41

Mclean, E.D. (1982). Soil pH and lime

requirements in page a…ed. Methods

of soil analysis part 2. Chemical and

microbiological properties (2nd Ed.).

Agronomy series No.SSA.Maidison,

Wis. USA.PP.199-234.

Nelson, D.W. and L. E. Sommers, (1982).

Total Organic Carbon and Matter in:

pp A.L.(ed.). Methods of soil analysis.

Part 2 chemical and microbiological

properties (2nd ed.). Agronomy series

No.9, ASA, SSA, Maidison, Wis.USA.

pp. 570.

Ogbodo, E.N. (2004). Effect of Tillage

Methods and Crop Residue Mulch on

Soil Physical Conditions, Growth and

Yield of Irrigation Maize at Abakaliki,

Southeastern Nigeria. Journal of the

Science of Agriculture, Food

Technology and Environment. Vol. 4,

2004: 1 – 9.

Ogbodo, E.N. (2005a). Response of rice

(Oryza sativa) to organic and inorganic

manure in an ultisol at Abakaliki

Southeastern Nigeria. Journal of

Agriculture, Forestry and Social

Sciences. Vol. 3 (1) 2005: 9 – 14.

84


Ogbodo, E.N. (2009). Effect of Crop Residue

on Soil Chemical Properties and Rice

Yields on an Ultisol at Abakaliki,

Southeastern Nigeria. American-

Eurasian Journal of Sustainable

Agriculture, 3(3): 422-447.

Ogbodo, E.N. (2010). Effect of Crop Residue

on Soil Physical Properties and Rice

Yield on an Acid Ultisol at Abakaliki,

Southeastern Nigeria. Res. J. Agric. &

Biol. Sci., 6(5): 647-652.

Ogobodo, E. N. and P. A. Nnabude (2004).

Evaluation of the Performance of

Three Varieties of Upland Rice in

Degraded Acid Soil in Abakaliki,

EbonyI State. Journal of technology

and Education in Nigeria, 9 (2): 1 – 7.

Ogbodo, E.N. I.I. Ekpe, E.B. Utobo (2009).

Use of Organic Amendments to

Improve Chemical Properties and Crop

Yield in Degraded Typic Haplustult in

South Eastern Nigeria. American-

Eurasian Journal of Sustainable

Agriculture, 3(3): 609-614, 2009.

Page, A.L., B.H. Miller and D.R. Keeney

(1982). Methods of Soil Analysis.

Second Edition. American Society of

Agronomy, Madison, Wisconsin

SAS Institute Lac, (2006). SAS/STAT User’s

Guide: Version 6, Fourth Edition, vol

2, Carry, NC., SAS Institute Inc, 2006.

846pp.

Tel, D. and F. Rao (1982). Animated and

Semi-anotamated Methods for Soil and

Plant Analysis pp.201-270.

85


EFFECT OF TILLAGE AND CROP RESIDUE ON SOIL PHYSICAL PROPERTIES

AND RICE YIELD ON AN ACID ULTISOL AT ABAKALIKI, SOUTHEASTERN

NIGERIA

OGBODO, E.N1. AND P.A. NNABUDE2 1Department of Soil Science and Environmental Management, Faculty of Agriculture and

Natural Resources Management, Ebonyi State University, P.M.B. 053 Abakaliki, Nigeria. 2Department of Applied Biological Sciences, Nnamdi Azikiwe University, Awka, Nigeria.

ABSTRACT

The alleviation of the soil physical constraints at Abakaliki, Ebonyi State Nigeria is a priority

issue. A study was carried out in 2009 and 2010 to evaluate the effect of combinations of

different tillage treatments [(No-tillage (NT); Hoe-Tillage (HT); ploughing (PL); ploughing and

harrowing (PHJ)] and Crop residues treatment [(No Residue (NR); Rice Straw (RS); Burnt Rice

Husk (BRH) and Legume Residue (LR)] on the soils physical properties, and rice growth and

yield . Improved varieties of rice (ITA 257; Ex-china and ITA 315) were used as the test crops.

The soil temperature and bulk density were significantly (p>0.05) reduced on soils treated with

the combinations of the tillage and crop residues compared to the soils that were either tilled or

not tilled but without crop residue treatment. The soils total porosity, water infiltration and

moisture content significantly (p<0.05) improved when treated with combinations of tillage and

crop residue compared to the combination of no-tillage, with or without crop residues

applications. Treating the soil with a combination of tillage and crop residue brought about

significant improvements in rice plant height and tillers, compared to where the soil was not

tilled or hoe-tilled with or without the application of residues. Rice growth on soils treated with

burnt rice husk was superior to the plants grown on soils treated with rice straw or legume

residue across the tillage methods. Rice grain yield was significantly (p<0.05) higher on soils

that received treatment combinations of tillage and residue than on the soil that was not tilled

with-or without residue treatment. Grain yield was also significantly (p<0.05) higher where the

soil was ploughed or ploughed and harrowed and treated with crop residue than when the soil

was hoe-tilled and either treated with crop residue or not. Grain yield was significantly (p<0.05)

higher when the soil was treated with burnt rice husk than with rice straw or legume residue

across the tillage methods. The grain yield of ITA 315 and Ex-china were significantly (p<0.05)

higher than ITA 257 in both years. The highest grain yield of 3.92 t/ha in the study was gotten

from ITA 315 grown on the soil that was ploughed and harrowed and treated with burnt rice

husk. This yield observation was attributed to better soil structure, lower soil temperature, higher

soil moisture, and the fact that the burnt rice husk provided additional benefits of improving the

soil chemical properties.

Key words: Tillage and Crop Residue, Soil Physical Properties, Acid Ultisol, Rice Yields,

Abakaliki, Southeastern Nigeria *Corresponding author. Tel.: +234 8037465495; e-mail:[email protected]

86



INTRODUCTION

The alleviation of the productivity constraints

of the soils of the Abakaliki area has continued

to agitate the minds of many Agriculturists.

The farmers, who are the major inhabitants of

the area, have over the years suffered declining

productivity of their crops owing to the soil

related problems. Many scientists have for this

reason embarked on researches aimed at

resolving these problems in order to achieve

sustainable crop production. Many of these

endeavors were aimed at measures that

improved the soils’ chemical status. There is

the need to emphasize on efforts that could as

well address the physical constraints of the

soils.

The studies that had been carried out in the

recent past towards this problem had achieved

limited results. There is therefore the need to

intensify efforts at finding a lasting solution to

the soils’ physical constraints, in order to

achieve an improved and secured food

production.

The present study centered on the evaluation

of the possibility of employing the

combination of tillage methods and crop

residues to remediate the direct effects of the

soils’ physical problems on crop productivity.

MATERIALS AND METHODS The experiments were conducted in the 2009

and 2010 farming seasons, at the Research and

Teaching Farm of the Faculty of Agriculture,

Ebonyi State University, Abakaliki. The area

is located within longitude 080 03/ E and

latitude 060 25/ N in the derived savanna zone

of Nigeria. The mean monthly temperatures

ranged between 24 oC and 28 oC. The rainfall

pattern was bimodal, with peaks in the months

of July and September. Annual amounts of

rainfall ranged between 1800 and 2000 mm.

Rainfall stabilized around May and stopped

around October, leaving a dry period between

November and April during the study seasons.

The soil is hydromorphic and has an

isohypothermic soil temperature regime and

belongs to the order Ultisol derived from shale

and classified as typic haplustult. The

description of some surface soil physical and

chemical characteristics is shown in Table 1.

The area was previously used for maize

production, before it was used for the

experiment.

Table 1. Pre-Planting Soil Texture and Chemical Properties

Soil Texture

Sand (%)

Silt (%)

Clay (%)

Textural Class

Chemical Properties pH (H2O)

Organic Matter (%)

Total N (%)

Available P (gm/kg)

K (cmol(+)/kg)

Ca (cmol(+)/kg)

Mg (cmol(+)/kg)

CEC(cmol(+)/kg)

44.80

34.40

20.80

Sandy Clay Loam

4.80

2.00

0.12

6.00

0.19

2.10

2.20

4.60

Experimental Design and Treatments

The experimental design used was 4 x 3 x 4

split-split plot factorial in a Randomized

Complete Block Design. Tillage methods was

the main treatment, rice cultivars was the sub

treatment whereas crop residue source was the

sub-sub treatment. Each treatment was

replicated three times. The tillage methods

were no – tillage (NT), Hoe – tillage (HT),

Ploughing (PL) and Ploughing and harrowing

87


(PH). The three rice cultivars were ITA 315,

Ex-china and ITA 257, whereas the crop

residue treatments were no residue (NR), Rice

Straw (RS), Burnt Rice Husk (BRH) and

legume residue (LR). The dry rice straw was

from the previous year harvest, the burnt rice

husk was collected from the rice mill dump,

whereas Centrocema pubensis was harvested

from the ones growing widely in the

surrounding bush. The improved rice cultivars

used for the trials were foundation seeds

sourced from the International Institute of

Tropical Agriculture (IITA), Ibadan.

Field Layout

The area of land used for the experiment

measured 769.5 m2. Each replicate measured

256.5 m2 and comprised of four tillage

methods, three rice cultivars and four crop

residue sources. There were three blocks

within each tillage treatment measuring 54 m2.

Each block comprised of 12 treatment units,

each measuring 16 m2. The replicates and

tillage methods were separated by one another

by 1m alleys respectively, whereas the

individual plots were separated by 0.5 m

alleys.

Treatment Applications

The ploughing was carried out once for the PL

plots, while the PH plots were ploughed once

and harrowed twice. For the HT plots, the

vegetation was slashed with a matchet and

removed, while the soil was tilled manually

with a hoe. A non-selective herbicide,

glyphosate (360g a.i) was sprayed on the

vegetation on the NT plots at the rate of 5

liters per hectare two weeks before sowing the

seed. The crop residues were applied as

surface mulch on the appropriate plots. 5 ton

per hectare (t/ha) equivalent of dry rice straw,

freshly harvested Centrosema pubensis and

burnt rice husk were applied on the

appropriate plots. For the NR plots, no crop

residue was applied while the existing plant

residues were removed. The rice seeds were

directly seeded by dibbling; using the sticks to

create opening and the seeds covered after

sowing. Three seeds were planted per hill at a

spacing of 25 cm x 25 cm, and later thinned

down to two seedlings per stand at 21 days

after planting (DAP), giving plant population

of 320,000 stands per hectare. Fertilizer was

applied at the rate of 40 kg P / ha as single

super phosphate, 40 kg K / ha as muriate of

potash and 80 kg N / ha as urea to all the plots.

One third of the N fertilizer was applied

alongside the P and K basally before residue

application; 4 days before planting the seeds,

whereas the remaining two thirds of N were

applied at 75 DAP.

Data Collection

Six soil auger samples were randomly

collected from the experimental area at 0-20

cm depth for pre-planting soil analysis. A t 65

days after planting, six auger samples were

taken from 0-10cm depth in each plot for the

determination of soil moisture. Also six

undisturbed soil core samples of 5 cm

diameter were taken from each plot at 30 DAP

for analysis of bulk density. Soil water

infiltration capacity was measured on each plot

at 60 DAP with a single ring infiltrometer. Soil

temperature measurements were taken at 14,

28, 42, 56, 70 and 84 DAP using a centigrade

soil thermometer, and the mean recorded.

Plant height and tiller number were measured

at 75 DAP. Plant height was taken as the

height from the base of the plant and the tip of

the tallest tiller using a meter rule. At dry

maturity, the rice panicles were harvested from

a net plot of 2 m x 2 m in the middle of each

plot, dried, threshed and the grain yield data

adjusted to 14% moisture, and converted to

t/ha.

Laboratory Methods

The pre-planting composite soil samples

(taken at 0 – 20cm depth) were analyzed in the

laboratory for the texture and chemical

properties. The soil particle size distribution

was determined by the hydrometer method

(Gee and Bouder 1986). The post harvest soil

samples taken from each plot were subjected

to chemical analysis. Total nitrogen was

determined by the Macro Kjeldahl method

(Bouycous, 1951). Available P was

88


determined using Bray II method as outlined

in Page et al. (1982). Organic carbon was

determined by the Walkley and Black method

(Nelson and Sommers, 1982). Soil pH (2:1 in

water) was determined by the glass electrode

pH meter (Maclean, 1982). Exchangeable

bases were extracted using the ammonium

acetate method (Tel and Rao, 1982)

DATA ANALYSIS

Analysis of variance and mean separation were

done using least significant difference test for

P≤0.05 procedure as described by SAS (2006).

RESULTS

Soil Physical Properties The effects of the combination of tillage

methods and crop residues on soil physical

properties are presented in Table 2. The

combination of individual tillage and crop

residues significantly reduced soil temperature

compared to the tillage treatment without crop

residue. The combination of tillage and crop

residue application also led to significant

reduction in soil bulk density compared to the

tillage without crop residue treatment. Bulk

density was also significantly lower where the

soil was ploughed or ploughed and harrowed

with residue treatment, than the combination

of hoe tillage and crop residue.

The bulk density values were lower in the

second year where the soil was tilled and

treated with crop residue. Tillage and crop

residue treatments significantly increased the

soil total porosity in both years. Ploughing or

ploughing and harrowing the soil with crop

residue treatments significantly increased the

soil total porosity than hoe tillage and no-

tillage with crop residue treatment. The

application of combination of tillage and crop

residue treatments to the soil led to significant

increase in soil water infiltration compared to

tillage without crop residue treatments.

Ploughing and ploughing and harrowing the

soil with residue treatments significantly

increased infiltration compared to hoe-tillage

and no-tillage in the first year, while in the

second year hoe- tillage, ploughing, and

ploughing and harrowing the soil with crop

residues significantly increased infiltration

compared to where the soil was not tilled with

or without crop residue. Combining the

different tillage methods with rice straw or

legume residues significantly increase water

infiltration than combining the tillage methods

with burnt rice husk or no residue application.

The combination of ploughing or ploughing

and harrowing and Rice straw or legume

residue significantly increased water

infiltration compared to the combination of

burnt rice husk. The combinations of the

residues with ploughing or ploughing and

harrowing the soil increased infiltration

compared to the combinations of the residues

with no-tillage or hoe-tillage.

Soil moisture was significantly higher when

the soil was treated with crop residue than

when there was no residue treatment across the

tillage methods. Soil moisture was

significantly higher when the soil was

ploughed or ploughed and harrowed and

treated with rice husk or legume residue than

when not-tilled or hoe-tilled with Rice straw or

legume residue treatment than burnt rice husk

treatment. The combination of each crop

residue and ploughing or ploughhing and

harrowing the soil significantly increased soil

moisture compared to that of the respective

crop residues and no-tillage treatment. There

were no significant differences in the soil

moisture between where the soil was not tilled

and treated with crop residue and where hoe-

tilled and treated with crop residue.

89


Table 2. Effect of Tillage and Crop Residue on Soil Physical Properties 1st Year 2nd Year

Crop Residue No Tillage Hoe

Tillage

Plough

Ploughed

&Harrow

Mean

No

Tillage

Hoe

Tillage

Plough

Ploughed

&Harrow

Mean

Temperature (0C) No Residue 30.6 31.3 31.1 30.1 30.6 30.9 30.9 30.5 28.8 30.3

Rice Straw 27.4 28.1 27.7 29.1 28.1 27.7 27.7 27.3 28.4 27.8

Burnt Rice Husk 28.4 28.7 28.1 28.0 29.6 29.4 28.4 28.4 28.7 29.4

Legume Residue 27.9 28.5 28.1 29.0 28.4 28.1 28.1 27.6 28.8 28.15

Bulk Density (g/cm3) No Residue 1.6 1.5 1.4 1.4 1.5 1.6 1.5 1.4 1.3 1.5

Rice Straw 1.5 1.4 1.3 1.3 1.4 1.5 1.4 1.3 1.3 1.4

Burnt Rice Husk 1.5 1.4 1.4 1.4 1.4 1.5 1.4 1.3 1.3 1.4

Legume Residue 1.5 1.4 1.3 1.3 1.4 1.5 1.4 1.3 1.3 1.4

Total Porosity (%) No Residue 39.6 43.0 47.0 47.0 44.2 36.0 43.0 47.0 51.0 42.3

Rice Straw 43.0 47.0 51.0 51.0 48.0 59.0 47.0 51.0 51.0 52.0

Burnt Rice Husk 33.0 47.0 47.0 47.0 46.0 39.6 43.0 51.0 51.0 46.0

Legume Residue 43.0 47.0 51.0 57.0 49.5 43.0 47.0 51.0 51.0 48.0

Infiltration (cm/hr) No Residue 50.6 51.2 54.6 55.8 53.8 50.4 56.1 55.0 55.7 54.3

Rice Straw 59.0 59.0 63.0 65.8 61.7 60.3 59.9 65.2 68.9 63.6

Burnt Rice Husk 49.6 52.9 59.3 61.7 55.9 48.4 57.7 54.4 57.8 54.6

Legume Residue 58.7 60.8 64.3 68.5 63.1 58.7 59.8 63.2 67.9 62.4

Soil Moisture (%) No Residue 19.1 20.5 21.7 24.8 21.6 19.2 20.7 21.5 24.7 21.5

Rice Straw 25.5 28.0 29.3 30.6 28.4 26.9 27.7 28.2 31.5 28.6

Burnt Rice Husk 22.8 24.1 25.4 28.0 25.1 22.4 23.3 26.8 28.6 25.3

Legume Residue 25.8 26.6 29.3 30.1 28.0 25.3 27.9 28.1 31.3 28.2

F-LSD (P < 0.05) Temperature Bulk Density Total Porosity Infiltration Moisture 1st Year 2.00 0.01 4.00 5.29 2.23

2nd Year 1.90 0.01 3.92 6.41 2.92

90


Rice Growth The effects of tillage and crop residue on rice

growth are presented in Tables 3 and 4. The

growth of the crops was superior on soils with

crop residue treatment than on soils without

residue treatment across the four tillage

treatment. The three rice varieties were

significantly (p<0.05) taller when the soil was

treated with crop residue than where the soil

was not treated with crop residue across the

four tillage treatment. The plants were

significantly (p<0.05) taller on ploughed,

ploughed and harrowed plots when treated

with crop residue or not treated with crop

residue than when the soil was not tilled or hoe

– tilled with or without crop residue treatment.

The three varieties produced significantly

(p<0.05) higher number of tillers when the soil

was tilled or not tilled and treated with crop

residue than when the soil was tilled or not

tilled but without crop reissue treatment.

Tillering of the three varieties was

significantly (p<0.05) higher when the soil

was ploughed, ploughed and harrowed with or

without crop residue treatment compared to

where the soil was not tilled or hoe-tilled, with

or without crop residue treatment. Generally,

tillering of ITA 315 and Ex – China were

significantly (p<0.05) higher than that of ITA

257.

Table 3. Effect of tillage and crop residue on number of tillers

NT+NR = No-Tillage + No Residue; NT+RS = No-Tillage + Rice Straw; NT+BRH = No-Tillage+ Burnt Rice Husk;


HT+BRH = Hoe Tillage + Burnt Rice Husk; HT+LR = Hoe Tillage + Legume Residue; PL+NR = Ploughing + No

Residue; PL+RS = Ploughing + Rice Straw; PL+BRH = Ploughing + Burnt Rice Husk; PL+LR = Ploughing +

Legume Residue; PH+NR = Ploughing and Harrowing + No Residue; PH+RH = Ploughing and Harrowing + Rice

Straw; PH+BRH = Ploughing and Harrowing + Burnt Rice Husk; PH+LR = Ploughing and Harrowing + Legume

Residue

Year Variety Year Variety

Treatment ITA 257 Ex-China ITA 315 Mean ITA 257 Ex-China ITA 315 Mean NT+NR 6.00 10.00 10.00 9.00 6.00 11.00 10.00 9.00 NT+RS 8.00 12.00 14.00 11.00 8.00 15.00 14.00 12.00 NT+BRH 10.00 14.00 16.00 13.00 11.00 15.00 16.00 14.00 NT+LR 8.00 12.00 14.00 11.00 10.00 13.00 14.00 12.00 HT+NR 8.00 11.00 12.00 10.00 8.00 12.00 11.00 10.00 HT+RS 10.00 14.00 18.00 14.00 10.00 14.00 15.00 13.00 HT+BRH 12.00 16.00 21.00 16.00 14.00 18.00 18.00 17.00 HT+LR 10.00 14.00 18.00 14.00 12.00 15.00 16.00 14.00 PL+NR 8.00 14.00 14.00 12.00 9.00 12.00 11.00 11.00 PL+RS 10.00 16.00 18.00 15.00 11.00 14.00 18.00 14.00 PL+BRH 14.00 19.00 20.00 18.00 14.00 18.00 24.00 19.00 PL+LR 12.00 14.00 15.00 14.00 10.00 14.00 19.00 14.00 PH+NR 9.00 14.00 14.00 12.00 9.00 14.00 12.00 12.00 PH+RS 12.00 18.00 18.00 16.00 12.00 16.00 18.00 16.00 PH+BRH 14.00 24.00 26.00 21.00 16.00 28.00 28.00 24.00 PH+LR 12.00 19.00 16.00 16.00 10.00 15.00 18.00 15.00 Mean 10.00 15.00 17.00 10.00 15.00 16.00 Year 1 Year 2 LSD (0.05) Tillage + Residue 2.00 3.00 Variety 5.00 5.00

91


Table 4. Effect of tillage and crop residue on plant height (cm) First Year Second Year

Treatment ITA 257 Ex-China ITA 315 Mean ITA 257 Ex-China ITA 315 Mean

NT+NR 52.00 52.00 52.00 52.00 56.00 58.00 57.00 57.00

NT+RS 58.00 64.00 63.00 62.00 57.00 66.00 64.00 62.00

NT+BRH 63.00 69.00 70.00 67.00 66.00 71.00 70.00 69.00

NT+LR 56.00 64.00 67.00 62.00 66.00 63.00 68.00 66.00

HT+NR 56.00 57.00 63.00 59.00 67.00 67.00 62.00 65.00

HT+RS 64.00 66.00 68.00 66.00 66.00 70.00 76.00 71.00

HT+BRH 73.00 70.00 71.00 71.00 70.00 71.00 84.00 75.00

HT+LR 66.00 67.00 74.00 69.00 68.00 72.00 79.00 73.00

PL+NR 59.00 76.00 68.00 67.00 61.00 67.00 66.00 65.00

PL+RS 62.00 73.00 76.00 70.00 74.00 75.00 73.00 74.00

PL+BRH 69.00 78.00 78.00 75.00 80.00 89.00 88.00 86.00

PL+LR 63.00 78.00 77.00 73.00 71.00 73.00 77.00 74.00

PH+NR 62.00 69.00 64.00 65.00 62.00 70.00 73.00 68.00

PH+RS 71.00 74.00 73.00 73.00 74.00 76.00 75.00 75.00

PH+BRH 72.00 73.00 73.00 73.00 72.00 79.00 77.00 76.00

PH+LR 70.00 71.00 70.00 73.00 69.00 77.00 76.00 74.00

64.00 70.00 71.00 68.00 72.00 73.00


LSD (0.05) Tillage + Residue 4.00 3.00

Variety 3.00 4.00 NT+NR = No-Tillage + No Residue; NT+RS = No-Tillage + Rice Straw; NT+BRH = No-Tillage+ Burnt Rice Husk;






Residue

Rice grain yield The influence of the combination of the various tillage methods and crop residue treatment on grain yield is presented in Table 5. For the ITA 257 variety, in the 1st year NT+BRH, NT+LR and NT + RS treatments led to 1.40, 1.00 and 0.90t/ha significantly higher grains respectively than the application of NT+NR, while HT+BRH, HT + LR and HT +RS led to 1.54, 1.00 and 0.60 t/ha significantly higher grains than HT + NR. Yield increases of 0.82 and 1.40 t/ha were obtained by using PL+LR and PL+BRH compared to PL +NR, whereas, yield increases of 0.51, 0.79 and 1.04 t/ha were attained by employing PH+RS, PH+LR and PH + BRH compared to the application of PH+NR. In the second year, the application of 257, NT + RS and NT + LR increased yield by 1.50 t/ha respectively while NT+BRH brought about 1.70t/ha yield increase than NT + NR. The HT+ RS, HT+LR and HT+ BRH raised yield in the order of 0.70, 1.33 and 1.64t/ha. Compare to HT+NR, whereas the PL+RS and PL+LR treatments each increased grain yield by 1.13 t/ha,

while PL + BRH brought about grain yield increase of 1.90 t/ha than PL + NR treatment. Also, PH + RS, PH + BRH and PH + LR treatments raised yield by 0.60, 1.07 and 1.27 t/ha respectively compared to the PH + NR treatment. The yield of ex-china increased significantly by 1.20, 1.22 and 1.40 t/ha when it was treated to NT+RS, NT+LR and NT+RS compared to NT+NR, while yield increases of 0.83, 1.10 and 1.20 occurred when HT+ LR, HT+RS and HT+BRS were employed compared to HT+NL PL + LR, PL + RS and PL+BRH which led to yield increases of 0.51, 0.62 and 1.59 t/ha compared to PL + NR, while PH + BRS led to yield increase of 0.46 t/ha compared to PH+NR. There was less variation in yield when the soil was ploughed and harrowed and treated with the different residue sources, in the first year. During the second year cropping, treatment of the soil with NT+RS raised yield by 1.50 t/ha, while NT+BRH and NT + LR treatments increased grain yield by 1.80t/ha a piece. The application of HT+LR brought about

92


0.90 yield increase, while the HT+BRH and HT+RS treatments led to 1.210 t/ha yield increase respectively. The treatment of the soil with employing PL+RS and PL + BRH treatments led to 1.16 and 1.40 t/ha significantly higher yield increases respectively whereas PH + LR raised grain yield by 1.20 t/ha compared to RH+NR treatment. The yield increase for ex-china seemed to drop as tillage intensity increased, with the application of legume residue better than other residues, across the tillage methods. The grain yield of ITA 315 in the first year, increased by 0.69, 0.99 and 1.09 t/ha when the soil was treated with NT + LR, NT + RS and NT+ BRH compared to NT+NR, while HT + LR, HT+BRH and HT+ RS treatments increased yield by 1.10, 1.31 and 1.50 t/ha compared to HT + NR. The application of PL + LR, PL + RS and PL +

BRS led to significantly higher yield increases of 0.69, 0.92 and 1.56 t/ha than the application of PL+NR, whereas when PH + RS and PH + BRH treatments were applied to the soil, grain yield increased 3rd by 0.70 and 1.24 tons/ha compared to where PH+NR was applied. For the second year experiment, the application of NT + RS, NT+ LR and NT + BRH treatments to the soil raised grain yield of ITA 315 by 1.20, 1.70 and 1.90 t/ha than NT x NR, while yield increases of 1.20, 1.50 and 1.53 t/ha were achieved by applying HT + RS, HT+BRH and HT + LR treatments to the rice production. On the other hand, employing PL + RS, PL + BRH and PL + LR to the soil increased grain yield by 1.33, 2.07 and 2.47 t/ha than the application of PL + NR treatment, whereas applying PH + BRH and PL + RS treatments led to significantly higher yield of 0.83 and 2.22 t/ha compared to PH + NR treatment.

Table 5. Effect of tillage and crop residue on rice grain yield (t/ha)


Treatment ITA 257 Ex-China ITA 315 Mean ITA 257 Ex-China ITA 315 Mean

NT+NR 0.40 0.60 0.91 0.64 0.30 0.60 0.80 0.57

NT+RS 1.30 1.80 1.90 1.67 1.80 2.10 2.00 1.97

NT+BRH 1.80 2.00 2.00 1.90 2.00 2.40 2.70 2.34

NT+LR 1.40 1.88 1.60 1.63 1.80 2.40 2.50 2.23

HT+NR 0.40 0.80 0.90 0.70 0.30 0.80 1.00 0.70

HT+RS 1.00 1.90 2.40 1.77 1.00 2.00 2.20 1.73

HT+BRH 1.94 2.00 2.21 2.10 1.94 2.00 2.50 2.15

HT+LR 1.40 1.63 2.00 1.68 1.63 1.70 2.53 1.95

PL+NR 0.60 1.27 1.31 1.10 0.50 1.47 1.20 1.10

PL+RS 1.00 1.89 2.23 1.71 1.63 2.63 2.53 2.26

PL+BRH 2.00 2.30 2.87 2.39 2.40 2.87 3.27 2.85

PL+LR 1.42 1.78 2.00 1.73 1.63 1.83 2.67 2.04

PH+NR 0.63 1.87 1.63 1.38 0.63 1.63 1.70 1.32

PH+RS 1.14 2.20 2.33 1.89 1.23 1.67 2.00 1.63

PH+BRH 1.67 2.33 2.87 2.29 1.70 1.93 3.92 2.52

PH+LR 1.42 1.78 2.00 1.73 1.93 2.83 2.53 2.36

Mean 1.63 1.77 1.82 1.40 1.93 2.27

First Year Second

year

LSD (0.05) Tillage + Residue 0.49 0.46

Variety 0.42 0.51

NT+NR = No-Tillage + No Residue; NT+RS = No-Tillage + Rice Straw; NT+BRH = No-Tillage+ Burnt Rice Husk;






Residue

93


DISCUSSION

Soil temperature was significantly (p>0.05)

lowered across the four tillage methods when

the soil was covered with crop residue. Soil

temperature was also lower on the no-till soil

than on the ploughed, ploughed and harrowed

or the hoe-tilled soils. Bulk density values

were significantly (p>0.05) reduced when the

soil was treated with rice straw and legume

residue mulch than when treated with burnt

rice straw across the four tillage methods. The

soil water infiltration capacity was

significantly (p<0.05) raised by the crop

residue and tillage treatments in both years of

the study. The soils that received rice straw

and legume residue mulch had significantly

(p<0.05) higher water infiltration than the soils

treated with burnt rice husk mulch across the

four tillage methods. Soil moisture content

was significantly (p<0.05) higher when the

soil was treated with crop residue across the

four tillage treatments. Soil moisture was also

significantly (p<0.05) higher in the soil treated

with rice straw and legume residue

respectively than the soil treated with burnt

rice husk across the whole tillage methods.

The lower temperature on the residue treated

soils irrespective of the tillage treatment was

ascribed to the reduction of the impact of the

direct heat of solar radiation on the soil surface

by the residue cover. This interception of solar

radiation conserved soil moisture which in turn

also moderated soil temperature. Soils with

high moisture content normally require higher

specific heat (Lal, 1986; ). The significantly

(p<0.05) lower temperatures of the no-till plots

without crop residue treatment was as a result

of the residue cover accruing from the natural

vegetation, unlike the other tillage methods

where the vegetation were either slashed and

removed, burnt, or ploughed under during

tillage operations. These results conform to the

report of Perterson and Fenster (1982), and

Bruce et al. (1990) who reported lower

temperature with tillage methods that leave

part or the entire crop residue on the soil

surface.

The lower bulk density of the tilled soils with

crop residue treatment was ascribed to the fact

that the tillage and crop residue treatments

improved the soil structure by increasing the

soil granulation and improved the soil

porosity. The tillage and crop residue

treatments therefore repackaged the soil

leading to the lower soil density per unit

volume. This is in conformity with the

findings of Hulugalle and Palada, (1990) . The

tillage and crop residue treatments improved

the soil structure, reduced compaction and

increased porosity hence improving the soils

water intake. The tillage and crop residue

mulch increased surface roughness, which

reduced runoff and increased time for the soil

to absorb water. The increased infiltration

owing to tillage and residue also improved

water storage capacity of the soil. On the other

hand, the lower soil temperature reduced

evaporation of moisture from the soil surface,

hence increasing water conservation. It was

also possible that the absorptive nature of the

organic material increased the soil water

holding capacity. These results conform to Lal

(1986) who also reported higher infiltration

and moisture on tilled and crop residue treated

soils. The lower water infiltration rate and

water storage capacity of the burnt rice husk

treated soil was ascribed to the clogging of soil

pores by the rice husk ash, which encourage

water run-off compared to the other residue

treatments.

Tillage and crop residue mulch treatment

provided the enabling environment for

superior crop growth. The improved soil

structure and tilth made root penetration and

proliferation easier. The plants therefore had

greater access to water, air and nutrients at the

root zone leading to increased crop

productivity. Hulugalle and Palada (1990) also

reported increase moisture, aeration and

fertility on residue mulched soils, which

transformed into greater crop growth.

The combined effect of tillage and crop

residue treatment, lead to significantly higher

grain yields for the three varieties. The grain

94


yield of the three varieties was significantly

higher on tilled soils with residue treatments

than the untilled soils with residue treatments.

Ploughing and harrowing the soil or ploughing

the soil alone and treating with crop residue

produced significantly higher grain yield than

where the soil was not tilled or hoe-tilled and

treated with crop residue. Treating the soil

with burnt rice husk also gave significantly

higher grain yield than treating with rice straw

or legume residue across the tillage methods.

The grain yield of ITA 315 and Ex-China were

significantly higher than that of ITA 257 when

subjected to the same tillage and crop residue

treatments.

The benefit derived from improved soil

physical properties accruing from tillage and

crop residue treatments such as higher soil

moisture, lower soil temperature, reduced soil

compaction and bulk density, increase aeration

and gaseous exchange, improved mobility of

water and nutrients and improved water and

nutrient conservation as a result of reduced

run-off brought about superior grain yield in

the study. There could have been reduced soil

acidity and improved soil chemical conditions

when the soil was tilled and treated with crop

residue, which improved crop productivity.

These conditions provided improved access of

plants roots to nutrients, leading to increased

grain yield. The superior crop growth observed

on tilled and residue treated plots naturally led

to superior phtotosynthetic efficiency of the

crop. The higher tillering ability of the crops

on the tilled and residue treated plots increased

grain yield compared to the plots that were not

tilled and / or not treated with crop residue.

Generally, the significantly (p<0.05) higher

grain yield of ITA 315 and Ex-China

compared to ITA 257 was attributed to

adaptability of the crops to the study area

(Ogbodo and Nnabude, 2004). These two

varieties showed superior growth particularly

higher tillering ability which transformed into

higher grain yield.

CONCLUSION

The study revealed that the physical

constraints of the soil of the study area could

to a reasonable extent be ameliorated with

tillage and crop residue managements.

Conventional tillage with crop residue

application proved to be superior in

remediation of the soils physical problems

than the no tillage and hoe-tillage methods

either with residue treatment or not. The

combination of ploughing, or ploughing and

harrowing, and burnt rice husk application to

the soil was the best method of resolving the

soils physical constraints among the treatments

used in the study. The growth and yield of ITA

315 and Ex-china were superior to that of ITA

257 in the study. The highest grain yield in the

study was achieved with ITA 315 grown on

soil that was ploughing and harrowed, with the

application of burnt rice husk. The yield

advantage of the crops grown soils treated

with burnt rice husk across the tillage methods

was attributed to the extra benefit of the ash

that neutralized the soil acidity and made other

nutrients available for plant uptake and

productivity compared to the other residues.

REFERENCES Blake, G.R. and K.H. Hartge (1986). Bulk

density. In: Methods of Soil analysis part 1. Physical and Mineralogical Methods. A. Klute (ed) Am. Soc. Agon. Madison, 101 USA: 365 – 375.

Bruce, R. R., G. W. Langdale and A. L. #

Dillard (1990). Tillage and Crop Residue Effect on Characteristics of a Sandy Surface Soil. Soil Science society Am. J. 54 (6):1744 – 1747.

Gee, G.W. and J.W. Bauder (1986). Particles

size analysis. In: Methods of Soil analysis part 1. A. Klute (ed) Am. Soc. Agron. Madision 101 USA: 38 - 41

Hulugalle, N. R. and M. C. Palada (1990).

Effect of Seedbed preparation method and Mulch on soil physical properties and yield of cowpea in a rice fallows of an inland valley swamp. Soil and Tillage research. 1990, 17, 1-2:101 – 113.

95


Klute, A., 1986. Water Retention: Laboratory

Methods. In: Klute, A (ed). Methods of

Soil analysis, part 1: Physical and

Mineralogical Methods, 2nd ed. ASA,

SSSA, Madison USA: 635 – 660.

Lal, R. (1986). Soil Surface Management in

the Tropics for Intensive Land Use and

High Sustained Production. Adv. Soil

Sci., 7:10 – 15

Maclean, E.O. (1982). Soil pH and lime

requirement. In: methods of soil

analysis part 2 A.L.page (ed) Am. Soc.

Agron. Madison 101 USA: 199 – 234.

Mbagwu, J. S. C. (1991). Mulching an Ultisal

in Southern Nigeria: Effects on

Physical Properties and Maize and

Cowpea Yields. J. Sci. Food Agric. 57:

517 – 526.

Nelson, D.W. and L.E. Sommers (1982). Total

Carbon, Organ Carbon and Organic

Matter: Methods of Soil analysis part

2. Chemical and Microbiological

properties.

Ogbodo, E. N. and P. A. Nnabude (2004).

Evaluation of the Performance of three

varieties of upland rice in degraded

acid soil in Abakaliki, EbonyI State.

Journal of technology and Education

in Nigeria, 9 (2): 1 – 7.

Page, A.L., R. H. Miller and D.R. Keeney,

1982. Methods of Soil Analysis II.

Amer. Soc. Agron. Madison,

Wisconsin, USA.

Perterson, D. A. and C. R. Fenster (1982). No-

till in the Great Plains. Crops and Soil

Magazine, 43: 7 – 9.

SAS Institute Inc. (2006). SAS/STAT user’s

guide: Version 6, Fourth Edition,

Vol. 2, Cary, NC., SAS Institute Inc.,

2006. 846 pp.

Tel, D. and F. Rao, 1982. Animated and semi

–anotamated methods for soil and plant

analysis pp.201-270.

96


SOIL FERTILITY EVALUATION OF SELECTED AQUIC HAPLUSTALFS IN

EBONYI STATE, SOUTHEAST NIGERIA

OGBODO, E. N1. and G. O. CHUKWU2

1. Department of Soil and Environmental Management, Ebony State University,

Abakiliki, Nigeria.

2. National Root Crops Research Institute, Umudike, Nigeria.

ABSTRACT

Soil fertility evaluation of selected Aquic Haplustalfs; Gleyic acrisols in Ebony State, Southeast

Nigeria, was assessed at 0-60 cm depth, as a basis for sustainable soil health management and

increased crop yields. Results showed that they are generally fine loam, extremely acidic, to

moderately acid, eutric soils with base saturation of over 60 %. However, they are low in organic

matter ( < 2 % ), total N ( < 0.15 % ) and exchangeable K ( < 2 Cmol/ kg ), but medium to

moderate in available P ( 17-39 mg/ kg ). The soils require drainage and application of organic

and mineral fertilizers to improve their productivity and boost crop yields.

Key Words: Soil Fertility, Aquic Haplustalfs, Ebony state, Nigeria.


INTRODUCTION

Soil fertility evaluation remains the most

veritable tool in assessing soil health, as a

guide to elucidating processes that could lead

to increased soil productivity. Studies have

been carried out on the soils of south eastern

Nigeria in the past (FDALR, 1985; Enwezor et

al., 1990). These were general reports for the

soils of the area. However, these soils have

undergone several transformations owing to

climatic changes, soil uses, agricultural

practices, and other factors including bush

burning. On the other hand, there is the need to

continuously assess soil quality by quantifying

the critical soil attributes. This will help to

establish ranges of value of soil quality

indicators. By this we monitor changes and

variability in soil properties. It has become

necessary to re-evaluate the soils of the study

area with specific details, for the specific soils,

with a view to evaluate the soils for specific

uses and resolving the persistent soil fertility

constraints to crop production in the

agricultural area.

The present study was carried out as site

specific, and targeted at the wetland areas in

particular. This is aimed to assist the various

agricultural change agents in the areas to

device management strategies that will guide

the farmers to improve their crop productivity.


Location: The investigation covered wetlands

located within Latitude 7o 30/ E and Longitude

5o 40/N and 6o 45/ N. The area lies within the

southeast rainforest and derived Savanna zone

of Nigeria. The soil is characterized by shale

parent materials and of shallow depth

97

Ogbodo and Chukwu NJSS/22(1)/2012


(FDALR, 1985), with intermittent water

logging conditions. The area is characterized

by with high temperature, with mean monthly

atmospheric temperature ranging between 24o

and 28o. The rainfall pattern is bimodal with

peaks in the months of July and September.

Annual rainfall ranges between 1500 mm and

2000 mm. The rainy season begins about May

and ends around November. The dry season

starts about October and ends around April.

Design: The study was a survey exercise

covering the wetlands of Ebonyi state, out of

which 9 major locations were particularly

selected as representative of the wetlands in

the state. Six sampling sites were randomly

chosen at each location for sample collection.

Field Study: Profile pits were dug at each

sampling site, at the depth of 0-60 cm, being

mindful that the area had been reported to have

shallow depth to impervious layer (FDALR,

1985 ). Soil samples were collected at the

walls of the pits with cores, at the intervals of

0-20 cm, 20-40 cm and 40-60 cm depths. The

samples from each pit were bagged

individually, and analyzed separately. The

average values of each parameter measured at

six sites of each location assumed the data for

the location.

Laboratory Methods: The soil samples

collected from the different locations were

analyzed separately in the laboratory for the

physical and chemical properties respectively.

The soil particle size distribution was

determined by the hydrometer method (Gee

and Bouder 1989), whereas bulk density was

determined by the Core method (Blake and

Hartge, 1986). Total porosity was calculated

from the bulk density data as the fraction of

the total volume not occupied by soil,

assuming a particle density of 2.65 g/cm3.

Total nitrogen was determined by the Macro

Kjeldahl method (Bououcous, 1951).

Available P was determined using Bray II

method as outlined by Page et al. (1982).

Organic carbon was determined by the

Walkley and Black method (Nelson and

Sommers, 1982). Soil pH (2:1 in water) was

determined by the glass electrode pH meter

(Maclean, 1982). Exchangeable bases were

extracted using the ammonium acetate method

(Tel and Rao, 1982)

Data analysis: The data on soil properties

were statistically analysed using summary and

descriptive statistics, and coefficients of

variation according to SAS (2006).


Soil Physical Characteristics

The bulk density and total porosity ranged

from 1.21 – 1.47g/cm3 and 44.6 – 54.0%

respectively (Table 1). The bulk density

increased with depth while the total porosity

decreased with depth. Consequently, there is

inverse relationship between the bulk density

and total porosity as one moves from 0 – 20,

20 – 40 to 40 – 60 in depth. (Table 1). The

results showed that the soil is not compacted at

the plough layer, and up to 40cm depth. Taylor

et al (1966) and Ashrad et al (1996) reported

that bulk density ranging from 1.1 – 1.4kg/m3

shows non compacted soil. The implication is

that there will be no hindrances to root

penetration, growth, and elongation to forage

the soil micro environment for nutrients and

moisture. This will also remove destruction for

roots and tubers that usually result in

deformation of tuber shapes that can reduce

eye appeal and market value. Similarly, the

total porosity showed that there is no risk of

compaction in the soils since the total porosity

from 0-60cm is >40% ). According to Harod,

(1975) when total porosity is less than 40% it

shows excess strength indicative of likely risk

of compaction and poor aeration.

98

Soil fertility evaluation in Ebonyi State

Table 1: Bulk Density and Total Porosity of Wetland Soils in Ebonyi State, Nigeria. Location

0-20

Bd

20-40

(kg/m2)

40-60

0-20

Tp

20-40

(%)

40-60

Oso

Akaeze

Amasiri

Isieke

Amachi

Nwida

Ndiagu

Alike

Omaka

Mean

CV (%)

1.17

1.14

1.24

1.26

1.34

1.25

1.10

1.25

1.16

1.21

6.00

1.25

1.33

1.61

1.30

1.38

1.25

1.27

1.26

1.29

1.32

8.00

1.48

1.54

1.56

1.54

1.43

1.43

1.47

1.47

1.32

1.47

5.00

56

57

53

52

48

53

58

53

56

54

5.00

53

50

40

51

48

52

52

51

52

49.8

7.00

44

42

41

42

46

46

45

45

50

44.6

6.00

Where Bd = bulk density, Tp = Total porosity.

Soil Texture

Table (2) shows particle size distribution, the

silt content is generally higher than sand and

clay contents at the epipedon (0-20cm) and

endopedon (40 -60cm). At Isieke, there is

evidence of argillic horizon at 20-40cm depth

(Soil Survey Staff 2008) because the clay

content was 24.4% as against 21.4% at 0-20cm

depth and 11.4% at 40-60cm depth. Generally,

the textural classes ranged from loam to clay.

At Oso, the endopedon (20-60cm) is

dominated by clay. Similarly, the epipedon at

Ndiagu is predominated by clay underlain by

clay loam soils. Apart from this few outliers,

one can describe the soils of the nine locations

as fine loamy soils (Table 2). The

predominance of silt separate indicates that

water holding capacity of the soils is high.

However, this poses a high challenge to

tillage. The textural classes indicate that the

soils are likely to be waterlogged, slippery and

heavy while they will be hard to very hard in

the dry season. Consequently, tillage

operations should be carried out when the soils

are at field capacity.

Table 2: Particle Size distribution (%) of Wetland soils of Ebonyi State, Nigeria.

Where SiL = Silty Loam, SiCL = Silty Clay Loam, CL = Clay loam

Soil Chemical Properties

The chemical properties of the soils are

presented in tables 3-5. The soil reaction,

organic matter contents, effective cation

exchange capacity and base saturation are

shown in Table 3. There is a variation in

acidity ranges of the soils. Soils of Akaeze,

Amasiri, Amachi and Omaka are extremely

Location Sand (%) Silt (%) Clay (%) Textural Class

0-20 20-40 40-60 0-20 20-40 40-60 0-20 20-40 40-60 0-20 20-40 40-60

Oso 41.2 27.2 29.2 33.4 41.4 39.4 25.4 31.4 31.4 Loam Clay CL

Akaeze 11.2 7.20 5.20 67.4 67.4 68.4 21.4 25.4 26.4 SiL SiL SiCL

Amasiri 26.5 31.2 23.2 54.1 53.4 59.4 19.4 15.4 17.4 SiL SiL SiL

Isieke 21.2 20.0 21.2 57.4 56.4 67.4 21.4 24.4 11.4 Sil Sil Sil

Amachi 11.2 9.20 9.20 53.4 55.4 55.4 35.4 35.4 35.4 Si CL Si CL Si Cl

Nwida 25.2 33.2 31.2 58.4 55.4 57.4 16.4 13.4 11.4 SiL SiL SiL

Ndiagu 22.2 25.2 21.2 30.4 43.4 41.4 44.4 35.4 27. 4 Clay CL CL

Alike 9.20 9.20 11.2 77.4 71.4 63.4 13.4 19.4 25.4 SiL SiL SiL

Omaka 23.2 35.2 45.2 59.4 41.4 27.4 17.4 23.4 27.4 SiL Loam CL

Mean 21.2 22.2 21.9 54.6 54.0 53.3 23.8 24.8 23.7

CV ( % ) 44.0 49.0 53.0 26.0 18.0 25.0 40.0 31.0 34.0

99


acidic ≤ pH 4.50 while Oso and Isheke soils

are very strongly acidic (pH 4.5 – 5.0).

However, the soils of Ndiagu and Nwida are

strongly acidic (pH 5.5 – 5.8). The overall

result indicates that the soils are acidic. The

results confirm earlier study by Chukwu

(2007) that soils of South eastern Nigeria

derived from shale are acidic.

The organic matter contents are low

irrespective of depth across locations, except

of 0-20cm depth at Oso and Akaeze, where the

organic matter contents are medium (>2.0%),

based on organic matter ratings of the south

eastern Nigeria soils by Enwezor et al (1990).

The soils are derived from shale which is

deposited from earlier cycles of weathering

(Ojanuga et al; 1981). As a consequence it had

lost most of its secondary elements (Ca and

Mg). The area is also marked by high rainfall

(1,500 – 2,000mm) per annum and high

temperatures ( FDALR, 1985). The soil

temperature regime is isohyperthemic (>22˚c)

(Chukwu, 2007). All these favour high rate of

organic matter decomposition. The area is also

prone to annual bush burning. These account

for the low organic matter content. Abundance

of soil organic matter resulting from mulch has

been reported to have a liming effect in soils

(Chukwu, 2001). The above scenarios explain

the acidic nature of the soils and the low

organic matter contents.

Table 3. Spatial distribution of Soil pH, Organic matter, ECEC and Base Saturation in

wetland soils of Ebonyi State. Location Soil pH (H2O) Orgnic Matter (%) ECEC ( Cmol /kg) B/S ( Cmol /kg)

0-20 20-40 40-60cm 0-20 20-40 40-60cm 0-20 20-40 40-60 cm 0-20 20-40 40-60 cm

Oso 4.90 5.20 5.10 3.20 0.88 0.90 7.13 9.17 8.28 91.03 90.40 96.14

Akaeze 4.40 4.30 4.60 2.98 0.47 0.66 12.04 8.57 11.26 92.69 86.93 87.20

Amasiri 4.50 5.00 4.00 0.85 0.90 0.52 9.7 11.98 9.85 91.76 85.95 83.76

Isieke 4.80 4.70 4.50 0.85 0.47 0.28 8.59 6.27 8.18 90.67 85.97 94.13

Amachi 4.10 4.20 4.30 1.50 0.66 0.24 9.21 10.12 8.51 84.37 84.19 82.15

Nwida 4.70 5.60 5.50 1.67 0.24 0.24 10.11 7.04 5.08 81.01 87.50 88.98

Ndiagu 5.50 5.70 5.80 1.67 1.21 1.52 12.00 12.66 9.96 82.67 88.63 83.13

Alike 4.40 4.50 5.00 1.20 0.52 0.29 6.79 5.96 7.40 72.89 82.96 72.96

Omaka 4.30 4.30 4.60 0.28 0.28 0.29 12.70 12.70 13.29 86.77 86.77 62.68

Mean 4.62 4.83 4.82 1.58 0.69 0.55 9.81 9.30 9.09 85.98 86.00 83.46

CV(%) 8.00 11.0 11.0 58.0 73.0 73.0 21 24 24 7.00 12.00 18

Based on soil fertility ratings of south eastern

Nigeria (Enwezor et al, 1990), the area suffer

nutrient deficiencies particularly N and K.

Total N is low (<0.15%). Similarly,

exchangeable K is also low ( <0.2cmol/kg).

The low organic matter content and the nature

of the parent materials might have accounted

for the observations. However, at the

epipedon, available P is generally medium

based on rating for Nigerian soils (Enwezor et

al, 1990; Adepelu,2000) Fertilizer use is

common in the area. The medium available P

at the epipedon except at Amasiri, Isieke,

Alike and Omaka could be attributed to the use

of mineral fertilizer (NPK). P is less mobile

and can be observed in the land after cropping

or at harvest. However, the low available P in

some locations corroborated the work of

Chukwu (2007) in Acid soils of south eastern

Nigeria.

100


Table 4: Distribution of Primary nutrients in Relation to depth in Wetland Soils of Ebonyi

State

Location Total N(%) Available P(mg/kg) Exchangeable K(cmol/kg)

0-20 20-40 40-60 0-20 20-40 40-60 0-20 20-40 40-60cm

Oso 0.14 0.06 0.04 39.3 10.5 8.80 0.20 0.07 0.12

Akaeze 0.14 0.03 0.03 30.5 5.60 7.10 0.14 0.06 0.04

Amasiri 0.04 0.07 0.03 8.90 14.7 4.50 0.03 0.04 0.03

Isieke 0.06 0.03 0.03 11.8 8.00 6.30 0.02 0.54 0.12

Amachi 0.08 0.03 0.01 19.3 5.20 4.00 0.04 0.03 0.04

Nwida 0.09 0.01 0.02 20.5 3.00 5.40 0.04 0.03 0.03

Ndiagu 0.09 0.06 0.07 25.7 18.3 15.1 0.10 0.15 0.07

Alike 0.08 0.03 0.01 17.5 6.20 4.10 0.03 0.03 0.02

Omaka 0.01 0.01 0.01 6.00 6.00 3.80 0.02 0.02 0.02

Mean 0.08 0.03 0.03 19.9 6.00 6.57 0.07 0.13 0.04

CV(%) 58.0 73.0 58.0 50.0 86.0 52.0 86.0 76.0 76.0

Table 5 shows total exchangeable bases.

Generally, exchangeable Ca is medium (3.2 –

6.0 Cmol/kg) while exchangeable Mg is

medium to high (1.0 – 4.8 Cmol/kg), (Landon,

1984). The exchangeable Na is low (<0.70

Cmo/kg). The medium to high levels of Ca

and Mg probably accounted for the eutric

nature of the soils studied because the base

saturation is above 70% in all locations. The

overall result indicates that despite the acidic

nature of the soil and the deficiency of N and

K that the soils are generally fertile (>50%

Base Saturation), (Landon, 1984). This seems

to contradict the general reports regarding the

soils of the area, as being low in fertility.

Table 5: Distribution of Total Exchangeable Bases (Ca, Mg and Na) in Wetlands of Ebonyi

State in Relation to Soil Depth.

Location Ca(cmol/kg) Mg(cmol/kg) Na(cmol/kg)

0-20 20-40 40-60 0-20 20-40 40-60 0-20 20-40 40-60cm

Oso 3.60 4.40 4.40 2.40 3.60 3.20 0.30 0.23 0.24

Akaeze 6.00 4.80 6.00 4.80 2.40 3.60 0.23 0.19 0.18

Amasiri 4.80 7.20 5.60 4.00 2.80 2.40 0.07 0.26 0.23

Isieke 4.80 2.20 4.00 2.80 1.20 3.60 0.17 0.45 0.09

Amachi 4.80 5.00 4.00 2.80 2.80 2.80 0.13 0.10 0.16

Nwida 5.60 4.00 2.40 2.40 2.00 2.00 0.15 0.13 0.10

Ndiagu 6.00 6.80 5.20 3.60 4.00 2.80 0.23 0.27 0.22

Alike 3.20 2.80 3.60 1.60 2.00 1.60 0.12 0.10 0.17

Omaka 6.00 6.00 5.20 4.80 4.80 2.80 0.20 0.20 0.31

Mean 4.98 4.80 4.49 3.24 2.80 2.76 0.18 0.21 0.19

CV(%) 20.0 24.0 24.0 33.0 23.0 23.0 36.0 34.0 36.0

CONCLUSION

The soils are prone to water-logging, acidic,

low in organic matter, cation exchange

capacity, N and K. However, the base

saturation is high. To improve the soil

productivity and enhance agricultural

transformation in the area, retaining crop

residue on the soil, application of organic and

mineral fertilizers, drainage and tillage when

the soil moisture is at field capacity are

recommended.

101


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data In: Simple soil, Water and Plant

Testing Technologies for Soil Resource

Management. IITA Ibadan/FAO Rome,

pp. 89 – 97.

Ashrad, M., A. lowery, and B. Grossman

(1966). Physical test for Monitoring

Soil guality. In: J. W. Doran and A. J.

Jones (eds.) Methods for assessing Soil

guality. Soil Sci. Soc. Am. Spec. Pub.

49. SSSA, Madison, WI: 123-142.

Blake, G.R. and K.H. Hartge (1986). Bulk

density. In: Methods of Soil analysis

part 1. Physical and ineralogical

Methods. A. Klute (ed) Am. Soc.

Agon. Madison, 101 USA: 365 – 375.

Chukwu, G.O. (2001). Residual effect of rice

husk on selected soil chemical

characteristics and yield of maize.

Discov. Innov. Kenya 13 (1/2): 58 –

62.

Chukwu, G.O. (2007) Soil fertitlity capability

classification for seed yam (Dioscerea

rondate Poir) on acid soils of

southeastern Nigeria. Unpublished

Ph.D thesis submitted to Federal

University of Technology, Minna,

Nigeria, 190pp.

Enwezor, W.O, A.C. Ohiri, E.E. Opuwaribo

and E.J.Udo (1990). A review of

fertilizer use on crops in Southeastern

zone of Nigeria In: Literature Review

of Soil Fertility Investigations in

Nigeria, FMANR, Lagos, Nigeria vol.

2:49-100.

Gee, G.W. and J.W. Bauder (1986). Particles

size analysis. In: Methods of Soil

analysis part 1. A. Klute (ed) Am. Soc.

Agron. Madision 101 USA: 38 - 41

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soils. In: Physical Conditions and Crop

Production. MAFF, Technical Bulletin

London 29: 25 – 51.

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Methods. In: Klute, A (ed). Methods of

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Carbon, Organ Carbon and Organic

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1982. Methods of Soil Analysis II.

Amer. Soc. Agron. Madison,

Wisconsin, USA.

SAS Institute Inc. (2006). SAS/STAT user’s

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Vol. 2, Cary, NC., SAS Institute

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–anotamated methods for soil and plant

analysis pp. 201-270.

102


GROWTH AND YIELD OF OKRA AND TOMATO AS AFFECTED BY PIG DUNG

AND OTHER MANURES ISSUE FOR ECONOMIC CONSIDERATION

IN BENUE STATE

OLATUNJI1, O AND V.U. OBOH2 1Department of Soil Science, University of Agriculture Makurdi

2Department of Agricultural Economics, University of Agriculture, Makurdi

E-mail: [email protected]

ABSTRACT

Pot experiments were conducted to compare the effects of pig dung and other sources of manure

on the production of okra (Abelmoschus esculentum) and Tomato (Lycopersicon esculentum

mill) at University of Agriculture, Makurdi. A survey was also conducted in Makurdi metropolis

to determine the comparative availability and cost of pig dung and other manures. Three levels of

organic manures were used, 0 ton/ha, 4 tons/ha and 8 tons/ha. Record of agronomic

characteristics such as leaf area, plant height, number of leaves/plant, the fresh pod weight was

taken as relevant. Increases in growth and yield of crops were recorded in response to application

of the manures. Pig manure was more effective than goat manure in increasing growth of tomato,

and was effective than poultry manure in increasing okra growth and yield. Application of Pig

manure increased pod yield. by 52%. In the study area pig manure is cheaper and also readily

available than poultry manure. It is highly recommended for vegetable crops production.

INTRODUCTION

The development of animal enterprises

produces a large amount of waste, which

becomes potential environmental hazard.

Hence, there is a renewed interest in proper

and effective use of organic manure to

maintain soil fertility. Aside from being source

of plant nutrients, organic wastes such as those

of poultry (Agbede and Ojeniyi, 2009)

increase the population of soil micro-

organisms which have some influence in

protecting plants against pathogens like

nematodes and soil borne insects and also

provides plant growth hormones like auxins (

Sanchez and Miller, 1986). The physical

properties of soil are also improved, (Odiete et

al, 1999, Akanni and Ojeniyi, 2008).The

application of organic manure has been found

to have higher comparative economic

advantage over the use of inorganic fertilizer.

A study conducted by Nwajiuba and

Akinsanmi, (2002) in Southeastern Nigeria,

showed that returns per hectare were higher in

organic farms though outputs were slightly

less than in inorganic farms.

However studies are scanty on response of

crops to Pig Dung. In Benue State, Nigeria,

Pig dung is available in appreciable quantity.

But its use as source of crop nutrients has not

received adequate research attention. Giwa and

Ojeniyi, (2004) investigated effect of Pig

manure and its integrated application with

NPK fertilizer on soil chemical properties and

103

Olatunji and Oboh NJSS/22(1)/2012


yield of tomato at Abeokuta , south west

Nigeria.

Pig dung and its combination with NPK

fertilizer significantly increased growth and

fruit yield and soil organic matter, P. K and

Mg were increased. The manure at 5t/ha

increased yield by 39%. The studies by Ojeniyi

et al., (2007) also found that pig manure

increased soil nutrients content and grain yield

of maize. This work is a comparative study of

the effect of Pig manure and other manures on

growth and yield of tomato and okra.

MATERIALS AND METHODS.

Experiment I

Experiments were conducted at University of

Agriculture, Makurdi using a soil classified as

typic ustropept. The experimental design was a

complete randomized design with four

replications.

Twenty plastics pots (20) of 4litre capacity

containing the equivalent of 4 kg of air dried

soil were used. The treatments consisted of 0

ton/ha (control), 4 tons/ha and 8 tons/ha of Pig

dung, 4 tons/ha and 8 tons/ha of Goat Dung

respectively were mixed with soil in an

attempt to allow mineralization to take place

before the transplanting of the tomato

seedlings from the nursery bed. Tomato

seedlings grown previously in a nursery bed

selected for uniformity were transplanted at

the rate of two seedlings into each of the 20

pots and later thinned to one per pot

throughout the experiment. Wetting of plants

with water was done at a consistent rate in

order to avoid waterlogging. The experiment

was terminated after 3 months.

Experiment II Twenty plastic pots (20) of 4 litre capacity

containing the equivalent of 4 kg of air dried

soil were used. The treatment consisted of 0

ton/ha (control), 4 tons/ha and 8 tons/ha of pig

dung, 4 tons/ha and 8 tons/ha of Poultry

dropping respectively were mixed with soil in

an attempt to allow for mineralization before

the plants of Okra (Jokoso variety) were

planted at the rate of 3 seeds per pot and

thinning was done after 4 weeks of planting

to one seed per pot. Throughout the

experiment wetting of plants was done in the

same way as in Experiment I.

Plant height above the soil, the leaf area,

number of leaves of tomato at different weeks

and weight of Okra plant, number and weight

of seeds per pod were recorded.

Soil Analysis

The soil used for the study was subjected to

routine analysis using a composite sample.

The soil pH was determined both in water and

0.01M CaCl2 using the glass electrode pH

meter. The particle size analysis was

determined using the hydrometer method.

Total Nitrogen was determined using the

regular macro-kjedahl method. Available

phosphorus was determined using the method

of Bray and Kurtz-Bray I extraction.

Exchangeable cations (Ca and Mg) were

extracted using 1M NH4 OAC and determined

on atomic absorption spectrophotometer. The

K in the soil sample was determined using a

flame photometer.

Data Collected from Pig and Poultry

farmers.

Thirty randomly selected commercial pig and

poultry farmers in Makurdi metropolis were

interviewed. A simple interview schedule was

administered to ascertain the comparative cost

of Pig dung and Poultry drippings

.

Statistical Analysis

The data collected from the pot experiments

were subjected to analysis of variance

(ANOVA) to test for differences among

treatments. The, means that showed significant

difference were separated using the Fishers

Least Significant Differences (F-LSD). Simple

descriptive statistics (Frequencies and

Percentages)were used to analyze the data

from farmers interview.


The soil used for the study classified as Typic

ustropept had pH (H2O) 6.8, pH (CaCl2) 6.20,

104

Effect of pig dung on okra and tomatoe

organic matter 1.45%, Total N 0.09%,

Available P 4.6 mg /kg, exchangeable K, Ca,

Mg being 0.22, 3.4 and 2.5 cmol/kg

respectively and CEC of 6.5 cmol/kg. The soil

was low in organic matter, N, P and CEC.

Therefore, it required application of organic

manures.

Table 1 shows that pig manure (PD) and goat

manure (G D) increased height of tomato at 2,

4 and 8 weeks after planting (WAT), but

increases were not significant. The manure at

4tons/ha increased plant height at 10 WAT,

whereas at 8tons/ha the manures reduced plant

height, hence plant growth.

At different weeks of observation, the manures

at 4 and 8 tons/ha increased number of tomato

leaves (Table 2) relative to the control. The

increases were significant (P= 0.05). The PG

at 4tons/ha gave higher values of number of

leaves than at 8tons/ha at 4, 6, 8 and 10 WAT

indicating that leaf growth was depressed by

8tons/ha. This was not observed in case of GD.

The PG at 4 and 8tons/ha increased leaf area at

5, 6 and 7 WAT and at 7 WAT the increases

were significant. In case of GD there were no

increases or the increases were not significant

(Table 3).

The PG at 4tons/ha was more effective in

increasing tomato height, number of leaves

and leaf area than G D at 4tons/ha. At 8tons/ha

PG had higher value of leaf area (56.5>

41.4cm2) and plant heights (26.0, 27.8cm) and

number of leaves (54.0, 57.0) were similar.

The dry matter yield of okra recorded at 27

WAT were 22.7, 34.9, 44.5, 21.8 and 26.0g for

the control, 4.0tons/ha PG, 8.0tons/ha PG,

4.0tons/ha PD and 8.0tons/ha PD respectively

(LSD 0.05= 13.5) the pod and weights were

2.3, 2.3, 3.5, 2.4 and 2.2 g (LSD 0.05=0.6)

Both manures increased Okra growth, but it

was only PG at 8.0tons/ha that increased pod

weight by 52%. In case of tomato the optimum

rate of PG was 4tons/ha and Giwa and Ojeniyi

(2004) found that PG 5tons/ha significantly

increased root growth, dry matter and fruit

yield of tomato. For maize Ojeniyi et al.,

(2007) found that 7.5tons/ha PG was optimum.

The PG was more effective than GD in

increasing growth of tomato and okra.

This could be due to quicker availability of

nutrients in P G due to its watery nature. For

example the water content for P G and P D

were found to be 72 and 35% respectively

(Brady and Weil, 1999).

Increase in growth and yield of tomato and

okra in response to application of PG is

consistent with earlier finding of Ojeniyi et al.,

2007. That the manure increased soil organic

matter, N, P and exchangeable K, Ca and Mg

is also in agreement of the finding of Giwa and

Ojeniyi (2004) that manure increased soil

organic matter, P, K and Mg.

Also Pig manure has been found to have less

C, lower C:N, more K and Mg compared to

Poultry and Goat manure by (Moyin-Jesu and

Ajao, 2008) who gave C:N ratio for the three

manures as 6.72, 6.93 and 7.93 respectively.

This indicates that pig manure decompose and

thus mineralizes fastest. The values for %K

were 14.4, 9.2 and 2.9 and Mg concentrations

were 4.8, 4.1 and 4.5%.

Ano and Ubochi (2007) also confirmed that

pig manure has less C:N ratio and higher Ca,

Mg and N compared to goat and poultry

manures . The values given for Ca were 1.37,

1.37 and 1.24%, Mg 1.30, 0.83 and 0.89%. N

0.52, 0.32 and 0.36%, OC 27.1, 28.4 and

29.6% and C:N ratio were 19.8, 20.8 and 23.9.

CONCLUSION.

The survey carried out showed that majority of

the pig farmers (73.3%) indicated that nobody

requested for pig dung from them and hence it

constituted environmental menace. Only

26.7% contacted the farmers for the product to

be given free of charge, while no one

bargained on any price with the farmers. In

contrast, only 20% of poultry farmers regarded

poultry droppings as an environmental

menace, 40% sold theirs while the remaining

105


40% were contacted to be offered free of

charge. This result implied that Pig dung is

relatively cheaper, more readily available and

of little or no economic importance to the

owners, and more effective than goat and

poultry manures in increasing growth of okra

and tomato in this study. The findings from

this work are supported by Innes, (2000) who

indicated that swine slurry was more

economical to use than poultry droppings.

Therefore pig dung should be encouraged in

the study location.

Table 1: Plant Height (cm) of Tomato as Affected by Pig and Goat Dung manures

Treatments Weeks After Transplanting (WAT)

t/ha 2 4 6 8 10

Control

4.0 PG

8.0 PG

4.0 GD

8.0 GD

Mean

7.75

11.75

12.13

9.00

12.38

10.60

15.00

21.00

19.00

16.50

18.00

17.90

23.25

31.75

33.00

22.00

26.00

27.20

24.90

28.50

29.00

25.00

27.50

27.08

28.00

31.75

26.00

25.00

27.80

26.80

F-LSD (0.05) NS NS NS NS 5.65

PG = Pig Gung, GD = Goat Dung, NS = Non Significant

Table 2: Number of leaves of tomato as affected by Pig and Goat dung manures


t/ha 2 4 6 8 10

Control

4.0 PG

8.0 PG

4.0 GD

8.0 GD

Mean

7.75

20.00

21.00

19.00

21.00

19.00

26.00

38.00

35.00

35.00

39.00

34.60

29.00

61.00

73.00

57.00

57.00

34.50

30.00

68.00

57.00

51.00

67.00

54.00

27.00

63.00

54.00

54.00

57.00

51.00

F-LSD (0.05) 2.6 NS 13.2 19.6 20.5


Table 3: Effect of Pig dung and Goat dung manure on the mean leaf area of Tomato (cm2)


t/ha 2 4 6 8 10

Control

4.0 PG

8.0 PG

4.0 GD

8.0 GD

Mean

18.08

17.17

22.28

21.63

19.85

19.80

24.42

25.03

14.01

25.64

25.64

28.86

28.78

33.79

45.32

27.91

29.21

34.99

35.09

42.88

55.34

35.59

32.65

40.31

38.53

50.80

56.45

38.85

41.35

45.59

F-LSD (0.05) NS 10.45 13.20 13.66 12.46


106


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Nwajiuba, C and A. Akinsanmi. 2002.

“Organic Manure use among

smallholders in the rainforest of

southeastern Nigeria”. Online-

http//www.Tropentag.de/2002/proceedi

ngs/node188.html.

Odiete, I., Ojeniyi, S.O., Akinola, O.M and

A.A. Achor. 1999. Effect of goat dung

manure on soil chemical and yield

components of okra, amaranthus and

maize. Proceedings 25th Annual

conference of Soil Science Society of

Nigeria, Benin City p174-178.

Ojeniyi, S.O., D. Akanni and M.A. Awodun.

2007. Effect of goat manure on some

soil properties and growth yield and

nutrient status of tomato. University of

Khartoun Journal of Agricultural

Sciences 15(3), 396-406.

Ojeniyi, S.O., B.T. Faleye, Taiwo, L.B.

Akande, M.O. and Adediran, J.A.

2007. Effect of some manure on soil

plant nutrient status, growth and yield

of maize in Southwest Nigeria. The 4th

African Soil Science Society

Conference, GIMPA Accra, Ghana. 7-

8 January, 2007.

Sanchez, P.A. and Miller, R.H. 1986. Organic

matter and soil fertility management in

acid soils of the tropics. Transactions

of the XIII Congress of International

Soil Science Society (Vol. V).

107


EFFECT OF NPK AND POULTRY MANURE ON COWPEA AND SOIL

NUTRIENT COMPOSITION

OLATUNJI, O1., S. A. AYUBA2, B.C. ANJEMBE3 AND S. O. OJENIYI4 1,2,3Department of Soil Science, University of Agriculture,

P.M.B. 2373, Makurdi, Benue State. 4Department of Crop Soil and Pest Management, Federal University of Technology

P.M.B 704, Akure, Ondo State. E – mail: [email protected]

ABSTRACT

Field experiment was conducted at University of Agriculture Makurdi in the Southern Guinea

Savanna ecology of Nigeria to test effect of NPK fertilizer and Poultry manure on performance

of cowpea and soil nutrient composition. The study conducted in 2008 and 2009 had a control,

NPK 20 – 10 – 10 (48 kgha-1) and poultry manure (PM) with or without NPK fertilizer. The test

soil was deficient in N and P. The PM, NPK and their combinations increased plant height,

number of branches, leaves, dry matter yield (DMY), number of peduncles, pods , seeds and seed

yield. The effect on plant height, DMY, number of pods and grain yield was significant. The 4t

ha-1 PM and 4t ha-1 PM + NPK gave highest and similar seed yield. The PM alone or with NPK

increased soil pH, N, P, K, Ca, Mg, CEC and O.M. The parameters increased with level of PM.

Addition of NPK to PM increased soil N, P, K, Ca, ECEC, OM while NPK reduced pH.

Application of PM at 4t ha-1 is recommended.

INTRODUCTION

Cowpea is a tropical food grain legume for

human and livestock. However low soil

fertility limits its yield. Although the crop

fixes nitrogen in symbiotic relationship with

rhizobium bacteria, it suffers from temporary

N deficiency during seedling growth once the

cotyledon reserve is exhausted. Hence starter

dose of N fertilizer is recommended to

enhance early growth of cowpea plant (Dart et

al.,1997). Also application of P is known to

stimulate performance and grain yield of

cowpea (Kolawole et al., 2003). Because of

problems associated with total dependence on

inorganic or organic fertilizer alone (Adeniyan

and Ojeniyi, 2003, 2005) the concept of

integrated nutrient supply i.e combined use of

inorganic and organic fertilizer is advocated to

enable sustainable crop production (Ojeniyi, et

al., 2003).

Integrated nutrient management ensures

balanced nutrient supply, control of acidity,

extended residual effect and improvement on

soil physical conditions compared with use of

inorganic fertilizer alone. Unlike its

application in maize and vegetable production

(Adeniyan and Ojeniyi, 2003, 2005; Adeoye, et

al., 2008; Ayeni, et al., 2009, 2010; Ewulo, et

al., 2009; Ojeniyi et al., 2009a, 2009b) studies

are scarce on combined application of the two

types of fertilizer in cowpea production.

In addition, because of the old impression that

cowpea can tolerate low soil fertility being a

N-fixer, attention has not been given to

108

Effect of NPK and manure on cowpea

enhancing performance of the crop using

organic manure. The need to improve yield of

cowpea in peri-urban soils of southeast Nigeria

has been met by application of inorganic

fertilizers which worsened the acidic problem

of the soil. Organic fertilizers have so far

served as a formidable alternative. Nnabude, et

al., (2006) found that compost at 4t ha-1 gave

highest cowpea grain yield, showing that

compost was beneficial to cowpea. In cowpea

production organic fertilizer has proved to be

effective in combating nematodes without the

usual side effects of nematicides. Abubakar

and Majeed (2000) obtained greater than 50%

reduction in nematode population with poultry

droppings.

This study was therefore designed to evaluate

the effect of poultry manure and its combined

use with NPK fertilizer on soil nutrients

composition, growth and yield components of

cowpea in Makurdi in the humid savanna

ecology of Nigeria.

MATERIALS AND METHODS.

Field Experiment:

The study based on NPK 20-10-10 fertilizer

and poultry manure (PM) in the 2008 and 2009

cropping seasons was conducted at the

University of Agriculture, Makurdi (70 410N,

80 350E ) in the southern Guinea Savanna agro

ecological zone of Nigeria. The soil is

classified as typical Ustropept.

The experiments were laid out in a

completely randomized block design with

three replications. The plot size was 4m x 3m.

The six treatments were as follow:

T1- No poultry manure, No NPK 20-10-10

(control)

T2- 48kg ha-1 NPK20-10-10

T3- 2t ha-1 poultry manure

T4- 2t ha-1 poultry manure with 48kgha-1 NPK

20-10-10

T5- 4t ha-1 poultry manure

T6- 4t ha-1 poultry manure with 48kgha-1 NPK

20-10-10

Sites were cleared manually using cutlass and

later ridged with hoe. Poultry manure (PM)

and the NPK 20-10-10 combined with poultry

manure were uniformly spread on the top of

the ridge and incorporated with hoe 2 weeks

before planting. Planting was done in August

for the two years at a spacing of 0.50m plant to

plant with two seedlings per stand after

thinning. Plots were weeded manually at

frequency they required. Plant data collected

included plant height, number of branches,

number of leaves, nodule production and dry

matter yield all taken at 50% to flowering. At

pod maturity, yield components including

peduncles per plant and number of pods per

plant, number of seeds per pods were taken.

Soil sampling and Analysis.

Before planting in 2008, surface (0-15cm) soil

samples were collected from 8 points and

bulked. The soil sample and the poultry

manure were analyzed. Post cropping

composite soil sample was collected per plot at

the end of the second cropping year. The soil

samples and the poultry manure sample were

air dried, crushed and allowed to pass through

2mm sieve. Particle size distribution was

carried out by the Hydrometer method, while

soil pH was measured with the glass electrode

pH meter in soil solution ratio 1: 2 in 0.01M

CaCl2. Soil organic carbon (OC) was

determined by the Walkey Black method and

the total N by the micro-Kjeldahl digestion

method (Bremner and Mulraney, 1982) after

digestion of samples with concentrated H2S04.

Availabile P was determined by Bray and

Kurtz (1995) extraction method.

Exchangeable cations were extracted using

NH4 OAC solution, K and Na were read using

flame photometer, while Ca and Mg were

determined on the atomic absorption

spectrophotometer. Effective cation exchange

capacity (ECEC) was established as the

summation of the exchangeable cations (K,

Na, Ca, and Mg).

Data Analysis

The statistical analysis was performed using

SPSS statistical package for the analysis of

variance (ANOVA). Means were separated

using fisher’s least significant difference

109

Olatunji, Ayuba, Anjembe and Ojeniyi NJSS/22(1)/2012

F.L.S.D at 5% level of probability when F

ratio was significant

RESULT AND DISCUSSION

Table 1 shows properties of the soil used for

the experiment. The soil is sandy loam and

very low in N and available P, their values

were below critical values. It is expected that

the test soil and cowpea would benefit from

added fertilizers since the N and P limit

cowpea performance.

The NPK fertilizer at 48kg ha-1, PM and their

combinations increased growth parameters of

cowpea such as plant height, number of

branches, leaves and dry matter yield (DMY)

in 2008 (Table 2) and 2009 (Table 3). The

effect on plant height and DMY was

significant. The number of nodules was

significantly reduced relative to control.

Rhodes (1981) and Ofori (1973) also observed

that nodulation in cowpea was inhibited by

application of N fertilizer. Graham and Scott

(1984) reported that N fertilizer at more than

30kg ha-1 inhibited nodulation. Eriksen and

Whitney (1984) reported that application of N

at flowering promoted vegetative dry weight

but reduced nodule dry weight. It is implied

that enhanced growth of cowpea associated

with application of NPK and PM was due to

improved and direct availability of nutrients

from the fertilizers rather than N from

nodulations. Effect of treatments on plant

height and DMY was significant. In both years

the 4t ha-1 PM + NPK increased plant height

and DMY significantly. Moreover, the growth

parameters increased between 2 and 4 tha-1

PM indicating that nutrients release from PM

had direct influence on growth of cowpea.

Also, PM should have had nematicidal effect

on cowpea (Nnabude, et al., 2006), Abubakar

and Majeed, 2000.

In 2008 and 2009, the PM, NPK and their

combinations increased number of penduncles,

pods, seeds, seed weight and seed yield per

plant. The effect on number of pods and grain

was significant in both years. In 2008, the 4t

ha-1 PM and 4t ha-1 PM + NPK increased grain

yield equally and significantly, in 2009, 2t ha-1

PM, + NPK, 4t ha-1 PM and 4t ha-1 NPK

increased grain yield significantly. They gave

similar values. In both years, 4t ha-1 PM and

4tha-1+ NPK had the highest and similar grain

yield. The yield components increased

between 2 and 4t ha-1 PM indicating that

nutrients released from PM increased cowpea

performance.

Table 6 indicates that PM alone, or with NPK

fertilizer increased soil pH, N, P, K, Ca, Mg,

CEC and OM compared to control or NPK

alone. The parameters increased with increase

in PM from 2 to 4t ha-1. Thus it is ascertained

that PM is a liming material in addition to

being a source of the nutrients. Similar

observations were made by other Workers.

(Adeniyan and Ojeniyi, 2003; Ewulo, et al.,

2008). The NPK reduced soil pH and slightly

increased N and P, thus it is acid producing

unlike the PM. It is observed that addition of

NPK to PM tended to increase soil N, P, K,

Ca, Mg, CEC and OM. This could be due to

enhanced release and mineralisation of

nutrients from native and added OM due to

synergistic effect of the NPK on OM,

(Adeniyan and Ojeniyi, 2005). Therefore

nutrients released to the soil from NPK and

PM led to enhanced growth and yield of

cowpea. Some studies reported that application

of N and P enhanced yield in Cowpea.

(Kolawole et al., 2005) and other legumes.

Also the increased OM should have had

nematicidal effect on cowpea.. This effect

should have obliterated effect of NPK on

yield.

In conclusion there was no significant effect of

addition of NPK added to PM on performance

of cowpea. Hence, application of PM at 4t ha-1

is recommended for cowpea. Relative to

control, 2t ha-1 + NPK, 4t ha-1 and 4t ha-1+

NPK increased mean grain yield (for 2008 and

2009) by 20, 24 and 27% respectively.

110


Table 1: Soil physical and chemical properties before planting.

Properties Values

pH (H20)

pH (CaCl2)

% Sand

% silt

% Clay

Textural class

Nitrogen (g 100g-1)

Phosphorus (mgkg-1

Potassium (cmolkg-1)

Calcium (cmolkg-1)

Magnesium (cmolkg-1)

Sodium (cmolkg-1)

ECEC (cmolkg-1)

Organic Carbon (g 100g-1)

Organic matter (g 100g-1)

6.20

5.90

75.60

17.20

7.20

Sand loam

0.09

4.60

0.22

3.44

2.48

0.31

6.48

1.25

1.45

Table 2: Effects of poultry manure and NPK 20-10-10 on growth parameters

of cowpea at 50% flowering stage in 2008

Treatments Plant height

(cm)

Branches/Plant

(No.)

Leaves/Plant

(No.)

Nodules/Plant

(No.)

Dry matter

(gplant-1)

Control

NPK 48 Kg/ha

2t/ha PM

2t/ha PM+NPK

4t/ha PM

4t/ha PM+NPK

Mean

F-LSD (0.05)

12.18

18.27

15.20

19.25

17.80

23.50

17.70

9.45

4.80

5.20

5.10

5.20

5.40

6.01

5.25

NS

28.50

30.20

29.00

31.50

31.40

33.40

30.67

NS

14.50

6.40

10.80

8.60

12.50

11.30

10.68

5.92

26.80

32.60

30.90

34.20

32.80

38.90

32.70

9.68


of cowpea at 50% flowering stage in 2009

Treatments Plant height

(cm)

Branches/Plant

(No.)

Leaves/Plant

(No.)

Nodules/Plant

(No.)

Dry matter

(gplant-1)

Control

NPK 48 Kg/ha

2t/ha PM

2t/ha PM+NPK

4t/ha PM

4t/ha PM+NPK

Mean

F-LSD (0.05)

13.40

23.80

20.40

26.50

23.50

38.60

24.32

15.20

6.10

8.20

8.20

9.40

9.70

9.80

8.57

NS

27.4

32.50

28.50

34.90

35.20

36.60

32.52

NS

21.80

10.30

15.50

14.80

17.50

17.20

16.18

9.25

25.50

38.50

37.50

42.80

40.20

46.70

31.50

18.75

111



of grain yield of cowpea at 50% flowering stage in 2008

Treatments Peduncle Plant

(No.)

Pods/Plant Seeds/Pods

(No.)

100 Seeds

(g)

Grain Yield

(tha-1)

Control

NPK 48 Kg/ha

2t/ha PM

2t/ha PM+NPK

4t/ha PM

4t/ha PM+NPK

Mean

F-LSD (0.05)

12.20

12.80

13.20

15.20

16.80

17.50

14.67

NS

17.90

19.50

19.20

22.80

20.60

24.50

20.75

5.60

8.10

9.40

9.60

11.20

11.00

11.60

8.48

NS

17.30

22.40

20.50

26.10

24.50

25.80

22.76

6.20

1.10

1.18

1.22

1.28

1.32

1.31

1.23

0.20

Table 5: Effects of poultry manure and NPK 20-10-10 on yield parameters

of grain yield of cowpea at 50% flowering stage in 2009

Treatments Peduncle Plant

(No.)

Pods/Plant Seeds/Pods

(No.)

100 Seeds

(g)

Grain Yield

(tha-1)

Control

NPK 48 Kg/ha

2t/ha PM

2t/ha PM+NPK

4t/ha PM

4t/ha PM+NPK

Mean

F-LSD (0.05)

12.60

13.10

14.20

16.50

17.20

18.20

15.30

NS

17.80

20.10

19.20

23.50

21.50

24.84

21.15

5.98

8.00

9.50

10.10

11.20

11.40

11.80

10.33

NS

16.80

23.50

22.10

27.60

26.70

28.50

24.20

NS

1.05

1.20

1.26

1.32

1.35

1.42

1.27

0.22

Table 6: Effects of poultry manure and NPK 20-10-10 fertilizer on chemical properties of

Soil after two seasons of cultivation Soil Properties Contol NPK 84

t/ha

2t/ha

PM+NPK

2t/ha PM 4t/ha PM 4t/ha

PM+NPK

pH (CaCl2)

Nitrogen (g 100g-1) (N)

Phosphorus (Mgkg-1) (P)

Potassium (cmol/kg-1) (K)

Calcium (cmol/kg-1) (Ca)

Magnesium (cmol/kg-1) (Mg)

Sodium (cmol/kg-1) (Na)

ECEC (cmol/kg-1)

Organic Carbon (g 100g-1)

Organic Matter (g 100g-1)

5.90

0.12

4.40

0.20

3.65

2.50

0.35

7.25

1.35

1.48

5.45

0.15

4.60

0.18

3.55

2.61

0.33

7.55

1.38

1.52

6.36

0.16

4.80

0.18

3.62

2.65

0.45

7.60

1.50

1.63

6.48

0.19

5.10

0.40

4.40

3.02

0.75

8.85

1.55

1.72

6.40

0.18

5.70

0.43

4.40

3.02

0.82

9.90

1.60

1.85

6.50

0.22

5.80

0.45

4.51

3.02

0.82

10.85

1.62

1.88

REFERENCES Abubakar, U and Majeed, Q. 2000. Use of

animal manure for the control of root-knot nematodes of cowpea. Journal of Agriculture and Environment 1: 23-33

Adeniyan, O.N and Ojeniyi, S.O. 2005. Effect

of poultry manure, NPK 15-15-15 and combination of their reduced levels on maize growth and soil chemical properties. Nigerian Journal of Soil Science. 15: Pp 34-41

Adeniyan, O.N and Ojeniyi, S.O. 2003. Comparative effectiveness of different levels of poultry manure with NPK fertilizer on residual soil fertility, nutrient uptake and yield of maize. Moor Journal of Agricultural Research 4(2). 191-197.

Adeoye, G.O., Adeoluwa, O.O., Oyekunle, M.

Shridhar, M.K.C., Makinde, E.A and Olowoake, A.P. 2008. Comparative evaluation of Organomineral fertilizer (OMF) and mineral fertilizer on yield and quality of maize. Nigerian Journal of soil science. 18:132-137.

112


Ayeni, L.S., Adetunji, M.T and Ojeniyi, S.O.2009. Integrated Application of NPK fertilizer Cocoa pod ash and poultry manure: Effect on maize performance plant and soil nutrient content. International Journal of Pure and Applied Sciences 2(2):34-41.

Ayeni, L.S., Omole, T., Adeleye, E.O and

Ojeniyi, S.O. 2010. Integrated application of poultry and NPK fertilizer on performance of Tomato in Derived Savanna Transition zone of Southwest Nigeria. Science and Nature 8(2):50-54.

Bray, R.H and L.T. Kurtz. 1995.

Determination of Total Organic and available forms of phosphorus in soils. Soil Science. 59:39-45.

Bremner, J.M and Mulvaney, C.S. 1982.

Nitrogen Total In: Methods of soil analysis 2nd ed. A.L. Page et al., (Eds) Pp. 595-624 ASA, SSSA Medison Winsconsin.

Dart, P.J., Day, R.A., Islam and J. Dobereiner.

1997. Some Effects of Temperature and Composition of the rooting medium in symbiotic nitrogen fixation in plants synthesis in: Tropical Grain Legume, Nutman, R.S (Ed.) Cambridge Univ. Press. Pp 361-383.

Ericksen, F.I and A. Whitney. 1984. Effects of

solar radiation requirements on growth and nitrogen fixation of soybean, cowpea and bush bean. Agron. J., 76: 529-534.

Ewulo, B.S., Babadele, O.O and Ojeniyi, S.O.

2009. Sawdust Ash and Urea Effect on soil and plant nutrient content and yield of Tomato. American-Eurasian Journal of Sustainable Agriculture 3 (1) 88-92.

Graham, A and R. Scott. 1984. Response of cowpea (Vigna unguiculata(L)walp) to nitrogen and inoculation. Trinidad Trop. Agric. 6:56-58.

Kolawole, G.O., G. Tian and B.B Singh. 2003.

Differential Response of cowpea lines to application of phosphorus fertilizer. In: challenges and opportunities of enhancing sustainable cowpea production. Fatokun, O.A., S.A. Tarawali, B.B. Singh, P.M. Karmawa and M. Tama (Eds.) International Institute for Tropical Agriculture (IITA), Ibadan pp:319-328.

Nnabude, P.C., Obi, C.O and Onuoha, E.

2006. Tillage and Kitchen wastes on peri-urban soil properties and vegetable cowpea (Vigna unguiculata(L)walp) production in Southeastern Nigeria. Nigerian Journal of Soil Science. 16:140-144

Ofori, C.S. 1973. The Importance of fertilizer

Nitrogen in Grain Legume production soils of gigantic origin in the upper region of Ghana. In : Proceedings of first IITA grain legume improvement workshop. 1973 pp: 155-161.

Ojeniyi, S.O., Owolabi, O., Akinola, O.M and

Odedina, S.A. 2009a. Field study of effect of organomineral fertilizer on maize growth yield soil and plant nutrient composition in Ilesa, southwest Nigeria. Nigerian Journal of Soil Science. 19(1):11-16.

Ojeniyi, S.O., Makinde, E.A., Odedina, S.A

and Odedina, S.N. 2009b. Effect of organic organomineral and NPK fertilizer on Nutritional Quality of Amaranthus in Lagos Nigeria. Nigerian Journal of Soil Science 19(2): 129-134.

Rhodes, E.R. 1981. The economic of

fertilizing cowpea (Vigna unguiculata(L)walp) with basic slag on an oxisol in Njala and the effect of the fertilizer on leaf lamina N, P, Zn contents and nodulation. Trop. Grain Legume Bull. 22: 6-10

113


SUITABILITY OF EXTRACTANTS FOR THE DETERMINATION OF AVAILABLE

SULPHUR FOR GROUNDNUT PRODUCTION IN SOME SOILS OF BENUE STATE,

NIGERIA

BEMGBA ANJEMBE1 AND M.T ADETUNJI2

1Department of Soil Science, University of Agriculture, Makurdi 2Department of Soil Science and Land Management

University of Agriculture, Abeokuta.

ABSTRACT

Occurrence of sulphur deficiency in Nigerian soils is becoming frequent and more extensive due

to intensive cultivation and shift from low analysis fertilizers to high analysis fertilizers which

do not contain sulphur. Information is still required on the parameters of evaluating sulphur

status and requirement of crops in the country. Studies were conducted in the laboratory,

greenhouse and farmers’ fields in 2004 and 2005 to evaluate four extractants (0.16 M KH2PO4,

0.10 M Ca (HPO4)2, 0.10 M LiCl and distilled water, for the determination of available sulphur

for groundnut production in some soils of Benue State. The soils include Abinsi, Adaka,

Ikpayongo, Tyowanye, Yandev, Gbatse, Tse-mker and Makurdi. Fields of 8 farmers cultivating

groundnut as sole crop were used to verify the findings of the laboratory and pot experiments.

Among the extractants, 0.10 M LiCl related significantly with pod yield and pod number. There

was also, significant relationship between the lithium chloride extractable S and the total S

values of the soils.

INTRODUCTION Sulphur as a yield limiting nutrient is

becoming increasingly important in many

Nigerian soils. Occurences of deficiency in

various crops are becoming more frequent and

extensive (Kang et al 1981, Adetunji and

Adepetu 1990, Obasi et al 2001). Information

is still required to adequately quantify the

extent and spread of the deficiency problem as

well as the parameters for evaluating the

status and requirement of crops in the country.

Sulphur occurs in soils in both organic and

inorganic forms, but only a fraction of it is

available for crop growth (Beaton et al 1968,

Metson 1979, Tabatabai 1982). Sulphate may

be present in the soil solution adsorbed on soil

surfaces or as insoluble compounds such as

gypsum (Nelson, 1982) or associated with

calcium carbonates (Roberts and Bettany,

1985). Adsorption of sulphate occurs on

positive charges that are pH dependent and

these sites are negligible above pH 6.5

(Tabatabai, 1982). The insoluble sulphate

compounds are probably not taken up directly

by the plant. On a theoretical basis then, the

solution and adsorbed forms of sulphate are

the primary pools of sulphate in the soil that

are immediately available for plant uptake.

Although there is a good theoretical basis for

the solution and adsorbed pools being present

in the soil, there are some practical limitations

to their quantification. Limitations occur in

both the extraction and subsequent chemical

114

Suitability of extractants for sulphur

quantification. Before choosing a method and

interpreting the results, these limitations

should be thoroughly understood. The choice

of the extractant will depend on analytical

equipment available and the type of soil to be

analyzed. Numerous extractants have been

used for soil sulphate (Beaton et al 1968).

Extractants may include water, acetates,

carbonates, chlorides, phosphates, citrates, and

oxalates (Beaton et al, 1968, Jones 1986,

Kilmer and Nearpass, 1960). The nature of the

anion influences the ability of the extractant to

displace adsorbed sulphate. The choice of a

method for extracting available sulphur from

soils then should be made carefully taking into

consideration the purpose of the analysis, the

soil type involved, the nature of the extractant

and the analytical method to quantify the

sulphur extracted.

This study was therefore carried out to evaluate

four extractants for the determination of

available sulphur for the production of

groundnuts in some eight selected soils

covering Abinsi, Adaka, Ikpayongo,

Tyowanye, Yandev, Gbatse, Tse-mker, and

Makurdi, in the groundnut producing areas of

Benue state.


The experiment involved laboratory studies,

pot experiment and farmers’ fields. Surface

soil samples (0-20cm) were collected from the

eight sites corresponding to four different

parent materials in the groundnut producing

areas of Benue state that have no previous

history of S fertilization .Sub samples of the

soils were sieved to pass 2mm sieve for

laboratory analysis. The samples were

analyzed for the following parameters using

standard procedures; pH was measured by

glass electrode in a 1: 2 soil, water ratio.

Exchange acidity was determined by the

titration method (Page et al., 1982).

Exchangeable bases were extracted with

neutral ammonium acetate solution buffered at

pH 7, Na and K in the extracts were

determined using flame photometer while Ca

and Mg were determined by Atomic

Absorption Spectrophotometer (AAS) (Page

et al., 1982). Organic matter was determined

by wet acid digestion (Walkey and Black,

1934). Total Nitrogen by the Kjeldahl

digestion method, phosphorus by Bray -1

procedure (Bray and Kutz 1945). Particle size

analysis by the hydrometer method

(Bouyoucos, 1951).

Four extractants were evaluated for the

determination of available Sulphur. These

were distilled water, 0.016 M KH2PO4, 0.10

Ca(HPO4)2 and 0.10M LiCl. Each extractant

was employed for the extraction of available

sulphur in all the samples.

Water soluble sulphur or solution sulphur was

extracted in distilled water and determined

turbidimetrically as BaSO4. Surface adsorbed

sulphur was estimated as the difference

between available sulphur and water-soluble

sulphur. Total soil sulphur was determined by

digesting the Samples using wet acid digestion

(Page et al., 1982). Activated charcoal, 0.05g

per 25cm3 of the extracts and or digest was

used for decolourising the extracts and digests,

while gelatin was used as a stabilizer. Sulphur

in the extracts and digests was determined

turbimetrically as BaSO4 (Adetunji, 1989).

The crop was grown in the pots and harvested

after 12 weeks. 4 kg of the sieved soils was

weighed into experimental pots. The

treatments were 0, 10, 20 and 30 kg S ha-1 and

the pots were arranged in a randomized

complete block design. The treatments were

replicated four times. Nitrogen was added as

urea at the rate of 40 kg ha-1, P as KH2PO4 at

the rate of 30 kg ha-1. K was applied as MOP

in the 0 kg S ha-1 to make up the rate of 30kg

ha-1 (Yusuf and Idowu, 2001) as the P and S

sources (KH2PO4 and K2SO4 respectively)

were expected to have met the K requirements

in the 10kg S ha-1 to 30 kg S ha-1 treatments.

Agronomic data collected included the

following:

a. Dry matter yield at harvest (12 WAP).

b. Number of pods per plant per pot at

harvest.

c. pod weight at harvest.

115

Bamgba and Adetunji NJSS/22(1)/2012

Eight farmers’ fields cultivated with groundnut

as sole crop were selected. On each farmer’s

farm, an area of land covering 5m x 5m was

measured out. Soil samples were taken from

that measured area. Yield of groundnut from

that area was collected and weighed. The soil

samples taken from these areas were analyzed

for available sulphur using the four extractants

(above).Average plant population per plot was

52. The sulphur values were then correlated

with the yield of groundnuts.

DATA ANALYSIS

Correlation analysis was carried out. The

amount of available sulphur extracted by the

four extractants was correlated with the

groundnut yield with the aim of determining

the best extractant for the determination of

available sulphur in the soils under study. Data

were also subjected to analysis of variance and

means separated by the Duncan Multiple

Range Test.

RESULTS

Soil Properties

The properties of the soils used in the pot

experiment are shown in Table 1. The pH

values ranged from 5.29 at Abinsi to 6.82 at

Gbatse with a mean value of 5.85. The soils

are sand, loamy sand and sandy loam in

texture. Organic matter content varied widely

from 0.70% at Tyowanye to 3.21% at Abinsi

with a mean value of 1.98%. Available P

(Bray – 1) values ranged from 3.20 in Gbatse

to 12.90 at Adaka. Total nitrogen ranged from

0.025% at Ikpayongo to 0.14% at Abinsi.

Exchangeable acidity ranged from 0.20 c mol

kg-1 at Abinsi to 1.20 c mol kg-1 at Makurdi.

Table 2 shows the yield data in the pot

experiment. This indicates that in all the yield

parameters, Adaka soil performed better. This

is followed by Ikpayongo in terms of pod yield

and number. Tyowanye soil produced the

poorest yield in all the parameters studied.

Table 3 shows the yield of groundnut on the

farmers’ plots. The yield ranged from 300 k

gha-1 (0.30 t ha-1) at Tyowanye to 920 kg ha-1

(0.92 t ha-1) at Ikpayongo. Adaka has 880 kg

ha-1 (0.88 t ha-1), Abinsi 800 kg ha-1 (0.80 t ha-

1). Makurdi and Gbatse had 560 kg ha-1 (0.56 t

ha-1), Yandev had 480 kg ha-1 (0.48 t ha-1),

while Tsemker had 320 kg ha-1 (0.32 t ha-1).

116


Table 1: Some Properties of the Experimental Soils

% mg kg-1 K Na Ca Mg Exch. ECEC Acidity

Abinsi

Adaka

Ikpayongo

Tyowanye

Yandev

Gbatse

Tse-mker

Makurdi

5.29

6.10

5.70

5.67

5.77

6.82

5.83

5.63

10.00

12.00

10.04

6.48

4.60

6.88

6.48

11.04

3.21

3.55

1.55

0.70

1.04

1.90

1.73

2.14

0.140

0.087

0.025

0.053

0.084

0.062

0.115

0.056

11.20

12.90

3.80

7.30

9.00

3.20

4.60

6.50

SL

SL

SL

S

S

LS

S

SL

0.31

0.42

0.46

0.37

0.35

0.52

0.51

0.40

0.24

0.22

0.29

0.23

0.19

0.21

0.25

0.21

4.4

6.1

6.4

1.8

4.0

7.2

8.7

3.2

2.2

2.6

4.4

1.6

2.2

3.4

4.2

2.8

1.00

0.20

0.60

0.80

0.40

0.80

0.80

1.20

8.15

9.54

12.05

4.8

7.14

12.13

14.46

7.81

* SL Sandy Loam.S - Sand LS - Loamy Sand

117


Table 2: Yield data in the pot experiment (g pot-1)

S/No. Location Pod Yield Dry matter yield Pod number per plant

1.

2

3.

4.

5.

6.

7.

8.

Abinsi

Adaka

Ikpayongo

Tyowanye

Yandev

Gbatse

Tse-mker

Makurdi

21.40c

38.09a

23.42b

11.57h

13.26g

14.63f

15.88e

19.78d

13.87b

18.24a

9.88c

10.1c

11.65d

13.75b

11.82d

13.00c

8.27a

8.92a

8.29a

5.70b

5.84b

6.47b

6.06b

7.93a

Within each parameter, means with the same letters are not significantly different according to

DMRT.

Table 3: Yield Data On Farmers’ Field

Location Yield (kg plot-1) Yield (kg ha-1) Yield (t ha-1)

Yandev

Tyowanye

Abinsi

Ikpayongo

Makurdi

Tsemker

Adaka

Gbatse

1.20

0.75

2.00

2.30

1.40

0.60

2.20

1.40

480

300

800

920

560

320

880

560

0.48

03.0

0.80

0.92

0.56

0.32

0.88

0.56

Evaluation of Extractants for Sulphur In

The Experimental Soils

Table 4 shows that Water extracted 12 mg kg-1

of sulphur from Makurdi soil. This was the

highest amount extracted by this extractant

from the experimental soils. This was followed

by Adaka (8.0 mg kg-1). Yandev had (7.0 mg

kg-1), Ikpayongo and Gbatse 6.0 mg kg-1,

Tsemker 5 mg kg-1, Tyowanye 4 mg kg-1 while

the least amount of 3 mg kg-1 was extracted

from Abinsi soil.0.016 M KH2PO4 extractable

sulphur was highest (11 mg kg-1) in

Tyowanye. This was followed by Adaka (6 mg

kg-1), Gbatse and Tsemker soils. 4.0 mg kg-1

was extracted from Abinsi and Ikpayongo

soils. The least amount of 2 mg kg-1 was

extracted from Yandev and Makurdi

soils.O.010M Ca(HPO4)2 extracted the highest

amount of sulphur (10 mg kg-1) from Gbatse.

This was followed by 8.0 mg kg-1from Abinsi,

Adaka and Tsemker soils. 7.0 mg kg-1 was

extracted from Ikpayongo, Makurdi 6.0 mg kg-

1, Tyowanye 4.0 mg kg-1 and 2.0 mg kg-1 from

Yandev. This was the least amount of sulphur

extracted by this extractant. 0.10 M LiCl

extracted the highest amount of 18 mg kg-1

from Adaka, this was followed by 13.0 mg kg-

1 from Ikpayongo, 10.0 mg kg-1 from Abinsi,

Makurdi 8.0 mg kg-1 Yandev, Gbatse and

Tsemker 6.0 mg Kg-1 each while the least

amount of 2 mg Kg -1 was extracted from

Tyowanye.

The value of Sulphur extracted by the four

extractants from the farmers’ plots indicates

that the soils are generally low in their sulphur

status (table 5). Water extracted the highest

amount of 12 mg kg-1 from Tsemker. The

least amount of 1.0 mg kg-1 was extracted

from Abinsi.

0.016 M KH2PO4 extracted the highest amount

of 18.0 mg kg-1 from Ikpayongo, 0.10 M Ca

(HPO4) 2 extracted 14.0 mg kg-1 from Yandev,

while the least amount of 4.0 mg kg-1 was

118


extracted by this extractant from Abinsi.0.10

M LiCl extracted 18.0mg kg-1 from Adaka, the

least amount of 2.0 mg kg-1 was extracted

from Tyowanye.

Table 6 shows that only the LiCl extractable S

correlated positively and significantly with the

fresh weight of pods and the pod number.

Table 7; again shows that only the LiCl

extractable sulphur correlated positively and

significantly with the yield parameters studied.

Table 4: Values of Sulphur Extracted by the Extractants (Mg kg-1) In The

Experimental Soils

Extractants

Location Water 0.016M

KH2PO4

0.01M

Ca(HPO4)2

O.10M

LiCL

Abinsi

Adaka

Ikpayongo

Tyowanye

Yandev

Gbatse

Tse-mker

Makurdi

Mean

3.0

8.0

6.0

4.0

7.0

6.0

5.0

12.0

6.4

4.0

6.0

4.0

11.0

2.0

6.0

6.0

2.0

5.1

8.0

8.0

7.0

4.0

2.0

10.0

8.0

6.0

6.6

10.0

18.0

13.0

2.0

6.0

6.0

6.0

8.0

8.6

Table 5: Evaluation of Extractants for Sulphur On Farmers’ Field

Location Water 0.016M

KH2PO4

0.01M

Ca(HPO4)2

O.10M

LiCl

Yandev

Tyowanye

Abinsi

Ikpayongo

Makurdi

Tse-mker

Adaka

Gbatse

Mean

6

10

1

2

2

12

2

2

4.63

2

3

1

18

3

1

3

8

4.88

14

13

4

7

11

6

9

6

8.63

6.0

2.0

10.0

13.0

8.0

6.0

18.0

6.0

7.38

Table 6: Correlation table for the four Extractants under Evaluation and Groundnut yield

in the Pot Experiment

r-values

Parameter Distilled water KH2PO4 Ca(HPO4)2 LiCl

Pod yield

Dry matter yield

No. of pods per plant

0.277

0.273

0.266

-0.149

-0.099

-0.357

0.380

0.459

0.429

0.964**

0.648

0.886**

** Correlation is significant at 1%

*Correlation is significant at 5%

119


Table 7: Correlation table for the four Extractants under Evaluation and Groundnut yield

on farmers’ fields

r-values

Parameter Distilled water KH2PO4 Ca(HPO4)2 LiCl

Pod yield -0.777 0.500 -0.419 0.967**

** Correlation is significant at 1%

*Correlation is significant at 5%

DISCUSSION

The sulphur values of the experimental soils

indicated that Adaka soil had the highest S

status with total S value at 129.0 mg kg-1,

while Tyowanye had the least value of 48.0mg

kg-1. The amount of S extracted by the

extractants under evaluation showed that LiCl

extracted the highest amount from Adaka,

Ikpayongo and Abinsi, the extracted values by

the other extractants from these soils were

lower. The LiCl extractable S values followed

the same trend with the total S values of the

soils. Interestingly, the values of S extracted

by LiCl from the other locations were lower

compared to these three above, unlike the

other extractants that extracted significantly

higher amounts from locations other than these

three. Also, among the experimental soils,

Tyowanye had the least total S status of 48.0

mg kg-1 ,LiCl, again extracted the least

amount of 2.0 mg kg-1 from this soil. The total

S values of the soils also indicated that,

Yandev, Gbatse and Tse-mker had the same S

status; the LiCl extractable values also gave

the same results. Water extractable S values

for these soils are in a progressively

decreasing order. Yield data in terms of pod

yield showed that the highest pod yield was

obtained in Ikpayongo soil at 20 kg s ha-1.

However on the average Adaka had the

highest mean yield. Tyowanye and Yandev

gave yield values that were significantly lower

than the other soils. Dry matter yield was also

highest at Adaka (20 kg s ha-1), the least yield

at that S level was again obtained at Tyowanye

and Yandev following the same trend with the

total S status and the LiCl extractable S. The

extractable S values from the farmers’ plots

followed the same trend. Correlating the

extractable S values and yield shows that only

the LiCl extractable S correlated positively and

significantly with pod yield and number at

harvest. There was also positive and

significant relationship between LiCl

extractable S and total S content of the soils.

CONCLUSION

Since the LiCl extractable S correlated most

significantly both the total S values of the soils

as well as the yield parameters of the test crop,

LiCl can thus be referred to as the best

extractant for available S in these soils. The

LiCl extractable S can also be referred to as

the available S in these soils. REFERENCES

Adetunji M.T (1989). Effect of post sampling

treatments on the turbimetric

determination of available sulphur in

the soil. Nigeria Journal of Agronomy

4: (3): 1-7

Adetunji M.T and Adepetu J.A (1987).

Sulphur sorption characteristics of soils

in South Western Nigeria. Nigeria

Journal of Soil Science. 7: 63-65.

Beaton J.D, Burns, G.R and Platou J. 1968.

Determination of sulphur in soils and

plants material. Technical bulletin (14).

The sulphur institute, Washington D.C

pp.56.

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Bouyoucos,G.H.(1975) A recalibration of the

hydrometer for testing mechanical

analysis of soils.Agricultural Journal.

43:434 –438.

Bray R.H and L.T.Kutz (1945). Determination

of total, organic and available forms of

phosphorus in soils. Soil Science. 59 :

45-59

Federal Department of Agricultural Land

Resources (1990). Soils Report 4: 70-

221

Jones M.B. (1986) Sulphur availability

indexes. In: Sulphur in Agriculture

M.A. Tabatabai ed. Agronomy 27:

American Society of Agronomy,

Madison W.I. pp 549-566.

Kang B.T. Okoro E.Acquaye D.and Osiname

O.A. (1981) Sulphur status of some

Nigerian soils from the savannah and

forest zones. Soil Science. 132(1): 220-

227.

Kilmer V.J. and Nearpass D.C. (1960) The

determination of available sulphur in

soils. Soil Science and Plant Analysis

16:289-300.

Metson A.J. (1979) Sulphur in New Zealand

soils I.A. review of sulphur in soils

with particular reference to adsorbed

sulphate sulphur. New Zealand Journal

on Agricultural Research. 22:95-114.

Nelson R.E. (1982) Carbonate and gypsum. In

A.L. page R.H Miller and D.R. Keeny

Eds. Methods of soil analysis. Part 2.

Chemical and microbiological

properties Agronomy No. 9. America

Society of Agronomy. Madison, W.I.

pp 181-197.

Obasi M.N., Isirimah N.O. and Ikpe F.N

(2001) A preliminary study on the

response of maize to sulphur

application in selected soil parent

materials in South Eastern Nigeria. In

proceedings of the 35th Annual

Conference of the Agricultural Society

of Nigeria September 16-20, 2001. Pp

155-159.

Page A.L. Ed. (1982). Methods of soil analysis

Part 2: Chemical and microbiological

properties 2nd ed. Agricultural Science

Society of America, Madison Pp 502-

537.

Roberts, T.I. and Bettany J.R. (1985). The

influence of topography on the nature

and distribution of Soil Sulphur across

a narrow environmental gradient.

Canadian Journal of Soil Sciences 65:

419-434.

Walkey, A. and Black I.A. (1934). An

examination of the degtjareff methods


proposed modification of the chromic

acid organic titration method. Soil

Science. 37:29-38.

Yusuf I.A. and Idowu A.A. (2001) NPK

requirement for soybean production in

the Southern Guinea Savannah.

Tropical Oil Seeds Journal 6:50-56.

121


EVALUATION OF NUTRIENT RESTORATIVE ABILITY OF SOME SELECTED

CROP AND SOIL MANAGEMENT PRACTICES IN MAKURDI, SOUTHERN GUINEA

SAVANNA, NIGERIA

AGBER, P.I.1 AND M.E. OBI2 1Department Soil Science, College of Agronomy, University of of Agriculture Makurdi

2Department of Soil Science, University of Nigeria Nnsuka


ABSTRACT Field experiments were carried out at the Teaching and Research Farm of the University of Agriculture, Makurdi Southern Guinea Savanna, during 2007 and 2008 cropping seasons to evaluate the nutrient restorative ability of some selected crop and soil management practices on soil productivity and yield of maize. The experiment was laid out in randomized complete block design (RCBD) arranged in a split-plot with four levels of crop and soil management practices including no fertilizer (control), NPK (300kg/ha), NPK (300kg/ha) + poultry manure (PM) (5 t/ha) and NPK (300 kg/ha) + Cow dung (CD) (5t/ha) and two tillage practices (no tillage and 30 cm raised seed bed) and replicated four times. The study used the percentage change in post harvest nitrogen content to develop an index of restorative ratings. Results of the study showed that the plots amended with NPK + PM gave higher seed yield of Maize (4 6t/ha) and higher left over N of 93.6 kg and 109/2 kg for 2007 and 2008 respectively. The highest P1 rating of +9.0 was also obtained from the same plot. The index developed could help farmers to predict the depletive or restorative effect of certain crop and soil management practices. Key words: Poultry manure, cow dung, maize, productivity index. All correspondence to (1)

INTRODUCTION Most soils of Nigeria are dominated by low activity clay minerals that are strongly weathered with low nutrient status (Ano, 1990). Bationo and Mokwunye (1991) also reported that the soils of the tropics are low in fertility. Tropical soils can not supply the quantities of nutrients required and yield levels decline rapidly once croping commences. Soil degradation and nutrient depletion have

become serious threats to agricultural productivity in Nigeria. In solving the infertility problem of tropical soils, traditional African farmers engaged in shifting cultivation. However, the demand for more land arising from increase in population pressure had led to a decrease in or complete disappearance of fallow periods. Continuous cultivation leads to reductions in organic matter and soil productivity. Other efforts

122

Crop and soil management practices in Makurdi

developed to restore and improve the productivity of these soils include crop rotations, intercropping, fertilization and organic manuring, mulching and agro forestry (Adekunle et al., 2004). The need for improved management practices, especially through the use of external inputs from organic and inorganic sources on these soils has been stressed (Busari et al., 2004). Complimentary use of organic and mineral fertilizer has proved a sound soil fertility management strategy in many countries of the world (Busari et al., 2004, Adeniyan and Ojeniyi 2005). The practice has a greater beneficial residual effect than can be derived from the use of either inorganic fertilizer or organic manure when applied alone (Makinde et al., 2001, Adekunle et al., 2004). Cultivation practices play a major role in nutrients and water sustainability. They are needed to increase agronomic stability and productivity while enhancing the environment (Hatfield et al., 1999). Therefore, complementary use of organic and inorganic fertlizer combines with appropriate cultivation practice becomes inevitable in fertility restoration in the tropical soils. This work was; therefore, designed to evaluate the efficacy of different crop and soil management practices on soil fertility restoration and growth and yield of maize.

MATERIALS AND METHODS Experiment was carried out during the 2007 and 2008 cropping seasons at the Teaching and Research farm of University of Agriculture Makurdi; in the southern Guinea savanna zone of Nigeria. A total land area of 23 m x 43.5 m (1000.5 m2) was used. The experimental design was a split – plot in a randomized complete block design with two tillage techniques and four management practices replicated four times. The tillage techniques served as the main plots while the management practices (soil amendments) as the sub plots treatment. The treatment, factors and rates are as follows:

Tillage techniques - Tno = No tillage - T30 = 30 cm till – raised seed bed The crop management practices - Mno = Maize + no soil amendments - Mnpk = Maize + NPK fertilizer (300 kg/ha) - Mnpk + PM = Maize + NPK fertilizer (300 kg/ha) + poultry manure (5t/ha) - Mnpk + CD = Maize + NKP fertilizer (300 kg/ha) + cow dung (5t/ha) The animal waste: cow dung and poultry manure were evenly spread on appropriate plots and worked into the soil during tillage. The amendments were allowed to decompose 14 days before planting the test crop (maize). The initial chemical properties of the soil were determined from bulked composite samples before planting. At harvest, soil samples were taken from each plot at 0 – 15cm depth, air dried and passed through 3mm sieve. Thereafter, the following soil chemical properties were determined. The soil pH was determined in water and 0.1N KCl using the method described by MacLean (1982). Organic carbon by Walkley and Black (1934), total N by the macro – Kjeidahl digestion (Bremmer, 1965), available P by Bray and Kurtz no. 1 method (1945). The cations were extracted using ammonium acetate and K was evaluated using flame photometer, and Ca and Mg by atomic absorption spectrophotometer (Juo, 1979). Soil productivity index calculation was formulated in terms of percentage changes in N content (Cook, 1962). The percentage change in N was used to determine the index of productivity for forecasting the effect of each management practice on soil productivity. Plant height, stem growth and leaf area index were taken at 9 WAP. Maize grain yield was determined at harvest. Data on soil N, growth parameters and seed yield were analyzed using correlation, regression and analysis of variance (F – test) to determine treatment effect. Means

123

Agber and Obi NJSS/22(1)/2012

were separated using the LSD technique at 5% level.

RESULTS AND DISCUSSION Soil properties of the site and chemical analysis of poultry manure and cow dung

used for the experiment The soil used for the experiment was low in organic matter. N, P and K and cation exchange capacity (table 1). Thus, the soil used was typical of upland soils in the tropics particularly Alfisols (Sanchez and Logan 1992). The low organic matter obtained may be partly due the effect of high temperature and relative humidity which facilitate rapid mineralization of organic matter. The soil has very low CEC reflecting intensely weathered status. The low CEC, low organic matter, and low total N are indicators of low inherent fertility status, which underscore the need for improved soil management techniques. The N and available P of the poultry manure were higher than that of the cow dung (Table 1). Cow dung however, contained higher K, Ca and Mg. If adequately applied, poultry manure contains reasonable amount of N that will raise the productivity of the soil and increase the yield of maize. Effect of crop and soil management

practices on growth and yield of maize The main effect of crop and soil management practices on mean leaf area index (LAI), stem growth, plant height and seed yield for 2007 and 2008 is presented in Table 2. Result of the

study show that fertilizer application significantly (P < 0.001) increased LA1, stem growth, plant height and seed yield. Cumulative results show that maize plots amended with NPK + PM had 81%, 53%, 83% and 232% increases in LA1, stem growth, plant height and seed yield respectively. This may be as a result of the combined beneficial effects of poultry manure and NKP fertilizer which make available nutrients especially nitrogen and organic matter for enhanced crop growth and higher grain yield. Higher grain yield resulting from the application of manurial treatments has been reported from other studies (Ojeniyi 2000, Ojeniyi and Adejobi 2002, Adeniyan and Ojeniyi 2005)/ Similarly, results of the study also show significant (P < 001) effects of tillage practices on LA1, stem growth, plant height and seed yield (Table 2). The tilled plots had 32%, 19%, 23% and 67% increases in LA1, stem growth, plant height and seed yield respectively relative to the no till plots. The improvement in soil physical properties following application of NKP + PM could have enhanced root proliferation, shoot growth and eventual seed yield. Upawansa (1997) earlier reported improvement in soil fertility exceeding expectations in an integrated system, probably because of combined effect of soil conservation, nutrient enrichment, enhancement of biological activities and improvement in moisture retention capacity.

Table 1: Chemical analysis of Poultry Manure and Cow dung used for the Experiment

Parameters Soil PM CD

Nitrogen (g kg-1) Organic matter (g kg-1) Phosphorus (g kg-1) Potassium (g kg-1) Calcium (g kg-1) Magnesium (g kg-1) CEC (g kg-1)

0.20 0.50 6.20 6.22 2.50 2.50 7.50

4.48 -

1.98 1.53 7.63 0.39

-

3.12 -

0.35 13.99 8.6 5.63

-

PM = Poultry manure CD = Cow dung

124


Table 2: Mean effect of crop and soil management practices on maize growth parameters

and seed yield

Treatment

Fertilizer

LA1 Plant Height

(cm)

Stem growth

(cm)

Seed yield

(t/ha)

Control

NPK

NPK + CD

NPK + PM

LSD

Tillage Practices

Tno

T30

LSD

0.09

0.11

0.23

0.19

0.01

0.14

0.17

0.01

26.1

26.5

49.9

96.5

9.75

43.2

56.2

6.80

5.0

5.4

6.3

7.4

0.47

5.7

6.3

0.33

1.27

2.98

3.57

4.22

0.39

2.41

3.80

0.28

Quantifying the effect of crop and soil

management practices on soil productivity The pre-cropping N, added N and post harvest

N contents from the experiment are presented

in Table 3. Results of the findings showed that

the initial (pre-cropping) N for all the plots

was 936 kg/ha. Prior to planting in each

season, plots amended with NPK, NPK + CD

and NPK + PM received 45 kg/ha, 60.6 kg/ha

and 67.4 kg N/ha respectively. The highest

value of post harvest soil N content was found

in plots amended with NPK + PM while the

lowest post harvest N value was found in

unamended plots.

Results of annual “left over N” for each crop

and soil management practices for 2007 and

2008 cropping seasons are presented in Table

4. The results show that the lowest “left over

N” was found in unamended plots while the

highest “left over N” was found in the plots

amended with NPK + P in the two cropping

seasons. Unamended plots had annual loss of

62.4 kg N/ha and 46.8 kg N/ha in 2007 and

2008 respectively. The maize plots amended

with NPK alone had identical loss of 31.2 kg

N/ha in both 2007 and 2008. The “left over N”

however, increase from the plots amended

with NPK + CD and NPK + PM. The increase

in “left over N” for NPK + CD plots was 31.2

kg N/ha and 46 kg N/ha for 2007 and 2008

respectively. Similarly, the increase in “left

over N” for plots amended with NPK + P were

93.6 kg N/ha and 109.2 kg N/ha for 2007 and

2008 respectively. A significant relationship

between soil post harvest N content and seed

yield was observed (table 5). This showed that

the soil amendments applied could deplete or

restore the fertility of the soil differently.

Table 3: Pre-cropping N, added N and post harvest soil N content (kg/ha) for crop and soil

management practices during the 2007 and 2008 planting seasons

Crop management

Practices

Pre-cropping

N + added N

Post harvest

N + added N

Post

Harvest N

Control (unamended)

NPK

NPK + CD

NPK + PM

LSD

936 + 0

936 + 45

936 + 60.6

936 + 67.4

873.6 + 0

904.8 + 45

967.2 + 60.6

1029.6 + 67.4

0.1847

826.8

873.6

1014

1138.8

0.0462

NB: The top soil (0 – 10 cm) of the study area has a weight of 1.56 x 106 kg/ha thickness of 10

cm and bulk density of 1.56 g/cm3. Therefore:

124


N kg/ha = N (%) x 1,560,000

100 1

Table 4: Mean annual “left over N” (kg/ha) for crop and soil management practices

Crop management

Practices

(N kg/ha)

2007 2008

Control (unamended)

NPK

NPK + CD

NPK + PM

- 62.4

- 31.2

+ 31.2

+ 93.6

- 46.8

- 31.2

+ 46.8

+ 109.2

NB: (1) pre-cropping N – post harvest N 2007 = left over N 2007

(2) post havest N 2007 – post harvest N 2008 = left over N 2008

Table 5: Relationship between seed yield (y) and post harvest soil nitrogen (N) content (X)

Dependent

Parameter

Year Regression

Model

Coefficient of

Determination

Maize

Seed

Yield

2007

2008

Y = -12.81 + 0.824(x)

Y = -7.230 + 0.892(x)

0.84**

0.90**

Table 6: Percent change in post harvest N and seed yield of maize under different

management practices

Crop management

Practices

Percentage change in N Percentage change

in seed yield 2007 2008

Control

(Unamended)

NPK

NPK + CD

NPK + PM

- 7.1

- 3.4

+ 3.2

+ 9.1

- 5.7

- 3.6

+ 4.6

+ 9.6

- 13.3

- 5.3

+ 8.1

+ 13

Soil productivity index (P1) for estimating

safe or unsafe cropping systems The percentages changes in N content in

relation to the changes in crop seed yield under

the different crop and soil management

practices presented in Table 6 were used to

develop an index of productivity rating (P1) to

be used by farmers to calculate safe or unsafe

cropping systems. The ascribed productivity

index ratings are presented in Table 7. The

productivity indexes were derived directly as

the mean of percentage change in nitrogen

between 2007 and 2008 cropping seasons.

Results of the study as presented in Table 7

show that the plots amended with NPK + PM

had the highest rating (+9.0). This was closely

followed by plots amended with NPK + CD

with the rating of + 4.0. The unamended plots

had the lowest rating of + 6.0. The results

obtained show that the crop and soil

management practice with P1 of +9.0 is better

than all the other practices with lower P1

values. This P1 can help farmers to compare

the productivity of soils of different sites. It

will also help farmers to predict the depletive

or restorative effect of certain crop and soil

management practices.

125


Table 7: Soil productivity ratings for four management practices

Management practice Productivity index (P1)

Control (unamended)

NPK

NPK + CD

NPK + PM

- 6.0

- 4.0

+ 4.0

+ 9.0

NB: Ascribed productivity index (P1) was

derived directly from the percent N change in

each year for each management practice and is

defined as average annual percent change in

soil post harvest nitrogen content.

Calculation of safe or unsafe cropping

system In Table 8, a hypothetical four year cropping

programme was used to illustrate the use of

this productivity index (P1) for selected crop

and soil management practices. This

illustration would determine whether

productivity would increase or decrease in the

different cropping systems adopted (Table 8).

The soil producivity ratings derived from the

percent change in nitrogen in each year for

each management practice were used in

calculating whether the cropping systems were

safe or unsafe. An assumed four hectares of

farm land was used. In the four hectares, each

hectare had different management practices for

four years. The total productivity index (P1) at

the end of each year was calculated (Table 9).

Table 8: Hypothetical four year cropping programme using different crop and soil

management practices

Plot/Year 1 2 3 4

1 Maize

+

NPK

Maize

+

NPK + CD

Maize

+

NPK + PM

Maize

+

NA

2 Maize

+

NPK + PM

Maize

+

NPK

Maize

+

NPK

Maize

+

Na

3 Maize

+

NPK + CD

Maize

+

NPK + PM

Maize

+

NA

Maize

+

NPK

4 Maize

+

NPK + PM

Maize

+

NPK + CD

Maize

+

NPK

Maize

+

NPK

NA = No amendment

CD = Cow dung

PD = Poultry droppings

Table 9: Calculated productivity index for the crop and soil management practices

Plot/Year 1 2 3 4

1

2

3

4

- 4

+ 9

+ 4

+ 9

+ 4

- 4

+ 9

+ 4

+ 4

- 4

+ 9

+ 4

- 6

- 6

- 4

- 4

126


CONCLUSION The study revealed that the crop and soil

management practices adopted were efficient

in soil productivity improvement. This P1 can

help farmers to compare the productivity of

soils of diffeent sites. It will also help farmers

to predict the depletive or restorative effect of

certain crop and soil management practices.

REFERENCES Adekunle I.O., O.E. Akinrinade and J.O.

Azeez (2004). Influence of the

combined application of cattle manure

and NPK fertilizer on soil chemical

properties, growth and yield of okro in

an conference of the Soil Science

Society of Nigeria held at the

University of Agriculture, Abeokuta

Nigeria between December 6-10, 2004.

Adeniyan, O.N. and S.O. Ojeniyi (2005).

Effect of poultry manure, NPK

15:15:15 and combination of their

reduced levels on maize growth and

soil chemical properties. Nig. J. Soil

Sci. 15: 34-41.

Ano, A.O. (1990). Potassium fixation,

speciation, distribution and exchange

thermodynamics in soils of eastern

Nigeria. Ph.D thesis, University of

Ibadan, Nigeria.

Bationo, A. and Mokwunye, A.U. (1991). Role

of crop manure and crop residue in

alleviating soil fertility constraints to

crop production with special reference

to saharian and Sudanian zones of

West Africa. Fertilizer Research, 29:

17-175

Bray, R.H. and L.T. Kurtz (1945).

Determination of total organic and

available form of P in soil, Soil Sci. 59:

39-45.

Bremmer, J.M. (1965). Nitrogen availability

indexes. In C.A. Black (ed). Methods

of soil analysis part 2. Agronomy

madison Wisconsin

Busaic, M.A., I.O. Adekunle and J.O. Azeez

2004. Effect of poultry manure and

phosphorus application on the

productivity and fodder quality of two

centrosenia species in an Alfisol.

Proceeding of the 29th Annual

Conference of the Soil Science Society

of Nigeria December 6-10, 2004 at the

University of Agriculture Abeokuta,

Nigeria.

Cook, R.L. (1962). Fitting Crops to Soils. Soil

Management for Conservation and

Production. Macmillan Publishers.

Hatfield, J.I., R.R. Allmaras, G.W. Relm and

B. Lowrey (1999). Ridge tillage for

corn and soybean production.

Environmental Quality impacts. Soil

and Tillage Research 48: 145-154.

Juo, A.S.R. (1979). Selected methods of soil

and plant Analysis. IITA manual

series. No. 1. Ibadan Nigeria.

Mclean, E.O. (1982). Soil pH and Lime

requirements in page A.L. (ed).

Methods of soil analysis. Part 2.

Chemical and Microbiological

properties second ed. Agronomy series

No. 9 ASA Madison, W.J., USA.

Odofin, A.J. (2005). Effects of No-tillage with

much on soil hydrology Minna area of

Nigerias Southern Guinea savanna.

Nigerian Journal of Soil Science 15(2):

9-15.

127


Ojeniyi, S.O. and K.B. Adejobi (2002). Effect

of ash and goat dung manure on

nutrient composition, growth and yield

of Amaranthus. Nig. Agricultural

Journal 33: 46-57.

Ojeniyi, S.O. (2000). Effects of goat manure

on soil nutrients content and okra yield

in rainforest area of Nigeria. Applied

Tropical Agriculture 50: 20-23.

Sanches. P.A. and Logan, T.J. (1992). Myths

and science about the chemistry and

fertility of soil in the tropics. Soil Sci.

Soc. of American and American

Society of Agronomy. 667 Segde Rd.

Madison. Wis 53711, USA. SSA.

Special publication, No. 29 pp 35-45.

Upawansa, G.K. (1997). New kekulan rice

cultivation: a practical and scientific

ecological approach. Rebuilding lost

soil fertility. LEISA. ILEIA Newsletter

13 No. Leusden, Netherlands pp.

Walkley, A. and Black (1934). An

examination of the degtiareff method


a proposed modification of the chronic

Acid Titration method. Soil Sci. 37:

29-38.

128


SHEAR STRENGTH AND COMPACTION CHARACTERISTICS OF

TERMITE MOUND SOIL (TMS)

MANUWA, S.I. AND OLAWOLU, O.E Department of Agricultural Engineering, The Federal University of Technology,

PMB 704, Akure, Nigeria


ABSTRACT Termite mounds are common features of agricultural landscape of the tropical regions of the

world, however published scientific research on TMS in relation to surrounding soil and possible

potential of TMS in agricultural production are scarce. The purpose of this study was to

investigate effect of moisture content on compaction and shear strength of TMS with a view to

comparing it with the surrounding. Standard laboratory methods were used to evaluate physical,

chemical and strength properties of sampled termite mound soils and their surrounding soils.

Results showed that the texture of a TMS varied from top to bottom of the mound and from that

of the surrounding soil (R). There was less organic matter, organic carbon, and nitrogen in the

TMS than in the R, however, there was higher phosphorus, calcium, potassium, magnesium and

sodium. Similarly, consistency (Atterberg) limits of TMS were significantly higher than those of

surrounding soils at 5% level of significance. Mean shear strength (cohesion) of TMS was higher

than that of the R. The shear strength ranged between 63.11 and 120.11 kPa for experimental

TMS while for the R it was between 40.52 and 72.46 kPa. The maximum shear strength of

compacted (15 blows) TMS was 195 kPa at 12% (db) moisture content. The results of this study

will be useful in characterizing TMS in relation to surrounding soil and also for assessing

potential uses of TMS in agricultural production.

Keywords: termite mound soil, surrounding soil, properties, compaction, shear strength.

INTRODUCTION Termites have been identified as common

biological agents that produce significant

physical and chemical modifications to

tropical and subtropical soils (Semhi et al.,

2008).

It has been reported that termites go through a

sequence of actions, from fetching, carrying,

to cementing mineral particles into mounds by

using their salivery secretion (Lopez-

Hernandez et al., 2001). Also, it has been

shown that termite activity increases the

content of organic matter in the soils that they

use for the construction of their nests and also

modifies the clay mineral composition of these

soil materials (Jouquet et al., 2002; Roose

Amsaleg et al., 2004).

Studies emphasized the role of termine on soil

texture and chemical properties (Wood et al.,

128

Characteristics of termite mound soil

1983), soil nutrient cycling and soil

metabolism (Menaut et al., 1985; Abbadie and

Lepage, 1989). But the strength properties of

termite mound soil are scarce in literature.

It was reported (Rupela et al., 2006) that

African, farmers collect termite-mound soil

and apply to cropped fields (Watson 1977) as

it can be rich in available nitrogen (by about

20%), total P (by 2.25 times) and organic

carbon (by 9.3%) than adjacent soil (Lopez-

Hernandez, 2001).

In the Southern Province of Zambia soils with

low water retention capacity are common, so

when termite mound soil is spread on these

soils it results in higher soil moisture content

and improved crop growth (Siame, 2005).

Literature also shows that termite mound soils

have high levels of calcium, phosphorus and

organic matter, which contribute to better crop

development, especially on the poor soils in

the area. Plants were also reported to take up

nutrients very easily from termite mound soil

and that TMS is proving a viable option to

local farmers (Fageria and Baligar, 2004).

Soil from Macrotermes (termite) spp mounds

has lower soil organic matter (SOM) content

that adjacent soil (Garnier-Sillam et al., 1988).

However, the study reported by Jouquet et al

(2003), Abbadie and Lepage (1989) showed

that structures built by subterranean fungus-

growing termite Ancistrotermes contained

greater amount of SOM than adjacent soil.

Therefore the objectives of this study were to

(i) determine the relative physical and

chemical properties and shear strength of TMS

and surrounding soil; and (ii) determining the

influence of moisture content on the shear

strength at different levels of compaction.


Study Site The study was carried out within the campus

of The Federal University of Technology,

Akure, Nigeria (70 151N, 50 151E). The mean

annual precipitations in the area ranged from

130 to 150 mm with average relative humidity

(80%). The climate consists a long wet season

from mid March to July, short dry season

(August break) July to August, short wet

season September to November and long dry

season from November to Mid March. The

vegetation is tropical rain forest.

Soil description and sampling Soil samples were collected from three

different termite mounds and surrounding soil

(3.0 m away from each mound). Soil sample

taken from the surrounding soil served as the

control within the study area. Two samples

were taken from each mound, at the top (T),

the base (B) and the third sample from the

surrounding soil (R). The three termite

mounds were termed A, B and C. Soil sample

was represented by S, so that SAB represents

soil sample of termite mound A, bottom

position and so on. The termite mounds had

varying height of A (2.0 m), B (1.1 m) and C

(1.2 m). The corresponding diameters of the

three termite mounds were 4.5, 6.0, and 8.5 m,

respectively. Samples were collected in May

2008 when the TMS were considered

workable (not too hard) before the onset of

heavy rains in the following months.

The textural analyses were determined by

standard methods similar to that reported

(Awadzi et al., 2004). The soil samples were

air dried and passed through a 2-mm sieve,

and the content of gravel (<2 mm) by weight

was determined. Particle size distribution was

determined by sieving sand fractions and by

using the hydrometer method for determining

the silt and clay fraction. Soil pH was

determined potentiometrically in 0.01 M CaCl2

at a soil-solution ratio of 1:2.5. Exchangeable

cations were extracted with 1M NH4Oac at pH

7. Calcium (Ca) and magnesium (Mg) were

determined by atomic absorption

spectrophotometry while potassium (K) was

determined by flame photometry.

129

Manuwa and Olawolu NJSS/22(1)/2012

Exchangeable acidity (H+ and Al3+) was

extracted with 1 M KCl and determined by

titration with NaOH. Total carbon content was

determined by dry combustion using an Eltra

CS500-apparatus. Total nitrogen (N) was

determined by the Kjeldahl method. Total

phsphorus (P) was determined

spectrophotometrically by the molybdenum

blue method using ascorbic acid as a reductant

after the soil samples were heated to 550oC

and extracted with 6 M sulphuric acid

In situ shear strength determination In situ shear strength was determined for all

the samples in August 2008. The timing was

not particularly significant apart from being

drier period, but as a matter of convenience.

The shear strength of soil samples were

measured with a shear vane tester (16mm

diameter vane) at depth 40, 80 and 120 mm on

each sample and the average strength was

calculated. The corresponding moisture

contents of the samples were also determined

with a moisture meter.

Laboratory determination of shear strength

of compacted soil Laboratory tests were conducted on all the

experimental soil samples after they were

sieved through 2 mm size sieve to determine

the shear strength using the shear vane tester.

The soil samples were subjected to 5, 10 and

15 blows respectively with a standard proctor

rammer (2.5 kg) at different moisture content

level in a cylindrical metal mould. The mould

was 100 mm in diameter and 120 mm height.

A round wooden pad was placed on the soil

before compaction in order to ensure unidorm

compaction of the soil in the mould. The shear

vane was graduated in kilopascal (kPa).

Measurements were taken at depth 40 and 80

mm respectively on each sample and the mean

value of each set of two-depth reading was

calculated and recorded.


Textural classification The textural analysis showed that TMS could

have more clay fractions than the surrounding

soil (R) and that the texture could vary from

top to bottom of the mound as shown in

mounds A and C (Table 1).

It was also observed that the surrounding soil

might have a textural class that is different

from that of the mound. The percentage clay

plus silt is significantly higher in TMS than the

R.

Physical, chemical and organic properties Table 2 shows the termite mound soils are

acidic soils but less acidic (greater pH values)

than surrounding soils without termite

mounds, though for mound C, the soil seems

to be more acidic (lesser pH values). The

organic matter content of the TMS was lesser

than that of the surrounding soil. This agrees

well with Garniier-sillam et al, 1988) but

contrary to some reports (Jouquet et al., 2003;

Abbadie and Lepage, 1989).

Consistency limits Termite mound soil has higher consistency

limits values than the surrounding soil (Table

3) and therefore higher plasticity indix than the

R, which indicate that they have high clay

fractions. There is also some localized

variation in consistency limits within each

mound. The liquid limit and plastic limit of

mound B (Table 3) is the highest among the

three mounds.

Insitu shear strength The shear strength of the termite mound soil

increased with soil depth in the field and inside

the mound. The base of the mounds recorded

highest shear strength compared to the top

portion of the mounds. The shear strength of

the surrounding soil was found to be lower

than that of the mounds. The mounds shear

strength increased with reduction in moisture

130


content but decreased as the water content

increased (this is expected) like during raining

season and it might even lead to mound

collapse during excess rainfall as a result of

high water content. Mound A, had part of it

collapsed due to heavy amount of rainfall.

Mound B had the highest mean shear strength

of 94.56 kPa, sample B Top position (SBT)

and 120.11 kPa, Sample B Base position

(SBB); this is probably due to high silt plus

clay content in it. Also Sample B Surrounding

soil (SBR) had 72.46 kPa. Mound A has the

least shear strength of a total mean value of

74.03 kPa at Sample A Top position (SAT)

and 63.13 Kpa at Sample A Base position

(SAB). This is due to presence of sandy soil

mixed with clay soil.

Shear strength of compacted termite mound

soils Generally, the shear strength of TMS

increased with the number of Proctor’s

hammer blows and reached a maximum at

about 15 blows in the moisture content range

of about 11 to 13% (db). It was observed that

about 90% of the maximum shear strength was

achieved at 10 blows.

Termite mound soil has greater shear strength

than corresponding adjacent soil (and therefore

is less susceptible to compaction) for all the

sampled mounds and the strength of the

mound also varied within the mound. This is

probably due to the variation of textural

fractions within the mounds.

CONCLUSION The following conclusions can be drawn from

this study;

The texture of a TMS varied from top to

bottom of the mound and with the surrounding

soil (R). There was less organic matter,

organic carbon and nitrogen in the TMS than

in the R, however, there were higher

phosphorus, calcium, potassium, magnesium

and sodium and consistency limits. Termite

mound soil has greater shear strength than

corresponding adjacent soil for all the sampled

mounds and the shear strength of TMS also

varied within the mound.

Table 1: Textures of Termite mound and adjacent soils

Soil type % Sand % Silt % Clay % (Silt + Clay) Texture

SAT

SAB

SAR

SBT

SBB

SBR

SCT

SCB

SCR

34

34

54

32

32

38

32

34

40

38

20

8

22

22

16

24

24

22

28

46

38

46

46

46

44

42

38

66

66

46

68

68

62

68

66

60

Clay loam

Clay

Sandy clay

Clay loam

Clay loam

Clay loam

Clay loam

Clay

Clay loam

131


Table 2: Chemical and organic properties of termite mound soil TERMITE MOUND A

Samples O/M

(%)

O/C

(%)

N

(%)

P

(mg/kg)

Ca2+

(cmol/kg)

K+

(cmol/kg)

Mg2+

(cmol/kg)

Na+

(cmol/kg)

pH

SAT

SAB

SAR

1.69

1.38

2.10

0.98

0.80

1.22

0.12

0.10

0.15

6.92

4.16

5.27

1.30

1.50

1.20

0.351

0.289

0.241

1.00

1.00

1.00

0.148

.0130

0.126

6.06

5.85

5.98

TERMITE MOUND B

SBT

SBB

SBR

1.62

1.62

2.13

0.94

0.94

1.24

0.12

0.13

0.16

6.87

1.76

0.80

2.00

2.00

2.00

0.249

0.233

0.264

1.70

1.10

1.40

0.139

0.126

0.165

5.19

5.30

4.91

TERMITE MOUND C

SCT

SCB

SCR

1.93

1.96

2.27

1.12

1.14

1.32

0.14

0.15

0.17

4.24

7.11

3.36

2.00

1.90

1.30

0.295

0.282

0.287

1.00

1.00

1.00

0.157

0.161

0.161

5.76

5.62

5.82

Table 3: Consistency limits of Termite mound soil (TMS) Soil Samples Liquid limit (%) Plastic limit (%) Shrinkage limit (%) Plasticity Indix

SAT

SAB

SAR

36.0

38.0

29.0

20.0

22.0

19.0

10.0

11.0

5.0

16.0

16.0

10.5

SBT

SBB

SBR

43.0

42.0

35.0

28.0

22.0

22.0

12.0

15.0

9.0

15.0

20.0

13.0

SCT

SCB

SCR

34.0

29.0

29.0

19.0

19.0

19.0

11.0

7.0

7.0

15.0

10.0

10.0

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of Subterranean fungus-corn chambers

Isoptera, Macrotermitinae) in soil

nitrogen cycling in a forest savanna

(Cote d Ivoire). Soil Biol. Bioch. 21:

1067-1071.

Fageria, N.K. and V.C. Baligar (2004).

Properties of termite mound soil and

responses of rice and beans to N, P and

K fertilization on such soil.

Communications in Soil Science and

Plant Analysis. 35: 15-16.

Garnier-Sillam, E., F. Toutain and J. Renoux

(1988). Comparaison de l’ influence de

deux termitieres (humivore et

champignonniste) sur la stabilite

structurale des sols forestiers tropicaux.

Pedobiol. 32: 89-97. In: Jouquet et al.,

2003.

Jouquet, P., Mamou, L., Lepage, M., Velde,

B. (2002). Effect of termites on clay

minerals in tropical soils; fungus-

growing termintes as weathering

agents. Eur. J. Soil Sci., 53 (4), 521-

527.

Jouquet, P., Mery, T., Roulland, C., Lepage,

M. (2003). Modulated effect of the

termite ancistrotermes cavothorex

(Isoptera, Macrotermitinae) on soil

properties according to the structure

built. Sociobiology 42, 403-412.

132


Lopez-Hernandez D. 2001. Nutrient dynamics

(C, N and P) in termite mounds of

Nausutitermes ephratae from savannas

of the Orinoco Llanos (Venezuela).

Soil Biology and Biochemistry 33:

747-753.

Menaut J.C., Barbault R., Lavelle P., Lepage

M., (1985). African savannas:

biological systems of humification and

mineralization. In: J.T. a.J. Mott (ed.)

Ecology and management of the

world’s savannas. Australian Acad.

Sci., Canberra. 14-33.

Roose Amsaleg, C., Brygoo, Y., Harry, M.

(2004). Ascomycete diversity in soil-

feeding termite nests and soils from a

tropical rainforest. Environment.

Microbiol., 6(5), 462-469.

Rupela, O.P., Humayun, P., Venkateswarlu, B.

And Yadav, A.K. (2006). Comparing

Conventional and Organic Farming

Crop Production Systems: Inputs,

Minimal Treatments and Data Needs.

Paper prepared for submission to the

Organic Farming Newsletter published

by the National Center for Organic

Farming (NCOF), Ministry of

Agriculture, Government of India, 06

April 2006.

Semhi, K., Chaudhuri, S., Clauer, N., Boeglin,

J.L. (2008). Impact of termite activity

on soil environment: A perspective

from their soluble chemical

components. Int. J. Environ. Sci. Tech.,

5 (4), 432-444, Autumn 2008.

Siame, J.A. (2005). Termite mound as

fertilizer. LEISA Magazine, pp 29,

June, 2005.

Watson JP. (1977). The use of mounds of the

termite Macrotermes falciger

(Gerstacker) as a soil amendment.

Journal of Soil Science 28: 664-672.

Wood T.G., Johnson R.A. and Anderson J.M.

(1983). Modification of the soil in

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133


TESTING THE GOODNESS OF FIT OF INFILTRATION MODELS FOR SOILS

FORMED ON COASTAL PLAIN SANDS IN AKWA IBOM STATE,

SOUTHEASTERN NIGERIA

OGBAN, P. I., OBI, J. C., ANWANANE, N. B., EDET, R. U., AND OKON, N. E.

Department of Soil Science, University of Uyo, Uyo, Nigeria


ABSTRACT

Infiltration of water into the soil is an important physical process affecting the fate of water

under field conditions, especially, the amount of subsurface recharge and surface runoff and

hence the hazard of soil erosion. The study was conducted to investigate the capability of six

infiltration models, namely, Kostiakov, modified Kostiakov (A) and (B), Philip, modified Philip

(A) and (B) to describe infiltration into soils formed on coastal plain sands parent material in

Akwa Ibom State, Southeastern Nigeria. A total of 18 infiltration runs were made with the

double infiltrometer technique. Model-predicted cumulative infiltration consistently deviated

from field-measured data, that is, the models over-predicted cumulative infiltration by several

orders of magnitude. However, there was a fairly good agreement between mean - measured

cumulative infiltration (274.2 cm, CV = 35.5%) and Philip (405.6 cm, CV = 34.9%) and

Kostiakov (480.3 cm, CV = 37.9%) models. The r2 values of the model parameters obtained

from linear regression analysis were generally low. The data however showed that the Kostiakov

(0.49) and modified Philip ((B) = 0.48) and ((A) = 0.48) provided best fit with the field-

measured data. The residual mean square error (RMSE) of the infiltration equations showed that

the classical Philip model had the least non-significant value (6.47) while other models had

significant (p≤0.01) values that range from moderately high (Kostiakov, 14.23) to very high

(modified Philip (B) , 426.20). T-test of measured versus predicted cumulative intake showed all

but the basic Philip infiltration model were significantly (p≤0.01) different from the field-

measured data, indicating the close agreement between the Philip model and the measured

values. The results confirmed that Philip model could be used for routine characterization of the

infiltration process on coastal plain sands parent material in Akwa Ibom State.

INTRODUCTION Infiltration of water into the soil is of great

practical importance to agriculture since it

determines the amount of subsurface recharge

and surface runoff, and hence the hazard of

soil erosion. Knowledge of the infiltration

process is a prerequisite for efficient soil and

water conservation. The infiltration rate can

mostly be evaluated under either ponded or

rainfall conditions, but the measurement is

time-consuming, could be expensive where

water is limiting, and preferential flow within

cracks can cause an over-estimation of the

infiltration process (Hume, 1993). Infiltration

134

Fit of infiltration models for soils


rate can also be predicted using infiltration

models, that range from those that are strictly

empirical to those that are deemed to be

mechanistic, but that generally vary in their

predictive capacity of the soil infiltration

characteristics (Haverkamp et al., 1988;

Majaliwa and Tenywa, 1998), and all are not

usable under all conditions. Consequently,

tests of their applicability and accuracy are

essential.

Several studies have attempted to quantify the

infiltration process (Green and Ampt, 1911;

Kostiakov, 1932; Horton, 1940; Philip, 1957;

Talsma and Parlange, 1972; Rao et al., 2006).

Equally, several studies have evaluated

existing models either for the purpose of

validation, to establish the model parameters

for different soils or comparison of model

efficiencies and applicability for different soil

conditions (Ahmed, 1982; Bach et al., 1986;

Davidoff and Salim, 1986; Obiechefu, 1991;

Topaloglu, 1999; Mudiare and Adewumi,

2000; Wudduvira et al., 2001; Haws et al.,

2004; Igbadun and Idris, 2007).

Cook et al.(1982) studied the infiltration

process on reclaimed surface mined soils using

Horton, Philip, Green and Ampt, and Parlange

(1973) equations, and reported that these

models generally failed to predict initial

infiltration rates adequately, although they did

simulate long-term infiltration rates relatively

well. Obiechefu (1991) evaluated the

Kostiakov, Horton, and Philip equations and

found that the Kostiakov model best predicted

the infiltration characteristics of permeable

soils in the Nsukka area of southeastern

Nigeria. Similarly, Mbagwu (1995) tested the

goodness of fit of the Kostiakov, modified

Kostiakov (A) and (B), Philip and modified

Philip (A) and (B) and found the modified

Kostiakov (B) and modified Philip (B) could

be used for routine characterization of the

infiltration process in highly permeable soils in

the Nsukka area of southeastern Nigeria.

Wuddivira et al. (2001) tested the performance

of the Kostiakov, Philip, and Horton models

and reported that the Kostiakov and Philip

models adequately described the infiltration

data, but that the Philip equation was superior

in predicting infiltration into Samaru soils in

Northern Nigeria. Similarly, Igbadun and Idris

(2007) evaluated the Kostiakov, Philip,

Kostiakov-Lewis function or modified

Kostiakov (A) (Elliot and Walker, 1982) and

modified Kostiakov (B) (Micheal , 1992) in

hydromorphic soils in Samaru, Zaria, Nigeria,

and found that all four models provided good

overall agreement with field-measured data

but that the Kostiakov and modified Kostiakov

models provided the best fit. The preceding

reviews show that the reliability of the models

is often location-specific, and sometimes

variable results may obtained within location.

This study was conducted to evaluate the

suitability of the Kostiakov, modified

Kostiakov (A) and (B), Philip, and modified

Philip (A) and (B) infiltration models to

describe the infiltration characteristics of soils

formed on coastal plain sands in Akwa Ibom

State, Southeastern Nigeria.


Environment of Study Area

The study was conducted in soils formed on

coastal plain sands parent material in Akwa

Ibom State, Southeastern Nigeria. The State is

located between latitudes 4° 30' and 5° 30' and

longitudes 7° 30' and 7° 56'. The climate is

tropical hot humid, characterized by two

distinct rain (April to October) and dry

(November to March) seasons. Rainfall is

bimodal (July and September) and heavy with

annual range between 2000 and 3500 mm.

Temperatures are uniformly high averaging

between 28 and 300. Similarly, relative

humidity is high, about 75%.

Over 75% of the State comprises

unconsolidated sediments of the coastal plains

and alluvium (Petters et al., 1989), mostly in

134

Ogban, Obi, Anwanane, Edet and Okon NJSS/22(1)/2012

the central and southern areas. The geologic

formation passes imperceptibly to a thick

sequence of sandstone and shale parent

material in the northern area of the State. The

soils are highly permeable and well-drained,

structurally unstable, and low in organic

matter content. The vegetation is mostly

secondary forests interspersed with wild oil

palms. Land use is the traditional shifting

cultivation with the associated slash-and burn

and bush fallow farming system. The bush

fallow or natural fallow age has been reduced

to about four (4) years (Ogban et al.,2004,

2005), the vegetation is immature (Areola,

1990), affecting the quality of the soil resource

base (Ogban and Obi, 2010).

Field methods

The study was conducted in 18 locations, from

where a total of 18 soil samples were collected

from 20 cm depth for particle size analysis.

Another set of 18 undisturbed samples were

collected from the depth zone with core

samplers 7.2 cm long and 6.8 cm internal

diameter for bulk density, total porosity, and

hydraulic conductivity. The soil samples were

collected prior to and adjacent the infiltration-

test points.

Eighteen (18) infiltration runs were carried out

using the double ring infiltrometer technique.

The rings, 30 and 55 cm diameter respectively,

were driven into the soil to a depth of 10 cm.

Plant materials were placed on the surface of

the soil to minimize disturbance of the surface

soil when water was applied. Water was

applied and ponded to a depth of about 15 cm.

The rate of water entering the soil and the

depth of water infiltrated as a function of time

were monitored in the inner ring for 120

minutes at each location.

DATA ANALYSIS

The six infiltration models were examined to

evaluate their parameters. These are Kostiakov

(equation 1), modified Kostiakov (A) and (B)

(equations 2 and 3), Philip (equation 4), and

modified Philip (A) and (B) (equations 5 and

6) (Table 1).

I = Ktα (1)

where K and α are constants.

I = K1tα1 + Kst (2)

where Ks is a laboratory determined hydraulic

conductivity of the soil.

I = K2tα2 + ic t (3)

where ic is the asymptotic final infiltration rate

of the soil.

I = St½ + At (4)

where S and A are constants.

I = S1t½ + Kst (5)

where Ks is as defined in equation (2) above.

I = S2t½ +ict (6)

where ic is as defined in equation (3).

Least square linear regression analysis and

curve fitting were used to determine the model

parameters. The principle of curve fitting is to

find an equation which fits the data with a

minimum deviation. To facilitate linear

regression, each model was first transformed

into its linear equivalent using logarithm, in

which I and t are the dependent and

independent variables, respectively, and the

coefficients of the linear functions are the

model parameters to be estimated. The values

of the parameters estimated were then

incorporated into the respective model

equations and the capability of each model to

simulate cumulative infiltration was evaluated

by comparing the model-simulated data with

the field-measured data.

RESULTS AND DISCUSSION The results of soil physical determinations are

shown in Table 2. The mean measured

cumulative infiltration for the 18 sites was

274.2 cm, with a standard deviation of 97.27

cm and a coefficient of variability (CV) of

35.5% (Table 3). A comparison between

measured and model-predicted cumulative

infiltration showed that consistently the values

predicted by the classical Kostiakov and Philip

135


models as well as the modifications thereof

deviated mostly from field-measured data, that

is, the models over-predicted cumulative

infiltration in this study. The data further

showed high spatial variability of measured

and predicted cumulative infiltration.

However, in terms of least deviations with

measured data, the classical Philip was

superior to the classical Kostiakov model

(Wuddivira et al., 2001).

The average value of the field-measured final

infiltration rate was 2.23 cmhr-1, with a

standard deviation of 0.81 cmhr-1 and

coefficient of variability of 2.76% (Table 4).

This indicates that as the infiltration rate

decreases and assumes asymptotically a final

value, the sampling locations were

characteristically similar in the soil water

intake parameters. Comparing the measured

and model-predicted values, the modified

Philip (B) and the basic Philip and Kostiakov

models in that order, showed strong agreement

with the measured data (Mbagwu, 1995). The

modified Kostiakov (A) and (B) and modified

Philip (A) showed wide deviation from the

measured data. Similarly, while the predicted

data from the former models were spatially

moderately variable, data from the latter three

models were moderately to highly variable and

therefore poorly predicted the final infiltration

rates of the soils (Dividoff and Salim, 1986;

Mbagwu, 1995).

The parameters of the six infiltration models

obtained from regression analysis were highly

variable (Table 5). The r2 value was used as a

measure of the goodness of fit of a model.

Considering the parameters of the main and

modified Kostiakov and Philip models, the r2

values obtained were generally low. However,

the model parameters were moderately high

for the classical Kostiakov and modified Philip

(B), and lowest for modified Kostiakov (A)

and the basic equation of Philip. The r2 value is

a measure of the goodness of fit of a model. In

this study therefore, all models were poor

predictors of infiltration rate into the soils. The

data however showed that the Kostiakov, and

modified Philip (B) and (A) provided best fit

with the field-measured data (Mbagwu, 1995;

Igbadun and Idris, 2007).

The residual mean square error (RMSE) of the

infiltration equations showed that the classical

Philip model had the least value (6.47), while

the other models had values that range from

moderately high (original Kostiakov = 14.23)

to very high (modified Philip (B) = 426.20)

(Table 6). Similarly, t-test of measured versus

predicted cumulative intake showed that all

but the basic Philip infiltration model were

significantly (p≤0.01) different from the field-

measured data (Table 7), indicating a strong

agreement between the Philip model and the

measured values. In other words, the Philip

model fits best the shape of the curve of

cumulative infiltration versus time (Wuddivira

et al., 2001; Oshunsanya, 2010).

Table 1: Infiltration models and their fitting parameters

Model Infiltration equation Fitting parameters

Kostiakov (1932) I = Ktα K, α

Modified Kostiakov (A) I = K1ta1 + Kst K1, Ks, α1

Modified Kostiakov (B) I = K2tα2 + ict K2, ic, α2

Philip (1957) I = St½ + At A, S

Modified Philip (A) I = S1t½ + Kst Ks, S1

Modified Philip (B) I = S2t½ + ict ic, S2

136


I is cumulative infiltration (cm); K, K1, K2 are

Kostiako’s time coefficient terms, (cm); t is

time elapsed (h); a, a1, a2 are Kostiakov’s time

exponent terms (dimensionless); Ic is steady

infiltration rate (cm h-1); A is Philip’s soil

water, transmissivity (cm h-1); S, S1 S2 are

Philip’s soil water sorptivity terms (cm h-1); Ks

is saturated hydraulic conductivity (cm h-1).

Table 2: Average values of soil physical and chemical properties

Soil property X sd CV

Sand --g k

g-1--

927 19.27 2.1

Silt g kg-1 28 19.70 71.1

Clay g kg-1 43 1.04 2.4

Organic matter 30.4 7.99 26.3

Ks cm h-1 12.32 7.33 59.5

Bulk density kg m-3 1524 54.28 28.1

Total porosity m3 m-

3

0.425 0.02 20.2

X is mean; sd is standard deviation; CV is coefficient of variation.

Table 3: Average statistics of cumulative infiltration from six infiltration models fitted

to 18 trials

Model X Sd CV

Measured 274.2 97.27 35.5

Kostiakov 480.3 181.87 37.9

Modified Kostiakov (A) 698.6 235.31 33.7

Modified Kostiakov (B) 1294.3 903.44 69.8

Philip 405.6 141.58 34.9

Modified Philip (A) 1573.7 977.99 62.2

Modified Philip (B) 1399.3 933.01 66.7

X is mean; sd is standard deviation; CV is coefficient of variation

Table 4: Average statistics of final infiltration rates from six infiltration models fitted

to 18 trials

Model X Sd CV

Measured 2.23 0.81 2.76

Kostiakov 3.50 1.09 31.14



Philip 3.41 1.16 34.02




137


Table 5: Average statistics of estimated values of the model parameters Kostiakov Modified Kostiakov (A) Modified Kostiakov (B) Philip Modified Philip (A) Modified Philip (B)

K Α r2 K1 KS α1 r2 K2 ic α2 r2 S A r2 S1 Ks r2 S2 ic r2

X 4.52 O.86 0.49 8.66 x 10-5 12.32 -704.5 O.40 2.28 2.23 0.19 0.46 2.46 2.06 0.44 -110.06 12.32 0.47 0.52 2.232 0.48

Sd 1.78 0.05 0.25 2.72 x 10-5 7.33 419.59 0.29 1.39 0.81 0.23 0.26 1.52 0.78 0.25 77.62 7.33 0.25 0.30 0.31 0.25

CV 39.4 6.7 50.5 3.14 x 10-5 59.5 -59.6 72.5 61 36.1 121.1 55.6 61.8 37.9 57.4 -70.5 59.5 54.0 57.7 36.1 52.5

X is mean; sd is standard deviation; CV is coefficient of variation; K, K1, K2 are Kostiakov’s time coefficient terms(cm h -1); Ks is

saturated hydraulic conductivity (cm h-1); a, a1 are Kostiakov’s time exponent terms (dimensionless); ic is steady infiltration rate (cm

h-1); S, S1, S2 are soil water sorptivity (cm h-½); A is soil water transmissivity (cm h-1).

138


Table 6: Residual mean square error (RMSE) for the infiltration models

Models X Sd CV

Kostiakov 14.23 14.91 104.8



Philip 6.47 6.89 106.5




Table 7: T-test of measured versus estimated cumulative infiltration

Model Mean difference tcal

Kostiakov -177.84 -9.58**

Modified Kostiakov (A) -1219.77 -5.96**

Modified Kostiakov (B) -429.04 -11.25**

Philip -388.91 -2.07ns

Modified Philip (A) -1197.53 -5.81**

Modified Philip (B) -1090.89 -4.87**

**Significant at 1%, ns Not significant

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parameters for some selected Samaru soils. M. Sc. Dissertation. Department of Agric. Engr., Ahmadu Bello University, Zaria, Nigeria.

Areola, O. 1990. The Good Earth. University

of Ibadan Inaugural Lecture Series. 40p.

Bach, L. B., Wierenga, P.J. and Ward, T. J.

1986. Estimation of the Philip infiltration parameters from rainfall simulation data. Soil Sci. Soc. Am. J. 50:1319-1323.

Cook, D. F., Magette, W. L., Jones, J. N.,

Shanholtz, V. O. and Hockman, E. L. 1982. Evaluation of infiltration equations on reclaimed mined soils. ASAE paper SER 83-007. ASAE. St. Joseph. M. I.

Davidoff, B. and Salim, H. M. 1986. Goodness

of fit for eight water infiltration models. Soil Sci. Soc. Am. J. 50:759-764.

Elliot, R. L. and Walker, W. R. 1982. Field evaluation of furrow infiltration and advance functions. Trans. ASAE 25:396-400.

Green, W. H. and Ampt, G. A. 1911. Studies

on soil physics: The flow of air and water through soils. J. Agric. Sci. 4:1-24.

Haverkamp, R., Kutilek, M., Parlange, J. Y.,

Rendon, L. and Krejca, M. 1988. Infiltration under ponded conditions: Infiltration equations tested for parameter time-dependence and predictive use. Soil Sci. 145:317-329.

Haws, N. W., Liu, B., Boast, C. W., Rao, P. S.

C., Kladivko, E. J. and Franzmeier, D. P. 2004. Spatial variability and measurement scale of infiltration rate on an agricultural landscape. Soil Sci. Soc. Am. J. 68:1818-1824.

Horton, R. E. 1940. Approach toward a

physical interpretation of infiltration capacity. Soil Sci. Soc. Am. Proc. 5:399-417.

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Hume, I. H. 1993. Determination of infiltration characteristics by volume balance for bother-check irrigation. Agric. Water Management 23:23-39.

Igbadun, H. E. and Idris, U. D. 2007.

Performance evaluation of infiltration models in a hydromorphic soil. Nig. J. Soil Env. Res. 7:53-59.

Kostiakov, A. N. 1932. On the dynamics of the

coefficient of water percolation in soils and on the necessity for studying it from a dynamic point of view for purpose of amelioration. Trans. Int. Congr. Soil Sci. 1932(A): 17-21.

Majaliwa-Mwanjalolo, J. G. and Tenywa, M.

M. 1998. Infiltration characteristics of soils of Kyetume ridge, Kabanyolo, Uganda. MUARIK Bull. 1:57-65.

Mbagwu, J. S. C. 1995. Testing the goodness

of fit of infiltration models for highly permeable soils under different tropical soil management systems. Soil Tillage Res. 34:199-205.

Micheal, A. M. 1992. Irrigation: Theory and

Practice. Vikas Publ. House. PVT Ltd. New Delhi, India. Pp. 464-472.

Mudiare, O. J. and Adewumi, J. K. 2000. Estimation of infiltration from field-measured sorptivity values. Nig. J. Soil Res. 1:1-3.

Obiechefu, G. C. 1991. Evaluation of

infiltration equations for Nsukka soils. The Nig. Agric. J. 26:27-42.

Ogban, P. I., Ukpong, U. K. and Essien, I. G.

2004. Interrelationship between bush fallow and the physical and chemical properties of “acid” sands in southeastern Nigeria. Nig. J. Soil Res. 5:32-45.

Ogban, P. I., Ukpong, U. K. and Essien, I. G.

2005. Influence of bush fallow on the physical properties of acid sands in

southeastern Nigeria. Nig. J. Soil Sci. 15:96-101.

Ogban, P. I. and Obi, J. C. 2010. The relation

between natural fallow and soil quality in Akwa Ibom State, southeastern Nigeria. Nig. J. Agric. Food Env. 6(3&4):34-43.

Oshunsanya, S. O. 2010. Predicting infiltration

rates and determining suitability of infiltration models under vetiver grass strips management systems in South-Western Nigeria. Nig. J. Soil Sci. 20(1): 36-44.

Parlange J. Y. 1973. Note on the infiltration

advance front from border irrigation. Water Resources Res. 9:1075-1078.

Petters, S. W., Usoro, E. J., Udo, E. J., Obot,

U. W. and Okpon, S. N. 1989. Akwa Ibom State: Physical Background, Soil and Land Use and Ecological Problems. Govt. Print Office, Uyo. 603p.

Philip, J. R. 1957. The theory of infiltration:

The infiltration equation and its solutions. Soil Sci. 83:345-347.

Rao, M. D., Raghuwanshi, N. S. and Singh, R.

2006. Development of a physically based infiltration model for irrigated soils. Agric. Water Management 85:165-174.

Talsma, T. and Parlange, J. Y. 1972. One-

dimensional vertical infiltration. Aus. J. Soil Res. 10:143-150.

Topaloglu, F. 1999. Comparing tillage

technique by infiltration model. Trop. J. Agric. Forestry 23:609-614.

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140


CONTAMINANT LIMIT (c/p index) OF HEAVY METALS IN SPENT OIL

CONTAMINATED SOIL BIOREMEDIATED WITH LEGUME PLANTS AND

ORGANIC NUTRIENT

UDOM, B.E.1 , ANO A. O.,2 AND CHUKWU L. I. 2 1Department of Crop and Soil Science, University of Port Harcourt,

P.M.B. 5323, Port Harcourt, Rivers State, Nigeria.

E-mail: [email protected] 2National Root Crops Research Institute, Umudike.

P.M.B 7006, Umuahia, Abia State, Nigeria.

ABSTRACT

Three legume plants (Gliricidia sepium, Leucaena luecocephala and Calapogonium caerulean)

alone or in combination with 0.5% (w/w) poultry manure were tested for their ability to reduce

the heavy metals and toxicity criteria of a sandy soil contaminated with 5% (w/w), (equivalent of

50,000 mg/kg) spent lubricating oil, each for two years. The oil and poultry manure led to build-

up of Ni, Pb, Zn and Cu in the soils. The contaminant – pollution index (c/p index) calculated

for Ni, Pb, Zn and Cu showed that at 3 months after oil contamination, concentration of Ni

ranged from 0.03 to 0.024 mg/kg, Pb from 0.01 to 0.18 mg/kg, Zn from 0.27 to 0.60 mg/kg, and

Cu from 0.12 to 0.81 mg/kg. The application of oil led to slight contamination of the soil with

Pb, moderate to severe contamination with Zn and Cu, whereas, plots treated with poultry

manure alone showed very severe contamination with Cu. Within 18 to 36 months, after oil

contamination, the Gliricidia, Leucaena and Calapogonium combined with poultry manure

reduced the toxicity levels of Ni, Pb, Zn and Cu. The Gliricidia was more effective in removal of

these metals. At 36 months, the Gliricidia sepium combined with poultry manure reduced the Ni,

Pb, Zn and Cu concentrations in the soil by 96%, 90%, 42%, and 50% respectively. Therefore,

these legume plants are promising species in phytoremediation of oil contaminated sites and for

general improvement of soil health. They can bioaccumulate high levels of these metals that

could be toxic to other plants or organisms.

Key words: contaminant limit, heavy metals, bioremediation, legume plants, organic nutrients

Email of corresponding author: [email protected]

INTRODUCTION

Heavy metals are widely and usually applied

to the elements such as Cd, Cr, Cu, Hg, Ni,

and Zn, which are commonly associated with

pollution and toxicity problems. It is a general

collective term applying to the group of metals

and metalloids with an atomic density greater

than 6g/cm3 (Alloway, 1990). However, some

of the elements in this group are required by

most living organisms in small but critical

concentrations for normally healthy growth.

Those metals which are unequivocally

essential, whose deficiency have adverse

effects in normal living conditions include Cu,

Mn, Fe and Zn for both plants and animals,

141

Contaminatant limit of heavy metals



Co, Cr and Se for animals, B and Mo for

plants.

The toxicity effects caused by excess

concentrations of these metals include

competition for sites with essential

metabolites, replacement of essential ions, and

damage to cell membrane (Ernst, 1996). Zinc,

Cu, Pb, Cd and Ni are generally the metals of

greatest concern. Zinc, Cu and Pb are

important because they can be phytotoxic.

Whereas, concern for Cd and Ni arises from

their possible entry into the food chain

(Chaney, 1994). If these metals move too

rapidly in a particular soil, they can pollute

ground water supplies, especially in areas with

high water table. It has been found that

limiting Cu-contaminated soils to pH 7 can

mitigate the toxicity by reducing the

bioavailability of the Cu. (Alloway and Ayres,

1997). Copper is also highly toxic to the soil

microbial biomass and this can affect various

aspects of soil fertility.

Disposal of petroleum products with high

heavy metal burdens on soil could result in

nutritional imbalance, phytotoxicity and

reduced crop production. Sediments and

polluted soils enriched in heavy metals are

subjected to erosion, which increase the risk of

pollution in the surrounding areas. (Merkl et

al.,2005). Excessive applications of metals

bearing materials to the soil in whatever form

have the potential of restricting plant growth

and reducing crop yields. Ultimately, yield

reduction has been the most important measure

of phytotoxicity for agronomic species, since it

affects the profitability of crop production and

limits the utility of the land. Heavy metal

accumulation and possible phytotoxicity are

therefore, the most critical long-term hazards

associated with disposal of petroleum products

to land.

Contaminant limit (c/p index) has been used

for assessment of toxicity risk of heavy metals

in a soil site. The limit value is equivalent to

maximum permissible risk level. It is intended

to indicate the environmental quality to be

achieved in a given period. (Kabata-Pendias

and Pendias,1984).

Spent lubricating oil includes mono-and multi-

grade crankcase oils from petrol engines,

together with gear oils and transmission fluids

with significant levels of heavy metals and

other undesirable properties present in all

petroleum products. Atuanya (1987) observed

that Nigeria accounts for more than 87 million

litres of spent oil annually and that most heavy

metals such as Va, Pb, Ni, Cu and Zn which

are below detection in unused lubricating oil,

showed high values in waste motor oil.

Contamination of open vacant plots and farm

lands with petrol oils and grease is becoming

more widespread problem than crude oil

pollution.(Anoliefo and Vwioko, 1995;

Atuanya, 1987).

The use of plants and organic nutrients to

modify soils contaminated with petrol oil and

grease will provide a solution for metal

stabilization and for minimizing erosion and

associated risks. Phytoremediation has shown

great potential as an alternative treatment for

remediation of heavy metal-contaminated soils

and ground water (Chen and Cutright, 2001,

Merkl et al., 2005, Gallizia et al., 2003,

Harayama et al., 2004). There is very little

information available in the literature on the

use of organic nutrients and legume plants to

reduce the risk levels of heavy metals in

contaminated sites. Moreover, the distinction

between contamination and pollution range

values of most metals in soils is uncertain.

This study will provide valuable input data in

the assessment of toxicity risk levels of Ni, Pb,

Zn and Cu in soils.


The study was carried out at the University of

Nigeria, Nsukka, Research Farm (Lat 06052’N

and Long 07024’E) The soil is a Typic

kandiustult (Nwadialo, 1989), derived from

False-Bedded Sandstone (Akamigbo and Igwe,

1990). The mean sand, silt, and clay contents

at the 0-30 cm depth were 820, 60 and 120 g

kg-1 soil respectively, (Table 1). The soil was

142

Udom, Ano and Chukwu NJSS/22(1)/2012

impacted with equivalent of 50,000 mg kg-1

soil (5% w/w) mono- and multi-grade

crankcase oils sourced from petrol and diesel

engines. The oil was applied in a single dose

each for two years. By the second year of the

experiment, oil contaminated plots had

equivalent of 100,000 mg kg-1 soil,

representing a total oil load of 10% (w/w).

Some properties of the soil and spent oil used

for the experiment are shown in Table 1.

Three (3) legume plants: Calapogonium

Caerulean, Gliricidia sepium, and Leucaena

leucocephala, alone or in combination with

0.5% (w/w), (equivalent of 50 mg kg-1) of

poultry manure were used to enhance

biodegradation. The legume seeds and poultry

manure were introduced to the plots at seven

(7) days after the oil contamination and

allowed for incubation, fourteen (14) days,

before planting the maize crop. The

Calapogonium caerulean was planted at 30 x

90 cm spacing, (giving density of 37,000

plants ha-1), whereas the Gliricidia ssp and

Leucaena ssp were planted at 1m x 90 cm

spacings, (density of 11, 111 plants ha-1).

FASR-W maize (zea mays) variety was used

as test crop, planted at 25 x 50 cm spacing,

giving a density of 50,000 plants ha-1. The

legume plants used were regularly pruned to

prevent shading of the maize crop and the

biomass incorporated into the soil.

The experiment was laid out as a Randomized

Complete Block Design (RCBD) with nine (9)

treatments, viz: uncontaminated (control) soil

(c), 5% spent oil (A5), 5% spent oil +

Calapogonium ssp (A5 + Ca), 5% spent oil +

Gliricidia spp (A5 + Gl), 5% spent oil +

Leucaena spp (A5 + Le), 5% spent oil +

poultry manure (A5 + Pm), 5% spent oil +

Calapogonium ssp + 0.5% poultry manure (A5

+ Ca + Pm), 5% spent oil + Gliricidia ssp +

0.5% poultry manure (A5 + Gl + Pm), 5%

spent oil + Leucaena ssp + 0.5% poultry

manure (A5 + Le + Pm) with five (5)

replications. The second application of 5%

(w/w) spent oil was done 12 months after the

first application.

Soil sample and measurement of heavy metal

Soil samples were collected from 0 – 30cm

depth at 3, 12, 18, 24, 30 and 36 months after

oil contamination, air-dried and crushed to

pass through a 2 mm sieve. Heavy metals (Ni,

Pb, Zn and Cu) were measured by atomic

absorption spectrophotometer (AAS), after

digesting 3 g air-dried soil sample in

concentrated HCIO4 – HNO3 as described by

(Carter, 1993). The values were compared

with the widely used normal and critical levels

set by Kabata – Pendias and Pendias (1984).

The contaminant limit (c/p index) was

calculated as the ratio between the heavy metal

content in the soil and the toxicity criteria (the

tolerable levels) and classified according to

Lacatusu (1998) as: very slight (c/p index <

0.1), slight (0.1 – 0.25), moderate (0.26 –

0.50), severe (0.51 – 0.75) and very severe

contamination) 0.76 – 1.00), and that of

pollution range as: slight (1.1 – 2.0) , moderate

(2.1– 4.0), severe (4.1 – 8.0), very severe (8.1

– 16.0) and excessive pollution (>16.0). The

distinction between contamination and

pollution range of heavy metals was

established according to Lacatusu (1998). The

legume plants used in this study are good

bioaccumulators of heavy metals (Merkl et al.

2005), fast growing with massive root system,

which penetrate the soil for several metres.


The soil is sandy loam with pH of 4.7 and low

in total nitrogen (Table 1). The spent oil has

high levels of Pb, Zn, and Cu and specific

gravity of 0.87.

Heavy metal concentrations

The heavy metal concentrations pH values of

the soil are shown in Table 2. There were

build-up of Ni, Pb, Zn and Cu in plots

contaminated with spent oil and similar build-

up in plots treated with poultry manure. PH

values ranged from 3.1 to 3.7 in spent oil-

contaminated plots leading to increase in soil

acidity between 2 and 36 percent relative to

the control. This confirmed that spent oil and

poultry manure are sources of heavy metals

contamination in soils (Udom et al, 2004,

143


Amadi et al, 1993). In 3 months, Pb, Zn and

Cu showed significant (P < 0.05) increases in

the oil contaminated plots relative to control

(Table 1). Plots treated with poultry manure

(Pm) alone, showed the highest values of 17,

48, 43.6 and 48.3 mg/kg of Pb, Zn and Cu

respectively, and similar trend at 6 months

after oil contamination. In 12 months, the

increase in Ni, Pb, Zn and Cu concentrations

in the contaminated plots (A5), were 158%,

702%, 118% and 446% respectively compared

to the control (Table I). The high levels of

these metals in the contaminated plots A5 is an

indication that Ni, Pb, Zn and Cu have been

introduced to the soil via the spent oil and

poultry manure applied. This confirmed the

observations of Amadi et al (1993) that most

heavy metals such as Va, Pb, Ni and Fe which

are below detection in unused lubricating oil

showed high values in waste motor oil, and

when disposed to soil, lead to contamination of

the soil.

At high concentrations, these metals can block

essential functional groups in the soil,

displacing other metals ions and modify the

active conformation of biological molecules in

soil and plants, causing reduction in growth

(Vangronsveld and Clijsters, 1994, Ernst,

1996).

Within 18 to 36 months, after oil application,

the Gliricidia, Leucaena and Calopogonuim

combined with poultry manure showed

reductions in Ni, Pb, Zn, and Cu. At 36

months, the Gliricidia sepium combined with

poultry manure significantly reduced the Ni,

Pb, Zn and Cu concentrations in the soil by

96%, 90%, 42% and 50%, respectively,

relative to the A5 soil. This implies that these

legume plants belong to the small group of

plants reported by Brown et al. (1995), that

can tolerate high levels of these metals.

Table 1: Some characteristics of the soil (0-30cm depth), poultry manure and spent oil used in the experiment

Parameters Unit Soil Poultry manure Spent oil

Sand (200-50µm)

Silt (50-2µm)

Clay(< 2µm)

Texture

Organic carbon

Total N

pH (H2O)

Specific gravity

Pb

Zn

Cu

g kg-1

g kg-1

g kg-1

-

g kg-1

g kg-1

-

-

mg kg-1

mg kg-1

mg kg-1

Sandy loam

6.84

0.76

4.7

-

1.48

18.6

7.0

-

28.6

4.5

6.5

-

BDL

182.8

46.1

-

31.5

2.79

-

0.87

286b

478b

164b

BDL – Below detection limit

b – Values in mgl-1

Contaminant-pollution index The contaminant-pollution index(c/p index) calculated for Ni, Pb, Zn, and Cu concentrations in the soil are shown in Table 2. At 3 months after oil contamination, the contaminant-pollution index of Ni ranged from 0.003 to 0.024 mg/ kg, and Pb from 0.12 to 0.81 mg/kg. The oil led to slight contamination of the soil with Pb, moderate to severe

contamination with Zn and Cu, whereas A5 + Pm showed severe contamination of the soil with Cu. This indicates that Zn and Cu are the major contaminant risk in spent oil impacted soils. At 12 months, Zn and Cu showed moderate to severe contamination in the A5 plots, and slight to very slight contamination with Pb.

144


After 18 months when additional 5% and 0.5% levels of spent oil and poultry manure respectively, were applied to the soil, the A5 soil showed severe risk levels of these heavy metals. This indicated that Ni, Pb, Zn, and Cu are commonly associated with contamination and toxicity problems in soils as earlier reported by Alloway and Ayres (1997). Copper at this level of concentration has been reported to inhibit plant growth, and interfered with several cellular processes in plants (Devez et al., 2003), and Pb and Zn at these levels can suppress homeostatic mechanism in microorganisms (Ernst, 1996).

Within 18 to 36 months, after oil contamination, the Gliricidia, Leucaena and Calapogonium reduced the c/p index Pb, Zn and Cu (Table 3). The Gliricidia sepium alone was more effective in reducing toxicity levels of these heavy metals. The c/p index of Pb, Zn, and Cu in the treated soils showed gradual reduction in 18, 24, 30 and 36 months. This is an indication that these legumes plants are promising in phytoremediation of heavy metal contaminated soils.

Table 2: Heavy metal content of the top 0 – 30cm soil of oil contaminated site as influenced by the treatments.

Treatment PH(H2O) PH (KCl) Ni Pb Zn Cu

mg kg-1

3rd Month

A5 3.7 3.3 2.4 15.3 31.4 39.0

A5 + Gl 3.8 3.3 2.2 15.2 30.9 30.1

A5 + Le 4.0 3.8 2.2 15.9 30.4 30.6

A5 + Ca 3.9 3.5 2.1 15.0 30.1 29.2

A5 + Pm 4.0 3.7 2.1 17.5 43.6 48.3

A5 + Gl + Pm 4.2 4.0 2.1 17.2 42.1 32.6

A5 + Le + Pm 4.4 4.0 2.1 17.3 41.5 33.1

A5 + Ca + Pm 4.1 3.8 2.1 17.3 41.8 30.9

C 4.0 3.5 0.3 1.0 18.6 7.1

LSD (0.05) 0.67 0.53 NS 0.5 0.6 7.0

6th Month

A5 3.1 3.0 2.3 15.1 32.7 30.29

A5 + Gl 3.6 3.4 1.1 15.0 30.8 28.3

A5 + Le 3.8 3.5 1.2 14.8 31.0 28.6

A5 + Ca 3.8 3.6 1.4 15.0 31.6 28.7

A5 + Pm 4.1 3.7 2.1 17.1 44.7 36.0

A5 + Gl + Pm 4.4 4.2 1.7 16.0 38.1 30.2

A5 + Le + Pm 4.3 4.0 1.7 16.2 39.5 29.7

A5 + Ca + Pm 4.4 4.0 1.9 15.2 39.2 29.1

C 4.3 4.0 0.2 1.2 18.3 7.1

LSD (0.05) 0.36 0.28 0.3 0.1 0.8 1.8

12th Month A5 3.2 3.0 3.9 8.2 40.8 38.8 A5 + Gl 4.1 3.8 2.4 6.9 33.1 26.9 A5 + Le 3.8 3.6 2.4 6.8 34.5 27.7 A5 + Ca 4.5 4.1 2.4 7.0 33.8 27.1 A5 + Pm 3.8 3.6 2.5 9.9 46.4 33.4 A5 + Gl + Pm 4.8 4.2 2.2 7.1 38.1 28.1 A5 + Le + Pm 4.2 4.0 2.3 7.2 38.4 29.4 A5 + Ca + Pm 4.1 4.0 2.4 7.1 38.5 29.5 C 4.3 3.9 0.2 1.0 18.7 7.1

145


LSD (0.05) 0.85 0.36 0.4 0.2 0.6 0.4 18th Month A5 3.1 3.0 3.9 28.0 45.8 42.6 A5 + Gl 4.6 4.3 1.1 15.1 24.8 37.9 A5 + Le 4.1 3.8 1.1 15.3 31.2 36.2 A5 + Ca 4.3 4.1 1.3 15.2 31.6 31.3 A5 + Pm 3.7 3.5 1.9 16.2 43.4 40.8 A5 + Gl + Pm 4.8 4.4 1.0 15.3 39.1 36.7 A5 + Le + Pm 4.6 4.4 1.3 15.4 30.4 39.2 A5 + Ca + Pm 4.8 4.4 1.2 15.4 31.2 38.1 C 4.2 4.0 0.2 1.5 17.6 10.0 LSD (0.05) 0.81 0.3 0.1 0.1 0.4 0.1

24th Month

A5 3.1 4355 3.9 28.1 44.7 38.7 A5 + Gl 4.8 3866 0.9 15.0 21.5 26.0 A5 + Le 4.3 3894 0.9 15.2 26.0 27.0 A5 + Ca 4.4 4011 0.9 15.2 26.8 27.1 A5 + Pm 3.8 4024 0.3 16.3 33.9 33.2 A5 + Gl + Pm 4.8 3668 0.8 14.2 30.6 27.7 A5 + Le + Pm 4.8 3699 0.8 14.3 36.6 28.4 A5 + Ca + Pm 4.6 3681 0.8 14.6 30.1 28.0 C 4.2 3079 0.3 1.4 17.7 7.1 LSD (0.05) 0.26 27.9 0.0 0.1 0.2 0.4 30th Month A5 3.4 4429 4.0 28.0 44.3 39.0 A5 + Gl 4.8 3776 0.8 19.7 21.2 21.2 A5 + Le 4.6 3801 0.8 10.8 26.1 25.1 A5 + Ca 4.8 3874 0.8 10.9 26.6 25.3 A5 + Pm 3.7 3882 1.3 10.2 30.7 28.1 A5 + Gl + Pm 4.8 3364 0.7 11.0 27.4 22.0 A5 + Le + Pm 4.6 3386 0.7 10.1 29.3 22.6 A5 + Ca + Pm 4.8 3400 0.1 10.0 29.1 23.9 C 4.2 3057 0.2 1.1 17.9 7.3 LSD (0.05) 0.14 22.9 0.1 0.1 0.1 0.6 36th Month A5 3.4 3946 4.0 28. 44.5 38.3 A5 + Gl 4.8 3674 0.8 10.5 20.9 20.6 A5 + Le 4.8 3689 0.8 10.6 25.3 22.1 A5 + Ca 4.7 3880 0.8 10.7 25.7 22.7 A5 + Pm 3.8 3981 1.0 10.1 30.0 27.0 A5 + Gl + Pm 5.0 3119 0.6 2.8 25.9 19.1 A5 + Le + Pm 4.8 3321 0.7 3.1 27.6 19.3 A5 + Ca + Pm 5.1 3472 0.6 3.3 27.9 19.1 C 4.1 3015 0.2 1.0 17.8 7.3 LSD (0.05) 0.37 121.3 0.0 0.0 0.1 0.1 100a 100a 70d 60a

a = Threshold tolerable limit (Kabata-Pendias and Pendias, 1984).

Table 3: C/p index of the soil and some heavy metals as modified by the treatments

Treatment Ni Pb Zn Cu

3rd Month A5 0.024a 0.16b 0.45c 0.65d A5 + Gl 0.022a 0.15b 0.44c 0.50c A5 + Le 0.022a 0.15b 0.44c 0.52d A5 + Ca 0.021a 0.15b 0.43c 0.47c A5 + Pm 0.021a 0.18b 0.63d 0.81e A5 + Gl + Pm 0.021a 0.17b 0.60d 0.55d

3.0

4.3 4.1 4.1 3.5 4.4 4.6 4.5 4.0 0.22 3.2 4.6 4.3 4.7 3.6 4.6 4.5 4.7 4.0 0.22 3.3 4.7 4.5 4.5 3.6 4.8 4.5 5.0 4.0 0.30

146


A5 + Le + Pm 0.21a 0.18b 0.59d 0.55d A5 + Ca + Pm 0.21a 0.17b 0.60d 0.52d C 0.003a 0.01a 0.27c 0.12b 6th Month A5 0.023a 0.15b 0.47c 0.51d A5 + Gl 0.011a 0.15b 0.44c 0.47c A5 + Le 0.012a 0.15b 0.44c 0.48c A5 + Ca 0.015a 0.15b 0.45c 0.48c A5 + Pm 0.021a 0.17b 0.64d 0.60d A5 + Gl + Pm 0.017a 0.16b 0.55d 0.51d A5 + Le + Pm 0.018a 0.16b 0.57d 0.49c A5 + Ca + Pm 0.019a 0.15b 0.56d 0.49c C 0.002a 0.02a 0.26c 0.12b 12th Month A5 0.039a 0.08a 0.58d 0.65d A5 + Gl 0.024a 0.06a 0.47c 0.45c A5 + Le 0.024a 0.07a 0.49c 0.46c A5 + Ca 0.024a 0.07a 0.48c 0.45c A5 + Pm 0.025a 0.10a 0.66d 0.56d A5 + Gl + Pm 0.022a 0.07a 0.55d 0.47c A5 + Le + Pm 0.023d 0.07a 0.55d 0.49c A5 + Ca + Pm 0.024a 0.07a 0.55d 0.49c C 0.003a 0.01a 0.27c 0.12b 18th Month A5 0.039a 0.28c 0.63d 0.71d A5 + Gl 0.011a 0.15b 0.36c 0.63d A5 + Le 0.011a 0.15b 0.45c 0.60d A5 + Ca 0.013a 0.15b 0.45c 0.52d A5 + Pm 0.019d 0.16b 0.62d 0.68d A5 + Gl + Pm 0.010a 0.15b 0.56d 0.61d A5 + Le + Pm 0.013a 0.15b 0.44c 0.65d A5 + Ca + Pm 0.012a 0.16b 0.45c 0.65d C 0.003a 0.02a 0.25b 0.17b 24th Month A5 0.039a 0.28c 0.64d 0.65d A5 + Gl 0.009a 0.15b 0.31c 0.44c A5 + Le 0.009a 0.15b 0.37c 0.45c A5 + Ca 0.009a 0.16b 0.38c 0.45c A5 + Pm 0.003a 0.14b 0.49c 0.55d A5 + Gl + Pm 0.008a 0.15b 0.45c 0.46c A5 + Le + Pm 0.008a 0.15b 0.44c 0.48c A5 + Ca + Pm 0.008a 0.15b 0.43c 0.47c C 0.003a 0.02a 0.25b 0.12b

30th Month

A5 0.040a 0.28c 0.63d 0.65d

A5 + Gl 0.008a 0.11b 0.31c 0.36c

A5 + Le 0.008a 0.12b 0.37c 0.42c

A5 + Ca 0.003a 0.11b 0.38c 0.42c

A5 + Pm 0.013a 0.10b 0.44c 0.47c

A5 + Gl + Pm 0.007a 0.11b 0.39c 0.37c

147


A5 + Le + Pm 0.007a 0.10b 0.42d 0.38c

A5 + Ca + Pm 0.007a 0.10b 0.42c 0.40c

C 0.002a 0.011a 0.26c 0.12b

36th Month

A5 0.04a 0.28c 0.64d 0.64d

A5 + Gl 0.01a 0.11b 0.30c 0.35c

A5 + Le 0.01a 0.11b 0.36c 0.37c

A5 + Ca 0.01a 0.11b 0.37c 0.38c

A5 + Pm 0.01a 0.10b 0.43c 0.45c

A5 + Gl + Pm 0.01a 0.03a 0.37c 0.32c

A5 + Le + Pm 0.01a 0.03a 0.40c 0.32c

A5 + Ca + Pm 0.01a 0.03a 0.40c 0.32c

C 0.002a 0.01a 0.26c 0.12b

a = Very slightly contaminated

b = Slightly contaminated

c = Moderately contaminated

d = Severely contaminated

e = Very severely contaminated

CONCLUSION

It is indicated that Gliricidia sepium, Leucaena

leucocephala and Calapogonium cerulean can

mitigate toxicity levels of Ni, Pb, Zn and Cu

and also reduce soil acidity. Within 18 to 36

months, there was general reduction in c/p

index for Pb, Zn, and Cu in plots treated with

legume plants. Consequently, they are an

excellent bioremediators of heavy metal

contaminated soils, and can be exploited in

clean-up of heavy metal contaminated soils.

However, the absence of any adverse growth

effect on these plants highlight the danger of

these metals being bioavailable to consuming

animals or humans through the food chain.

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149


CHARACTERIZATION, CLASSIFICATION AND MANAGEMENT OF OLOKORO

SOILS UMUAHIA, ABIA STATE NIGERIA FOR INCREASED DIOSCOREA

DUMETORUM YIELDS.

ONYEKWERE, I.N.1, NWOSU, P .O.1, EZENWA, M . I. S.2 AND ODOFIN, A. J.2

1 Soil Science Division, NRCRI Umudike Abia State.

2 Soil Science Department, FUT Minna Niger State.

Email [email protected]

ABSTRACT

Trifoliate yam (Dioscorea dumetorum) is an important food security crop in Nigeria, it occupies

a prominent position in the diets and farming systems in the South East agroecological zone

especially in Abia State. Olokoro Soils, Umuahia South, Abia State, Nigeria grown to Trifoliate

yam (Dioscorea dumetorum) were studied characterised and classified. Profile pits were dug and

studied, using the rigid grid survey techniques, soil samples from pedogenetic horizons were

collected processed and analysed, and results showed that the soils colour ranged from dark

grayish brown (10 YR 4/2) to dark reddish brown, (5 YR 4/2), the soils were weakly to strongly

aggregated, and posses loamy sand to sandy clay loam textures. pH ranged from 4.5 to 4.9

organic carbon ranged from 5 to 36mg kg-1. The exchangeable bases and CEC were low while

the base saturation ranged from 31 to 50%.

Based on the criteria of soil Taxonomy the soils have been classified as Haplic Nitosol in the

FAO/UNESCO Soil Map of the world legend. Integrated use of lime inorganic and organic

fertilizer is recommended to ameliorate the soils and to increase and sustain good yields

Key words: Characterization, Classification, Management, Olokoro Soils, Dioscorea

Dumetorum, Yields.

INTRODUCTION Trifoliate yam (Dioscorea dumetorum) is an

all important food security crop in Nigeria and

variously grown by resource poor farmers.

Mostly women who intercrop it with maize,

vegetables, cassava, okra cowpea etc. it

occupies a prominent position in the diets and

farming systems in South Eastern Agro-

ecological Zone especially in Abia State,

Nigeria.

Nutritionally Dioscorea dumetorum is superior

to commonly consumed yams, having high

protein, minerals and vitamins most especially

vitamin A contents. Research has shown that

it contains crude protein content of 11.07%,

fibre content of 2.06% and total carotenoid

content of 217.73 (ug/100g) (Ezeocha et al.

2009).

The cultivation of this medicinal crop is

seldom practiced now, and not much research

attention is given to it. And can be included

among the neglected crops. The problem of its

neglect extends to yield. This low yield can

be attributed to inherent low fertility of the

soils because soil is a vital natural resources

in which many agricultural activities take

150

Onyekwere, Nwosu, Ezenwa and Odofin NJSS/22(1)/2012

place, so must be managed to guarantee high

productivity and sustain yield.

Adoption of soil management option that will

guarantee high productivity basically depends

on the nature and properties of the soil.

Characterization of soil is helpful in the

appraisal of soil productivity (Mgbagwu et al,

1983) and as well determines optional type of

soil management.

However, for Dioscorea dumetorum, farmers

in Olokoro Umuahia Abia State, Nigeria

recorded an increase in the present yields. The

knowledge of the soil properties and

classification will enable their proper use,

management and technology transfer.

Therefore, the objective of this work was to

characterize and classify Olokoro soils,

Umuahia, Abia State, Nigeria and give

possible management measures for an increase

in Dioscorea dumetorum yields.


The surveyed area covered about 600 hectares

and is located in Olokoro Umuahia South

Local Government Area (LGA) of Abia State

Nigeria. The area falls within the tropical

rainforest zone and lies between latitude 50 271

and 50 28 N and 70 291 to 70 321 E, situated at

the elevation of 154.25m cutting across

Federal Girls College Umuahia through

National Cereals Research Institute Amakama

Olokoro Outstation to National Root Crops

Research Institute Umudike, representing the

three geographical locations of Olokoro

(Azuiyi, Epe and Umutowe).

The soils are derived from coastal plain sand.

The total annual rainfall of the area is about

2.200mm, the mean annual temperature is

about 310C and the mean annual relative

humidity is about 75%. The soils occupy very

complex upper, middle and lower slopes

positions but the overall micro-relief consist of

slightly undulating to gently sloping terrain of

not more than 3% gradient.

A detailed soil survey using the rigid grid

format was conducted. Transverses were cut

along a properly aligned base line at 300m

intervals while auger borings were made at

25cm interval to a depth of 100cm. Physical

and morphological (colour, texture, structure,

consistency and inclusions) soil descriptions

were made, Following which three soil units

were delineated. Then three profile pits were

dug and described according to the guideline

for profile pit description (Soil Survey Staff,

1998). Soil samples were collected from

identified soil horizons packaged in soil bags,

then labeled and transported to the laboratory

for analysis.

The soil samples were air dried, gently

crushed, sieved through a 0.5mm sieve

because of organic carbon and total Nitrogen

and analysed in the laboratory using standard

routine methods. Soil pH (H20) was

determined in 1:2 soil/water suspensions using

a glass electrode. Organic carbon was

determined using Walkey and black titration

method, total nitrogen was determined using

Kyeldahl method; available phosphorus was

determined using Bray P 1 of Bray and Kurtz

method. Exchangeable bases were extracted

using IN NH4OAC at pH 7 and determined by

the EDTA titration method and Ca, K and Na

by flame photometry method and Mg by

EDTA titration, using Molybdenum blue

Colorometry.


Meteorological Properties

The Meteorological data of the study area are

shown in Table 1.

151

Classification of Olokoro soils

Table 1: Ten Years Meteorological Data of the Study Area

Temperature (oC) Rainfall (mm) Rel humidity (%) Sunshine

Year Minimum Maximum Days Amount 1500 900 Hours

1999 22.67 31.10 159 2701.3 63 79 4.6

2000 23.25 31.92 138 1680.6 66 77 4.2

2001 22.33 31.33 137 2351.4 64 79 4.5

2002 22.67 31.25 137 2351.4 64 79 4.4

2003 22.83 31.75 134 2256.5 66 79 4.1

2004 22.42 31.92 123 1911.4 63 78 4.1

2005 22.50 32.08 147 2064.8 67 80 4.3

2006 22.75 31.50 122 2038.3 66 81 4.9

2007 22.42 31.67 142 2416.7 62 76 4.1

2008 22.58 31.50 141 2395.6 61 76 4.7

Source: National Cereals Research Institute Amakama Olokoro Out-station Meteorological Unit.

Morphological Properties

Data of the morphological properties of the soils studied are shown in Table 2.

Table 2: Field Morphological Description of Pedons Studied Horizon Depth Matrix

Colour

Texture Structure Consistency

(Moist)

Boundary Other

Feature

Pedon 1

AP 0-15 5YR 3/2 LS 1fsg vfr Cs m2rts

AB 15-35 5YR 4/3 SL 1fsbk fr Gs m2rts

Bt1 35-70 5YR 4/6 SCL 2msbk fr Cs f2rts

Bt2 70-110 5YR 4/4 SCL 2msbk fr Gs m2rts,

3chcl

Bt3 110-150 5YR 3/2 SL 2msbk fr - f2rts, 3chcl

Pedon 2

AP 0-27 5YR ¾ SL 2msbk sfm Cw m1rts,m3rts

AB 27-56 5YR 5/6 SCL 2msbk fm Gw m1rts

Bt1 56-98 5YR 5/6 SCL 2msbk fm Cw f2rts

Bt2 98-150 5YR 4/6 SCL 2msbk vfm - f2rts

Pedon 3

AP 0-15 10 YR 4/2 SL 1msg fr Gw m1rts

AB 15-40 10 YR 4/3 SL 1msbk fr Gw m1rts

Bt1 40-85 10 YR 4/4 SCL 2msbk fr Gw f1rts

Bt2 85-120 7.5 YR 5/4 SCL 2msbk fm Gw f2rts

Bt3 120-150 7.5 YR 5/6 SCL 2msbk fm - f2rts

Short hand Notation and Meaning for Table 1:

Boundary: a = abrupt, b = broken, c = clear, d = diffuses, s = smooth, w = wavy, I = irregular.

When a dash (-) is present the property is not recorded.

Structure: sbk = sub angular blockly, sg = single grained, c = coarse, cr = crumb, f = fine, m =

medium, l = weak, 2 = moderate, 3 = strong.

Consistency: Sfm = slightly firm, frm = firm, vfm = very friable, fr = friable.

Texture: s = sand, SCL = sandy clay loam, Sl = sandy loam, LS = loamy sandy.

Remarks: rts = roots, m = many, c = common, f = few, q = fine, 2 = medium, 3 = coarse, Fe-mm

= manganiferrous concretion

Qtz = quartz fragments, Fe = iron nodules, chcl = Charcoal

152


Morphological Properties

The field morphological properties of the

pedons studied are presented in table 2. The

soils include very deep drained, loamy sand to

sandy clay loam dark grayish brown (10 YR

4/2) to dark reddish brown (5 YR 3/2) at the

upper horizon, sandy clay loam dark brown

(10 YR 4/3) to dark reddish brown (5 YR 3/2)

moist at the sub-soils. The rather deep nature

of the soils can be attributed to the nature of

the parent materials of the soils, which is

coastal plain sands (Federal Ministry of

Agriculture and Natural Resources, 1990).

The loamy sand to sandy clay texture of the

soils confers a weak single grained to

moderate medium sub-angular blocky

structure.

Physical properties

The physical properties of the pedons studied are shown in table 3.

Table 3: Physical Properties of the Pedons Studied

Horizon Depth Particle Size clay

(%)Silt

(%)

Silt

Clay +

Silt

(%)

Silt/Clay

Ratio

Texture

Class

Pedon 1

Ap 0-15 81.40 14.80 18.6 18.60 0.22 LS

AB 15-35 80.80 16.80 2.40 19.20 0.14 SL

Bt1 35-70 71.81 16.79 3.40 28.20 0.14 SCL

Bt2 70-110 73.81 24.80 3.39 26.20 0.15 SCL

Bt3 110-150 75.80 18.80 5.40 24.20 0.29 SL

Pedon 2

Ap 0-27 76.60 21.60 1.80 23.40 0.08 SL

AB 27-56 77.52 19.78 2.70 22.50 0.14 SCL

Bt1 56-98 68.01 29.59 2.40 32.00 0.08 SCL

Bt2 98-150 62.01 36.00 1.40 37.40 0.04 SC

Pedon 3

Ap 0-15 86.24 9.20 4.56 13.76 0.50 SL

AB 15-40 78.24 19.20 2.56 21.76 0.13 SL

Bt1 40-85 72.24 24.20 3.56 27.76 0.15 SCL

Bt2 85-120 72.24 25.20 2.56 27.76 0.15 SCL

Bt3 120-150 73.24 25.20 1.56 26.76 0.06 SCL

Particle Size Distribution

The sand fraction of the pedons studied ranged

from 62.01 to 86.24%, in pedon one it

decreased down the depth, whereas there was

no definite pattern of distribution in the other

pedons.

The silt content ranged from 1.40 to 18.60%

and did not maintain any particular pattern of

distribution. The clay content ranged from

9.20 to 36.00%, and increased with depth in

pedon three which is as a result of elluviation-

illuviation processes going on in the soils and

it fails to maintain any pattern of distribution

in other pedons. (Silt + Clay) % values of the

soils ranged from 13.76 to 37.40%, which is

corroborated by Ezenwa (1987).

The values of silt/clay ratio of the soils ranged

from 0.04 to 0.50, an indication that apart from

soils of AP and Bt3 horizons in pedon 1 and

AP horizon in pedon 3 all the soils are old

soils derived from old parent materials

Ayolagha (2001) reported that “old” parent

materials usually have silt/clay ratio less than

0.15 with low degree of weathering, and

Asmoa (1985) reported that soils with silt/clay

ratio less than 0.25 indicates low degree of

weathering.

153


Textural Classification

The textual classification of the AP horizons in

all the pedons studied ranged from sandy loam

to sandy clay loam. Generally the textual

classification of these soils agrees with

optimum criterion of light medium loams,

sandy soils (Onyekwere et al 2009) required

for unhindered anchorage and bulking of roots

and tubers and for easy harvest. This gives the

indication that these soils are conducive for

Dioscorea dumetorum production

Primary Nutrients N, P and K are primary nutrients most

commonly demanded by root and tuber crops

most especially Dioscorea dumetorum as well

as other crops in plant nutrition. This explains

why most compound fertilizers and fertilizer

requirements for this crop are based on N, P

and K (Onyekwere et al 2009). The results of

these nutrients are shown in Table 4

Table 4: Primary Nutrients of the Pedons Studied

Horizon Depth (cm) Total N (%) Available P

(mgkg-1)

Exchangeable

K

Cmol (+) kg-1

Pedon 1

Ap 0-05 0.14 36.00 0.07

AB 15-35 0.11 36.00 0.03

Bt1 35-70 0.06 18.00 0.04

Bt2 70-100 0.08 30.00 0.04

Bt3 100-150 0.10 31.00 0.03

Pedon 2

Ap 0-27 0.21 33.00 0.07

AB 27-56 0.16 8.00 0.04

Bt1 56-98 0.15 7.00 0.40

Bt2 98-150 0.14 5.00 0.03

Pedon 3

Ap 0-15 0.08 9.00 0.02

AB 15-40 0.06 11.50 0.03

Bt1 40-85 0.04 15.50 0.03

Bt2 85-120 0.01 15.60 0.01

Bt3 120-150 0.01 20.00 0.05

Total Nitrogen

The total nitrogen content of the soils studied

ranged from 0.01 to 0.21%. apart from soils of

Pedon 1 the values of other Pedons decreased

down the slope. The surface soils (AP

horizons) had total nitrogen content range of

0.08 to 0.21% with a mean value of 0.14%.

Apart from that of pedon 2 that had value

exceeding the critical level of 0.15% required

for sustainable Dioscorea dumetorum

production. The remaining pedons studied

were deficient in total N. The low content of

total N in the soils could be attributed to low

organic matter of these soils, since inorganic N

is accounting for only a small portion of total

N in soils (Almu and Audu 2001). The low

amount of total N reflects the amount of

organic carbon in the soils. Variable response

to applied nitrogen was thus expected in these

soils.


The available phosphorus values of the pedons

ranged from 7.00 to 36.00 mgkg-1. Pedon 1

had no definite pattern of distribution of

available P. Pedon 2 values decreased with

depth, while those of pedon 3 increased with

depth. The upper horizons had values that

ranged from 9.00 to 36.00 mgkg-1, with a

mean value 26 mgkg-1. The mean value

154


obtained exceeded the critical limit of

8.0mgkg-1. Bray 1-P established for crops in

South Eastern Nigeria including Dioscorea

dumetorum (FPDD) 1989) and the critical

level of 15 mgkg-1 Bray 1 extractable P

recommended by Thomas and Peaslee (1973)

cited by Onyekwere et al. (2009). This result

showed that the soils had the available P

requirement for Dioscorea dumetorum

production.

Exchangeable Potassium

The values of the exchangeable K of the soils

studied ranged from 0.01 to 0.07 cmol (+) kg-1.

Pedons 1 and 3 did not maintain any definite

pattern of distribution of exchangeable K,

while values of pedon 2 decreased with depth.

The surface soils had values that ranged from

0.02 to 0.07 cmol (+)kg-1, with a mean value of

0.05 cmol (+)kg-1, having values below the

critical limit of 2.0 cmol (+)kg-1 recommended

for soils of South Eastern Nigeria (FPDD)

1989),for Dioscorea dumetorum production.

These suggest that all the soils will show

substantial responses to applied potassium.

According to Chukwu (1997), Olokoro

farming area is subjected to annual and

seasonal bush burning which occur about

January to April. Burning deprives the soils of

natural organic matter from vegetation and

exposes the soils to erosive impact of heavy

annual precipitation (about 2000mm) in this

area. This aggravates leaching due to the

coarse nature of the soils. There is high

demographic pressure in the area necessitating

unavoidable pressure on the land in quest for

food and money with consequential reduction

in fallow periods. These factors explain the

deficiencies of total N and exchangeable K

observed.

Table 5: Selected Chemical Properties of the Pedon Studied

Horizon Depth

(cm)

pH

(H20)

0C

%

Exchangeable

Bases

Ca Mg Na

Exch. Acidity CEC

(cmol (+)Kg-1 NH4OAC

ECEC Base

Salt

(%)

Pedon 1

Ap 0-15 4.9 2.06 0.58 1.65 0.09 1.40 6.29 3.80 38.00

AB 15-35 4.9 1.50 0.39 1.15 0.04 1.60 6.42 3.20 50.00

Bt1 35-70 4.8 0.70 0.39 0.96 0.09 1.40 3.10 2.90 48.00

Bt2 70-100 4.8 0.90 0.39 0.96 0.10 1.20 2.98 2.80 50.00

Bt3 100-150 4.9 1.75 0.80 1.60 0.08 5.2 7.90 7.72 32.6

Pedon 2

Ap 0-27 4.9 2.27 0.30 2.50 0.09 6.10 11.19 8.86 31.00

AB 27-56 4.7 1.27 0.80 1.60 0.08 5.20 7.88 7.72 32.60

Bt1 56-98 4.8 0.99 1.00 1.40 0.09 5.20 8.25 8.09 35.70

Bt2 98-150 4.7 0.69 0.60 1.60 0.08 5.30 10.00 7.81 32.00

Pedon 3

Ap 0-15 4.9 1.75 0.40 0.60 0.06 0.80 2.70 1.88 40.00

AB 15-40 4.7 0.99 1.46 0.70 0.02 2.00 4.42 4.21 50.00

Bt1 40-85 4.8 0.66 1.16 0.77 0.04 4.00 6.06 4.00 33.30

Bt2 85-120 4.5 0.67 1.65 0.15 0.01 2.10 3.96 2.35 46.00

Bt3 120-150 4.9 0.16 1.16 0.38 0.08 1.00 3.90 3.10 41.00

155


Selected Chemical Properties

Selected chemical properties of the pedons

studied are presented in Table 5.

Soil Reaction

The soil reaction expressed as pH (H20) were

strongly acidic, with a range of 4.5 to 4.9.

There was no definite pattern of changes in pH

down the slope in all the pedons studied. The

AP horizons had an average value of 4.9.

Liming the soils and increasing the base status

with organic manure provides good

amelioration option for Dioscorea dumetorum

yield.

Organic Carbon

The organic carbon content varied from very

low to moderate that is from 0.70 to 2.27%.

They were distributed irregularly down the

slope, apart from pedon 2 where it decreased

down the slope. The AP horizons had a value

range of 1.75 to 2.27% with a mean value of

2.03%. Maintenance of a satisfactory organic

matter status is essential to the production of

most of the Nitrogen and half of the

Phosphorus taken up by unfertilized crops

(Von Uxekull 1986), including Dioscorea

dumetorum

Exchangeable Bases

The soils are very low in their content

exchangeable Ca, with surface soils value that

varied from 0.30 to 0.58 cmol (+)kg-1.

Exchangeable Mg in the surface soils were

moderate with values that varied from 0.60 to

2.50 cmol (+)kg-1, while exchangeable Na

were low ranging from 0.06 to 0.09 cmol

(+)kg-1.

Effective Cation Exchange Capacity

(ECEC)

ECEC values of the soils varied from 1.88 to

8.86 cmol (+) kg-1. This result indicates that

the effective Cation Exchange Capacity of the

soils is low. The low ECEC and nutrient

reserves of the soils have been attributed to the

fact that soils of South Eastern Nigeria are

strongly weathered have little or no content of

weatherable rock in sand and silt fraction and

have predominantly kaolinite in their clay

fractions (FPDD, 1989).

Classification of the Soils

The soils were classified according to the

USDA Soil Taxonomy (Soil Survey Staff

1975) and correlated with the FAO/UNESCO

Soil Legend (FAO/UNESCO 1988). Table 6.

The soils are formed under udic moisture

regime. There is an evidence of argillic,

horizon, and presence of an old and well

developed B horizon, so the three pedons were

therefore classified as ultisols. The soil finally

met the requirement for classification as Typic

Paleudult under the subgroup level. In the

FAO/UNESCO all the soils of the three

pedons were classified as Dystric Nitosol.

Table 6: Taxonomic Classification of Soils Studied

Pedon USDA FAO/UNESCO

Pedon 1 Typic Paleudult Haplic Nitosol



CONCLUSION AND RECOMMENDATION From the study it was revealed that the soils

were deep, well drained, loamy sand to sandy

clay loam, dark grayish brown to dark reddish

brown, acidic, with low to moderate nitrogen,

low exchangeable K and organic carbon

content while the available P contents were

low to high. The textual classification of the

soils were conducive for the production of

Dioscorea dumetorum. The soils were

classified as Typic Paleudult under USDA soil

156


Taxanomy and as Dystric Nitosol under

FAO/UNESCO system.

For sustainable increase in the production of

Dioscorea dumetorum, the following

recommendations are made:

Stop burning of grasses after clearing of

farms.

Living the crop residues after harvesting.

Liming the soils to an appreciable pH level at

the rate of 0.5 to 1 ton/ha .

Use of organic fertilizer to increase the organic

carbon base of the soils.

Nitrogen fertilization at the rate of 90kgN/ha

for pedon 1 and 3, 45kgN/ha for pedon 2 to

increase the total N content of the soils. Phosphorus fertilization at the rate of 25mgkg-1 for pedons 2 and 3 and Potassium fertilization

at the rate of 75kg K20/ha for all the pedons to

increase the exchangeable K content. (or

application of 600kg NPK/ha)

REFERENCES

Almu, H, and Audu M.D. (2001). Physico-

chemical Properties of Soils of A' Awa

Irrigation Project Area Kano State in

Management of Wetland Soils for

Sustainable Agriculture and

Environment. Pp 135-139.

Asomoa. G.K. (1983). Particle size and free

Iron oxide distribution in some

Latosols and ground water Lacterites

of Ghana Geoderma 10:285-297.

Chukwu, G.O (1997). Conserving uplands

through sloping agriculture Land

technology. Proceeding Forestry

Association of Nigeria Conference

Ibadan. Pp 293-298.

Ezenwa, M .1.S. (1987). Some physico-

chemical Characteristics of Soils Is of

Basement Complex and Adjoining

Basaltic Rocks of Northern part of

Nigeria in Soil Resources for Rural

Development. Pp 205-214.

Ezeocha, V.C., Oti, E, Etudaye H and Aguyo

(2009). Effect of Variety on the

Chemical Composition of Trifoliate

Yam (Dioscorea dumetorum) in Global

food crisis and Nigerian Agriculture.

Pp 963-964.

FAO/UNESCOP, (1988). Soil Map of the

World. World Soil Resources Report

60 F AO, United Nations, Rome.

FMA and NR, (1990). Literature Review on

Soil Fel1ility Investigation in Nigeria

(in five folumes). Federal Ministry of

Agriculture and Natural Resources

Abuja. Pp 281.

FPDD (1989). Literature on Soil Fertility

Investigation in Nigeria produced by

the Federal Ministry of Agriculture

and Natural Resources Lagos.

Mbagwu, J.S.C. Lal, R. and Scott T.W.

(I983). Physical properties of 3 soils in

Southern Nigeria Soil Sci. 136(1 )48.

Onyekwere, I.N, Chukwu, G.O. and Ano, A.O.

(2009). Characteristics and

Management of Soils of Akamkpa

Area, Cross River State Nigeria for

increased Cocoyam Yields. Nig. Agric.

Journal 40 NO.1:271-278.

Soil Survey Staff (J 975). Soil Taxonomy a

basic system of Soil Classification for

making and interpreting soil surveys

U.S. Govt. Printing Office Washington

D.C.

Soil Survey Staff (1998) Keys to Soil

Taxonomy SMSS Technical

Monograph No. 19 5th edition,

Pocahontas Press Inc. Blacksburg

Virginia.

Von Uxehull H.R. (1986). Efficient fertilizer

use in Acid Upland Soils of the humid

tropics. F AO fertilizer and Plant

Nutrition bulletin No.1 O. 59 pp.

157


RHEOLOGICAL PROPERTIES OF SOIL GROUPS IN CENTRAL SOUTH-EASTERN

NIGERIA IN RELATION TO OTHER PHYSICAL PROPERTIES

E.U. ONWEREMADU, B.N. NDUKWU, G.E. OSUJI AND M.A. OKON

Department of Soil Science and Technology, Federal University of Technology,

P.M.B. 1526 Owerri, Nigeria E-mail: [email protected]

ABSTRACT Rheological properties of soils formed over different parent materials were investigated in

central southeastern Nigeria in 2010. Random sampling technique quided by the geology of the

study area was employed in field studies. A total of 150 soil samples were subjected to

laboratory analyses. Soil data were analyzed using analysis of variance (ANOVA) of the PROC

mix-model of SAS. Means were separated by standard error of difference at 5% level of

probability. Correlation coefficient was used to estimate the degree of relationship between

rheological properties and soil physical attributes. There was significant (p<0.05) positive

relationship between gravimetric moisture content or clay and rheological properties. Sand had

significant (p<0.05) negative relationship with plasticity index.

Keywoards: Parent materials, Rheology, Physical properties, Tropical soils.

INTRODUCTION The strength of soils changes with differences

in soil water content. But, responsiveness of

soil groups to soil water vary due to other

inherent soil attributes as well as management

factors. Brady and Weil, (1999) remarked that

soil moisture, plasticity and particle size of

soils determine stability of soils in response to

loading forces from traffic, tillage and building

foundations.

In central southeastern Nigeria, six major soil

groups were identified as alluvial, coastal plain

sands, false bedded sandstones, lower coal

measures, shale and upper coal measures –

formed soils (Onweremadu, 2006). These soil

groups vary in their soil moisture retention

capacity as well as particle size distribution.

Ndukwe et al. (2009) reported rheological

differences among Nigerian clays. Clay

content, nature of clay, nature of exchangeable

cations and organic matter content of soils

vary, and these influence plasticity and general

activity levels of soils. Clay has much greater

cohesion, plasticity and activity than other

primary soil particles. Differences in the

aforementioned attributes alter hydraulic

properties of soils as including water flow

characteristics of the pedosphere. There exists

spatial heterogeneity in soil water behaviour

(Gerke et al., 2001) and non-uniform water

repellency in different soils under diverse

vegetation types (Dekker et al., 2001) and land

use (Hallet et al., 2004). Based on these, we

investigated variability in rheological

properties of soils formed over different parent

materials in central southeastern Nigeria.

Study Area The study was conducted in the central

southeastern Nigeria (Abia and Imo State)

lying between latitudes 4040’ and 70 15’N, and

158

Onweremadu, Ndukwu, Osuji and Okon NJSS/22(1)/2012

longitudes 6040’ and 8015’E. Soils are derived

from alluvium, coastal plain sands, false

bedded sandstones, lower coal measures, shale

and upper coal measures. Central southeastern

Nigeria is characterized by lowlands except for

North-east lying hilly landscapes. It has a

humid tropical climate with mean annual

rainfall ranging from 1800 to 2500 mm. The

annual temperature ranges from 26oC to 31oC

while its relative humidity is generally high

throughout the year. Central southeastern

Nigeria is a typical rainforest area,

characterized by multiple vegetal forms

dominated by oil palm trees (Elaeis

guineensis). The plants are arranged in tiers

and evergreen.

Field Sampling Prior to field studies, a reconnaissance visit

was made. Field soil sampling was guided by a

geologic map of the study area. Five soil

profile pits were dug on each of the six soil

groups, namely alluvium, coastal plain sands

(Benin formation), false bedded sandstones

(Ajalli formation), lower coal measures

(Mamu formation), shale (Bende-Ameki

formation) and upper coal measures (Nsukka

formation). In all, a total of 30 profiles pits

were dug and described using the FAO (1998)

guidelines. One hundred and fifty soil samples

were used for the study. These soil samples

were air dried and sieved using a 2mm sieve.

In addition to the above, 150 core soil samples

were collected from profile pits based on

horizon differentiation and used for bulk

density determinations.

Laboratory Analysis Particle size distribution was determined by

hydrometer method and bulk density was

estimated by core procedure. Atterberg limits

were determined by Cassagrande method

while plasticity index was computed as liquid

limit minus plastic limit. Soil moisture was

measured gravimetrically.

Data Analysis Soil physical and rheological data were

subjected to analysis of variance of the PROC

Mix model of SAS (Little et al., 1996). Means

were separated using standard error of the

difference at 5% level of probability.

Relationship between rheological properties

and other soil physical properties were

estimated using correlation analysis.

RESULTS AND DISCUSSION Soil physical properties varied significantly

(p<0.05) among soil groups except bulk

density (Table 1). Higher values of sand sized

particles were reported in soils formed over

upper coal measures, alluvium, coastal plain

sands and false bedded sandstones while clay

predominated in soils derived from shale and

lower coal measures. This pattern reflected in

the gravimetric moisture content, with shale-

derived soils having highest value (460 g kg-1)

while least value was reported in soils formed

over upper coal measures (208 g kg-1)

Table 1: Some soil physical properties

Parent Material Sand Silt Clay BD Gm

Gkg-1 (Mgm-3) (g kg-1)

Alluvium

Coastal plain sand

False bedded sandstones

Lower Coal Measures

Shale

Upper Coal Measures

SED 0.05

P-Value

808

694

744

475

377

835

58.3

<0.0001

42

73

73

202

131

32

25.2

<0.0001

150

233

183

323

492

133

45.8

<0.0001

1.45

1.41

1.46

1.42

1.45

1.47

0.03

ns

278

315

288

417

460

208

51.4

<0.0001

BD = bulk density, M = gravimetric moisture content.

159

Rheological properties of soil

Rheological properties of soil groups are

shown in Table 2 and values differ

significantly (P<0.05). Soils formed over shale

and lower coal measures had higher plasticity

values of 32.7 and 22.4, respectively. The

plasticity of these soil groups could be a

reflection of clay content of soils as soils

derived from shale and lower coal measures

indicated higher clay content. Plasticity index

values affected shrinkage behaviour of soil

groups as given by the coefficient of linear

extensibility (Table 2).

Table 2: Rheological soil properties

Parent material LL PL Pl COLE

Alluvium

Coastal plain sand

False bedded sandstones

Lower Coal Measures

Shale

Upper Coal Measures

SED 0.05

P-Value

27.7

9.7

30.0

33.4

59.5

3.5

1.32

<0.0001

3.7

1.4

15.4

11.0

27.8

2.0

0.76

<0.031

24.0

8.3

15.0

22.4

32.7

1.5

0.53

<0.0001

0.011

0.025

0.031

0.058

0.101

0.008

0.004

0.0002

LL = liquid limit, Pl = Plastic limit, P1 = Plasticity index

COLE = Coefficient of linear extensibility.

High clay contents of soils derived from shale

and lower coal measures as opposed to other

four groups imply the possibility of higher

activity in the forms which portends instability

of soils especially under high engineering

activity.

Rheological figures were significant (p<0.05),

indicating positive correlations betwen

rheological attributes and particle size

fractions (Table 3).

Table 3: Relationship between rheological properties and some physical properties (n=150).

Factor Correlated Pearson Correlation Coefficient (r) Significance (P<0.09)

COLE vs m

COLE vs Clay

COLE vs BD

COLE vs Sand

LL vs BD

LL vs Sand

PL vs m

PL vs Clay

P1 vs M

P1 vs BD

P1 vs Sand

0.73

0.61

0.06

0.48

0.03

0.53

0.71

0.65

0.67

0.02

0.31

<0.0001

<0.001

Ns

<0.0001

Ns

<0.0001

<0.001

<0.001

<0.001

ns

ns

COLE = coefficient of linear extensibility, m = gravimetric moisture content, BD = bulk

density, LL = liquid limit, PL = plastic limit, P1 = plastic index.

Atterberg limits (Liquid limit, plastic limit and

plasticity index) had significant (p<0.05)

positive relationship with gravimetric moisture

and clay content. Coefficient of linear

extensibility had strong positive relationship

with gravimetric moisture and clay contents.

These findings suggest possible use of these

soil physical attributes in predicting these

rheological properties in soil groups of central

Southeastern Nigeria. Sand content had

significant (p<0.05) correlation with

rheological properties (Table 3), implying its

160

Onweremadu, Ndukwu, Osuji and Okon NJSS/22(1)/2012

efficacy in predicting soil behaviour in the

study area.

Strong relationship between soil moisture and

plasticity index (r = 0.67, p<0.0001) (Table 3)

indicates that soil moisture is a major

determinant of soil compressibility (McNabb

and Boersma, 1996) among other factors such

as bulk density (1mhoff et al., 2004). But, the

r-value (0.67) suggests that other

undetermined factors could be influencing

plasticity of soil groups.

REFERENCES Dekker L.W., Doerr, S.H., Ooshridie, K.,

Ziogas, A.K. and Ritsema, C.J. (2001).

Water repellency and critical soil water

content in sludge sand. Soil Sci. Soc.

Am. J., 65: 1667-1674.

Food and Agricultural Organization (1998).

Guidelines for soil profile description,

2nd edition/Rome. Pp 66.

Gerke, H.H., Hangen E., W. Schaaf and

Huunfi, R.F. (2001). Spatial variability

in potential water repellency in a

linguistic mine soil afforested with

Pinus Nigra Geoderma. 102: 252-274.

Hallet, P.D., Nunan, N., Douglas, J.T. and

Young, I.M. (2004). Millimeter-scale

spatial variability in soil water

sorptivity: Scale surface elevation and

sub critical repellency effects. Soil Sci.

Soc. Am. J., 68: 352-358.

Imhoff, S., Daa Silva, A.P. and Fallow, D.

(2004). Susceptibility to compaction,

load support capacity and soil

compressibility of Hapludox. Soil Sci.

Soc. Am. J., 68: 17-24.

Little, R.C., G.A., Millikin W.W.., Strong,

R.C. Wolfinger (1996). SAS System

for mixed models. Statistical System

Inc. Cary, North Carolina, U.S.A. 633

pp.

McNabb, D.H. and Boersma, L. (1996). Non-

linear model for compressibility of

partly saturated soils, Soil Science Soc.

Am. J., 60: 333-34.

Ndukwe, O.C.N. Onweremadu, E.U. and U.M.

Nyoyoko (2009). Nigerian local clay:

A possible substitute for bentonite in

drilling fluid (spud mud) based on

rheology int. J. Eng., 3 (3): 311-317.

Onweremadu, E.U. (2006). Application of

geographical information systems on

soils and soil related environmental

problems in Southeastern Nigeria. A

Ph.D Thesis of the Department of Soil

Science, University of Nigeria,

NSUKKA, 330 pp.

161

Rheological properties of soil

RESPONSES OF MELON (COLLOCYNTHIS CITRULLUS ) AND SOIL CHEMICAL

PROPERTIES TO DIFFERENT N - SOURCES IN ADO – EKITI, SOUTHWESTERN

NIGERIA

B. OSUNDARE

Department of Crop, Soil, and Environmental Sciences

University of Ado – Ekiti, Nigeria

ABSTRACT A two – year field experiment was conducted at the Teaching and Research Farm of the University of Ado – Ekiti, Ekiti State, Nigeria, during 2008 and 2009 cropping seasons to determine the effects of different N – sources on soil nutrient status and yield of melon (Collocynthis citrullus). The experiment was laid out in a randomized complete block design with three replicates. The different sources of N were: Calcium ammonium nitrate (CAN), Ammonium sulphate (AS), Urea (U), NPK 15 – 15 – 15 and control i.e. no fertilizer (NF). The results indicated that there were significant (P=0.05) differences among the various N – sources with respect to their effects on soil nutrient status and yield of melon. The percentage decreases in soil organic carbon (SOC) after cropping were 58, 39, 49, 28 and 21 for NF, CAN, AS, U and N P K, respectively. Similarly, application of the different N – sources resulted in decreases in total nitrogen after cropping by 48, 26, 40, 14 and 7% for NF, CAN, AS, U and NPK 15 – 15 – 15, respectively. Averaged over two – years of experimentation, values of melon seed yields were 0.37, 0.61, 0.85, 1.22 and 1.15 t ha-1 for NF, U, CAN, NPK and AS, respectively. Key words: N – sources, fertility, yield, melon.

INTRODUCTION Low soil nitrogen has been reported to be a limiting factor to crop production in many parts of the world (Harriz, 2006; Been et al; 2011). Nitrogen plays key roles in the growth and development of crops. It influences the yields mainly through leaf area expansion, which in turn, increases the amount of solar radiation intercepted, and dry matter production (Cam, 2009; Brader, 2011). In many parts of the world, sources of nitrogen commonly used include Diammonium phosphate (DAP), Calcium ammonium nitrate (CAN), Sulphate of ammonia (SA) or Ammonium sulphate (AS) and compound fertilizers, such as NPK 15 – 15 – 15; 20 – 20 – 20 (Kurtz, 2004; Sas, 2006). Other sources of N include urea and ammonium nitrate, depending on their local availability (Kurtz; 2004). However, the use of sulphate of

ammonia is discouraged due to its high residual acidity (Sas, 2006). Previous studies had demonstrated significant effects of different N – sources on the growth and yield of melon (Adeuya, 2008; Cern, 2010; Mucido, 2010). In all these studies, significant differences among N – sources with respect to their effects on growth and yield attributes of melon were reported. Similarly, significant effects of N sources on major soil nutrients had been demonstrated by Fessil (2009); Cheng (2009); Handra (2011). Elsewhere, in the tropics, few studies had been conducted on the growth and yield of melon, as affected by different sources of N. In view of the paucity of published work on different N sources on melon performance, this study sought to investigate the effects of different

162

Osundare NJSS/22(1)/2012

sources of N on soil nutrient status and melon performance. MATERIALS AND METHODS Study site: A two – year field experiment was carried out at the Teaching and Research Farm of the University of Ado – Ekiti, Ekiti State, Nigeria, during 2008 and 2009 cropping seasons. The soil of the study site is an Alfisol (SSS, 2003) of the basement complex, highly leached, and with low to medium organic matter content. The site of study had earlier been cultivated to certain arable crops, among which were maize, melon, cassava before it was left to fallow for some years prior to the commencement of this study. The fallow vegetation was manually slashed and thereafter, the land was ploughed and harrowed. Collection and analysis of soil samples: Prior to planting, ten core soil samples, randomly collected from 0 – 15 cm top – soil , were bulked to form a composite, which was analyzed for physical and chemical properties. At the end of the second cropping season, another set of soil samples was collected and analyzed. The soil samples were analyzed in accordance with the procedures outlined by IITA (1989).

Experimental design and treatments: The experiment was laid out in a randomized complete block design with three replicates. The N – sources were: Calcium ammonium nitrate (CAN), Ammonium sulphate (AS), Urea (U), NPK 15 – 15 – 15 and control i. e. no fertilizer (NF). All the different N – sources fertilizers were applied at the rate of 200 kg ha-1 (Fondufe, 1995) in two split doses, at four and six weeks after planting (WAP). Planting and weeding: Planting was done on March 12 and March 20 in the respective 2008 and 2009 cropping seasons. Two melon seeds were planted per stand at a spacing of 1 m x 1 m, but later thinned to one plant per stand (10,000 plants ha-1), three weeks after planting. Weeding was carried out manually at 3 and 6 WAP, using a hand hoe. Collection and analysis of data: At harvest, data were collected on yield and yield components of melon. All the data collected were subjected to analysis of variance (ANOVA), and treatment means were compared, using the Duncan Multiple Range Test (DMRT) at 5% level of probability. RESULTS The physical and chemical properties of soil in the study site before cropping are presented in Table 1.

Table 1: The physical and chemical properties of soil in the study site before cropping Parameters Values pH Organic carbon (g kg-1) Total nitrogen (g kg-1) Available phosphorus (mg kg-1)

5.6 0.95 0.58 0.86

Exchangeable bases (cmol kg-1) Potassium Calcium Magnesium Sodium Acidity ECEC

0.44 0.40 0.60 0.51 0.32 2.27

Texture (g kg-1) Sand Silt Clay

680 200 120

163

Effect of N sources on melon and soil

Changes in soil nutrient status after cropping Table 2 shows the soil nutrient status as

affected by N – sources at the end of the

experiment.

CAN resulted in 18% increase in soil pH after

cropping, while contrasting decreases of 18,

32,29 and 46% for NF, AS, U and NPK,

respectively. The percentage decreases in soil

organic carbon (SOC) after cropping were 58,

39, 49, 28 and 21 for NF, CAN, AS, U and

NPK, respectively. Similarly, the percentage

decreases in total nitrogen after cropping were

48, 26, 40, 14 and 7 for the respective NF,

CAN, AS, U and NPK. N – sources decreased

available P after cropping by 47, 38, 28, 21

and 13% for NF, CAN, AS, U and NPK 15 –

15 – 15, respectively. Similarly, decreases in

exchangeable K were 59, 43, 18, 32 and 9%

for NF, CAN, AS, U and NPK, respectively.

Application of CAN resulted in 40% increase

in exchangeable Ca, compared to decreases of

33, 15, 3, and 13% for NF, AS, U and NPK,

respectively. In addition, decreases in

exchangeable Mg were 57, 45, 20, 32 and 43%

for NF, CAN, AS, U and NPK and for Na,

decreases were 65, 51, 26, 39 and 14% for

NF, CAN, AS, U and NPK, respectively.

Table 2: Soil nutrient status as affected by different N – sources after cropping Treatments Org. C Total N Av. P Exchangeable bases (cmol kg-1)

(N-sources) pH (g kg-1-) (g kg-1) (mg kg-1) K Ca Mg Na

Control

CAN

AS

Urea

NPK

4.6b

6.3a

3.8c

4.0c

3.0d

0.40e

0.58c

0.48d

0.68b

0.75a

0.30e

0.43c

0.35d

0.50b

0.54a

0.46e

0.53d

0.62c

0.68b

0.75a

0.18e

0.25d

0.36b

0.30c

0.40a

0.27d

0.56a

0.34c

0.39b

0.35c

0.26d

0.33c

0.48a

0.41b

0.34c

0.18e

0.25d

0.38b

0.31c

0.44a

Mean values in the same column followed by the same letter are not significantly different at

P=0.05

Seed yield, and yield components of melon

Table 3 shows the effects of N – sources on

seed yield, number of fruits per plant and

average fruit weight of melon at harvest.

On the two – year average, values of melon

seed yield were 0.37, 0.66, 0.85, 1.22 and 1.15

t ha-1 for NF, U, CAN, NPK and AS,

respectively. Similarly, values of number of

fruits per plant were 4.3, 6.1, 7.9, 10.4 and 9.0

for NF, U, CAN, NPK and AS, respectively.

Values of average fruit weight were 0.54, 0.70,

0.87, 1.10 and 0.97 kg for NF, U, CAN, NPK

and AS, respectively.

Table 3: Seed yield, number of fruits per plant and average fruit weight of melon as

affected by different N – sources at harvest Treatments Melon seed yield (t ha-1) Number of fruits per plant Average fruit weight (kg)

(N-sources) 2008 2009 Mean 2008 2009 Mean 2008 2009 Mean

Contrtol

Urea

CAN

NPK

AS

0.40e

0.64d

0.89c

1.25a

1.18b

0.33e

0.58d

0.81c

1.19a

1.11b

0.37

0.61

0.85

1.22

1.15

4.6e

6.3d

8.0c

10.6a

9.1b

4.0e

5.9d

7.8c

10.1a

8.8b

4.3

6.1

7.9

10.4

9.0

0.56e

0.71d

0.90c

1.12a

1.00b

0.51e

0.68d

0.83c

1.07a

0.93a

0.54

0.70

0.87

1.10

0.97

Mean values in the same column followed by the same letter are not significantly different at

P=0.05

DISCUSSION

In this study, the decreases in the soil organic

carbon (SOC) after cropping, observed in all

the plots where different N – sources fertilizers

were applied agree with the findings of Kowal

(2009) and Idah (2011), who obtained

significant decreases in soil organic matter

(SOM), at termination of experiments

involving mineral fertilizer application. This

observation can be adduced to the fact that, the

addition of the synthetic fertilizers may have

resulted in the provision of favourable soil

164


conditions for the soil microbes with resultant

stimulated organic matter decomposition. In

view of the decline in SOM, associated with

inorganic fertilization, the addition of organic

fertilizers (plants and animal remains) to

inorganic fertilizers – treated soils is strongly

recommended.

The decreases in virtually all the nutrients after

cropping, observed in the plots where N –

sources fertilizers were not applied (i.e.

control) can be ascribed to uptake by melon as

well as leaching losses. Similarly, the

decreases in the soil pH in the control plots

after cropping can be attributed to decreases in

the exchangeable bases, due perhaps, to

leaching and / or melon uptake. The increase

in soil pH after cropping, associated with

application of CAN can be adduced to the

increase in the value of exchangeable Ca, as

CAN contains Calcium ions (Ca2+). The

decrease in available P and exchangeable K,

Mg and Na can be attributed to melon uptake,

as P is indispensable in the formation of good

root system, flowering and seed production in

plants. The decrease in soil pH (i. e. increased

acidity), observed in the plots where

ammonium sulphate [(NH4)2SO4] fertilizer

was applied can be adduced to the acidifying

effects of ammonium sulphate due to hydrogen

ions (H+), resulting from oxidation of the

ammonium ion (NH4+). Besides, this

observation can be attributed to the decreases

in the exchangeable bases, associated with

ammonium sulphate application.

The decreases in N value after cropping,

obtained in plots where CAN, ammonium

sulphate and urea were applied can be

attributed to melon uptake, leaching and

ammonia volatilization, since these three

fertilizers contain ammonium ions (NH4+),

which are readily reduced to ammonia gas

(NH3) in the soil. Although, differences were

obtained in the quantity of N lost through

ammonia volatilization from these fertilizers,

due to differences in their composition and

properties. For instance, in CAN, half of the N

is in form of NH4+, while the rest half is in

form of nitrate (NO3-) . So, only half of the

applied N (i.e. NH4+ form) is therefore

vulnerable to volatilization, which is a distinct

advantage over the other ammonium –

containing fertilizers. The decreases in N, P

and K values after cropping, despite the

addition of NPK fertilizer, implies that these

nutrient elements were absorbed and utilized

by melon.

The significantly higher value of melon seed

yield for CAN than that of urea agrees with the

findings of Adeuya (2008); Cern (2010);

Mucido (2011). This observation points to the

superiority of CAN to urea, as far as nitrogen

nutrition of melon is concerned. The

superiority of CAN stems from its ability to

supply N in the forms of NH4+ and NO3

-,

compared with urea, that can only supply N in

the form of NH4+. Thus, the presence of NH4

+

and NO3- in CAN accounts for the higher

yield performance of melon in CAN than the

urea (Osaki et al; 1995). Besides, CAN has

Calcium ions (Ca2+) which is an extremely

important element in the maintenance of cell

membrane integrity, as well as cell division,

hence, stimulating growth and development in

plants. Moreover, the calcium element helps

in the neutralization of soil acidity, hence,

enhancing availability of certain nutrient

element in the soil (Kurtz, 2004).

Much as the significant difference in melon

seed yield between CAN and urea can be

ascribed to the aforementioned factors,

however, another factor that can be implicated

for the significant differences between CAN

and urea in melon seed yield performance is

the difference between CAN and urea. This is

in the respect to the amount of N lost in the

form of an ammonia gas through volatilization

from these two N – sources. This is because

the amount of N lost in CAN through

volatilization is not as high as that of N lost in

urea.

The higher value of melon seed yield for

ammonium sulphate than that for urea and

CAN can be attributed to the presence of

165


sulphur in the ammonium sulphate fertilizer,

as sulphur has been reported as one of the

essential nutrient elements needed for

satisfactory growth and development of crop

plants (Osaki et al; 1995). The highest melon

seed yield value consistently recorded for

NPK fertilizer treatment can be ascribed to the

complementary roles of P and K in the

nutrition of melon. Therefore, for a good

melon performance, the recommendation of a

judicious and balanced combination of these

three nutrient elements is imperative.

CONCLUSION

Application of nitrogen from different N –

fertilizer sources resulted in significant

decreases in soil organic carbon , total N,

available P and exchangeable bases at the end

of each year experiment. The increases in

seed yield and yield components of melon

under different N – sources can be ranked as:

control < urea < CAN < AS < NPK.

REFERENCES Adeuya, O. (2008): Effects of N – sources on

melon yield performance. Journal of

Applied Sciences. 21: 1-5

Been, T; Osai, K.O; Loe, B.S. (2011): Study

on factors responsible for nitrogen

deficiencies of the Tropical soils. Soil

Science. 16:21 – 25.

Brader, I. A. (2011): Long – term trends in the

fertility of soils under continuous

cereal cultivation. International Journal

of Pure and Applied Sciences. 40:203 –

209.

Cam, W.F. (2009): Effects of poultry manure

on soil physico – chemical properties

and maize yield In southeastern

Nigeria. Soil Fertility Research.

26(21):321 – 326.

Cern, B.R. (2010): Influence of fertilizer types

and tillage practices on the yield of

melon interplanted with maize. Plant

Nutrition. 18:17 – 24.

Cheng, M.I. (2009): Soil fertility evaluation

under different sources of N – fertilizers. Journal of Agriculture and Applied Sciences. 60:423 – 428.

Fessil, C. (2009): Comparative effects

fertilizer types on soil nutrient status and tuber yield of white yam in Ghana. Soil and Plant Science. 17:11 – 17.

Fondufe, E.Y. (1995): Assessment of different

fertilizer models for application under different cropping systems. Ph.D Thesis, University of Ibadan, Nigeria. 282 pp.

Handra, D. E. (2011): Long – term effects of

application of N – fertilizers on an Alfisol in northern Province of Cameroon. Soil Science Research. 28:111 – 116.

Harriz, A.D. (2006): Nitrogen nutrition of

melon. M. Sc. Dissertation, Ahmadu Bello University, Zaria, Nigeria. 61 pp.

Idah, S.O. (2011): Tillage and soil organic matter dynamics. Soil Organic Matter.

16:25 – 32. IITA, (1989): Automated and semi –

automated methods of soil and plant analysis. Manual Series, No 7, IITA, Ibadan, Nigeria.

Kowal, E. H. (2009): Soil organic carbon

under long – term tillage practices. Soil Fertility and Tillage Research. 22:153 – 159.

Kurtz, E. C. (2004): Urea in root and tuber

crops production. Soil Fertility and Plant Nutrition. 17:81 – 86.

Mucido, M. M. (2011): Effects of inorganic

fertilizer types and weeding frequency on yield and yield components of melon. Crop Physiology. 12:110 – 115.

166


Osaki, M; Sshirai, J. Shinamo, T. and Tadano,

T. (1995): Effects of ammonium and

nitrate assimilation on the growth and

tuber swelling of potato plants. Soil

Science and Plant Nutrition. 41 : 709 –

719.

Sas, E. Z. (2006): Evaluation of efficacy of N

– fertilizers in improving soil fertility

and crop yield. European Journal of

Soil and Crop Science. 61: 709 – 719.

Soil Survey Staff (SSS) (2003): Keys to soil

taxonomy, 9th edition. USDA Natural

Resources Conservation Services, U.S.

Department of Agriculture,

Washington D.C. 306 P.

167


ASSESSMENT OF DEGRADATION STATUS OF SOIL IN SELECTED AREAS OF

BENUE STATE SOUTHERN GUINEA SAVANNA OF NIGERIA

A.O. ADAIKWU1, M.E. OBI2 AND A. ALI3 1&3Department of Soil Science, University of Agriculture P.M.B 2373,

Makurdi, Benue State, Nigeria. [email protected] 2Department of Soil Science University of Nigeria Nsukka

ABSTRACT

The assessment of degradation status of soils in selected areas of Benue state was carried out in

2009. The physical and chemical properties of these soils were evaluated in the laboratory and

the results obtained were compared with the standard indicators and criteria for land degradation

assessment according to FAO, 1979. The results showed that most of the cultivated parts of the

study areas were highly degraded compared to the soils under vegetative fallow which were

moderately degraded. The textural composition of the soil ranged from loamy sand to sandy

loam to clay loam. Saturated Hydraulic conductivity ranged from 0.31 to 0.74 cmh-1

corresponding to slow and moderate permeability. The pH ranged from slightly to moderately

acidic condition in some locations and strongly acidic in the eroded parts. The organic matter

was very low in all the study areas. Available phosphorus was low in all the locations. Total

Nitrogen was predominantly very low in most of the cultivated areas to low in the fallow soils.

Cation Exchange capacity (CEC) also ranged from very low to low. The soils were classified as

follows: SIWES Farm Typic ustochrepts, Obarike Oju, Vertic tropaquept and Otobi Typic

Kandiaqualf. NYSC farm, Typic Kandiustalf; Adum-Ito, Typic Kandiustalf; and Otukpa, Oxic

Ustropept. It is recommended that soil conservation practice should be intensified in these areas.

The practice should include the use of organic manure such as cow dung and poultry droppings

for the fertilization of the fragile low fertility soils. There should also a programme for periodic

monitoring of the fertility status of the soil from the time the soil is first cultivated.

INTRODUCTION

Soil degradation is one of the greatest

challenges facing mankind. Its extent and

impact on human welfare and the global

environment is more severe now than ever

before. Due to its enormous impact, soil

degradation leads to political and social

instability. It is associated with enhanced rate

of deforestation, intensive use of marginal and

fragile soil, accelerated runoff and erosion,

pollution of natural waters, and emission of

green house gases into the atmosphere.

Soil degradation means a reduction of the

biological and economic productivity

potentials of rain-fed cropland, irrigated

cropland or range, pasture and forested land by

one or a combination of processes (Amalu,

1998). Such processes include, among others,

displacement of soil materials by wind and

water erosion, deterioration of soil physical

and chemical properties and long-term loss of

natural vegetation.

168

Adaikwu, Obi and Ali NJSS/22(1)/2012


The principal types of soil degradation are

physical, chemical, and biological degradation

(FAO 1994). Physical degradation refers to the

deterioration of the physical properties of the

soils. It includes soil compaction and hard

setting, soil erosion and sedimentation and

laterization. Biological degradation of the soil

includes a reduction in soil organic matter

(OM) content, decline in biomass carbon, and

decrease in activity of soil flora and fauna,

high soil and air temperature due in part, to the

use of chemicals and soil pollutants. Chemical

degradation is caused majorly by nutrient

depletion and excessive leaching of cation in

soils with low activity clay. The buildup of

some toxic chemicals and elemental imbalance

that are injurious to plant growth also

constitute chemical degradation of the soil.

In the Southern guinea savanna, particularly

Benue State, which is regarded as the “Food

Basket of the Nation”, farming is the

predominant economic activity. The

continuous unguided use of the soils for

agricultural production and other benefits had

exposed the soils to different forms of

degradation

The Objectives of the Study:

The main aim of this study is to assess the

degree of degradation of soils in selected areas

of Benue State using some soil quality

indicators with a view to making modest

recommendations on the rehabilitation and

proper management of degraded soils. It has

the following specific objectives;

1. To conduct a reconnaissance survey of

the selected study areas in Benue State

so as to identify appropriate study sites.

2. To assess the level of soil degradation in

the study areas through the laboratory

evaluation of some selected soil quality

indicators.

3. To establish the degree of degradation of

the soils of the study areas using

standard indicators and criteria for soil

degradation assessment (FAO, 1979).


The Study Area

The study areas are in Benue state popularly

known as the Food Basket of the nation.

Benue falls within latitudes 6o20N to 7o55N

and longitudes 7o30E and 9o40E. It shares

boundaries with six other states of Nigeria,

these include, Nassarawa to the north, Taraba

and Cross River to the south, Enugu and

Ebonyi to the South East and Kogi to the

West. It has a land area of about 30,955 square

kilometers. The state is bounded on the north

by 280km of River Benue and traversed by

202km of River Katsina-Ala in the Inland

areas.

Study Sites The followings areas were selected for the

assessment:

i. NYSC Farm, Nyiev Udei village in

Guma LGA of the State;

ii. SIWES Farm, University of

Agricultural Makurdi;

iii. National Root Crop Research Institute

(NRCRI), outpost, Otobi;

iv. Adum-Ito in Obi local Government

Area;

v. Odoba–Otukpa near Audu Ogbe’s

Cashew plantation Local Government

Area;

vi. Obarike in Oju Local Government

Field Methods

Soil sampling was carried out from January to

June 2009. In each of the study sites, an area

of two hectares of land was chosen and a bulk

sample, comprising of 20 auger points,

randomly selected, was collected and properly

labeled. In addition at each of these study sites,

soil samples were collected from an adjacent

soil at a distance of about 100m away.

Samples were labeled as A and B respectively

for such location. Samples labeled ‘A’ were

from the cultivated areas while sample ‘B’

represented soils under fallow condition. The

sampling covered 0 – 15cm depths for the

surface and 15-30cm for the subsurface. A

core sampler was also used to collect soil

samples for bulk density determination.

169

Assessment of degradation of soil

At each of these locations, a soil profile pit

was dug at site ‘A’. The topography was

described in terms of slope, physiography and

drainage based on field observations. The soils

were classified according to Soil Survey Staff

(1994). The present and past land use histories

were obtained partly through field

observations and partly through

interviews/interactions with the local farmers.

The soil samples were then taken to

NICONSOL Laboratory, University of

Agriculture, Makurdi, for evaluation

Laboratory Methods Particle Size Distribution The Bouyoucos

hydrometer method (1951) was used to

determine the particle size distribution of the

samples, while the soil textures were

determined using the USDA textural triangle.

Bulk Density The soil dry bulk density was

determined using the core method

Soil Total Porosity:

The total porosity of the soil samples was

calculated from the relationship.

% F = (1 – Bd/pd) x 100

Where F = porosity

Bd = bulk density g/cm3

Pd = particle density of the soil estimated at

2.65 g/cm3

Saturated Hydraulic Conductivity

The constant head method was used to

determine Ksat.

Soil Chemical Analysis

A total of 24 composite samples were air dried

ground and sieved to collect soil fraction less

than 2 mm size. These represent four samples

in each of the locations. The sampling covered

the depths of 0-15cm and 15-30cm for the

cultivated (A) and the fallow (B) soils. Twenty

three samples were also drawn from the 6

profile pits dug during the field study. The

following chemical properties of the soil were

analyzed.

Soil pH The soil pH in water (1:1) and in KCl

(1:1) were determined by electrometric

method.

Organic Carbon The wet oxidation method

of Walkley and Black (1934) was used to

determine the organic carbon content of the

soil samples.

Total Nitrogen This was determined by the

Macro-Kjeldahl digestion method (Jackson,

1965).

Cation Exchange Capacity (CEC) The CEC

was determined by neutral, 1N Ammonium

acetate method.

Available Phosphorus Bray-1 method was

used to determine the extractable phosphorus

(Bray & Kurtz, 1945).

Exchangeable Bases

Ca and Mg These cations were determined

by EDTA titration method (Jackson, 1965).

Sodium (Na) and Potassium (K) The EDTA

extracts of Na and K were determined with

flame photometer at Benue State Rural Water

Supply and Sanitation Agency, Makurdi.

Base Saturation This was calculated by

dividing the sum of exchangeable bases by

CEC and multiplying by 100.

Effective Cation Exchange Capacity

(ECEC) This was calculated by summing up

the exchangeable bases plus the exchangeable

acidity.

Exchangeable Sodium Percentage (ESP)

This was calculated by dividing the

exchangeable sodium by CEC.

Soil Degradation Assessment

The degradation status of the soils in the

various locations was assessed by field

observation and the standard indicators and

criteria for land degradation assessment by

Food and Agricultural Organization (FAO,

1979). Table 1 shows these indicators and

criteria. The four degrees of degradation

identified includes:

170


1. Slightly degraded soil, where

productivity ranges between 75-100%.

2. Moderately degraded soil, productivity

range between 50-75%.

3. Highly degraded soil, productivity is

between 25-50%.

4. Very highly degraded, productivity is

between 0-25%

Table 1 Indicators and Criteria for Land Degradation Assessment

Indicator Degree of Degradation

1 2 3 4

Soil bulk density

(g/cm-3)

<1.5 1.5 – 2.5 2.5 – 5 < 5

Permeability (cm/hr) <1.25 1.25 – 5 5 – 10 > 20

Content of Nitrogen Element

(multiple decrease) N (%)

>0.13 0.13 – 0.10 0.10 – 0.08 <0.08

Content of Phosphorus Element

(cmol kg-1)

>8 8 – 7 7 – 6 < 6

K content (cmol kg-2) >0.16 0.16 – 0.14 0.14 – 0.12 <0.12

Content of ESP (Increase by % of

(CEC)

<10 10 – 25 25 – 50 < 50

Content of Base Saturation (Decrease

of saturation in more than 50%

<2.5 2.5 – 5 5 – 10 > 10

Excess salts (Salinization) (Increase in

conductivity mmhos/cm/vr

<2 2 – 3 3 – 5 < 5

Content of humus in soil >2.5 2.5 – 2 2 – 1.0 <1.0

Source: FAO (1979)

Key: Class 1: None-slightly degraded. Class 3: Highly Degraded

Class 2: Moderately degraded. Class 4 Very Highly Degraded


Physical Properties of the Soils in the Study

Areas: The result of the particle size distribution

obtained in this study as presented in Table 2

indicates different textural composition of the

soils. The textural classes are the intrinsic

properties of the soils, which are sufficiently

permanent and are often used to characterize

the soil physical make up (Hillel, 1980). The

fallow soils in the six locations indicated

higher clay content compared with the

cultivated (Table 2). This agrees with Troech

and Thompson, (1993) who argues that good

soil management practice may marginally

increase the clay content and improve

productivity but cannot change the textural

class of the soil. According to Fitz-Patrick

(1986), the textural class of the soil is a

function of weathering in asociation with

parent materials influenced by climate over

time. The texture of the soil has high influence

on the physical and chemical properties of the

soils which are used as quality indicators for

soil degradation assessment.

171


Table 2: Physical Properties of the Soils of the Study Areas Location Depth

(cm) Bulk

Density (gcm-3)

Total Porosity

(%)

Sat. Hydr condc.

(cmhr-1)

Sand (%)

Silt (%)

Clay (%)

Textural Class

SIWES Farm

0-15A 15-30A 0-15B 15-30B

1.44 1.46 1.52 1.56

46 45 43 41

0.62 0.65 0.53 0.57

88 86 80 78

10 12 12 14

2 2 8 8

Loamysand Loamysand Sandyloam Sandyloam

Oju 0-15A 15-30A 0-15B 15-30B

1.85 1.97 1.69 1.74

30 26 36 36

0.31 0.33 0.51 0.53

46 44 58 58

18 18 20 20

36 38 22 22

Clayloam Clayloam Loam Loam

Otobi 0-15A 15-30A 0-15B 15-30B

1.54 1.49 1.64 1.64

42 44 38 38

0.58 0.58 0.58 0.57

78 76 61 60

15 13 19 16

7 11 20 24

Sandyloam Sandyloam Sandyloam Loam

NYSC 0-15A 15-30A 0-15B 15-30B

1.36 1.39 1.48 1.5

49 48 44 43

0.59 0.55 0.55 0.57

61 57 57 55

21 21 16 16

18 22 27 29

Loam Loam Loam Loam

Adum 0-15A 15-30A 0-15B 15-30B

1.28 1.33 1.54 1.51

52 50 42 38

0.79 0.74 0.65 0.60

85 58 69 65

12 8

14 14

3 7 17 21

Loamysand Loamysand Sandyloam Standyloam

Otukpa 0-15A 15-30A 0-15B 15-30B

1.45 1.46 1.58 1.60

46 45 40 40

0.74 0.69 0.58 0.55

85 85 69 67

12 12 18 20

3 3 12 13

Loamysand Loamysand Sandyloam Sandyloam

A-cultivated soils, B-fallow soils. The soil parameters used for the assessment of the physical degradation of the soils of the sites studied indicated that, on permeability rating; the soils were slightly degraded (SD) in all the studied sites (Table 5), FAO (1979). In addition, the soils were mostly moderately degraded (MD) with respect to bulk density (BD). The cultivated parts in SIWES farm as well as the subsurface (15-30 cm) of Otobi, NYSC farm, Adum-Ito and Otukpa all indicated SD soils with respect to BD. The BD of soil is greatly influenced by the organic matter (OM) content. The correlation between BD, clay and OM was significant. This implies that the lower BD in the cultivated part compared with the fallow were indications of lower clay content and OM in the former. The continuous cultivation of the soils tends to modify the soil BD and pore size distribution since the operation loosens, granulates and

crushes the soil particles. On the other hand, the high bulk density in the fallow soils compared with the cultivated soils agrees with Ojeniyi (1989), who reported higher BD with zero tillage compared with conventional tillage. This observation implies that the continuous exposure of untilled soils to intensive rainfall, without mechanical tillage could compact the soils. Moreover, in the Savanna region of Nigeria, Ike (1986) reported high BD under untilled soil compared with the cultivated ones. Ohiri (1988) reported significantly higher BD and penetrometer resistance for zero tilled soils compared with conventionally tilled soils. Kayombo and Lal (1984) indicated a range of 1.35–1.5 gcm-3 as the critical BD for cassava production in an alfisol.

172


Chemical Properties of the Soils of the Study Areas The results of the chemical analysis of the soils in the six locations are presented in Table 3. From the table, the pH of the soil in water is predominantly moderate to slight acidic condition (USDA-SCS 1974). These are typical characteristics of savanna soils. Harpstead (1973) reported that Guinea Savanna soils were less leached and, hence of moderate to near neutral acid condition. The pH values in most of these areas were in the range of 5.5 to 6.5 (Table 3) which could be considered reasonably well for plant growth and development in the agroclimatic zone. Most soil quality indicators can be affected by the pH of the soil.

The cation exchange capacity (CEC) in the study areas are predominantly low, ranging below 12 cmol/kg in all the locations (Table 3). The low CEC may be related to the low organic matter (OM) content. Lal and Kang (1982) had observed that the higher the OM content of the soil, the higher the CEC. Lombin et al (1991) also reported that organic matter content was a major contributor to the CEC of the soil. The correlation between OM and CEC was significant, which agrees with the above position. The application of organic residue and the avoidance of bush burning are management practices that play important role in reversing the trend of nutrient depletion in conjunction with conversion to lower tillage system (Haine and Uren, 1990) and the establishment of mulches (Lal, 1986).

Table 3 Soil quality indicators (QI) for land degradation assessment

Locations Depth Cm

Bd g/cm3

Permeability Cm/hr

B.Sat %

N P K Esp OM

Cmol/kg (ppm) Cmol/kg % %

SIWES A 0-15 1.44 0.62 64 0.04 4.40 0.13 5.78 0.40 Farm A 15-30 1.46 0.65 64 0.08 4.40 0.10 5.61 0.40 B 0-15 1.52 0.53 63 0.13 5.56 0.17 3.53 1.19 B 15-30 1.56 0.57 56 0.13 5.46 0.16 2.94 1.10

Oju A 0-15 1.85 0.31 58 0.13 4.58 0.13 9.57 1.31 A 15-30 1.97 0.33 57 0.11 4.50 0.13 8.81 1.31 B 0-15 1.69 0.51 56 0.13 5.46 0.27 7.48 1.49 B 15-30 1.74 0.53 59 0.12 5.38 0.24 8.77 1.45

Otobi A 0-15 1.54 0.58 52 0.08 4.52 0.12 6.21 0.89 A 15-30 1.49 0.58 53 0.08 5.80 0.11 7.28 0.93 B 0-15 1.64 0.58 63 0.13 4.48 0.23 5.88 1.76 B 15-30 1.64 0.57 59 0.13 4.46 0.22 5.26 1.72

NYSC A 0-15 1.36 0.59 77 0.07 4.48 0.10 4.25 1.24 Farm A 15-30 1.39 0.55 70 0.08 4.00 0.08 3.77 1.14 B 0-15 1.48 0.57 70 0.13 4.56 0.24 3.69 1.72 B 15-30 1.50 0.55 66 0.14 4.52 0.22 2.43 1.72

Adum A 0-15 1.28 0.79 58 0.10 4.48 0.09 8.4 0.79 A 15-30 1.33 0.74 55 0.10 4.00 0.06 8.57 0.80 B 0-15 1.54 0.65 62 0.14 5.50 0.19 3.04 1.56 B 15-30 1.51 0.60 62 0.13 4.48 0.20 2.80 1.49

Otukpa A 0-15 1.45 0.74 70 0.10 4.48 0.11 7.71 0.69 A 15-30 1.46 0.69 60 0.08 4.46 0.10 6.50 0.73 B 0-15 1.58 0.58 62 0.13 4.52 0.15 3.29 1.56 B 15-30 1.60 0.55 66 0.13 4.50 0.19 2.67 1.45

173


The chemical degradation of the soils of these

studied sites indicated different degrees of

degradation with respect to the parameters

used. For instance, the soils were not-slightly

degraded (SD) with respect to exchangeable

sodium percentage (ESP) at the depth of 0-15

cm and 15-30 cm in all the studied sites.

Available phosphorus was VHD in all the

study sites (Table 5) FAO, (1979). Phosphorus

is the second most critical element influencing

plant growth and production throughout the

world. It is taken up by plants from soil

solution as orthophosphate anion H2PO4- or

HPO4. For southern guinea savanna

agroecology of Nigeria, Agbede (2009)

recommended 225 kg/ha or 4.5 bags of P for

soils that are low in available P (less than 8.0

ppm) for maize production.

The degree of degradation with respect to

potassium (K+) ranged from not-slightly

degraded (SD) to very highly degraded (VHD)

soils. The surface (0-15 cm) of the fallowed

soil in SIWES farm, the fallowed parts of

Otobi, NYSC farm, Adum-Ito and the

subsurface of Otukpa studied sites were all SD

with respect to K. The fallowed part of Oju

and the subsurface (15-30 cm) of the fallowed

part of the SIWES farm were moderately

degraded (MD). The cultivated parts of the

SIWES farm, Obarike Oju were highly

degraded (HD) and the cultivated parts of

Otobi, NYSC farm, Adum-Ito and Otukpa

were VHD with respect to K+.

With respect to nitrogen content, the

degradation status of the soils in these study

areas ranged from highly degraded (HD) in

most of the cultivated sites to moderately

degraded in the fallow soils (Table 5). All the

soils under fallow conditions were MD as well

as the cultivated sites of Obarike Oju and

Adum-Ito. The cultivated sites of the SIWES

farm, subsurface (15-30 cm) of Otobi, and

NYSC farm as well as the cultivated sites of

Otukpa were all HD with respect to N content.

Table 3 indicates very low nitrogen content in

most of the cultivated part to low in the fallow

soils. This trend is an indication of nutrient

loss in the farms due to continuous cultivation

as well as nutrient loss during the harvesting

period. Nitrogen as a soil quality indicator is

one of the key nutrients in plant growth.

Agbede (2009) listed nitrogen as the most

important of all the 16 essential plant elements

needed for plant growth, development and

reproduction and also the most easily limiting

or deficient throughout the world especially in

the tropics. Nitrogen as a mobile element can

easily be lost. The continuous cultivation

exposed the soil to sheet erosion which

washed away the top soil including plant

nutrients. For soils that are low in nitrogen

content (less than 0.15) Agbede (2009)

recommended 200 kg or 4 bags of urea or 383

kg or 7¾ bags of CAN for maize production in

southern guinea savanna agroecology of

Nigeria.

The rating of base saturation (BS) indicated

that the soils were predominantly VHD (Table

5). These include the cultivated site and the

surface (fallow) of SIWES farm, NYSC farm,

the fallow site of Adum-Ito and Otukpa. The

soils in Obarike-Oju, the cultivated part of

Otobi were HD with respect to BS while the

fallow parts of Otobi and the cultivated part of

Adum-Ito were MD with respect to BS.

The biological degradation was more

pervasive compared with the physical and the

chemical degradation in all the sites studied.

The soils at the surface (0 – 15 cm) and

subsurface (15 – 30 cm) of both the cultivated

and the fallow areas were very highly

degraded (VHD) with respect to organic

matter (OM) content (Table5) FAO, (1979).

This is an indication of very high biological

degradation, which is typical of savanna soils.

The values of organic matter (OM) content in

all the locations as presented in Table 3 were

very low (Metson, 1961). The very low

organic matter contents are indicative of very

high biological degradation of all the soils of

the study areas. The OM depletion may be, in

part, due to crop uptake exacerbated by

continuous cropping without adequate

174


measures of nutrient replacement either

through the use of inorganic fertilizer or other

forms of soil conservation measures. However,

the low OM content is a phenomenon

associated with the savanna soils, which could

be due to high temperatures that rapidly break

down OM and inhibit nitrogen fixation by

rhizo-bacteria, (Harpstead, 1973). The practice

of bush burning that is most common in the

savanna could also destroy soil organisms and

cause reduction in the biodiversity of the soil’s

flora and fauna. Organic matter is closely

related to the CEC of the soil. Lal and Kang

(1982) reported that the higher the OM the

higher the CEC. The correlation between OM

and CEC was highly significant which agrees

with this position. Organic matter has direct

imprint on soil physical properties by

improving water transmission and root

penetration. Agbim and Adeoye (1991)

reported that OM improves soil permeability.

Kang and Balasubramania (1990) stated that

high rates of OM addition was needed to solve

the problem of soil acidity arising from

continuous cropping in West African Alfisols.

The contribution of animal wastes to increase

the level of soil OM had been reported by

Ojeniyi (2000), and by Okpara and Mbagwu

(2003). Gao and Cheng (1996) also observed

significant increase in organic carbon content

of the soil as a result of added organic

amendments in tropical soils with low activity

clays, low CEC and low plant nutrient levels.

Proper management of organic matter is highly

desirable. Agbede (2009) recommended that

incorporated crop residue must be of high

quality, that is, must have C/N ratio of below

20/1. Leguminous plants provide such high

qualityresidues.

Table 4: Assessment of Individual Soil Quality Indicators (QI)

Locations

Depth

(cm)

B.D.

(gcm-3)

Permeability

(cm/hr)

B. Sat

(%)

N

(%)

P

(ppm)

K

(cmol/kg)

ESP

(%)

Om

(%)

SIWES

Farm

Obarike

Oju

Otobi

NYSC

Farm

Adum

Ito

Otukpa

A

A

B

B

A

A

B

B

A

A

B

B

A

A

B

B

A

A

B

B

A

A

B

B

0 - 15

15-30

0 –15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

0-15

15-30

SD

SD

MD

MD

MD

MD

MD

MD

MD

MD

MD

SD

SD

SD

SD

MD

SD

SD

M D

M D

SD

SD

M D

M D

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

VHD

VHD

VHD

HD

HD

HD

HD

HD

HD

HD

MD

MD

VHD

VHD

VHD

VHD

M D

M D

VHD

VHD

VHD

VHD

VHD

VHD

HD

HD

MD

MD

MD

MD

MD

MD

MD

MD

VHD

HD

VHD

HD

MD

MD

MD

MD

MD

MD

HD

HD

M D

M D

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

HD

HD

SD

MD

HD

HD

MD

MD

SD

SD

VHD

VHD

VHD

VHD

SD

SD

VHD

VHD

SD

SD

VHD

VHD

M D

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

SD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

VHD

H.D. ------------- Highly degraded; VHD ----------Very highly degraded

Key: SD --------------- None-Slightly degraded; M D. -----------Moderately degraded


A-cultivated soils, B-fallow soils CONCLUSIONS An investigation was conducted in 2009 to assess the degree degradation of the soils in some selected areas of Benue state. The main objective was to assess the degree degradation of the soils in these study areas, using the standard indicators and criteria for land degradation assessment (FAO, 1979). The results of the study show that soil degradation in these areas ranged from highly degraded to moderately degraded soils. On a comparative basis, most of the soils that were cultivated showed higher degree of degradation compared to the fallow areas. From the study, 42 % of the soils were highly degraded while 58 % were moderately degraded. The soils were classified according to the provisions of soil survey staff (1999) on the basis of the physical and chemical properties of the soils evaluated RECOMMENDATIONS Base on the findings of this study the following recommendations are made; 1. The application of mineral fertilizer

nutrients especially nitrogen, phosphorus, and potassium is necessary. Accordingly 200 kg or 4 bags of urea or 383 kg or 7¾ bags of CAN are recommended for maize production in southern guinea savanna agroecology of Nigeria for soils that are low in nitrogen (less than 0.15 %), as well as 225 kg/ha or 4.5 bags of P for soils that are low in available P (less than 8.0ppm).

2. The use of organic manure such as cow dung and poultry dropping is recommended to improve the productivity of these degraded soils. However, farmers are encouraged to leave crop residues on their farms and incorporate same during tillage rather than burning them.

3. The Portions of the SIWES farm, NYSC farm and the site at Otobi that had been used continuously for cultivation for quite some time should be allowed to fallow, as the higher degree of degradation observed may be due to their prolonged use.

4. There should be a programme for monitoring the fertility status of the soils at regular intervals.

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177


EFFECTS OF LAND USE TYPES ON SOIL QUALITY IN A SOUTHERN GUINEA

SAVANNAH, NASARAWA STATE OF NIGERIA

AMANA, S. M; JAYEOBA, O. J AND AGBEDE, O. O Department of Agronomy, Nasarawa State University,

Lafia Campus, Nigeria

ABSTRACT

This research was carried out at the College of Agriculture, Lafia Research field in 2010

cropping season. The objective of this study was to investigate effects of long term cultivation on

soil properties. Surface soil samples (0-15cm) were collected from three sites in each of the five

land use types including: cassava, legume, maize, oil palm plantation and secondary forest. The

samples were subjected to physical and chemical analyses to access the extent of change in soil

quality. According to the results of statistical analysis, bulk density (BD), mean weight diameter

(MWD), water stable aggregates (WSA), soil organic matter content (SOM), total nitrogen (TN),

total porosity (TP), pH and available phosphorus (P) were significantly affected by land use

types. Differences in bulk density (1.65-1.81g/cm3) among the land use types were highly

significant (p<0.05) due to pore disruption by cultivation and percent sand resulting in decreased

total porosity. The mean weight diameter and water stable aggregates were better in secondary

forest compared to other land use types. Soil organic matter content and total nitrogen were

generally very low, but were significantly different (p<0.05). Available phosphorus and CEC

were high for all the land use types. The pH in all the land use types was slightly acidic with

mean of 6.38. The results of study suggest that the continuous cultivation of the land has

degraded the soil properties and there is therefore the need to adopt appropriate management

practices to achieve high soil quality and sustainable productivity.

Key words: soil properties, land use types, soil quality

INTRODUCTION

Human population pressure upon land

resources and their demand for food has

resulted in the increase land use, and intensive

Agriculture (Houghton, 1994; Geissen et al.,

2009). Intensive land use may cause important

changes in soil physical and chemical

characteristics, and can affect soil fertility,

increase soil erosion or cause soil compaction

(Geissen, 2009). Land use changes through

cultivation may rapidly diminish soil quality,

as ecologically sensitive components of

tropical soils are not able to buffer the effect of

intensive agricultural practices (Islam and

Weil, 2000). Most areas of land previously

developed from tropical rainforest have been

degraded because of land misuse. Nutrient

mining and soil degradation are presently

considered as problems in arable farms (Ande

and Onajobi, 2009). Severe deterioration in

soil quality may lead to a permanent

degradation of land productivity (Kang and

Juo, 1986; Islam and Weil, 2000).

Assessment of the effects of land use and soil

management practices on soil properties is of

178

Amana, Jayeoba and Agbede NJSS/22(1)/2012

importance to detect changes in soil quality.

These effects on soil properties also provide

essential information for assessing

sustainability and environmental impact (Ishaq

and Lal, 2002; Ceyhum, 2009). Effect of land

use types on the determination of soil quality

has been reported (Amhakhian et al., 2006;

Islam and Weil, 2009; Conant et al., 2003). Up

till now few or no work has been done on soil

quality in the Southern Guinea Savannah agro-

ecology zone. The aim of the study is to assess

the effects of land use types on the properties

of soils in this area.


The study area was located in the College of

Agriculture, Lafia North Local Government

area of Nasarawa State, of Nigeria (0.8.33’N,

08.32’E and 175m high). Mean annual rainfall

in the area is 1132mm, minimum and

maximum temperature ranges between 24 8oC

and 33oC respectively. The soil is an Oxisol

(ferrasol, FAO). It is well drained, porous and

brownish red below the surface, made of

kaolinite clay. The soil type is mostly sandy

loam and pH varies from 5 to 6.5. The selected

sites have been under cultivation for over 30

years and secondary forest was left fallow for

about 10 years. The selected areas were of

uniform topography and soil types.

Soil sampling

Disturbed and undisturbed soil samples were

collected in September, 2010 from three

locations in each of the five land use types

(cassava, maize, legume, palm plantation and

secondary forest). The land use types were

either adjacent to one another separated by no

more than 1000m, within the same

physiographic unit and with similar slope and

aspect. Soil samples were taken at the depth of

0-15cm (top soil) in each of the three selected

areas. Soil samples were taken in plastic bags

to the laboratory and air dried for analysis.

Laboratory studies

Physical properties: - Particle size distribution

was determined using disturbed soil samples

by the hydrometer method as described by

Boyoucous (Gee and Bauder, 1986). Bulk

density was determined by core method and

total porosity was calculated assuming a

particle density of 2.65g/cm3. The size

distribution of aggregates was measured by

wet sieving through a series of sieve (2.0, 1.0,

0.5, 0.25mm). The percent water stable

aggregates (%WSA) on each of the size range

were then determined, thus

% WSA = (Ma+s – Ms) x 100

(Mt – Ms)

Where;

Ma+s = Mass of the resistant aggregates plus

sand (g)

Ms = Mass of sand fraction alone (g)

Mt = total mass of the sieved soil (g)

The nodded of Van Bavel (1950) as modified

by Kemper and Roseau (1986) was used to

determine the mean weight diameter (MWD)

of the wet stable aggregates. Thus

n

MWD =∑XiWi

i=1

Where;

Xi = Mean diameter of each size fraction (mm)

Wi = proportion of the total mass in the

corresponding size fraction after deducting the

weight of stones

Chemical properties

Soil organic carbon was determined by the

Walkley – Black method (Nelson and

Sommer, 1996). Total nitrogen (TN) was

determined by Kjeldahl (Brenner, 1996)

method. Soil pH and electrical conductivity

(EC) were measured by pH/conductivity

method (Rhoades, 1996) in soil water solution.

Available phosphorus extracted by Bray-1

extractant (Bray and Kurtz, 1945). Ca2+ and

Mg2+ were read by atomic absorption

spectrophotometer while K+ and Na+ were

read with flame photometer. Cation exchange

capacity (CEC) was by the summation of

exchangeable bases. The base saturation was

calculated as ratio of exchange bases to the

179

Effect of land use types on soil

effective cation exchange capacity (ECEC)

expressed in percentage.

Data analysis: One- way analysis of variance

(ANOVA) procedure was used to compare the

effects of land use types on soil quality. Means

were compared by least significant difference

(LSD) at P<0.05 level.

RESULTS AND DISCUSSION.

Physical properties

Table 1, showed the results of physical

properties of the various land use types. The

particles size distribution of top soil (0-15cm)

shows that there is no difference in the textural

class of the soils under the different land use

types. The textural class remained sandy loam

(SL) in all the locations. This means that land

use does not have effect on texture since

texture is largely determined by parent

material (Obi 1999). The bulk density (BD)

values were significantly different for the land

use types. Bulk density was statistically

significant (p<0.05) with mean value of

1.74g/cm3. The bulk density values were

generally high in all the land use types, with

highest value in secondary forest (1.81g/cm3).

This high soil bulk density might be due to

intensive agricultural practice, low organic

matter content for crop land and compaction of

top soil due to overgrazing of the pasture (Lal,

1986; Ceyhun, 2009).

The effect of land use types on total porosity

(Table 1) showed significant difference

(P<0.05). Total porosity was generally low

with mean value of 34.4%, highest in corn

(37.7%) and lowest in secondary forest 31.6%.

The low value in secondary forest may be

attributed to the high bulk density. This result

disagrees with the finding of Ande and

Onajobi (2009) who recorded 53.9% in

secondary forest of about 20years. However,

the soils recorded here have different textural

class.

The percentage water stable aggregate (WSA)

and mean weight diameter (MWD) values

(Table 1) of secondary forest land were higher

than the cultivated land. Both MWD and WSA

were significantly different from other land

uses (P<0.05). Compared to the secondary

forest, cultivated land use types decreased both

WSA and MWD. That is, the loss of large

sized water stable aggregates under cultivation

was associated with significant reduction in

stability as measured by the MWD (Table 1).

The decreases in soil aggregation resulted in

the increased bulk density in the cultivated

land. This process could get worse by the

continuous use of machinery for cultivation

(Lal et al., 1997).

Table 1: Effects of land use types on soil physical properties of top soil (0-15cm). Land use types Soil Texture Bulk

density

g/cm3

Sand

%

Soil

%

Clay

%

Porosity

%

Aggregate

stability %

MWD

mm

Cassava (CV) Sandy loam 1.68 7496 6 19.04 36.7 10.76 0.67

Corn (M) Sand loam 1.65 74.96 6 19.04 37.7 10.91 1.43

Legume (LG) Sandy loam 1.77 74.96 8 17.04 33.2 27.51 1.13

Oil Palm (POP) Sandy loam 1.78 74.96 8 17.04 32.8 9.74 1.34

Forest(F) Sandy loam 1.81 76.96 6 17.04 31.6 56.82 2.02

LSD 0.118 ns ns ns 1.365 0.952 0.089

Chemical properties

In Table 2, some of the soil chemical

properties were significantly different in soils

under different land use types. Soil

characteristics have changed over the past 30

years with land use. Long term cultivation

significantly (P>0.05) decreased soil organic

matter content (som) in the cropped lands and

it has crucial effect on soil physical and

chemical properties. Organic matter content

was significantly higher in secondary forest

(5.75g/kg) than the cultivated land.

180


Total nitrogen was generally low ranging from

0.11g/kg in maize to 0.29g/kg in secondary

forest. Total nitrogen was slightly higher in

legume field (LG) than the other cultivated

land. This could be due to its ability to fix

nitrogen in the soil. The low total nitrogen

observed in the soils may be due to intensive

cultivation (Power, 2004).

Available P content in all soils was medium

(17.68mg/kg) to high (23.10 mg/kg).

Phosphorus was significantly different in all

the land use types with the highest value of

23.10mg/kg in oil palm plantation (POP). This

means that P fixation by Fe and Al-oxides

occur in the soil (Sanchez et al., 2003) due to

slightly acidic medium.

The pH values varied significantly from 6.20

in POP to 6.5 in secondary forest (Table 2).

The pH was slightly acidic in all the land use

types. Biomass from incorporated stubble after

harvest could have retained enough base

forming cations to increase pH of the surface

soil (Islam and Weil, 2000). Percentage base

saturation values were generally high in the

land use types and were significant different

from one another. Electrical conductivity in all

the land use types was not significantly

different.

Table 2: Effects of land use types on chemical properties of the top soil (0-15cm). Land use types pH in

water

ECe O.M

g/kg

TN g/kg Available P,

mg/kg

CEC

C/mol/kg

% base

saturation

Cassava(CV) 6.48 50 4.18 0.21 18.38 15.30 79.40

Corn(M) 6.41 50 2.22 0.11 18.90 14.35 69.53

Legume(LG) 6.24 50 4.57 0.23 21.88 17.13 77.34

Oil palm(POP) 6.20 60 2.61 0.13 23.10 14.18 69.54

Forest(F) 6.58 60 5.75 0.29 17.68 13.50 73.19

LSD 0.1546 ns 0.962 0.005 1.561 1.451 2.005

CONCLUSION

This study indicated that long-term cultivation

of lands resulted in destruction of soil

properties. The land use types have

significantly reduced SOM, TN, TP, MWD

and WSA, as it has increased the soil bulk

density. In summary, the finding of this study

indicates that continuous cultivation of these

lands for crop production may lead to loss of

soil productivity and land degradation. It is

clear, that there is need to adopt appropriate

management practices to achieve high soil

quality and sustainable productivity.

REFERENCE

Amhakhian S.O; Isitekhale, H.H;Ezeku P.I.,

2006.Assessment of soil structure

under different land uses in Anyingba,

North Central, Nigeria International

Formal of Agricultural Research (PAT)

volume 1 No.1

Bray R.H, Kurtz L.T (1945). Determination of

total organic and available forms of

phosphorus in soils. Soil Sci. 59:39-45

Bremner, J.M: Method of Soil Analysis, Part

3. Chemical Methods, Soil Science of

America and American Society of

Agronomy, SSSA Book Series No. 5,

Madison-USA (1996).

Conant, R.T.J. Six and K. Paustian: Land use

effects on soil carbon fractions in the

southeastern United States. I

Management-intensive versus

extensive grazing. Biol. Fertile Soils,

38, 386 392 (2003).

Gee, G. W. and Bauder J.W. 1986. Particle

size analysis, In: Wute A (ed) Methods

of Soil Analysis. Part 1 physical and

mineralogical methods. 2nd edition.

Madison, WI. USA: ASA-SSA,

Pp.383-411

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Houghton, R.A., 1994. The worldwide extent

of land-use change. Bioscience 44,

305-313.

Islam, K.R., and Weil, R.R., 2000. Soil quality

indicator properties in mid-Atlantic

soils as influenced by conservation

management J. Soil Water Conser. 55,

69,2269-2284

Kang, B.T., Juo, ASR., 1986. Effect of forest

clearing on soil chemical properties

and crop performance. In: Lal, R.,

Sanchez, P.A. Cummings, Jr., R.W.

(Eds), Land Clearing and Development

in the Tropics. Belkema, Rotterdam,

pp. 79-83

Kemper, W.D. and R.C. Rosenau: Methods of

Soil Analysis. Part 1, Physical and

Mineralogical Methods-Agronomy

Monograph, No.9 (2nd Edn.) ASSA,

USA (1986)

Lal, R., P. Henderlong and M. Flowers:

Forages and row cropping effects on

soil organic carbon and nitrogen

contents. In: Management of carbon

sequestration in soil (Eds.: R. Lal, J.M.

Kimble, R.F. Follett and B.A. Stewart).

CRC Press, Boca Raton, FL. Pp. 365-

380 (1997).

Nelson, D.W. and L.E.Sommer: Methods of

Soil Analysis. Part3. Chemical

Methods, Soil Science of America and

American Society of Agronomy, SSSA

Book, Series No. 5 Madison-USA

(1996).

Obi, M. E. 1999. Physical and chemical

responses of a degraded sandy clay

loam soil to cover crops in southern

Nigeria. Plant and Soil 211: 165-172.

Powers, J.S., 2004. Changes in soil carbon and

nitrogen after contrasting land-use

transitions in northeastern Costa Rica.

Ecosystem 7,134-146.

Sanchez, P.A. Palma, C.A., Buol, S.W., 2003.

Fertility capability soil classification: a

tool to help assess soil quality in the

tropics. Geoderma 114, 57-185.

Ceyhun, G., 2009: The effects of land use

change on soil properties and organic

carbon at Dagdami river catchment in

Turkey. Journal of Environmental

biology 30(5) 825 – 830.

Gersien V., Sanchez – Hernandez, R.,

Kampicher, C., Ramos-Reyes, R.,

Sepulvada-Lozada A., Ochoa-Goana,

S., Dejong, B.H.J., Itueta-Lwanga E.,

and Hernandez-Dauma S. 2009. Effects

of Land-Use change on some

properties of tropical soils-An example

from southeast mexico. Geoderma 151,

87 – 97.

Ande, T.O. and Onajobi, J. 2009. Assessment

of effects of controlled land use types

on soil quality using inferential

method. African journal of

Biotechnology Vol. 8(22), pp 6267 –

6271.

Ishaq, M.I., and Lal. R. 2002. Tillage effects

on soil properties at different levels of

fertilizer application in Punjab,

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182


SOIL PROPERTIES AND RESPONSE OF YAM TO ASH

APPLICATION AT AKURE, NIGERIA

KAYODE, B.O.1, OJENIYI, S. O.2, AND ODEDINA, S.A.1

1Department of Agronomy, Federal College of Agriculture, Akure 2Department of Crop Soil and Pest Management

Federal University of Technology, Akure, Nigeria

ABSTRACT Two experiments were conducted at the Federal College of Agriculture Akure, Southwest

Nigeria to test effectiveness of a crop waste wood ash as source of nutrients for plantain (Musa

paradisica) and yam (Dioscorea rotundata). Effect of wood ash at 0, 0.4, 0.8 and 1.2 kg/plant

was studied as to the effect on soil chemical properties and performance of the crops. The test

soil was low in organic matter (OM), total N, available P, exchangeable K and Mg. The soil pH,

OM, N, P, K, Ca and Mg increased with level of ash. The 0.4 kg/plant ash increased the number

of leaves of plantain and tuber weight of yam significantly. Tuber weight was increased by 44%.

INTRODUCTION Ash derived from burning of plant residues is a

natural fertilizer for farmers especially in the

tropics where the slash and burn land

preparation is done. However research has not

been focused on the effectiveness of different

types of ash on different crops until recently

(Odedina et al 2003; Owolabi et al 2005;

Nottidge et al 2007; Awodun et al 2007;

Ewulo et al, 2009). In addition to being source

of macro and micro nutrients, ash raises soil

pH thus it has a liming effect through the

supply of basic elements especially Ca and K.

Studies carried out in different parts of Nigeria

indicate that ash derived from cocoa pod,

wood, sawdust and other plant residues

increased availability of nutrients in soil,

nutrient uptake, soil pH and enhances the

performance of crops such as amaranthus,

tomato, pepper, cowpea, okra, tomato, maize

and cocoa seedlings (Ojeniyi et al, 2010,

Ayeni et al, 2008a, 2009, 2008b, 2008c,

Ojeniyi and Adejobi, 2002; Awodun et al,

2007).

Information is scarce on response of plantain

crop to ash application. This work carried out

in Akure Southwest Nigeria investigated the

response of plantain and yam to application of

ash and its concomitant effect on soil

properties.


Field Experiments

Experiments were carried at Federal College

of Agriculture Akure in the rainforest zone of

southwest Nigeria. Land was manually

cleared. In the first experiment on plantain

between August 2010 to August 2011, four

wood ash levels 0, 0.4, 0.8, 1.2 kg were

applied on soil surface to each plant the

spacing being 1m x 1m. The treatments were

replicated four times. Each of the 16 plots had

four plants. Ash was applied in May 28, 2011.

Between 2 and 8 weeks after treatment

application, data were collected bi-weekly on

plant girth, number of leaves and plant height.

In the second experiment on yam, another site

was cleared in 2011. The four ash treatments

were applied to yam on surface soil. The four

183

Effect of ash on soil and yam

ash treatments were replicated four times

given 16 plots. Yam heaps were spaced at 1 x

1m in each plot that contained 20 heaps. Yam

sets were planted in March 2011, and ash

applied in May 2011 when rain was steady.

Weeding was done 18 days after ash

application.

At 8 weeks after ash application (WAT) data

were taken on five plants selected per plot on

plant height, number of leaves and girth. At

harvest, tuber weight, mean tuber girth and

length were determined.

RESULT AND DISCUSSION The test soil was inadequate in most nutrients

(Table 1) such as organic matter (OM), total

N, available P, exchangeable K and Ca

considering the critical values set for soils in

southwest Nigeria (Akinrinde and Obigbesan,

2000; Adeoye and Agboola, 1985)

Table 1: Pre-test soil chemical analysis (plantain experiment)

Soil Property Value

pH (H2O)

OM %

Total N %

Available P mg/kg

Exchangeable K cmol/kg

Exchangeable Ca cmol/kg

Exchangeable Mg cmol/kg

Texture

7.7

1.86

0.14

14.6

0.14

0.70

1.50

Sandy Clay Loam

It is shown that soil pH, OM, N, P, K, Ca and

Mg increased with level of wood ash applied

to plantain. However it is the 4 t/ha ash that is

optimum since there was no clear increases in

soil nutrients after the 0.4 t/ha ash per plant.

The values of soil pH, OM, N, P, K, Ca and

Mg at this level is adequate for crop

production, although values recorded for OM

and N were marginal. Therefore, in terms of

soil fertility, application of ash at 0.8 and 1.2

kg/plant is superfluous.

Table 2: Soil analysis as affected by ash application (plantain experiment)

Treatment

Ash kg/ha

pH

(H2O)

OM

%

N

%

P

mg/kg

K

cmol/kg

Ca

cmol/kg

Mg

cmol/kg

0

0.4

0.8

1.2

LSD (0.05)

6.9

9.2

7.4

7.5

NS

1.79

2.13

2.37

3.83

0.47

0.13

0.18

0.22

0.28

0.40

12.2

19.3

27.3

55.5

10.7

0.12

0.30

0.37

0.51

0.07

0.10

0.44

0.62

0.70

0.30

1.4

3.1

3.8

4.7

0.81

The findings from this work on the role of

wood ash is consistent with findings from the

work of Nottidge et al 2007, that affirm the

role of ash as a liming material and effective

source of nutrients for crops such as

vegetables, maize and cocoa (Ojeniyi and

Adejobi, 2002; Odedina et al, 2003; Ayeni et

al 2008c)

The studies also showed that ash increased the

uptake of nutrients by the crops, and nutrient

contents of the soil leading to increase in their

growth and yield. Since the test soil in this

work is inadequate in OM, N, P, K and Ca, it

is expected that ash would increase the fertility

of the soil and raise its pH (Table 2).

Table 3 contains data on growth parameters of

plantain as affected by ash application.

184

Kayode, Ojeniyi and Odedina NJSS/22(1)/2012

Parameters such as girth, number of leaves and

plant height were increased by ash at

0.4kg/plant. The increase was significant with

respect to the number of leaves. After the

0.4g/tree level (0.8 and 1.2g/tree) growth was

reduced or slight.

Table 3: Growth of Plantain as Affected by Wood Ash

Ash

Kg/Plant

Plant Girth

8 WAP

Number of

Leaves

Plant Height

(cm)

0

0.4

0.8

1.2

LSD (0.05)

37.2

46.9

39.4

46.6

NS

11.9

14.1

12.1

13.7

0.70

243.9

327.4

274.1

335.5

NS

The yam yield components are shown in Table

4. The ash treatments namely 0, 0.4, 0.8 and

1.2 kg/plant increased tuber weight

significantly. The increases in tuber girth and

length were not significant. Application at

0.4kg/tree is optimum because increases in

tuber weight given by 0.4, 0.8 and 1.2 kg/tree

were similar being 44, 43 and 48%

respectively. The 0.4 kg/tree rate is

recommended for both plantain and yam.

Table 4: Yam Tuber Yield as affected by Wood Ash

Ash

kg/Plant

Tuber Weight

kg

Tuber Girth

cm

Tuber length

(cm)

0

0.4

0.8

1.2

LSD (0.05)

1.26

1.82

1.50

1.86

0.40

34.8

36.1

40.7

39.8

NS

31.3

33.3

36.7

36.5

NS

This work has shown that wood ash served as

liming material and fertilizer. Soil acidity was

reduced and nutrients released to enhance soil

fertility. Hence the growth of plantain and yam

yield were increased significantly. Application

at 0.4 kg/plant is recommended.

REFERENCES Adeleye, E.O.; Adeleye, A.A. and Ojeniyi,

S.O. (2004). Effects of wood ash manure on soil nutrients status leaf nutrient and yield of yam on an alfisol in Southwestern Nigeria. The Nigerian Journal of Research and Production 5(5) 76-82.

Awodun, M..A.; Otaru, M.S. and Ojeniyi S.O.

(2007). Effect of saw dust ash plus urea on maize performance and nutrient status of maize. Asian Journal of Agricultural Research 1, 1-4.

Awodun, M.A.; Ojeniyi S.O.; Adesoye, A. and

Odedina, S.A. (2007). Effect of oil palm bunch refuse ash on soil and plant nutrient composition and yield of maize. American–Eurasian Journal of sustainable Agriculture 1, 50-54.

Ayeni, L.S.; Adetunji, M.T.; Ojeniyi, S.O.;

Ewulo, B.S. and Adeyemo, A.J. (2008a). Comparative and cumulative effect of cocoa pod husk and poultry manure on soil and maize nutrients contents and yield. American Eurasian Journal of Sustainable Agriculture 2(1), 92-97.

Ayeni, L.S.; Adetunji M.T. and Ojeniyi S.O

(2008b). Comparative nutrients release from cocoa pod ash poultry manure and NPK 20:20:20 fertilizer and their

combinations – incubation study,

185

Effect of ash on soil and yam

Nigerian Journal of Soil Science 18, 114-123.

Ayeni, L.S.; Ayeni, O.M.; Ojo, O.P. and

Ojeniyi, S.O. (2008c) Effect of saw

dust and wood ash applications in

improving soil chemical properties and

growth of cocoa seedlings in the

nurseries. Agricultural Journal 3(5),

323-326.

Ayeni, L.S.; Adetunji, M.T. and Ojeniyi, S.O.

(2009). Integrated application of NPK

fertilizer, cocoa pod ash and poultry

manure: Effect on maize performance

plant and soil nutrient content.

International Journal of Pure and

Applied Sciences 2(2), 34-41,

Ewulo, B.S.; Babadele, O.O. and Ojeniyi, S.O.

(2009). Saw dust ash and urea effect on

soil and plant nutrient content and yield

of tomato. American – Eurasian

Journal of Sustainable Agriculture

3(1), 88-92.

Nottidge, D.O.; Ojeniyi S.O. and Asawalam,

D.O. (2007). Effect of different levels

of wood ash on nutrient contents of

maize and grain yield in an acid ultisol

of Southeast Nigeria. Nigerian Journal

of Soil Science 17, 98-103.

Odedina, S.A.; Odedina, J.N.; Ayeni, S.O.;

Arowojolu, S.A.A.; Areyeye, S.D. and

Ojeniyi, S.O. 2003. Effect of types of

wood ash on soil fertility nutrient

availability and yield of tomato and

pepper. Nigerian Journal of Soil

Science 13, 61-67.

Ojeniyi, S.O.; Awanlemhen, B.E. and Adejoro,

S.A. (2010). Soil plant nutrients and

maize performance as influenced by oil

palm bunch ash plus NPK fertilizer.

Journal of American Science 6(12),

456-460.

Ojeniyi, S.O. and Adejobi, K.B. (2002). Effect

of ash and goat dung manure on leaf

nutrients composition growth and yield

of amaranthus. The Nigerian

Agricultural Journal 33, 46-57.

Owolabi .O.; Ojeniyi, S.O.; Amodu, A.O. and

Hazan, K. (2005). Response of cowpea

okra and tomato to saw dust ash

manure. Moor Journal of Agricultural.

Research 4(2), 178-182.

Ponsu, M. and Gautheyron, J. (2003).

Handbook of Soil Analysis

Mineralogical Organic and Inorganic

Methods Springer – Verlay, Berlin.

New York.

186

Kayode, Ojeniyi and Odedina NJSS/22(1)/2012

USE OF AGRICULTURAL WASTES FOR IMPROVING SOIL CROP NUTRIENTS

AND GROWTH OF COCOA SEEDLINGS

AKANNI, D.1; ODEDINA, S.A1 AND OJENIYI, S. O.2 1Department of Agronomy, Federal College of Agriculture, Akure, Nigeria

2Department of Crop Soil and Pest Management

Federal University of Technology, Akure, Nigeria

(Correspondence to 2)

ABSTRACT

The quest for organically produced cocoa in the world market necessitated recent focus on

research into the use of agricultural wastes as source of nutrients in cocoa (Theobroma cacao)

production. This work carried out at Federal College of Agriculture Akure is the comparative

study of effect of kola testa (KT), cocoa pod ash (CPA), melon testa (MT), cowpea pod (CP),

kola pod (KP) and cocoa testa (CT) and NPK fertilizer (NPK) on soil and crop nutrient

composition and growth cocoa seedlings. The nutrient composition of the wastes was also

determined. The test soil was slightly acidic, medium in organic matter (OM) and low in N and

available P. In terms ofnutrient of N, P and K, the MT, CP and CPA respectively have the

highest percentages. The KT, CT, CPA and MT had highest and similar values of C:N ratio.

NPK gave highest soil OM, N, Mg, leaf N, P, K and Ca. MT gave highest soil P, Ca, leaf Ca and

Mg, CPA which gave highest soil K had relatively high soil P, N, Mg and leaf K and Ca. KT

gave relatively high soil K, Mg, leaf K and Mg. The CT, KT, CPA and KP increased number of

leaves significantly. The KT, MT, CPA and NPK gave higher and similar values of fresh matter

yield and tended to give highest values of soil and plant N, P, K, Ca and Mg. In addition to

nutrients release the relatively high C:N ratio (27 – 31 C:N ratio) of KT, CPA and MT should

have contributed to their better effect on growth of cocoa seedlings.

INTRODUCTION There is quest for organically produced farm

produce in international markets. This is

particularly so in the case of horticultural and

plantation crops such as coffee, cocoa and

fruits. Hence, there is shift on part of

producers to establish organically certified

farms and tap into the lucrative organic export

markets. In Papua New Guinea small-scale

highland coffee farmers now produce certified

organic coffee bound for Australian and US

markets, earning far higher incomes than they

ever had. In Sao Tome, about 200 tonnes of

organically produced cocoa beans are exported

annually.

In Nigeria research effort into methods of

establishing organic cocoa farms is quite

recent. One aspect of this effort is to study into

use of agricultural wastes and organomineral

fertilizer for soil amendment and supplying of

nutrients to cocoa seedlings (Akanni and

Ojeniyi, 2011, Moyin Jesu and Atoyosoye,

2002). In their study, Moyin Jesu and

187

Use of wastes for improving soil

Atoyosoye (2002) found that agricultural

wastes such as wood ash, cocoa pod husk, rice

bran and oil palm bunch ash increased growth

significantly and leaf N, P, K, Ca and Mg

contents of cocoa seedlings and soil N and P.

They were more effective than NPK fertilizer.

Studies by Ojeniyi and Egbe (1981), Ojeniyi et

al (1982) and Ojeniyi and Egbe (1983) had

found that cocoa trees require supplementary

application of N, P and K fertilizers in

southwest Nigeria. Ojeniyi (1986) indicated

that more emphasis should be placed on

supplementary nutritional needs of young

cocoa plants compared with old plants because

soil organic matter, N, K, Ca and Mg

increased with age of cocoa trees while P

reduced.

In this work agricultural wastes which have

not been studied namely; melon testa, cowpea

and kola pod, cocoa testa were studied in

addition to cocoa pod ash and NPK fertilizer

as to their effects on soil and plant nutrient

composition, and growth of cocoa seedlings.


Nursery experiment was conducted on cocoa

seedlings at Federal College of Agriculture,

Akure, Ondo State, Nigeria. After land

clearing, a shade was erected. Polythene pots

of 20 x 12cm that had drainage holes were

filled with top soil and the weight was 1.7kg

each. Wet seeds were planted at one seed per

pot and there were 420 pots to cover eight

manure fertilizer treatments replicated three

times. The treatments were (a) the control, 2.5

t/ha each (b) kola testa (c) cocoa pod ash (d)

melon testa (e) cowpea pod (f) kola pod (g)

cocoa testa, and (h) 400 kg/ha NPK 15:15:15

fertilizer. Five pots were allocated to each

treatment. The kola testa, cocoa pod ash, kola

pod (ground) and cocoa testa were obtained

from Cocoa Research Institute of Nigeria,

Ibadan: melon testa and cowpea pod were

obtained from the market at Akure. A seed

was planted in a pot. The surface soil in the

nursery was protected using nylon to prevent

insect attack. Fencing of the nursery was done

with wire mesh to prevent rodent attack.

Treatments were allocated using a complete

randomized block design. Watering with can

water was done twice daily (morning and

evening) and it continued after emergence at 2

weeks. The NPK fertilizer and organic

manures were applied as mulch materials at 4

weeks after planting.

Plant Data Collection As from 6 weeks after planting (WAP), data

were collected bi-weekly on plant height, stem

girth, number of leaves, till 20 WAP. At 20

WAP, samples of fresh root and fresh shoot

were weighed. The weight of dry root and

shoot were determined by oven-drying fresh

samples at 80oC for 24 hours.

Leaf Analysis The twenty-four samples of oven-dried leaves

were ground for the tree replicates and

chemically analysed as described by Faithful

(2002). The N was determined by the macro-

kjeldahl method. The samples were extracted

using the nitric-perchloric acid mixture, P was

evaluated using vanadomolybdate colorimetry,

K by flame photometer, and Ca and Mg by

atomic absorption spectrophotometry.

Soil Analysis A composite surface (0-15cm) soil samples

was collected on the site where soil was

collected to fill the pots used for growing

cocoa seedlings..

After the harvest of plants at 20 WAP, twenty-

four composite soil samples were collected for

the three replicates, samples were air-dried and

2mm sieved for analysis as described by Pensu

and Gautheyron (2003). Total N was

determined by micro-kjeldahl method, organic

matter by wet dichromate oxidation method,

available P by vanadomolyb date colorimetry

and Bray-P1 extraction. Exchangeable K, Ca

and Mg were extracted using ammonium

acetate, K was determined on flame

photometer, and Ca and Mg by atomic

absorption spectrophotometer. The pH in 2:1

water – soil medium was determined.

188

Akanni, Odedina and Ojeniyi NJSS/22(1)/2012

Analysis of Agricultural Wastes The wastes used as manure were kola testa,

cocoa pod ash, melon testa, cowpea pod, kola

pod and cocoa testa. The air-dried samples

were ground and analysed as for the leaf

samples (Faithful, 2002).

RESULT AND DISCUSSION Table 1 shows chemical analysis of soil used

for the experiment. The soil is slightly acidic,

organic matter (OM), is low in total N,

available P and exchangeable Ca, K and Mg

(Akinrinde and Obigbesan, 2000) are

adequate.

Chemical analysis of agricultural wastes is

shown in Table 2. In terms of the composition

of major nutrients (N, P, K), the melon testa

(MT), cocoa pod (CP) and cocoa pod ash

(CPA) respectively have the highest

percentages respectively. The cocoa testa

(CT), kola pod (KP) and kola testa (KT)

respectively had least composition in terms of

NPK. However the CT had highest

concentration of Mg. The CP had highest

concentration of Ca. The KT, CT, CPA and

MT had the highest and similar values of C:N

ratio.

Table 1: Soil chemical properties before planting

pH Om

%

Total N

%

Available P

mg/kg

Ca K Mg

Cmol/kg

6.4 2.1 0.12 6.5 2.4 1.2 0.96

Table 2: Chemical analysis of agricultural wastes (%)

Waste C:N OM N P K Mg Ca

Kola testa (KT)

Cocoa pod ash (CPA)

Melon testa (MT)

Cowpea pod (CP)

Kola pod (KP)

Cocoa testa (CT)

31

30

27

15

21

30

2.14

2.01

1.01

0.90

1.71

0.23

0.04

1.40

1.30

0.71

0.92

0.58

11.7

10.1

16.7

12.0

6.0

10.1

2.01

2.45

3.40

3.07

2.20

1.66

0.01

1.29

0.81

1.51

2.06

2.14

1.36

2.68

2.05

2.70

0.61

2.25

Data of soil chemical properties as influenced

by the agricultural wastes are presented in

Table 3. The NPK fertilizer increased soil OM,

N, P, Ca and Mg. The increased OM, Ca and

Mg could be due to enhanced OM, Ca and Mg

could be due to enhanced biotic activity and

resultant decomposition of organic material

and mineralization of organic nutrients. Ayeni

et al (2009) also found that NPK fertilizer

increased soil OM, N, P, K, Ca and Mg and

micronutrients.

The CPA increased soil N, P, Ca, Mg and K.

Ayeni et al (2008a, 2008b, 2009), Ajayi et al,

(2007a, 2007b) had also found that cocoa pod

ash significantly increased soil macronutrients

and had liming effect. Related to this is the

observation in this work that cocoa testa

increased soil N, P and Ca. It is also found that

CP (cowpea pod) increased soil OM, P, Ca and

Mg; MT (melon testa) increased soil N, P, Ca,

cola testa (KT) increased soil N, P, Ca, Mg

and Cola pod powder (KP) increased soil N, P

and Mg. Generally, the agricultural wastes

increased soil OM and macronutrients.

189


Table 3: Soil chemical properties as affected by NPK fertilizer and organic wastes

Treatment OM

%

N

%

P

mg/kg

Ca Mg K Ph

--- cmol/kg---

NPK

Kola testa

Cocoa pod ash

Melon testa

Cowpea pod

Kola pod

Cocoa testa

Control

1.11a

0.64ab

0.82ab

0.59ab

1.06a

0.87ab

0.39b

0.88ab

0.91

0.57

0.79

0.62

0.43

0.68

0.63

0.25

NS

1.95a

1.88b

2.39ab

3.06a

1.57b

1.88b

2.15ab

1.44B

2.76

2.63

2.84

3.43

3.39

2.63

3.19

2.59

NS

1.91a

0.94abc

1.12a

0.76c

1.10ab

0.99abc

0.72c

0.78bc

0.41

0.52

0.82

0.54

0.53

0.58

0.35

0.55NS

7.1

7.9

7.4

7.5

7.6

7.4

7.6

7.4

NS

Data on leaf nutrient composition are shown in

Table 4. Only NPK and cowpea pod (CP)

increased leaf N. All the agricultural wastes

and NPK increased leaf K and Mg. The

exception is that CPA did not increase leaf Mg

and CT and KT did not increase leaf P. The

wastes did not increase leaf Ca probably

because of the relatively high exchangeable Ca

content of soil compared with K and Mg.

Unlike in this study with cocoa seedlings,

other works (Ayeni et al, 2009, Ayeni et al,

2008, Ajayi et al, 2007a, 2007b) showed that

the CPA increased uptake of N, P, K, Ca Mg

and micronutrients by crops such as cola (Cola

nitida) and maize (Zea mays)

Data on soil and plant analysis can be

summarized thus: The NPK gave highest soil

OM, N, Mg and leaf N, P, K and Ca. The MT

gave highest soil P, Ca and leaf Ca, Mg, and

relatively high leaf N, P and K. The CPA gave

highest soil K, relatively high soil P, N, Mg

and leaf K and Ca. The KT gave relatively

high soil K, Mg and leaf K and Mg.

Table 4: Leaf nutrient composition of cocoa seedlings as affected by NPK fertilizer and

organic wastes (%)

Treatment N P K Ca Mg

NPK

Kola testa

Cocoa pod ash

Melon testa

Cowpea pod

Kola pod

Cocoa testa

Control

0.94a

0.44b

0.50b

0.61b

0.70ab

0.50b

0.54b

0.60b

1.20a

0.23b

0.30b

1.12a

0.44b

0.40b

0.32b

0.23b

2.80a

1.10c

1.10c

1.83b

0.94cd

1.01cd

0.90cd

0.82d

1.10ab

0.82ab

1.00ab

1.10ab

0.74ab

0.90ab

1.03ab

1.20a

0.90cd

1.73ab

0.71e

1.97a

1.11c

1.10ad

0.90de

0.73e

Data on growth parameters such as plant

height, stem girth and number of leaves are in

Table 5. Though the NPK and agricultural

wastes increased plant height and stem girth

the increases were not statistically significant.

CT, KT, CPA, KP, MT and CP respectively

increased the number of leaves. The increases

given by CT, KT, CPA and KP were

significant. The NPK did not increase number

of leaves.

The fresh and dry matter, and root yield are

presented in Table 6. The wastes and NPK

significantly increased fresh matter (shoot)

yield (FMY), and the KT, MT and CPA gave

highest values. Increases in fresh root yield

(FRY), dry matter yield (DMY) and dry root

yield (DRY) were not significant. Aside from

availability of N, P, K, Ca and Mg due to the

agricultural wastes, the higher FMY given by

KT, MT and CPA respectively could be

attributed to slow release of nutrients

190


contained in them over a longer period due to

their relatively high C:N ratio. The period of

determination of growth parameters was 14

weeks. Other wastes such as kola pod (KP),

cocoa pod (CP) and kola testa (CT) should

have decomposed and mineralized faster due

to their relatively low C:N ratio (Table 2).

Although CT had high C:N ratio (30) similar

to the values for KT, CPA and MT, this is

merged by relatively low N, P and K contents.

Infact, the CT and KP respectively had least

aggregate value for NPK which are the major

nutrients. This should have adversely affected

nutrient availability to cocoa seedlings. Hence,

CT and KP with least aggregate value for NPK

had least FMY and DMY among the wastes.

The CT also gave least N, P and K contents.

The wastes such as the KT, MT, CPA and

NPK that gave highest and similar values of

FMY tended to produce highest values of soil

and plant N, P, K, Ca and Mg. Therefore,

increased nutrient availability induced by the

agricultural wastes enhanced significantly the

growth of cocoa seedlings. In addition, slow

nutrients release associated with the high C:N

ratio of KT, MT and CPA contributed to the

enhanced performance of cocoa seedlings. The

optimum C:N for composts is indicated to be

between 20:20:1. Composts with ratio less

than 20 quicken release of nutrients by

preventing nutrient immobilization

(Chukwujindu et al, 2006).

Table 5: Growth of cocoa seedlings as affected by NPK fertilizer and organic wastes at 20

WAP

Treatment Plant height

(cm)

Stem girth

(cm)

No of leaves

NPK

Kola testa (KT)

Cocoa pod ash (CPA)

Melon testa (MT)

Cowpea pod (CP

Kola pod (KP)

Cocoa Testa (CT)

Control

30.6

33.8

36.0

33.8

36.8

36.5

31.3

28.4

NS

2.80

2.80

2.80

2.80

2.70

2.60

2.60

2.40

NS

18.3b

25.0ab

23.3ab

20.7b

20.7b

22.7b

27.3a

21.0b

Table 6: Fresh and dry matter yield of cocoa seedlings as affected by NPK fertilizer and

organic wastes

Treatment Fresh matter

yield (g)

Fresh root yield

(g)

Dry matter

yield (g)

Dry root yield

g)

NPK

Kola testa (KT)

Cocoa pod ash (CPA)

Melon testa (MT)

Cowpea pod (CP

Kola pod (KP)

Cocoa Testa (CT)

Control

27.5ab

28.7a

24.7ab

27.4ab

18.1c

14.2b

20.0c

13.7b

9.01

6.70

7.20

7.60

6.60

8.60

6.70

6.5

NS

6.70

8.70

5.00

7.80

5.70

3.90

5.20

3.70

NA

2.50

1.70

2.80

2.00

2.20

2.10

1.90

1.70

NS

191


CONCLUSION Agricultural wastes such as kola testa, cocoa pod ash, melon testa, cowpea pod, kola pod and cocoa testa are composed of major nutrients which were released into soil to increase soil N, P, Ca, Mg at various degrees and this led to increased nutrients content and growth of cocoa seedling. The kola testa, cocoa pod ash and melon testa were more effective in increasing leaf production and fresh matter yield and plant K, Ca and Mg. REFERENCES Akanni, D.I. and Ojeniyi, S.O. (2011).

Influence of sunshine organic and organomineral fertilizers on growth of oil palm and cocoa seedlings, plant and soil nutrients. Nigeria Journal of Soil Science 21(1), 80-84.

Ajayi, C.A.; M.A. Awodun and S.O. Ojeniyi,

(2007a). Effect of cocoa husk ash on growth and stem nutrient uptake of kola seedlings. Asian Journal of Agricultural Research 4(1), 31-34.

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Ewulo, B.S. and Adeyemo, A.J. (2008a). Comparative and cumulative effect of cocoa pod husk ash and poultry manure on soil and maize nutrients content and yield. American Eurasian Journal of Sustainable Agriculture 2(1), 92-97.

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Ayeni, L.S., Adetunji, M.T. and Ojeniyi, S.O. (2009). Integrated application of NPK fertilizer cocoa pod ash and poultry manure effect on maize performance plant and soil nutrient content. International Journal of Pure and Applied Science 2(2), 34-40.

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Chemical Analysis. A practical Handbook. CABI Publishing. Pp. 206.

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192


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