BAHIAGRASS AND RHIZOMA PEANUT MIXTURES: EFFECTS ON HERBAGE CHARACTERISTICS, BELOWGROUND RESPONSES, AND NITROGEN CYCLING

By

ERICK RODRIGO DA SILVA SANTOS

A THESIS PRESENTED TO THE GRADUATE SCHOOL

OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2017

© 2017 Erick Rodrigo da Silva Santos

To my family

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ACKNOWLEDGMENTS

I would like to thank the North Florida Research and Education Center – NFREC,

the Florida Department of Agriculture and Consumer Services, and Dr. Jose Dubeux for

sponsoring my studies at the University of Florida, making possible the completion of

my MS degree.

I gratefully would like to thank to my advisor, Dr. Jose Dubeux, who has not

withheld efforts to advise and teach me for many years. I will be always thankful for all

the time he has spent on making me improve my skills and for the good role model he

is, as a person and researcher. I would also like to thank my committee members, Dr.

Ann Blount, Dr. Cheryl Mackowiak, Dr. Lynn Sollenberger, and Dr. Nicolas DiLorenzo,

for accepting my invitation, for instructing me with practical and theoretical inputs, and

for the help in the development of my study.

All the work presented in this thesis would never have been completed without

the help of many students, interns, and staff from the NFREC. I would like to thank

Alejandra Gutierrez, Augustin Lopez, Camilla Gomes, Camila Sousa, Daci Abreu, David

Jaramillo, Elijah Conrad, Gustavo Bertoldi, Hiran Marcelo, Jennifer Shirley, Jose

Diogenes, Jose Rolando, Joyce Patu, Liza Garcia, Luana Dantas, Luara Canal, Marco

Goyzueta, Marina Bueno, Martin Ruiz-Moreno, Pierre Yves, Priscila Beligoli, Raul

Guevara, Rebekah Wright, Rodrigo Menezes, Susannah Wright, Tatiana Pereira, and

Ulises Riveros, for all the work and funny moments we had together during and after the

completion of the study.

I would like to thank Gleise Medeiros for all the support and companionship along

these years. For all listed above, I will be always thankful.

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TABLE OF CONTENTS page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES ............................................................................................................ 8

LIST OF FIGURES .......................................................................................................... 9

LIST OF ABBREVIATIONS ........................................................................................... 12

ABSTRACT ................................................................................................................... 13

CHAPTER

1 LITERATURE REVIEW .......................................................................................... 15

Florida Cattle Industry and Hay Operation .............................................................. 15

Bahiagrass .............................................................................................................. 16 Nitrogen Cycle – Changes and Challenges ............................................................ 17 Nitrous Oxide Emissions ......................................................................................... 18

Ammonia Volatilization............................................................................................ 21

Nitrate Leaching ...................................................................................................... 22

Biological Nitrogen Fixation (Bringing Legumes into the System) ........................... 24 Grass-Legume Mixtures in Grasslands ................................................................... 26

Bahiagrass-Rhizoma Peanut Mixtures .................................................................... 28 Hypothesis and Objectives ..................................................................................... 29

2 HERBAGE RESPONSES AND BIOLOGICAL N2 FIXATION OF RHIZOMA PEANUT AND BAHIAGRASS ENTRIES IN MONOCULTURE OR IN MIXED SWARDS ................................................................................................................ 30

Introduction ............................................................................................................. 30

Materials and Methods............................................................................................ 32

Experimental Site ............................................................................................. 32 Treatments and Experimental Design .............................................................. 33 Plot Establishment and Management ............................................................... 33 Response Variables ......................................................................................... 34

Herbage accumulation and botanical composition ..................................... 34

Crude protein and in vitro organic matter digestibility ................................ 35 Total aboveground N, %Ndfa, and BNF ..................................................... 35

Statistical Analysis ............................................................................................ 36 Results and Discussion........................................................................................... 36

Herbage Accumulation ..................................................................................... 36

Botanical Composition ...................................................................................... 38 Nutritive Value .................................................................................................. 39

Bahiagrass CP ........................................................................................... 39

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Bahiagrass IVOMD .................................................................................... 40 Rhizoma peanut CP ................................................................................... 41 Rhizoma peanut IVOMD ............................................................................ 42

Total Nitrogen Aboveground ............................................................................. 43 % Nitrogen Derived from the Atmosphere (%Ndfa) .......................................... 44 Biological Nitrogen Fixation .............................................................................. 45

Conclusions ............................................................................................................ 46

3 BELOWGROUND RESPONSES OF RHIZOMA PEANUT AND BAHIAGRASS GERMPLASMS IN MONOCULTURE OR IN MIXED SWARDS ............................. 59

Introduction ............................................................................................................. 59

Material and Methods ............................................................................................. 62 Experimental Site ............................................................................................. 62 Treatments and Experimental Design .............................................................. 62 Plot Establishment and Management ............................................................... 63

Statistical Analysis ............................................................................................ 65 Results and Discussion........................................................................................... 66

Root and Rhizome Biomass ............................................................................. 66 Root and Rhizome Nitrogen Concentration and Content ................................. 68 Root and Rhizome Carbon Content ................................................................. 70

C:N Ratio .......................................................................................................... 71

Root and Rhizome δ15N ................................................................................... 71

δ13C and C3:C4 Proportion in Roots and Rhizomes .......................................... 72 Conclusions ............................................................................................................ 73

4 NITROGEN LOSSES IN BAHIAGRASS-RHIZOMA PEANUT MIXTURES AND MONOCULTURES ................................................................................................. 83

Introduction ............................................................................................................. 83

Materials and Methods............................................................................................ 85 Experimental Site ............................................................................................. 85

Treatments and Experimental Design .............................................................. 85

Plot Establishment and Management ............................................................... 86

Response Variables ......................................................................................... 87 Ammonia Volatilization ............................................................................... 87 Nitrate Concentration in Leachate .............................................................. 88 Nitrous Oxide Emissions ............................................................................ 89

Statistical Analysis ............................................................................................ 90

Results and Discussion........................................................................................... 90 Ammonia Volatilization ..................................................................................... 90 Nitrate Concentration in Leachate .................................................................... 92 Nitrous oxide concentration .............................................................................. 93

Conclusions ............................................................................................................ 94

5 FINAL REMARKS ................................................................................................. 101

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LIST OF REFERENCES ............................................................................................. 104

BIOGRAPHICAL SKETCH .......................................................................................... 113

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LIST OF TABLES

Table page 2-1 Bahiagrass in vitro organic matter digestibility (IVOMD) fertilized with N or

growing in mixtures with rhizoma peanut (RP). .................................................. 47

2-2 Rhizoma peanut in vitro organic matter digestibility (IVOMD) growing in monoculture or mixed with bahiagrass. .............................................................. 48

4-1 Nitrogen fertilization type and date, according to date and day of study. ............ 95

4-2 Nitrate concentration in leachate. ....................................................................... 96

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LIST OF FIGURES

Figure page 2-1 Monthly rainfall in 2015 and 2016, and 30-yr average in the experimental area,

Quincy, FL. ......................................................................................................... 49

2-2 A) Minimum, maximum, and average monthly temperature, and B) Solar radiation in the experimental area during 2015 and 2016. .................................. 50

2-3 Herbage accumulation of bahiagrass-rhizoma peanut (RP) mixtures and monocultures in 2015 and 2016 as affected by treatment ˟ season ˟ year (P = 0.0143; SE = 376.06), according to PDIFF procedure adjusted by Tukey (P < 0.05). .................................................................................................................. 51

2-4 Botanical composition of bahiagrass-rhizoma peanut (RP) mixtures as affected by treatment (P = 0.0121, SE = 0.03405), season (P < 0.0001, SE = 0.02809), and year (P < 0.0001, SE = 0.02184) according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................................ 52

2-5 Bahiagrass crude protein concentration as affected by treatment ˟ season ˟ year (P < 0.0001, SE = 0.7171) when in mixed swards with rhizoma peanut (RP) or in monoculture and fertilized with 90 kg N ha-1 harvest-1, according to PDIFF procedure adjusted by Tukey (P < 0.05). ................................................ 53

2-6 Rhizoma peanut crude protein concentration when growing in monoculture or grown in mixture with bahiagrass as affected by A) treatment ˟ year (P = 0.0087, SE = 10.4) or B) season ˟ year (P <.0001, SE = 5.1), according to PDIFF procedure adjusted by Tukey (P < 0.05). ................................................ 54

2-7 Total rhizoma peanut (RP) aboveground N when growing in monoculture or mixed with bahiagrass as affected by: A) treatment ˟ season effect (P = 0.034, SE = 7.4) and; B) season ˟ year (P <.0001, SE = 5.7); and total N aboveground of bahiagrass when growing in monoculture or mixed with rhizoma peanut as affected by C) treatment ˟ year (P <.0001, SE = 1.8) and D) season ˟ year effect (P <.0001, SE = 2.05), according to PDIFF procedure adjusted by Tukey (P < 0.05), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................................................. 55

2-8 Total aboveground N of bahiagrass-rhizoma peanut (RP) mixtures or monocultures as affected by A) Treatment (P = 0.0003, SE = 5.9) and; B) season ˟ year effect (P <.0001, SE = 5.3), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................................................. 56

2-9 Percentage of N derived from atmosphere (%Ndfa) in rhizoma peanut as affected by treatment ˟ year (P = 0.0131, SE = 3.4), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................................ 57

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2-10 Rhizoma peanut biological N2-fixation as affected by A) treatment (P < 0.0001, SE = 3.2) and; B) season x year (P < 0.0001, SE = 3.1), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................................ 58

3-1 A) Rainfall (mm), B) temperature (°C), and C) solar radition (W m-2) in Quincy – FL, during 2015 and 2016. ................................................................................. 74

3-2 Belowground biomass of bahiagrass-rhizoma peanut mixtures in contrast with their monocultures. Treatment ˟ year effect (P = 0.0053, SE = 1536.21), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................ 75

3-3 Root and rhizome N concentration of bahiagrass-rhizoma peanut mixtures in contrast with their monocultures. Treatment ˟ year effect (P = 0.0223, SE = 1.004), according to PDIFF procedure adjusted by Tukey (P < 0.05). ................ 76

3-4 Root and rhizome N content of bahiagrass-rhizoma peanut mixtures in contrast with their monocultures. Treatment ˟ year effect (P = 0.0245, SE = 25.76), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................ 77

3-5 Root and rhizome C pool of bahiagrass-rhizoma peanut mixtures and monocultures during 2 yr. Year effect (P = 0.0003, SE = 299), according to PDIFF procedure adjusted by Tukey (P < 0.05). ................................................ 78

3-6 Root and rhizome C/N ratio of bahiagrass and rhizoma peanut growing in mixtures or monoculture. Treatment ˟ year effect (P <.0001, SE = 6.5462), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................ 79

3-7 Root and rhizome δ15N of bahiagrass and rhizoma peanut growing in mixtures

or monoculture. Treatment ˟ year effect (P = 0.0063, SE = 0.328), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................ 80

3-8 Root and rhizome δ13C of bahiagrass and rhizoma peanut growing in mixtures or monoculture. Treatment effect (P <.0001, SE = 0.9507), according to PDIFF procedure adjusted by Tukey (P < 0.05). ................................................ 81

3-9 Contribution of bahiagrass and rhizoma peanut (RP) to belowground biomass of mixed stands (P > 0.05, SE = 0.09994), according to PDIFF procedure adjusted by Tukey (P < 0.05). ............................................................................. 82

4-1 Daily rainfall, relative humidity, and temperature at the NFREC, Quincy - FL, during the experimental period.. ......................................................................... 97

4-2 NH3-N (kg N ha-1) loss per day from N-fertilized bahiagrass in contrast with bahiagrass-rhizoma peanut (RP) mixtures and monocultures of RP. * Indicate the first sampling after N fertilization.. ................................................... 98

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4-3 Cumulative NH3-N loss from N fertilized bahiagrass (90 kg N ha-1 harvest-1) in comparison with rhizoma peanut (RP) monoculture and mixtures of bahiagrass and RP.. ........................................................................................... 99

4-4 Soil N2O emission on bahiagrass and rhizoma peanut monocultures or in their mixtures. Evaluation effect (P < 0.0001, SE = 0.019). Different letters mean significant difference among evaluations, according to PDIFF procedure adjusted by Tukey (P < 0.05). ........................................................................... 100

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LIST OF ABBREVIATIONS

ADG Average daily gain

BC Botanical composition

BNF Biological N2 fixation

CP Crude protein

CRH Critical relative humidity

GC Grazing cycle

HA Herbage accumulation

IVOMD In vitro organic matter digestibility

Ndfa Nitrogen derived from the atmosphere

RDM Residual dry matter

RH Relative humidity

RP Rhizoma peanut

TNAG Total nitrogen aboveground

TNAGB Total nitrogen aboveground in bahiagrass

TNAGRP Total nitrogen aboveground in RP

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

BAHIAGRASS AND RHIZOMA PEANUT MIXTURES: EFFECTS ON HERBAGE CHARACTERISTICS, BELOWGROUND RESPONSES, AND NITROGEN CYCLING

By

Erick R S Santos

May 2017

Chair: Jose C. B. Dubeux, Jr. Co-chair: Lynn Sollenberger Major: Agronomy

Bahiagrass (Paspalum notatum Flügge) is the dominant forage crop in Florida’s

cow-calf operations, and it requires nitrogen (N) fertilization to be productive. Forage

legumes such as rhizoma peanut (RP; Arachis glabrata Benth), fix atmospheric N2 and

may decrease the need for industrial N inputs. Mixing RP and bahiagrass appears to be

a useful management practice in Florida. This study aimed to evaluate herbage

characteristics, belowground responses, and N losses from bahiagrass and RP

genotypes growing in mixtures or monocultures. Treatments were two bahiagrass

entries (‘Argentine’ and DF9, receiving 90 kg N ha-1 harvest-1), two RP entries (Ecoturf

and Q6B), and the combinations of each entry of bahiagrass with each entry of RP

(Argentine-Ecoturf, Argentine-Q6B, DF9-Ecoturf, and DF9-Q6B), replicated three times

in a randomized complete block design during 2015 and 2016. In 2015, mixtures and

monocultures had similar herbage accumulation, however, in 2016, Argentine herbage

accumulation was greater in two harvests. Bahiagrass proportion was greatest for

Ecoturf-Argentine, while RP was greatest for Q6B-DF9. No difference among

treatments was found for total N aboveground. The RP monocultures had greater

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biological N2 fixation than RP growing in mixtures. Root-rhizome biomass in mixtures,

and their N and C content, did not differ from RP or bahiagrass monocultures, however

they were greater in 2016 than in 2015. In 2016, mixture C:N ratio in the belowground

biomass were equivalent to N-fertilized bahiagrass monocultures. Bahiagrass and RP

belowground proportion did not differ among the mixtures. Ammonia volatilization losses

were greater for N-fertilized bahiagrass, however no difference among treatments was

found for NO3- concentration in leachate or N2O concentration (mg L-1). The association

of bahiagrass and RP proved to produce as much as N fertilized bahiagrass with lower

N losses due to NH3 volatilization.

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CHAPTER 1 LITERATURE REVIEW

Florida Cattle Industry and Hay Operation

Florida cattle total herd is approximately 1,690,000 heads, including calves

(USDA-NASS, 2015). Beef cattle (cows) and dairy cattle (cows) inventories were

915,000 and 125,000, respectively. For most of these animals, forage crops are the

primary feed source, and all of them receive forage as part of their diet.

Despite generally favorable rainfall and temperature conditions for growing

forages in Florida, perennial pasture growth decreases as temperatures decrease and

daylength shorten in fall. Strategies such as the adoption of mixed cool-season annual

grasses (Dubeux et al., 2016) or mixed stands of annual grasses and cool-season

legumes (Garcia et al., 2016) may improve animal average daily gain (ADG) during this

time of the year. However, there remains a gap or transition period where neither,

warm-season or cool-season forages are available for grazing animals. In north Florida,

these periods occur from November to December, and in May (Sollenberger and

Chambliss, 1991).

Forage conservation, via hay, haylage, or balage, is an important means for

feeding livestock during the cool season and/or drought years. In 2015, over 117,000 ha

of hay were harvested in FL and the sales generated nearly 130 million USD (USDA-

NASS, 2015). Total hay production in Florida ranges from 600,000 to 800,000 Mg yr-1

(Chambliss et al., 2006). In 2015, total hay production 6.3 Mg ha-1 or a total state-wide

production of 737,000 Mg yr-1 (Johansson and Harris, 2016).

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Bahiagrass

Florida cow-calf operations rely on grazing systems and bahiagrass (Paspalum

notatum Flügge) is the most planted perennial forage grass in the state at over 1 million

hectares (Chambliss and Sollenberger, 1991). Most bahiagrass land is used for grazing

animals and some for hay, sod, and seed production (Chambliss and Sollenberger,

1991).

Bahiagrass is a perennial, rhizomatous warm-season grass that was likely

introduced from Brazil in 1914 (Trenholm et al., 2015); it has viable seeds and can be

vegetatively propagated (Ball et al., 1996a). Comprising the stem and the racemose

panicle, bahiagrass grows from 10 to 60 cm and yields approximately 3.3 to 10.3 Mg ha-

1, depending on N fertilization (0 and 270 kg N ha-1, respectively) and management

(Hanna and Sollenberger, 2007).

Bahiagrass is responsive to improved management practices. Beaty et al. (1974)

observed herbage accumulation of ‘Pensacola’ bahiagrass varying from 2,440 kg ha-1

yr-1 without irrigation and N fertilization to 14,440 kg ha-1 yr-1 when irrigated and fertilized

with 336 kg N ha-1. Pensacola bahiagrass chemical composition harvested at 5-wk

regrowth intervals and analyzed for N, acid detergent fiber (ADF), lignin, and neutral

detergent fiber (NDF) was 18, 400, 61, and 790 g kg-1 (OM basis), respectively (Flores

et al., 1993). Stewart et al. (2007) evaluated herbage and animal responses under three

different management intensities (low: 40 kg N ha-1 yr-1, stocking rate of 1.2 AU ha-1;

medium: 120 kg N ha-1 yr-1, 2.4 AU ha-1; and high: 360 kg N ha-1 yr-1, 3.6 AU ha-1) in

bahiagrass pastures under continuous stocking. Average daily gain of Angus heifers

ranged from 0.28 to 0.35 kg d-1. Forage nutritive value varied according to management

intensity. Lower intensity resulted in greater herbage mass and lower crude protein (CP)

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and in vitro organic matter digestibility (IVOMD). When herbage mass was 3.42 Mg ha-1

(low management intensity), CP and IVOMD were 99 g kg-1 and 459 g kg-1,

respectively. On the other hand, when herbage mass was 2.95 Mg kg-1 (high

management intensity) CP and IVOMD were 140 g kg-1 and 505 g kg-1, respectively.

Forage quality (expressed as average daily gain) and nutritive value were influenced by

N fertilization and stocking rate.

Fertilizing warm season grasses with N improves herbage accumulation and

nutritive value (Beaty et al., 1974; Hanna and Sollenberger, 2007; Stewart et al., 2007).

The cost of synthetic N fertilization; however, may compromise farmer’s profitability in

an unstable market. In addition, manufacturing, transportation, storage, and

management of N fertilizers are a potential source of environmental pollution (Lal,

2004).

Nitrogen Cycle – Changes and Challenges

Nitrogen is the most abundant element in the atmosphere. It comprises 78% of

the atmosphere while oxygen comprises only 21%, and other gasses < 1%. Nitrogen is

an essential macronutrient for plants. It is important for amino acid and protein

synthesis, besides it being an integral part of the chlorophyll molecule and it is required

for photosynthesis (Snyder and Leep, 2007). Regardless of its abundance, most

atmosphere N exists as a dinitrogen molecule (N2), and it is not directly available for

animal or plant uptake; however other forms, such as ammonia (NH3) and nitrous oxide

(N2O) might be absorbed in small amounts and metabolized by leaves (Grundmann et

al., 1993). The dinitrogen consists of a triple-bond molecule containing a strong bond

that can only be broken down by an industrial processes (e.g., Haber-Bosch process),

lightning, or free-living or symbiotic microorganisms found in soils (Russelle, 2008).

18

Since World War II, the use of synthetic N fertilizer has been highly adopted by

developed countries and its use has broadly changed global cycles and atmospheric

composition. Manufacture of synthetic N fertilizer is possible through the Haber-Bosch

process, which breaks down the dinitrogen molecule triple-bond into ammonia (NH3),

which can then be converted to N fertilizers. Since N is often the most limiting nutrient

for plant growth, fertilizing fields with synthetic N fertilizer has helped to triple crop

production over the past 60 years (Mosier et al., 2005). However, fertilizing with soluble

N fertilizers can potentially pollute the atmosphere and groundwater. Nitrogen losses

also represent an inefficiency in agricultural production and therefore affects farm

profitability.

Nitrogen fertilizer use relates to global population. As population growth is

expected to continue for decades to come, more intensive food production is required.

Since N has a great impact on crops and livestock production, it is estimated that its use

will continue to increase in the upcoming years. The associated pollution caused by its

manufacture storage, transportation, and use (Lal, 2004), will likely follow a similar

trend.

Nitrous Oxide Emissions

In 2010, greenhouse gas (GHG) emissions from agriculture, forestry and other

land use (AFOLU) accounted for 21 to 24% of the total GHG emissions (IPCC, 2014;

FAO, 2016). Despite a decline in forestry conversion to agriculture use, agriculture has

increased its contribution to total GHG emission. The three main GHGs responsible for

the greater proportion of climate change are carbon dioxide (CO2), methane (CH4), and

nitrous oxide (N2O). A total of 49.4 GtCO2-eq yr-1 of anthropogenic GHG emissions

were emitted in 2010, which represents an increase of 2.2% yr-1 since 2000. They likely

19

contributed to an increase of 0.5° to 1.3°C in the global mean surface temperature

between 1951 and 2010 (IPCC, 2014). Out of the total emitted from all sectors, 10.6

GtCO2-eq yr-1 were derived from AFOLU, yet the amounts of GHG that are generated

by pre- and post-production stages are not taken into account in the AFOLU pool,

instead, they are included mainly in the industry, energy generation, and transportation

sectors (FAO, 2016).

Emissions from each of the three GHGs for all sectors were 38, 7.5, and 3.1

GtCO2-eq yr-1 for CO2, CH4, and N2O, respectively. AFOLU emissions for the same

gasses were 5.2, 3.2, and 2.3 GtCO2-eq yr-1, representing 13.7, 42.7, and 74.2% from

the total of all sectors for CO2, CH4, and N2O, respectively (FAO, 2016). Ruminant

methane emission through eructation is caused by enteric fermentation and varies

according to the diet (Pinares-Patiño et al., 2016). It dominates GHG emissions from

AFOLU (FAO, 2016), being responsible for 40% of the total. Added to that, in grassland

systems synthetic fertilizers, manure applied to soils, manure management, and manure

deposited by livestock on the pasture account for 12, 4, 7, and 16% of total GHG

emission, respectively.

Nitrous oxide has a warming potential 298 times greater than carbon dioxide

(CO2), and 13 times greater than methane (CH4) (Solomon, et al., 2007). Nitrification

and denitrification processes in soils contribute to nitrous oxide emissions (Bremer,

2006; Lessa et al., 2014), During microbially-mediated nitrification, ammonium (NH4+) is

oxidized to nitrite (NO2-) and then oxidized to nitrate (NO3

-). Ammonia oxidizers will use

NO2- as electron acceptor when O2 is limiting, which will result in N2O production

(Robertson and Groffman, 2015).

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Although nitrification might directly or indirectly contribute to N2O emissions,

denitrification is the major source of N2O in the atmosphere. Denitrification is a

continuous process where NO3- is reduced sequentially to NO2

-, NO, N2O, and N2 (Li et

al., 2013). The proportion of N2 vs. N2O will likely favor N2O emissions when soils are

wet, due to greater presence of the nitrous oxide reductase (nos) enzyme (Robertson

and Groffman, 2015). Ideal conditions for promoting N2O emissions are anaerobic

conditions, availability of N-oxides, a carbon source, and the presence of the

nitrifying/denitrifying microorganisms.

Nitrous oxide emissions increase after organic (Lessa et al., 2014) or inorganic

(Mosier et al., 1991; Bremer, 2006) N fertilization, but then decrease over time (Bremer,

2006; Klumpp et al., 2011). Both, urine and dung are sources of N2O emissions;

however, N2O emissions from urine are much greater than emissions from feces. Lessa

et al. (2014) found that 0.0193 g N g-1 N-excreta from bovine urine was emitted as N2O,

while only 0.0014 g N g-1 N-excreta was released from bovine dung. Nitrous oxide

emissions due to mineral N fertilization peak soon right after fertilization (Bremer, 2006;

Klumpp et al., 2011). The emission rate and timing are affected by fertilizer chemical

composition and application rate (Bremer, 2006), sward composition (Klumpp et al.,

2011), soil chemical and physical properties (Mosier et al., 1991), and environmental

conditions (Mosier et al., 1986, 1991).

Grasslands play an important role in N2O emissions, whether they are naturally

fertilized by lightning or N-fixing plants, or when industrial N-fertilizers or manure are

applied, and whether they carry animals or not. Tilsner et al. (2003) performed a study

in an extensively managed grassland and evaluated the effects of N fertilization and

21

N2O fluxes. They found 4.6 ± 2.6 mol m-2 h-1 annual emission for fertilized plots, while

plots that did not receive N fertilization emitted 1.4 ± 0.8 mol m-2 h-1. Bremer (2006)

found peak fluxes of 407 g N2O-N m-2 h-1 in perennial ryegrass swards fertilized with

250 kg urea-N ha-1 after a 36 mm rain event and observed a flux decrease after

reaching a peak. In the same study, Bremer (2006) reported greater annual emissions

of N2O-N when perennial ryegrass was fertilized with 250 kg N ha-1 as ammonium

sulfate (58%) or urea (63%), when compared with 50 kg Urea-N ha-1.

Ammonia Volatilization

Another form of gaseous N loss is through NH3 volatilization. In the US, 3.9 Tg

were emitted in 2014 (USEPA, 2014) and agricultural emissions accounted for 81% of

the total. Animal wastes had the greatest contribution to this pool. They represented

55% of the emissions while fertilizers were responsible for 26%. In Europe, animal

waste emissions also led the rank of ammonia losses through volatilization. Ferm

(1998) has shown that 11.7 Tg N yr-1 are lost from livestock excreta in Europe and cattle

excreta accounted for 61% (7.2 Tg N yr-1) of this value. Approximately 80% of the N

consumed by forage-fed ruminants is excreted as dung or urine and only 20% is

converted into meat or milk (Guyader et al., 2016). Ammonia (NH3) is the most reactive

form of nitrogen in the atmosphere. It can be oxidized to N2O or react with acidic gases

and particles, forming hygroscopic salt particles containing (NH4)2SO4 and NH4NO3

(Ferm, 1998).

Overrein and Moe (1967) have shown that NH3 losses are influenced by the rate

of applied urea, temperature, soil depth, moisture content, soil type, and soil pH.

Increasing rates of urea application increases urea hydrolysis rate and consequently

22

NH3 gaseous losses. Contrasting temperatures of 28 and 4°C, the authors found

greater losses for greater temperatures. Management practices, such as crop irrigation

after fertilization may decrease N-losses due to NH3 volatilization by incorporating the N

into the soil (Jantalia et al., 2012). Among the sources of industrial N fertilizer, urea is

the most utilized form in the US.

Untreated urea loses more N by NH3 volatilization than any of the other dry N

fertilizer formulations. Many have reported on how the type of N fertilizer and farming

method control NH3 volatilization rates (Ferm, 1998; Jantalia et al., 2012). Ferm (1998)

estimated that 1.8, 5, 9.3, and 16% of NH3 losses were due to volatilization from

ammonium nitrate, ammonium phosphate, ammonium sulfate, and urea, respectively.

The utilization of slow-release urea-based fertilizer might mitigate losses through NH3

volatilization. Vaio et al. (2008) found differences in the amount of NH3 losses from urea

compared with two other forms of urea-based N fertilizers. They found losses of 25, 17,

and 17%, for urea, urea-NH4NO3 (UAN) and Nitamin, respectively.

Nitrate Leaching

Nitrate (NO3-) leaching to the groundwater is another source of pollution caused

by excess N in the soil. Nitrates are the major contaminant responsible for

eutrophication in rivers (Nguyen et al., 2010) and estuaries resulting in the death of

aquatic animals. In addition, the presence of nitrates in high concentrations in drinking

water may cause health problems in humans (e.g. blue baby syndrome) and animals.

Countries differ somewhat in what safe NO3-N drinking water limits should be. The

European Community Directive has established a limit of 11.3 mg NO3--N L-1 in drinking

water to be safe for human consumption (Gu et al., 2015). In the USA, the US

23

Environmental Protection Agency has established a limit of 10 mg NO3--N L-1 (USEPA,

2016).

Rainfall frequency and intensity (Buckthought et al., 2015), soil texture, soil water

holding capacity, soil organic matter, and land management are factors that affect

nitrate leaching to the groundwater (Monteagudo et al., 2012). The combination of high

N application rates and intensive grazing can result in greater nitrate leaching from

pastures than fields harvested for hay (Eriksen et al., 2015). Grazing cattle have a

significant effect on nitrate leaching because they return much of the N back to the soil

through excreta deposition, and usually the distribution of the excreta in the pasture is

not uniform (Dubeux et al., 2009). The combined effect of urine patches and high rates

of N fertilizer application contribute to greater amounts of N losses (Buckthought et al.,

2015). Irrigated croplands, however, are considered as the main land use responsible

for eutrophication in rivers (Monteagudo et al., 2012).

In Ireland, limits of synthetic N fertilizer application challenge producers to find

other options to increase crop production, and the government already has programs to

financially reward producers who have environmental friendly production systems

(Richards et al., 2015). Organic N fertilization is one of the options that may be adopted

in order to decrease NO3- leaching. Richards et al. (2015) have found significant

decreases in NO3- leached from pastures where organic N was applied.

In hay fields, the distribution of N is more uniform, leading to minimal losses

when compared to the same N fertilizer rate application in pastures. Moreover, these

loads may still be potentially high when great amounts of N fertilizer are applied and the

soil is not well managed. Gu et al. (2015) evaluated the effect on nitrate leaching of two

24

different rates of manure/urea application (90 and 180 kg N ha-1) during the wheat

(Triticum aestivum L.) growing season. They reported an increase in leaching of 22.2

and 32.0%, for N rates of 90 vs. 180 kg N ha-1, for manure and urea, respectively. In

both scenarios, grazed or not grazed lands, increasing levels of N fertilization will

increase NO3- leaching, mainly when soils are not well managed.

Biological Nitrogen Fixation (Bringing Legumes into the System)

Forage legumes are known for their nutritive value and biological N fixation

(BNF) potential. They usually have greater CP concentration and digestibility than

warm-season grasses, and they can potentially improve animal performance and

diversify the diet. Environmental benefits, such as mitigation of CH4 emission and

greater grassland biodiversity also add value to the adoption of forage legumes into

grass-monoculture pastures (Guyader et al., 2016).

Biological N2 fixation is a process where free-living or symbiotic bacteria break

down the N2 triple-bond and incorporate it into the soil. Azotobacter, Clostridium, and

Bacillus are examples of free-living bacteria capable of performing BNF. A group of

bacteria generally known as rhizobia (e.g. Rhizobium, Bradyrhizobium, Sinorhizobium,

and Azorhizobium) are symbionts in legumes and express a mutualistic relationship,

where the bacteria supply the plant with N and in turn, the bacteria can benefit from

carbohydrates generated through photosynthesis (Russelle, 2008).

The potential of forage legumes to fix atmospheric N has been reported and

reviewed by many authors (Peoples et al., 1995; Russelle, 2008; Burchill et al., 2014;

Sulieman and Tran, 2014; Apolinário et al., 2015). In the southern US, some commonly

seen cool-season legumes are red clover (Trifolium pratense), white clover (Trifolium

25

repens), and crimson clover (Trifolium incarnatum). These legumes fix in the range of

69 to 373, 54 to 291, and 124 to 185 kg N ha-1, respectively (Peoples et al., 1995).

Nitrogen Fixation and Forage Response of Rhizoma Peanut

In Florida, rhizoma peanut (RP) is the most planted perennial forage legume, and

it has a good potential for BNF and excellent nutritive value across plant entries.

Dubeux et al. (2017) have found a wide range in BNF by RP in a well-established trial

comparing seven entries during 2 yr. Average BNF was 176 and 228 kg N ha-1 in 2014

and 2015, respectively.

Herbage accumulation of RP has been reported by several authors. Mullenix et

al. (2016a) reported herbage accumulation of 8040 and 7800 kg DM ha-1 for four

cultivars or germplasms of mob-stocked RP when 50 or 75% of the canopy was

removed, respectively. Terrill et al. (1996) reported herbage accumulation of 5.2, 7.1,

and 10.6 Mg DM ha-1 yr-1 (for the 3 yr following establishment) for ‘Florigraze’, and

values ranging from 123 to 152, 460 to 506, 332 to 379, and 68 to 88 g kg-1 DM for CP,

NDF, ADF, and lignin. However, herbage accumulation and nutritive value vary among

entries (Dubeux et al., 2017; Mullenix et al., 2016). Prine et al. (2010) registered Ecoturf

as a new RP germplasm with potential for both ornamental or forage use. Ecoturf 4-yr

average yield was 8300 and 10500 kg ha-1, for north and south Florida, respectively,

and CP and IVOMD were 152 and 668 g kg-1, respectively.

Establishment price, weed control, and poor competitiveness of legumes are

some of the reasons that reduce legume adoption and introduction of legumes into

perennial grass pastures. Nonetheless, RP is well-adapted to Florida’s climate and the

presence of rhizomes and low N fertilization requirement (Ball et al., 1996b) are key

26

features improving RP competitiveness with grasses. Mullenix et al. (2016a) evaluated

the appearance of grasses in RP stands and found values ranging from 7 to 24%.

These values varied according to entry and harvest frequency (3 or 6 wk), and

suggested that entries of RP are likely to respond differently to management practices

and the purpose of utilization of them can vary greatly.

Grass-Legume Mixtures in Grasslands

Because N fertilization of grasslands increases production costs and may impact

the environment, utilization of forage legumes in association with warm-season grasses

may be a more sustainable practice. Once growing in association with legumes,

grasses may utilize the N that is being added to the soil from BNF. However, if the N

losses from BNF fixation are minimal, how could grasses have access to this N? Two

different scenarios will be considered to address this point. The first scenario describes

a grazing system, and the second scenario will focus on a hay operation.

Grazing animals remove nutrients from one area of a pasture and redistribute

them to others through excreta deposition. Most of the nutrients ingested by ruminants

return to the soil via feces and/or urine deposition, and only 5-30% are exported as

animal products (Rotz et al., 2005). Kirchmann and Witter (1992) reported 22% of

water-soluble N in total N of fresh feces from milking cows grazing a grass-clover

sward. In Florida, total N in dung and urine for animals grazing bahiagrass averaged

1.90 and 2.68 g kg-1, respectively (White-Leech et al., 2013). Deposition is not generally

uniform and may result in accumulation of these nutrients in congregation areas (i.e.,

shaded areas and water troughs) (Mathews et al., 1994; Dubeux et al., 2009). Mathews

et al. (1994) analyzed soil nutrients in different grazing intensities and reported greater

N concentration in the Ap1 horizon for the zone closer to the shade and water trough

27

(16-22 mg kg-1), compared with the intermediate zone (12-14 mg kg-1), and the most

distant zone (12-13 mg kg-1). Observing the animal behavior in a bahiagrass pasture,

Dubeux et al. (2009) reported a greater urine and dung distribution index for the zone

closer to the water than for the intermediate and most distant zones (6.3 vs 2.1 vs 0.8;

and 5.7 vs 2.8 vs 0.8, for urine and dung, respectively).

In hay operations, the nutrient removal is usually greater when compared to

grazing systems (Mathews et al., 1994), nonetheless, the distribution of nutrients tends

to be more uniform due to mechanical fertilizer application and removal of the forage

component. Decomposing plant litter is one means whereby nutrients are recycled in

hay fields (no animal excreta present), and litter has a slower nutrient release rate than

excreta, therefore the nutrients become available to the plants over a longer period.

Mixing legumes and grasses improves the litter quality and decomposition rate of the

biomass, but this also depends on factors such as N concentration in the plant material

and annual precipitation (da Silva et al., 2012). Inclusion rates of calopo (Calopogonium

mucunoides Desv.) litter into signalgrass [Brachiaria decumbens (Stapf) R. D. Webster]

resulted in greater litter decomposition rate when compared with 100% signalgrass (da

Silva et al., 2012). In the same trial, the litter C:N ratios for 2007 and 2008 were lower

for the 50:50 treatment than for the 100% signalgrass (29.3 vs 77.0; and 33.2 vs 92.9,

respectively). In hay systems, as opposed to grazing systems, most of the nutrients in

the aboveground material are exported as a product (hay or haylage) and are not cycled

back into the system (Mathews et al., 1994). Nonetheless, some of the belowground

biomass (root-rhizomes) can die, mineralize, and become a source of N to non-legumes

plants (Heichel and Henjum, 1991; Haby et al., 2006; Frankow-Lindberg and Dahlin,

28

2013). Mullenix et al. (2016b) observed that RP root-rhizome mass ranged from 3,170

to 4,450 kg ha-1 and contained nearly 18 g N kg-1. The association of grass and legume

results in a greater amount of fixed N than pure stands of legume, due to mutual

stimulation of N uptake by both components (Nyfeler et al., 2011), and reduces losses

to the environment due to more efficient utilization of the soil N.

Bahiagrass-Rhizoma Peanut Mixtures

Mixing bahiagrass and RP is an attractive option for mitigating the use of N

fertilizer in Florida pastures. Both forages are well adapted to the climate, are broadly

used as monocultures, and may improve pasture and animal performance. Costs of

establishing mixed systems and management throughout the year are factors reducing

inclusion of warm-season legumes into grass pastures. Castillo et al. (2014) studied the

establishment of RP into bahiagrass pastures, with the goal to reduce establishment

costs and weed infestations. The authors proposed to strip-plant RP into bahiagrass

(Castillo et al., 2013a); in a manner that allowed the bahiagrass to continue to be used

for hay during the RP establishment period. To reduce weed pressure and

establishment cost, they suggested glyphosate applications, followed by no-till planting

and post-emergence use of imazapic with or without 2,4-D. Castillo et al. (2013b)

reported that establishment was improved with the use of imazapic plus 2,4-D, and an

application of 50 kg N ha-1.

Mullenix et al. (2014) studied how the RP growth habit would affect

establishment and spread when strip-planted into bahiagrass pastures. They concluded

that decumbent germplasms, Ecoturf and Arblick, and intermediate growth habit

Florigraze, could be added in bahiagrass pastures successfully when the swards were

used for hay instead of grazing during the 2 yr after planting.

29

Meanwhile, few studies have been carried to evaluate the overall pasture

performance and nutritive value of bahiagrass-RP mixtures. Dunavin (1992) studied the

association of Florigraze with ‘Tifton 44’ bermudagrass [Cynodon dactylon (L.) Pers.],

‘Floralta’ limpograss [Hemarthria altissima (Poir.) Stapf and C. E. Hubb], and Pensacola

bahiagrass during 8 yr, and observed a good association among them during the first

four years. However, there was a severe decline in the presence of RP in the last four

years in the RP-bahiagrass mixtures. Management practices adopted during

establishment (Castillo et al., 2013b, 2014) and new entries (Mullenix et al., 2014) might

provide better options for long-duration compatibility in mixed swards.

Hypothesis and Objectives

We hypothesized that mixing bahiagrass and RP might mitigate N losses and

create more sustainable low-input forage production system along the years, while

increasing quality and lowering production cost of grasslands. Thus, the overall

objective of this study was to assess the environmental and agronomic advantages of

mixed swards of different cultivars of bahiagrass and RP and contrast them with

monocultures of RP and of bahiagrass receiving N fertilization. The specific objectives

of this work were to contrast effects of bahiagrass-RP mixtures on: i) forage

characteristics including herbage accumulation, botanical composition, in vitro organic

matter digestibility, crude protein, BNF, and belowground biomass and composition; and

ii) GHG emissions including NH3 volatilization, N2O emission, and NO3- concentration in

leachate.

30

CHAPTER 2 HERBAGE RESPONSES AND BIOLOGICAL N2 FIXATION OF RHIZOMA PEANUT

AND BAHIAGRASS ENTRIES IN MONOCULTURE OR IN MIXED SWARDS

Introduction

In Florida, cow-calf operations account for more than 1 million cows, heifers, and

bulls (USDA-NASS, 2015), and most of this production system relies on bahiagrass

(Paspalum notatum Flugge) pastures, which covers over 1 million ha in the state

(Chambliss and Sollenberger, 1991). Bahiagrass is a rhizomatous perennial warm-

season grass (Ball et al., 1996a), introduced from Brazil in 1914 (Trenholm et al., 2015)

and well adapted to Florida. However, it has generally low nutritive value and requires N

fertilization for greater herbage accumulation, nutritive value, and animal performance

(Stewart et al., 2007). Nonetheless, N fertilization may compromise farmers’ profitability

in a fluctuating market. In addition, manufacturing, storage, transportation, and use of N

fertilizer may result in environmental problems, such as eutrophication in rivers and

estuaries (Monteagudo et al., 2012) and global warming (IPCC, 2014). The introduction

of legumes into grass swards may create a long-term sustainable production system,

because legumes are capable of fixing atmospheric N2 (Russelle, 2008) and

transferring it to non-legume plants when growing in association (Haby et al., 2006;

Frankow-Lindberg and Dahlin, 2013). In addition, mixing grasses and legumes can

potentially stimulate legume biological nitrogen fixation (Nyfeler et al., 2011).

Rhizoma peanut (RP; Arachis glabrata Benth.) is a warm-season perennial

legume (Ball et al., 1996b) that is well-adapted to the southern US (Terrill et al., 1996;

Redfearn et al., 2001; Butler et al., 2007; Mullenix et al., 2016a), and it is commonly

cultivated for hay production or pastures for grazing animals. Different from most warm-

climate forage legumes in Florida, RP is productive and persistent over a wide range of

31

management practices (Ortega-S. et al., 1992b). Dubeux et al. (2017) reported the RP

potential to fix atmospheric-N2 and its significant belowground biomass, and total N and

C stored in roots and rhizomes. Besides being a source of N to the soil, RP presents

good forage nutritive value (Mullenix et al., 2016a; Dubeux et al., 2017) and improves

animal performance in mixed swards (Hernández Garay et al., 2004). Williams et al.

(2004) reported improvement in average daily gain of Romosinuano (Bos taurus) calves

in a creep feeding system where calves had access to a RP area. However, not many

studies have investigated the benefits of mixed RP and warm-season grasses. In one of

the few works performed, Dunavin (1992) evaluated the association of ‘Florigraze’ (RP)

with ‘Pensacola’ bahiagrass and reported proportions of RP ranging from 2 to 80% in a

period of 8 years, with an increase from the first to the second year, but a linear

decrease from the second to the eighth year. Management practices adopted during RP

planting (Castillo et al., 2014), establishment year (Castillo et al., 2013a; b), as well as

entries utilized, might affect the performance of the pasture along the years.

Recently, the University of Florida has registered Ecoturf as a RP germplasm

used for ornamental or forage purposes (Prine et al., 2010). Ecoturf is a low-growing RP

suited for the lower Costal Plains and peninsular Florida. When compared with

‘Florigraze’, ‘UF Tito’, and ‘UF Peace’, Ecoturf presented a lower dry matter yield (DMY)

under clipping management to a constant stubble height (Prine et al., 2010). However,

there was no difference in herbage accumulation among these four entries under

grazing (Mullenix et al., 2016b), probably because stubble height in this study was

adjusted based on growth habit of the RP entry. Thus, unlike the clipping study where

cutting height was fixed across entries, the endpoint stubble height in the grazing study

32

was proportional to pre-grazing canopy height, harvesting more of the dense forage in

the lower part of the Ecoturf canopy (Mullenix et al., 2016b).

‘Argentine’ is one of the most common bahiagrass cultivars planted in Florida

(Trenholm et al., 2015), and it is known for its persistence under defoliation (Interrante

et al., 2010) and good seed production (Adjei et al., 2000). New entries of bahiagrass

and RP are being tested at the University of Florida. Among new entries, Q6B (RP) and

DF9 bahiagrass may also be an option for successful mixed swards.

Information is limited about performance of RP in mixed swards with bahiagrass,

and this information may be crucial for increasing the adoption of warm-season mixed

pastures in Florida. This study evaluated the performance of bahiagrass-RP mixtures in

comparison with their monocultures. The specific objectives were to contrast herbage

responses and biological N2 fixation of two RP and two bahiagrass cultivars, in

monocultures or in binary mixtures.

Materials and Methods

Experimental Site

The study was conducted at the North Florida Research and Education Center,

Quincy, FL (30°32' N 84°36'W) during 2015 and 2016. Soils at the experimental site are

classified as Orangeburg loamy sand (fine-loamy, kaolinitic, thermic Typic Kandiudults).

Soil analysis in 2013 reported pH of 6.04 and Mehlich-1 extractable P, K, Mg, Ca, S, B,

Zn, Mn, Fe, Cu of 60, 51, 45, 365, 8, 0.4, 3.6, 45, 93, and 0.8 mg kg-1, respectively.

Total rainfall for 2015 and 2016 was 1379 and 2304 mm (Fig. 2-1), respectively.

Average, minimum, and maximum daily temperature for 2015 and 2016 were 20.1, 7.1,

30.8; and 19.7, 7.4, and 30.9°C, respectively (Fig. 2-2a), and solar radiation during the

experimental time is shown in the Fig. 2-2b).

33

Treatments and Experimental Design

There were eight treatments with three replications (24 experimental units),

arranged in a randomized complete block design. Treatments consisted of two

bahiagrass entries (Argentine and DF9), two RP entries (Ecoturf and Q6B), and the

combinations of each entry of bahiagrass with each entry of RP, i.e., Argentine-Ecoturf,

Argentine-Q6B, DF9-Ecoturf, and DF9-Q6B. Grass monocultures were fertilized with 90

kg N ha-1 harvest-1 as recommended by Mylavarapu et al. (2013) for standardized

fertilization in bahiagrass hay fields. Both DF9 and Q6B are experimental lines,

therefore have not been officially released by the UF-IFAS.

Plot Establishment and Management

Plots were established in 2011 in a fallow field previous planted to bahiagrass.

Glyphosate (N-[phosphonomethyl] glycine) plus 2.2 kg N ha-1 as (NH4)2SO4 (ammonium

sulfate) was applied at 12 L ha-1 in order to eradicate all vegetation. The land was tilled

to remove roots and rhizomes from bahiagrass, which can penetrate deeply into the

soil. In order to complete the eradication, two additional applications were performed.

Plots were 3-m wide by 3-m long with 1.2-m alleys between. The alleys were covered

with a black plastic mulch to prevent alley weeds from spreading into the experimental

units. Argentine and DF9 were broadcast seeded in July 2011; both grass monoculture

and grass-RP plots were seeded with the grass component. The grasses did not

establish well because 2011 was a droughty year. To fill gaps in the stand, 90 rooted

plants were inserted in each plot in late summer 2011. Rhizoma peanut monoculture

plots were planted using 7.5-cm potted plants (plugs) at a density of 1 plant per 0.09 m2,

in the same period as the bahiagrass. The goal was to allow the bahiagrass to establish

before plugging the RP into the mixed treatments, in early April 2012. The plots were

34

mowed once in 2012 and twice in 2013 and 2014, and the forage mass was left in

place. Plots were weeded by hand twice per year.

Once evaluations started in 2015, weeds were manually removed every 14 d as

needed. After each forage harvest, plots were staged at 7.5-cm stubble height using a

push mower (Husqvarna HU 700F). All plots were fertilized with 224 kg ha-1 of 0-5-20 (5

kg P ha-1, 37 kg K ha-1) and 224 kg ha-1 of Kmag (37 kg K ha-1, 20 kg Mg ha-1, and 45

kg S ha-1) following IFAS recommendations for hayfield maintenance (Mylavarapu et al.,

2013), after plots were staged and then after each harvest, except for the last harvest of

the year. Grass monocultures were fertilized with 90 kg N ha-1 after plots were staged

and then after each harvest, except for the last harvest of the year, summing up a total

of 270 kg N ha-1 in 2015 and 360 kg N ha-1 in 2016. Two different types of N fertilizer

were used. On 11 July and 10 Aug. 2015, a commercial formula 34-0-0 (340 g kg) was

applied; in 20 Sept. 2015, 11 Apr., 21 May, 5 July, and 13 Aug. 2016 a commercial

formula 34-0-0 (248 g Urea-N kg-1, 92 g ammoniacal-N kg-1, and 100 g S kg-1) was

applied.

Response Variables

Herbage accumulation and botanical composition

Three harvests were performed in 2015 (August, September, and October) and

2016 (July, August, and September). First, second, and third harvests of each year are

referred as early, middle, and late season, respectively. Herbage accumulation (HA)

was estimated by clipping two 0.25-m2 quadrats per plot at a 7.5-cm stubble height

every 6 wk, except for the first harvest in 2015, which occurred 4 wk after the plants

were staged. Mixtures were hand-separated in order to estimate the proportion of each

component. All samples were dried in a forced air drier at 55°C for 72 h and the dry

35

weight was recorded in order to calculate the herbage accumulation and botanical

composition (BC) of the components (bahiagrass or RP) in the sward.

Crude protein and in vitro organic matter digestibility

Samples used to estimate HA and BC were then ground to pass a 2-mm screen

using a Wiley Mill (Model 4, Thomas-Wiley Laboratory Mill, Thomas Scientific,

Swedesboro, NJ, USA). Sub-samples were taken and ball-milled in a Mixer Mill MM 400

(Retsch, Newton, PA, USA) at 25 Hz for 9 min. Samples ground at 2 mm were used to

determine IVOMD using the methodology described by Moore and Mott (1974). Crude

protein concentration was estimated by multiplying the total N by 6.25 (Azevedo et al.,

2014). Total N method is described, below.

Total aboveground N, %Ndfa, and BNF

Ball-milled samples were analyzed for total N and δ15N using a CHNS analyzer

and the Dumas dry combustion method (Vario Micro Cube; Elementar, Hanau,

Germany) coupled to an isotope ratio mass spectrometer (IsoPrime 100, IsoPrime,

Manchester, UK). The total N aboveground (TNAG) was obtained by multiplying the N

[%] by the HA of each component, where TNAGB was the total N aboveground in

bahiagrass and TNAGRP was the total N above ground in rhizoma peanut. In mixed

plots TNAGB and TNAGRP were summed to estimate TNAG. Biological N2-fixation was

determined by using the natural abundance technique (Freitas et al., 2010). The

proportion of N derived from the atmosphere (%Ndfa) in the aboveground material was

determined by using the equation described by Shearer and Kohl (1996):

%𝑁𝑑𝑓𝑎 = (𝛿15𝑁𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 − 𝛿15𝑁𝑁2−𝑓𝑖𝑥𝑖𝑛𝑔 𝑙𝑒𝑔𝑢𝑚𝑒) ∗ 100

(𝛿15𝑁𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 − 𝐵)

36

Where δ15Nreference is the δ15N value for the non-fixing reference plant, δ15NN2-fixing legume is

the δ15N value for the N2-fixing rhizoma peanut variety in this study, and B is the δ15N

value for the N2-fixing plant grown in the absence of inorganic N. In this study, we used

B = -1.35‰ reported by Okito et al. (2004) for Arachis hypogea L. Reference plants

collected next to the experimental area were collected every year and averaged for the

calculation. Reference plants included Dactyloctenium aegyptium (L.) Willd., Cerastium

glomeratum Thuill., Amphiachyris dracunuloides (DC.) Nutt., Bidens bipinnata (L.),

Linaria canadensis (L.), Ambrosia artemisiifolia (L.), Lepidium spp. (L.), Andropogon

virginicus glaucus (L.), and Richardia scapra (L.) with δ15N ranging from 0.68 to 2.77‰.

Biological N2 fixation was estimated by multiplying the TNAG by the %Ndfa.

Statistical Analysis

Data were analyzed using PROC MIXED from SAS (SAS for Windows V 9.4,

SAS Institute, 2009, Cary, NC, USA). Fixed effects included treatment, harvest date,

year, and their interactions. Blocks and the interactions of treatment × block were

considered random effects. An orthogonal contrast was used to compare the HA of

bahiagrass-RP mixtures with monocultures of bahiagrass and RP. The LSMEANS were

compared using the PDIFF procedure adjusted for Tukey’s test. Differences were

declared significant at P ≤ 0.05.

Results and Discussion

Herbage Accumulation

There was a treatment ˟ season ˟ year interaction (Figure 2-3; P = 0.0143; SE =

376) for HA. Argentine + 90 kg N ha-1 harvest-1 HA (4027 kg DM ha-1) in the early

season of 2016 was greater than the early season in 2015 (1973 kg DM ha-1), which

may have been caused by the difference of growth interval between staging and early

37

season harvest of each year. Treatments did not differ among each other in 2015. In the

early season of 2016, Argentine + 90 kg N ha-1 harvest-1 HA was 4027 kg DM ha-1 and it

was greater than the mixtures HA; however, it did not differ significantly from DF9 + 90

kg N ha-1 harvest-1 (2973 kg DM ha-1) or RP monocultures (2640 and 2840 kg DM ha-1,

for Ecoturf and Q6B, respectively). In the middle season of 2016, Argentine + 90 kg N

ha-1 harvest-1 HA was 3120 kg DM ha-1 and did not differ from DF9 + 90 kg N ha-1

harvest-1 (1347 kg DM ha-1), RP monocultures (1547 and 1627 kg DM ha-1, for Ecoturf

and Q6B, respectively), and the mixture Q6B-DF9 (1347 kg DM ha-1). Thus, Argentine +

90 kg N ha-1 harvest-1 was greater than all mixtures of bahiagrass-RP in 1 out of 6

harvests, while DF9 + 90 kg N ha-1 harvest-1 was never greater than the other

treatments.

Argentine has been reported as the most productive bahiagrass cultivar

(Vendramini et al., 2013), and it is probably more N-use efficient than DF9. Also, DF9 is

a dwarf entry and it has a shorter growth than others bahiagrass entries. There was no

significant difference between treatments among the seasons in 2015 (P > 0.05).

Average HA for early, middle, and late season were 2480, 1700, and 610 kg DM ha-1,

respectively. The average yield for 2015 late season was lower than the average yield

of 2016 late season (P < 0.0001). This difference was caused because environmental

variation in both years. Precipitation (Fig 2-1), average temperature (Fig 2-2a), and

solar radiation (Fig 2-2b) was greater during the late season of 2016 than the late

season of 2015; 119 vs 7 mm, 25.1 vs 20.5°C, and 151 vs 187 W m-2, respectively.

Mullenix et al. (2016a), evaluated four RP entries (Ecoturf, Florigraze, UF Peace,

and UF Tito) under 50 or 75% herbage removal (by height) and 3- or 6-wk regrowth

38

intervals and reported HA per season ranging from 1280 to 4330 kg DM ha-1. They also

found greatest HA in the early season, however, late season HA did not decrease as

much as in this study, perhaps because the current study occurred in a colder

environment. During the cool-season, bahiagrass (Gates et al., 2001) and RP growth

are reduced. In fall, these perennial plants drive their C assimilates toward rhizomes in

order to support winter respiration requirements and regrowth in the next warm season

(Volenec and Nelson, 2007), decreasing aboveground growth.

Botanical Composition

There were effects for treatment (P = 0.0121), season (P < 0.0001), and year (P

< 0.0001) on the BC (Figure 2-4). Among mixtures, Ecoturf-Argentine had the greatest

contribution (67%) of bahiagrass, while Q6B-DF9 had the greatest proportion (57%) of

RP. Ecoturf-DF9 and Q6B-Argentine did not differ between each other or from other

mixtures in proportions of bahiagrass (54 and 56%, respectively) or RP (46 and 44%,

respectively). In terms of cultivars, Q6B was the RP entry that tended to perform more

strongly in the stand, while Argentine was the bahiagrass entry with a more competitive

behavior. Ecoturf and DF9 generally had less dominance in the BC than the other same

species entry in the study.

There was no BC difference for the late season. In the early season, bahiagrass

had generally greater expression in the BC; in the middle season, RP had greater

contribution in the stand. In 2015, it was observed a greater proportion of bahiagrass in

the stand, while in 2016 the greatest proportion was attributed to the RP. There are not

many studies combining RP and bahiagrass. Dunavin (1992) evaluated the association

of RP and three warm-season grasses in an 8-yr study. Harvest frequency in the

respective study varied according to forage availability, 1 harvest was made in the 1st

39

year, and 2 harvests were made in the 2nd. In subsequent years, 3 to 4 harvests were

made, according to the author’s criteria. A stubble height of 6 cm was used in the study.

The studied grasses were ‘Tifton 44’ bermudagrass [Cynodon dactylon (L.) Pers.],

‘Floralta’ limpograss [Hemarthria altissima (Poir.)], and ‘Pensacola’ bahiagrass. The

author found proportions of RP ranging from 16 to 71, 17 to 61, and 2 to 80% in

bermudagrass, limpograss, and bahiagrass, respectively. After eight years, the RP

component in Tifton 44 bermudagrass was 25% while in Pensacola bahiagrass it was

only 2%. Nonetheless, the presence of RP in bahiagrass declined over time. In the first

6 yr of the study, RP represented 22 to 80% of the stand (with a peak in the second

year, and decline in the following years). For the last two years of the study RP

represented 5% (1987) and 2% (1988).

Nutritive Value

Bahiagrass CP

There was a treatment ˟ season ˟ year interaction (P < .0001, SE = 0.7171) for

bahiagrass CP concentration (Figure 2-5). Crude protein concentration of the entry DF9

in the early season of 2015 was 143 g kg-1, and did not differ significantly from

Argentine (122 g kg-1) or DF9 present in mixture with Q6B (118 g kg-1). Greater

concentration of CP in early season of 2015 might be related to two main factors: the N

fertilizer application and the shorter interval between the staging cut and the early

season harvest (4 wk). Interrante et al. (2009) conducted a study evaluating two harvest

frequencies for five entries of bahiagrass and reported that all the entries had greater

CP concentration when harvested every 7 d instead of 21 d. There was no significant

difference among treatments for 2015 middle season (P > 0.05), however, in the late

40

season, the N-fertilized bahiagrass treatments were greater than the other treatments

(126 and 129 g kg-1, for Argentine and DF9, respectively).

In 2015, except for Argentine associated with Q6B, all treatments had a lower CP

concentration in the middle season than in the early and late season. Shorter regrowth

interval for the early-season harvest and slower growth in the late season likely were

the causes of the seasonal response observed.

There was no difference among treatments in the early season of 2016. In the

middle and late seasons, DF9 and DF9 growing with Q6B did not differ, however DF9

CP concentrations were greater in both seasons than all the other treatments. Crude

protein concentration in bahiagrass was greater for the early season of 2015 when

compared with the early season of 2016 for the N-fertilized bahiagrass or the mixtures

containing DF9, however, no difference was found for treatments mixed with Q6B.

Johnson et al. (2001) reported N fertilization as a practice responsible for increasing

nutritive value in bahiagrass. Stewart et al. (2007) managed bahiagrass pastures at 3

different intensity levels; low (40 kg N ha-1 yr-1, 1.2 AU), medium (120 kg N ha-1 yr-1, 2.4

AU), and high (360 kg N ha-1 yr-1, 3.6 AU), and reported that bahiagrass CP when

managed at a high intensity (140 g kg-1) was greater than low (99 g kg-1) and medium

(113 g kg-1) intensities treatments. In addition, the animal gain ha-1 was greater for the

high intensity treatment with 252 kg ha-1, while in the low intensity treatment the gain

was 101 kg ha-1.

Bahiagrass IVOMD

Only the samples from 2015 were analyzed for bahiagrass IVOMD. There was a

treatment ˟ season effect (P = 0.0026, SE = 17.1) for bahiagrass IVOMD in the first year

(Table 2-1). Treatments did not differ in early and middle season; however, Argentine

41

had a greater IVOMD (579 g kg-1) than bahiagrass from all the mixtures, except

Argentine growing with Ecoturf in the late season. DF9 IVOMD differed from Argentine

in the late season; however, it did not differ from any of the bahiagrass present in the

mixtures. Interrante et al. (2009) found bahiagrass IVOMD ranging from 530 to 565 g

kg-1 for five different entries (Argentine, Tifton 7, Pensacola, Tifton 9, and PCA Cycle 4)

under two harvest frequencies and two stubble heights. Except for Argentine, greater

IVOMD was observed at 7-d harvest frequency in comparison with a 21-d interval, and

there was no effect of stubble height on this response.

Cold damage might have reduced DF9 bahiagrass IVOMD before the end of the

experiment. DF9 had brownish dry leaves, reflecting less tolerance to cold weather or

daylight variation than Argentine. The lowest bahiagrass IVOMD (395 g kg-1) was found

in the late season for DF9 in mixture with Ecoturf. IVOMD season averages were 589,

470, and 456 g kg-1, for the early, late, and middle season, respectively, and were

significantly different (P > 0.0001) from each other. The same factors that affected CP

concentration, i.e., plant maturity in the early season and slower growth in the late

season may also have affected IVOMD (Interrante et al., 2009).

Rhizoma peanut CP

There was a treatment ˟ year interaction for RP CP concentration (Figure 2-6a; P

= 0.0087, SE = 8.1). In 2015, Q6B in monoculture was greater than RP of all the

mixtures; however, the same result was not observed in 2016. In general, RP

monocultures usually had equal or greater CP concentration than when RP was in

mixtures. Values ranged from 152 to 203 g kg-1, for the mixture Ecoturf-DF9 and Q6B,

respectively. Mullenix et al. (2016a) reported values ranging from 165 to 210 g kg-1 in a

study performed in central Florida with four entries of RP. In this study, Ecoturf CP

42

concentrations were 194 and 192 g kg-1 when harvested at 3 or 6 weeks, and they did

not differ according to sampling time.

There was also a season ˟ year effect (P < 0.0001, SE = 5.1) for RP CP, with

values ranging from 162 to 189 g kg-1 (Figure 2-6b), for the early and late season of

2016, respectively. During the middle and late season of 2016, RP CP concentration

was greater than in the previous year. This may have been due to greater rainfall during

the late season of each year (October 2015 vs. September 2016). In the case of RP,

water stress may have resulted in loss of some leaves, which resulted in a greater

proportion of shoot:leaf ratio, decreasing the CP concentration. Besides greater rainfall

occurring in the first year than in the second year during the early season, the 4-wk.

harvest might have affected RP CP concentration. In this case, plant maturity was more

important in determining forage CP than water availability.

Rhizoma peanut IVOMD

Only the samples from 2015 were analyzed for RP IVOMD. There was a

treatment effect for RP IVOMD (P = 0.05, SE = 5.7). When Ecoturf was mixed with DF9,

it had a greater IVOMD than Q6B mixed with Argentine; however, other treatments did

not differ from these treatments or among each other (Table 2.2). Values ranged from

703 to 733 g kg-1 for Q6B-Argentine and Ecoturf-DF9, respectively. These values were

similar to values found in other recent studies, 660-690 g kg-1 (Mullenix et al., 2016a),

and 645-750 g kg-1 (Dubeux et al., 2017). Williams et al. (2004) reported improvement

in Romosinuano calf performance when the animals were creep-grazing a RP area.

Animals may even be finished in RP with a small reduction in quality grade when

compared with concentrate-finished steers (Bennett et al., 1995).

43

Total Nitrogen Aboveground

There was a treatment ˟ season effect (P = 0.03444, SE = 7.4) on TNAGRP.

Greater N yields were found in the early season for the monocultures (Figure 2-7a).

Q6B and Ecoturf yielded 75 and 69 kg N ha-1, respectively, however they did not differ

from Q6B/DF9 mixture (50 kg N ha-1), which may reflect the great potential of Q6B to

compete with grasses. The least TNAGRP was found in the middle season for the

mixture Ecoturf/Argentine (8.1 kg N ha-1), which supports the lower presence of RP

found in the BC due to a more competitive nature of Argentine bahiagrass. Since total N

aboveground is a function of total N * HA, monocultures of RP were benefited by the

greater proportion of it in the monoculture stands. During the early season of 2015,

TNAGRP was greater (P.>0001; SE = 5.7) than middle and late season of the same year

(Figure 2.7b; 49, 24, and 10 kg N ha-1, respectively). In 2016, TNAGRP was greater

during the early season than in the middle season (41 vs. 27 kg N ha-1, respectively),

however it did not differ significantly from the late season (34 kg N ha-1).

There was a treatment ˟ year interaction for TNAGB (Figure 2-7c; P <.0001, SE =

1.8 kg N ha-1). Fertilized Argentine had the greatest yield in 2016, and differed

significantly from 2015 Argentine and DF9 in both years. However, no difference was

found between Argentine in the first year compared to DF9 in both years. Greater HA

for bahiagrass monocultures occurred due to N-fertilization (90 kg N ha-1 harvest-1). The

effects of N fertilization on bahiagrass have already been reported in the literature (Blue,

1973; Beaty et al., 1974, 1980; Stewart et al., 2007). Ecoturf-DF9 and Q6B-Argentine

had greater TNAGB in the first year in comparison with the second year. Values ranged

from 6 to 40 kg N ha-1 harvest-1, for Q6B-Argentine and Argentine, respectively. Season

˟ year effect was also significant for TNAGB (P <.0001, SE = 2.05). Bahiagrass growing

44

in the early season of 2015 yielded 28 kg N ha-1 while the late season of the same year

yielded 8 kg N ha-1 (Figure 2-7d). Herbage accumulation decreased in the late season

and directly affected TNAGB. The difference in temperature can also explain the

difference found in the late season of both years.

There was a treatment effect for total N aboveground (P = 0.0003, SE = 5.9).

Rhizoma peanut monocultures yielded 50 and 53 kg N ha-1 harvest-1, for Ecoturf and

Q6B, respectively, and did not differ significantly from Q6B-DF9 (42.5 kg N ha-1) and

Argentine (34.7 kg N ha-1), however they were greater than the other treatments (Figure

2-8a). Great HA and N concentration in Q6B contributed for the high TNAG yield. When

forage quantity is not a limiting factor, the addition of high quality forage in grazing

systems improves animal performance.

There was a season ˟ year effect for TNAG (P <.0001, SE = 5.3 kg N ha-1).

Forages growing in the early season 2015 yielded 58 kg N ha-1 and was greater than

any other season in both years (Figure 2.8b). Forages growing in the late season 2015

had the least N yield and differed from the late season in 2016. This might be explained

by lower HA associated with reduced day length and lower temperatures.

% Nitrogen Derived from the Atmosphere (%Ndfa)

There was a treatment ˟ year effect for %Ndfa (P = 0.0131, SE = 0.048). In 2015,

there was a greater %Ndfa in RP aboveground tissue for Q6B-Argentine, Ecoturf-

Argentine, and Ecoturf-DF9 than in 2016. The other treatments had no difference from

one year to the other (Figure 2-9). Mixed stands were greater in %Ndfa than Q6B,

however, they did not differ from Ecoturf in 2015. No significant difference was found in

%Ndfa in 2016, with values ranging from 59 to 83% in the entire study. Dubeux et al.

(2017) found %Ndfa in seven RP cultivars ranging from 67 to 96%. Nyfeler et al. (2011)

45

have shown that nitrogen fixation in legumes can be stimulated in the presence of non-

N-fixing plants, however, further investigations must be made in order to provide

enough information whether or not the presence of bahiagrass in the stand is

stimulating the %Ndfa in RP harvested or not.

Biological Nitrogen Fixation

Monocultures of RP had greater BNF than all the mixtures throughout the

experimental period (P <.0001, SE = 3.2). Ecoturf and Q6B fixed 32 and 31 kg N ha-1

harvest-1, while the mean for mixed stands was 13 kg N ha-1 harvest-1 (Figure 2-10a).

There was no difference among the mixed stands, however, there was a season ˟ year

interaction (P <.0001, SE = 3.1). In 2015, BNF in the early season averaged 34 kg N ha-

1, while in the late season of the same year BNF was only 7.6 kg N ha-1 (Figure 2-10b).

There was a significant difference between 2015 and 2016 late season, which was

probably caused by the favorable environmental conditions of 2016 late season

compared to 2015 late season.

Biological nitrogen fixation is an important mechanism to sustain life on earth.

Association of legumes with non-N-fixing species may reduce the costs for N

fertilization. As BNF is a function of the HA and %Ndfa in RP, the portion of N that may

have been transferred to bahiagrass was not taken into account. Studies, where the N

transfer from RP to warm-season grasses in Florida are investigated, may help to

respond the question whether or not the bahiagrass is stimulating the BNF from RP or

not. Mixed stands of bahiagrass and RP might not only reduce production cost, but also

decrease environmental damages due to N losses from the production system.

46

Conclusions

In 2015, mixtures and monocultures had similar HA. However, Argentine had

greater HA than the mixtures in the early and middle season of 2016 (except from Q6B-

DF9 middle season). Mixtures produced as much biomass as legume monocultures and

N-fertilized DF9. Herbage accumulation in the late season was affected by lower

temperature and decreased day length. The entry Q6B was more competitive than

Ecoturf, while Argentine was more competitive than DF9. Biological N2 fixation was

greater for RP monocultures, however, the proportion of N transferred to the bahiagrass

was not estimated. The % of N derived from the atmosphere in RP was stimulated in

mixed stands in 2015, however, the same results were not found in 2016. Nutritive

value of mixed stands was not always affected for single components; however, RP had

greater IVOMD and CP than bahiagrass. Thus, mixtures with greater participation of RP

might result in greater average forage nutritive value. Further studies are necessary to

study associative effects of bahiagrass and RP forage and how does it affect forage

nutritive value. Mixtures of RP and bahiagrass present an option to reduce N fertilization

and enhance forage nutritive value on pastures.

47

Table 2-1. Bahiagrass in vitro organic matter digestibility (IVOMD) fertilized with N or growing in mixtures with rhizoma peanut (RP).

Early Middle Late

--------------- g kg-1 ---------------

Argentine 545 a+ 417 a 579 a

Ecoturf-Argentine 518 a 402 a 489 ab

Ecoturf-DF9 481 a 407 a 395 c

DF9 474 a 389 a 460 bc

Q6B-Argentine 512 a 424 a 477 bc

Q6B-DF9 468 a 394 a 424 bc

Treatment x season (P = 0.0026, SE = 17.1 g kg-1, n = 54) +Means within a column not followed by the same letter differ according to PDIFF procedure adjusted by Tukey (P < 0.05).

48

Table 2-2. Rhizoma peanut in vitro organic matter digestibility (IVOMD) growing in monoculture or mixed with bahiagrass.

Treatment g kg-1

Ecoturf 718 ab+

Ecoturf/Argentine 726 ab

Ecoturf/DF9 733 a

Q6B 728 ab

Q6B/Argentine 703 b

Q6B/DF9 718 ab

P 0.05

SE 5.7 +Different letter means significant difference between treatments according to PDIFF procedure adjusted by Tukey (P < 0.05).

49

Figure 2-1. Monthly rainfall in 2015 and 2016, and 30-yr average in the experimental area, Quincy, FL.

0

100

200

300

400

500

600

700

800

900

1000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Rai

nfa

ll (m

m)

2015 2016 30 yr Average

50

Figure 2-2. A) Minimum, maximum, and average monthly temperature, and B) Solar radiation in the experimental area during 2015 and 2016.

-10.00

-5.00

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

Jan

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per

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re °

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A

Min Max Average

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Oct

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No

v-1

6

Dec

-16

Sola

r R

adia

tio

n (

W m

-2)

B

51

Figure 2-3. Herbage accumulation of bahiagrass-rhizoma peanut (RP) mixtures and monocultures in 2015 and 2016 as affected by treatment ˟ season ˟ year (P = 0.0143; SE = 376.06), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Early Middle Late

Her

bag

e A

ccu

mu

lati

on

(kg

DM

ha-1

har

vest

-1)

2015

Argentine Ecoturf Ecoturf/Argentine Ecoturf/DF9 DF9 Q6B Q6B/Argentine Q6B/DF9

0

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1000

1500

2000

2500

3000

3500

4000

4500

Early Middle Late

Her

bag

e A

ccu

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on

(kg

DM

ha-1

)

2016

Argentine Ecoturf Ecoturf/Argentine Ecoturf/DF9 DF9 Q6B Q6B/Argentine Q6B/DF9

52

Figure 2-4. Botanical composition of bahiagrass-rhizoma peanut (RP) mixtures as

affected by treatment (P = 0.0121, SE = 0.03405), season (P < 0.0001, SE = 0.02809), and year (P < 0.0001, SE = 0.02184) according to PDIFF procedure adjusted by Tukey (P < 0.05).

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

ETArg

ETF9

Q6BArg

Q6BF9

Early

Middle

Late

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

2015

2016

Grass % RP %

53

Figure 2-5. Bahiagrass crude protein concentration as affected by treatment ˟ season ˟ year (P < 0.0001, SE = 0.7171) when in mixed swards with rhizoma peanut (RP) or in monoculture and fertilized with 90 kg N ha-1 harvest-1, according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

20

40

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80

100

120

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160

Early Middle Late

Bah

iagr

ass

cru

de

pro

tein

co

nce

ntr

atio

n (

g kg

-1)

2015

Argentine Ecoturf/Argentine Ecoturf/DF9 DF9 Q6B/Argentine Q6B/DF9

0

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iagr

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ntr

atio

n (

g kg

-1)

2016

Argentine Ecoturf/Argentine Ecoturf/DF9 DF9 Q6B/Argentine Q6B/DF9

54

Figure 2-6. Rhizoma peanut crude protein concentration when growing in monoculture

or grown in mixture with bahiagrass as affected by A) treatment ˟ year (P = 0.0087, SE = 10.4) or B) season ˟ year (P <.0001, SE = 5.1), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

20

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60

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Ecoturf Ecoturf/Argentine Ecoturf/DF9 Q6B Q6B/Argentine Q6B/DF9

RP

cru

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n (

g kg

-1)

A

2015 2016

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Early Middle Late

RP

cru

de

pro

tein

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nce

ntr

atio

n (

g kg

-1)

B

2015 2016

55

Figure 2-7. Total rhizoma peanut (RP) aboveground N when growing in monoculture or

mixed with bahiagrass as affected by: A) treatment ˟ season effect (P = 0.034, SE = 7.4) and; B) season ˟ year (P <.0001, SE = 5.7); and total N aboveground of bahiagrass when growing in monoculture or mixed with rhizoma peanut as affected by C) treatment ˟ year (P <.0001, SE = 1.8) and D) season ˟ year effect (P <.0001, SE = 2.05), according to PDIFF procedure adjusted by Tukey (P < 0.05), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

10

20

30

40

50

60

70

80

90

Eco Eco/Arg Eco/DF9 Q6B Q6B/Arg Q6B/DF9

TNA

GR

P(k

g N

ha-1

)A

Early Middle Late

0

10

20

30

40

50

60

70

80

90

Early Middle Late

TNA

GR

P(k

g N

ha-1

)

B

2015 2016

0

5

10

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45

Argentine Eco/Arg Eco/DF9 DF9 Q6B/Arg Q6B/DF9

TNA

GB

(kg

N h

a-1)

C

2015 2016

0

5

10

15

20

25

30

35

40

45

Early Middle Late

TNA

GB

(kg

N h

a-1)

D

2015 2016

56

Figure 2-8. Total aboveground N of bahiagrass-rhizoma peanut (RP) mixtures or

monocultures as affected by A) Treatment (P = 0.0003, SE = 5.9) and; B) season ˟ year effect (P <.0001, SE = 5.3), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

10

20

30

40

50

60

70

Argentine Ecoturf Eco/Arg Eco/DF9 DF9 Q6B Q6B/Arg Q6B/DF9

Tota

l N a

bo

vegr

ou

nd

(kg

ha-1

har

vest

-1)

A

0

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40

50

60

70

Early Middle Late

Tota

l N a

bo

vegr

ou

nd

(kg

N h

a-1)

B

2015 2016

57

Figure 2-9. Percentage of N derived from atmosphere (%Ndfa) in rhizoma peanut as

affected by treatment ˟ year (P = 0.0131, SE = 3.4), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Eco Eco/Arg Eco/DF9 Q6B Q6B/Arg Q6B/DF9

%N

dfa

2015 2016

58

Figure 2-10. Rhizoma peanut biological N2-fixation as affected by A) treatment (P <

0.0001, SE = 3.2) and; B) season x year (P < 0.0001, SE = 3.1), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

5

10

15

20

25

30

35

40

Eco Eco/Arg Eco/DF9 Q6B Q6B/Arg Q6B/DF9

RP

Bio

logi

cal N

2Fi

xati

on

(kg

N h

a-1h

arve

st-1

)A

0

5

10

15

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30

35

40

Early Middle Late

RP

Bio

logi

cal N

2Fi

xati

on

(kg

N h

a-1h

arve

st-1

)

B

2015 2016

59

CHAPTER 3 BELOWGROUND RESPONSES OF RHIZOMA PEANUT AND BAHIAGRASS

GERMPLASMS IN MONOCULTURE OR IN MIXED SWARDS

Introduction

Forage legumes are capable of fixing atmospheric N2, decreasing the need for N

fertilization. This is especially important in mixed swards with non-N fixing plants and

might create a more sustainable system (Suter et al., 2015). In addition, the presence of

grasses in legume stands can potentially stimulate the biological N2-fixation (BNF) due

to nutrient competition (Nyfeler et al., 2011). In Florida, bahiagrass (Paspalum notatum

Flügge) covers over 1 million ha making it the most planted forage species in the state

(Chambliss and Sollenberger, 1991). Bahiagrass is a rhizomatous warm-season grass

well adapted to Florida (Ball et al., 1996a). It is commonly used for grazing and hay

production, surviving under different management practices and intense stress (Stewart

et al., 2007; Interrante et al., 2009; Vendramini et al., 2013). Therefore, it is challenging

to find forage legumes capable of successfully competing with bahiagrass.

Rhizoma peanut (RP; Arachis glabrata Benth.) is a warm-season legume

adapted to a wide range of grazing managements (Ortega-S. et al., 1992b), and it is an

option for mixed swards in the southern USA. Williams et al. (2004) reported an

increase in average daily gain (ADG) of Romosinuano (Bos taurus) when calves were

grazing RP in a creep grazing system. Rhizoma peanut can also be used to finish cattle.

In comparison with concentrate-finished Brahman (Bos indicus) steers, animals finished

in RP pastures had a low reduction in quality grade (Bennett et al., 1995), with lower

production cost. However, the benefits RP can bring go over animal performance in a

mixed sward are not well established. Hernandez Garay et al. (2004) found that

60

decreasing proportion of ‘Arbrook’ RP and increasing proportion of perennial warm-

season grasses over time was associated with declining animal performance.

One mechanism for movement of N from a legume to a grass in a mixed-species

sward is mineralization of decaying plant litter. In a study performed in Brazil, da Silva et

al. (2012) found an increase in decomposition rate of signalgrass [Brachiaria

decumbens (Stapf) R. D. Webster] litter with increasing inclusion rates of calopo

(Calopogonium mucunoides Desv.), a common tropical legume in the region. Litter C:N

ratio ranged from 77 to 93, 29 to 33, and 19 to 24, when the ratio of signalgrass to

calopo was 100:0, 50:50, and 0:100, respectively. It has also been shown that

bahiagrass pastures receiving more N fertilizer and grazed at a greater stocking rate

have greater litter N concentration than less intensively managed pastures, resulting in

greater C:N, C:P, lignin:N, and litter deposition rate (Dubeux et al., 2006). Rhizoma

peanut would fit as a tool to increase soil N and enhance nutrient cycling in bahiagrass

pastures.

Belowground responses of RP can be even more important for nutrient turnover

in the soils. Although many authors have reported RP as a forage legume with great dry

matter yield and good nutritive value (Ortega-S. et al., 1992b; Prine et al., 2010;

Mullenix et al., 2016a), RP belowground biomass and nutrient pool can even be greater

(Dubeux et al., 2017). Nonetheless, the values currently found in the literature for RP

belowground biomass are inconsistent. Ortega-S. et al. (1992a) evaluated three

different levels of residual dry matter (RDM; 500, 1500, and 2500 kg ha-1) and four

lengths of grazing cycle (GC; 7, 21, 42, and 63 d) on RP. They observed significant

differences in rhizome mass by the end of the second grazing season. Rhizome mass

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ranged from 450 to 4100 kg ha-1, and the lowest mass was associated with low RDM

(500 kg ha-1) and more intensive GC (7-d). Mullenix et al. (2016b), analyzed the RP

biomass of four entries and found values ranging from 3170 to 4450 kg ha-1, for ‘UF

Peace’ and ‘Ecoturf’, respectively. Root-rhizome mass declined at the end of the second

year for pastures grazed every 3-wk in comparison with the ones grazed every 6-wk.

Dubeux et al. (2017) found RP root and rhizome mass of a 5-yr-old stand to range from

10.6 to 27.8 Mg ha-1, for ‘Florigraze’ and ‘Latitude 34’, respectively. Latitude 34 was not

significantly different from Ecoturf in the trial, which had a belowground biomass of 27.0

Mg ha-1; this value was approximately six times greater than the value found by Mullenix

et al. (2016b) for the same entry. One factor contributing to this difference is length of

stand life and defoliation management. The plots used by Mullenix et al. (2016b) were

2-yr-old plots while those used by Dubeux et al. (2017) had been established for 5 yr. In

addition, the management practices adopted in both studies were different, while

Dubeux et al. (2017) harvested the plots 3 times a year, at a 5 cm stubble height, while

Mullenix et al (2016b) imposed relatively heavy grazing treatments in the plots,

removing 50 or 75% of the above ground biomass every 3 or 6 wk.

Belowground N present in roots and rhizomes of RP is an N pool that might

become available for warm-season grasses after decay and mineralization. Across four

difference entries, Mullenix et al. (2016b) reported RP root-rhizome N concentration

ranging from 15 to 18 g N kg-1, which was similar to values (13 to 16 g N kg-1) found

previously by Ortega-S. et al. (1992a). Among seven different entries, Dubeux et al.

(2017) found values from 11.1 to 20.1 g N kg-1, for Arbrook and Florigraze, respectively.

Studies of belowground biomass of mixed stands of bahiagrass and RP are not

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available in the literature. Understanding belowground processes might provide

answers for a better management of mixed bahiagrass-RP pastures.

The objective of this study was to evaluate the belowground responses of

bahiagrass-RP mixtures in contrast with their monocultures. The specific objectives

were to determine the belowground biomass, proportion of bahiagrass-RP in the

belowground biomass, root and rhizome N and C concentrations, C:N ratio, C and N

content, δ13C, and δ15N.

Material and Methods

Experimental Site

The study was conducted at the North Florida Research and Education Center,

Quincy – FL (30°32' N 84°36'W) during 2015 and 2016. Soils at the experimental site

are classified as Orangeburg loamy sand (fine-loamy, kaolinitic, thermic Typic

Kandiudults). Soil analysis in 2013 reported pH 6.04 and Mehlich-1 extractable P, K,

Mg, Ca, S, B, Zn, Mn, Fe, Cu of 60, 51, 45, 365, 7.6, 0.4, 3.6, 45, 93, and 0.8 mg kg-1,

respectively. Total rainfall for 2015 and 2016 was 1379 and 2304 mm, respectively

(Figure 3-1a). Average, minimum, and maximum daily temperature for 2015 and 2016

were 20.1, 7.1, 30.8; and 19.7, 7.4, and 30.9°C, respectively (Figure 3-1b).

Treatments and Experimental Design

There were eight treatments with three replications (24 experimental units),

arranged in a randomized complete block design. Treatments consisted of two

bahiagrass entries (Argentine and DF9), two RP entries (Ecoturf and Q6B), and the

combinations of each entry of bahiagrass with each entry of RP, i.e., Argentine-Ecoturf,

Argentine-Q6B, DF9-Ecoturf, and DF9-Q6B. Grass monocultures were fertilized with 90

kg N ha-1 harvest-1 as recommended by Mylavarapu et al. (2013) for standardized

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fertilization in bahiagrass hay fields. Both DF9 and Q6B are experimental lines,

therefore have not been officially released by the UF-IFAS.

Plot Establishment and Management

Plots were established in 2011 in a fallow field previous planted to bahiagrass.

Glyphosate (N-[phosphonomethyl] glycine) plus 2.2 kg N ha-1 as (NH4)2SO4 (ammonium

sulfate) was applied at 12 L ha-1 in order to eradicate all vegetation. The land was tilled

to remove roots and rhizomes from bahiagrass, which can penetrate deeply into the

soil. In order to complete the eradication, two additional applications were performed.

Plots were 3-m wide by 3-m long with 1.2-m alleys between. The alleys were covered

with a black plastic mulch to prevent alley weeds from spreading into the experimental

units. Argentine and DF9 were broadcast seeded in July 2011; both grass monoculture

and grass-RP plots were seeded with the grass component. The grasses did not

establish well because 2011 was a droughty year. To fill gaps in the stand, 90 rooted

plants were inserted in each plot in late summer 2011. Rhizoma peanut monoculture

plots were planted using 7.5-cm potted plants (plugs) at a density of 1 plant per 0.09 m2,

in the same period as the bahiagrass. The goal was to allow the bahiagrass to establish

before plugging the RP into the mixed treatments, in early April 2012. The plots were

mowed once in 2012 and twice in 2013 and 2014, and the forage mass was left in

place. Plots were weeded by hand twice per year.

Once evaluations started in 2015, weeds were manually removed every 14 d as

needed. The plots were harvested staged three times in 2015 (July, August,

September) and four times in 2016 (April, May, July, and August). After each forage

harvest, plots were staged at 7.5-cm stubble height using a push mower (Husqvarna

HU 700F). All plots were fertilized with 224 kg ha-1 of 0-5-20 (5 kg P ha-1, 37 kg K ha-1)

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and 224 kg ha-1 of Kmag (37 kg K ha-1, 20 kg Mg ha-1, and 45 kg S ha-1) following IFAS

recommendations for hayfield maintenance (Mylavarapu et al., 2013), after plots were

staged and then after each harvest, except for the last harvest of the year. Grass

monocultures were fertilized with 90 kg N ha-1 after plots were staged and then after

each harvest, except for the last harvest of the year, summing up a total of 270 kg N ha-

1 in 2015 and 360 kg N ha-1 in 2016. Two different types of N fertilizer were used. On

11 July and 10 Aug. 2015, a commercial formula 34-0-0 (340 g kg) was applied; in 20

Sept. 2015, 11 Apr., 21 May, 5 July, and 13 Aug. 2016 a commercial formula 34-0-0

(248 g Urea-N kg-1, 92 g ammoniacal-N kg-1, and 100 g S kg-1) was applied.

Response Variables

Soil Bulk Density

Soil bulk density was estimated individually for each plot by sampling 309 cm3 of

soil and drying it at 105°C, with values ranging from 1.14 to 1.41 g cm-3. Soil bulk

density was determined using the undisturbed core method (Grossman and Reinsch,

2002).

Root-Rhizome Mass

Two 0- to 20-cm depth x 10.8-cm diameter soil cores were taken per

experimental unit at the beginning (9 July 2015, before N fertilization in bahiagrass

plots) and at the end of the experimental period (23 Sept. 2016) by using a golf hole

cutter (Standard Golf Company, Cedar Falls, IA, USA). Soil cores (soil + roots +

rhizomes) were dried at 55°C for 72 h, and then washed in an 850-μm sieve in order to

remove the soil and foreign material. The same protocol was used to dry the root-

rhizome samples again. Root and rhizome dry mass per unit of soil mass was recorded

65

and used for further calculations. Root and rhizome mass per ha was estimated

considering the 0- to 20-cm soil layer and soil bulk density. Results were expressed on

an organic matter (OM) basis to avoid contamination with soil particles.

Root-rhizome Composition

Samples used to determine the root-rhizome mass were ground to pass a 2-mm

screen using a Wiley Mill (Model 4, Thomas-Wiley Laboratory Mill, Thomas Scientific,

98 Swedesboro, NJ, USA) and ball-milled in a Mixer Mill MM 400 (Retsch, Newton, PA,

USA) at 25 Hz for 9 min. Samples were analyzed for N and C concentrations using a

CHNS analyzer by the Dumas dry combustion method (Vario Micro Cube; Elementar,

Hanau, Germany) coupled to an isotope ratio mass spectrometer (IsoPrime 100,

IsoPrime, Manchester, UK), which analyzed the samples for δ13C and δ15N. Total C

content and total N content were obtained by multiplying the respective element

concentration by the belowground OM biomass. The proportion of bahiagrass and RP in

the belowground biomass was estimated by the two pool mixing model (Fry, 2008)

utilizing the δ13C signature of the mixtures where monoculture plots served as

reference, using the formulas:

ƒ1 = (𝛿𝑠𝑎𝑚𝑝𝑙𝑒 – 𝛿𝑠𝑜𝑢𝑟𝑐𝑒2)/(𝛿𝑠𝑜𝑢𝑟𝑐𝑒1 – 𝛿𝑠𝑜𝑢𝑟𝑐𝑒2)

ƒ1 = 1 – ƒ2

Where ƒ1 is the proportion of bahiagrass, ƒ2 is the proportion of RP, δsample is

the δ13C in the mixed sample, δsource1 is the δ13C in the bahiagrass component, and

δsource2 is the δ13C in the RP component (Shearer and Kohl, 1986).

Statistical Analysis

Data were analyzed using PROC MIXED from SAS (SAS for Windows V 9.4,

SAS Institute, 2009, Cary, NC, USA). Fixed effects included treatment, year, and the

66

interaction treatment × year. Blocks and the interaction treatment × blocks were

considered as a random effect. The LSMEANS were compared using the PDIFF

procedure adjusted for Tukey’s test. Differences were declared significant at P ≤ 0.05.

Results and Discussion

Root and Rhizome Biomass

There was a treatment ˟ year effect for belowground (root and rhizome) biomass.

The interaction occurred because in 2016 Argentine and DF9 monocultures had twice

as much belowground biomass as they did in 2015 (Figure 3-2). There were no

differences among treatments in 2015, and values ranged from 5,880 to 11,700 kg OM

ha-1, for DF9 and Q6B-Argentine, respectively. In 2016, Argentine had the greatest

belowground biomass (19,100 kg OM ha-1), however it did not differ significantly from

DF9 (17,600 kg OM ha-1) or any of the mixtures (average was 14,700 kg OM ha-1).

Belowground biomass of RP monocultures was 9,270 and 10,200 kg OM ha-1, for Q6B

and Ecoturf, respectively, however, they did not differ from the mixtures or DF9

monoculture. Interrante et al. (2009) evaluated two stubble heights (4 and 8 cm) and

two harvest frequencies (7 and 21 d), across five entries of bahiagrass (Argentine,

‘Tifton 7’, ‘Pensacola’, ‘Tifton 9’, and PCA Cycle 4). Root and rhizome mass ranged

from 1,510 (PCA Cycle 4 at 8-cm stubble height) to 2,530 kg DM ha-1 (Argentine at 4-

cm stubble height). For harvest frequency, Tifton 9 at 7-d frequency had belowground

mass of 1,240 kg DM ha-1, while Argentine at a similar frequency had 2,280 kg DM ha-1.

The greater response for Argentine when harvested at 4 cm may be an expression of its

plasticity to defoliation.

Nitrogen fertilization has proven to have a positive effect on total belowground

biomass. Holechek (1982) performed a greenhouse and a field experiment to evaluate

67

the effect of N and P fertilization in comparison with no-fertilization in four different

species; wheatgrass (Agropyron dasystachyum), fairway crested wheatgrass

[Agropyron cristatum (L.) Gaertn], alfalfa (Medicago sativa L.), and fourwing saltbush

[Atriplex canescens (Pursh) Nutt.]. The author found significant increases in

belowground biomass for all four species in the greenhouse trial under fertilization. In

the field experiment, only alfalfa did not differ significantly from the unfertilized

treatment. According to the author, N was less limiting to alfalfa than to other species.

Later on, Tardif and Leroux (1992) found a linear increase in rhizome biomass for two

biotypes, and a linear and quadratic response for one biotype of quackgrass [Elytrigia

repens (L.) Nevski] when fertilized with 0, 150, and 250 kg N ha-1. Smooth crabgrass

(Digitaria ischaemum) and bermudagrass (Cynodon dactylon Stapf.) belowground

biomass increased in 18 and 39%, respectively, when N fertilization rates increased

from 20 to 120 g N g soil-1 (Zhu et al., 2015). On Pensacola bahiagrass, increasing N

fertilization rates resulted in greater stolon-root systems when compared with non-N

fertilized plots (Blue, 1973).

Dubeux et al. (2017) found belowground biomass ranging from 10,600

(Florigraze) to 27,800 kg ha-1 (Latitude 34) when accessing seven RP cultivars. There

was also an increase in belowground biomass across all cultivars from 15,100 to 25,000

kg OM ha-1, for 2014 and 2015, respectively. In this study, Ecoturf average belowground

biomass across years was 9,860 kg OM ha-1, and was lower than 27,000 kg OM ha-1

found by Dubeux et al. (2017) and greater than 4450 kg DM ha-1 found by Mullenix et al.

(2016b). Management and time of establishment of these trials, however, were different.

Dubeux et al. (2017) harvested the plots three times during the growing season of 2015

68

and 2016 with a regrowth interval of 9 wk, while Mullenix et al. (2016b) had grazing

animals removing 50 or 75% of the herbage mass every 3 or 6 wk. Additionally, the

Mullenix et al. (2016b) plots had been planted less than 2 yr before defoliation began,

while the Dubeux et al. (2017) plots had been established 5 yr before evaluations start.

Ortega-S. et al. (1992a) evaluated the influence of length of grazing cycle (GC)

and residual dry matter (RDM) after grazing of Florigraze RP. The found the lowest

rhizome biomass for the more intensive GC (7 days) and the least RDM (500 kg ha-1).

Intensive grazing resulted in utilization of rhizome energy pool to sustain aboveground

growth. In this study, the herbage removal was not as intensive as the one performed

by Ortega-S et al. (1992a), and the N fertilization more likely stimulated root-rhizome

growth.

Root and Rhizome Nitrogen Concentration and Content

There was a treatment × year effect for N concentration in roots and rhizomes (P

= 0.0223, SE = 1.004). The difference occurred because DF9 had a greater N

concentration in 2016 than in 2015 (9.9 and 4.1 g N kg-1, respectively). In the first year,

Q6B and Ecoturf had the greatest N concentration, 13.1 and 13.5 g N kg-1, respectively;

however, they did not differ significantly from Q6B-DF9 (8.3 g N kg-1). Mixtures and

bahiagrass monocultures were not different from each other in 2015 and averaged 5.4 g

N kg-1. In 2016, greater belowground N concentration was observed for Ecoturf (14.4 g

N kg-1) and Q6B (11.7 g N kg-1), however, Q6B was not significantly different from all

the other treatments, while Ecoturf did not differ significantly from DF9, Ecoturf-

Argentine, and Q6B-DF9. The application of N fertilizer increased the N concentration in

DF9 bahiagrass root-rhizome fraction; however, it was not sufficient to detect a

difference in Argentine. Productivity and persistence of Argentine in low N input systems

69

have been reported by Vendramini et al. (2013). Under 2 or 4 wk grazing frequency,

similar results were found for the root and rhizome mass. Another potential explanation

is the dilution effect caused by greater belowground biomass in 2016 than in 2015.

Nitrogen fertilizer application of 84, 168, and 336 kg N ha-1 resulted in N

concentration increase in Pensacola bahiagrass roots of 10.6, 12.7, and 17.3 g N kg-1,

respectively (Beaty et al., 1974), compared to 9.5 g N kg-1 when no N was applied.

Rhizoma peanut N concentration in Ecoturf and Q6B approached values reported

before for various RP entries, 13 to 16 g N kg-1 (Ortega-S. et al., 1992a), 15 to 18 g N

kg-1 (Mullenix et al., 2016b), and 11.1 to 20.1 g N kg-1 (Dubeux et al., 2017).

There was a treatment ˟ year effect (P = 0.0245, SE = 25.7643) on N content (kg

N ha-1). The difference occurred because in 2016 Q6B-DF9, Argentine, Ecoturf-

Argentine, and DF9 yielded more N than in 2015 (Figure 3.4; 126, 168, 169, and 177 kg

N ha-1, respectively). However, in both years, treatments did not differ among each

other. The average for 2015 was 61 kg N ha-1, while the average for 2016 was 139 kg N

ha-1 (P < 0.0001). Increase in N yield in the second year was caused by an increase in

both N concentration and biomass, mainly in bahiagrass entries.

During the growing seasons (from May to October) of 2005, 2006, and 2007,

Interrante et al. (2009) reported values for root-rhizome mass ranging from 150 kg N ha-

1 (for Tifton 7 and Tifton 9, harvested every 7 d) to 240 kg N ha-1 (Argentine, harvested

every 7 d). In the respective study, plots were fertilized with 200 kg N, 36 kg P, and 132

kg K ha-1 yr-1 (40 kg N ha-1 harvest-1). In this study, the N fertilization rate was greater,

however the N content for roots and rhizomes of both bahiagrass entries were lower

than the N content found by Interrante et al. (2009) for Argentine. The effect of N

70

fertilization in root and rhizome biomass have been reported before. Pensacola

bahiagrass N content (kg DM ha-1) in roots varies according to N fertilizer rates. When

fertilized with 0, 84, 168, and 336 kg N ha-1, Pensacola bahiagrass belowground N

content were 36, 112, 173, 191 kg N ha-1, respectively (Beaty et al., 1980).

Ecoturf belowground N content was 574 kg ha-1, when plots were sampled 5 yr

after planting (Dubeux et al., 2017), which is about six times the value found in this

study. Rhizomes act as an energy storage organ in perennial crops. Rhizoma peanut

directs energy to rhizomes and preserves the energy in order to regrow in the next

season. Frequent harvests decrease the energy in the rhizome to support plant growth

(Ortega-S. et al., 1992a). In this study, mixtures were capable of performing the same

as fertilized grass and RP monocultures. The amount of belowground N is an important

characteristic for mixed stands, once the addition of N decreases C:N ration and speed

up nutrient recycling via decaying belowground tissues.

Root and Rhizome Carbon Content

There was no significant difference (P = 0.2165, SE = 626.11) among treatments

for C content, and the average was 4,450 kg C ha-1. However, there was a year effect

(P = 0.0003, SE = 299). The C contents for 2015 and 2016, were 3,540 and 5,360 kg C

ha-1, respectively (Figure 3-5). Most likely, the increase in biomass caused by

fertilization and plant response to defoliation increased C content in the second year.

Carbon dioxide is one of the greenhouse gases (GHGs) responsible for global warming.

This gas contributed 78% of the GHG emissions from 1970 to 2010 (IPCC, 2014).

Agriculture is one of the sectors with highest input of GHG in the atmosphere (IPCC,

2014; FAO, 2016); however, well-managed grasslands act as a sink and mitigate GHG

71

emissions by sequestering CO2 from the atmosphere and incorporating it into the soils

(Soussana et al., 2010).

C:N Ratio

There was a treatment ˟ year (P <.0001, SE = 6.5462) effect on C:N ratio,

because in the second year the N-fertilized bahiagrass treatments had lower C:N ratio

than in the first year (Figure 3-6). Increasingly rates of N fertilization resulted in greater

N concentrations in Pensacola bahiagrass roots (Blue, 1973; Beaty et al., 1980). Thus,

C:N ratio declined in the second year due to N fertilization. Dubeux et al. (2006)

reported that in intensively N-fertilized systems, bahiagrass litter decomposition rate

was greater compared to low N input systems. In 2015, before the N application, DF9

and Argentine had the greatest C:N ratio (103 and 104, respectively); however they

were not different from the mixtures Ecoturf-Argentine, Q6B-Argentine, and Ecoturf-

DF9. The lowest values were 31.5 and 32.8, for Ecoturf and Q6B monocultures,

respectively; however, they were not different from the mixture Q6B-DF9 (53).

Root and Rhizome δ15N

There was a treatment ˟ year effect (P = 0.0063, SE = 0.328) on root and

rhizome δ15N. Interaction occurred because in 2016 DF9 was less depleted than in

2015 (Figure 3-7; -0.76 and 1.68‰, for 2015 and 2016, respectively). There was no

significant differences among treatments in 2015, however, in 2016 DF9 was less

depleted than all treatments. Argentine δ15N was 1.04‰, and did not differ from DF9 or

Q6B-DF9 (-0.13‰). More depleted δ15N is associated with utilization of atmospheric N2,

whether biologically or industrially fixed. Bahiagrass has demonstrated potential to fix

atmospheric N. When associated with Azotobacter paspali, bahiagrass roots had an

increase of 18% in root mass N (Kass et al., 1971). Mixtures and monocultures of RP

72

did not differ among each other and averaged -1.21 and -1.02‰ in 2015, and 2016,

respectively. In the first year, all values were negative, indicating the presence of

biological N fixation in RP (Dubeux et al., 2017) and possibly in the bahiagrass,

however, intra-plant variation in isotopic concentration may occur by multiple

assimilation events, organ-specific loss of N, and resorption and reallocation of N

(Evans and Evans, 2001). Genotype also affects δ15N isotopic composition (Evans and

Evans, 2001). Dubeux et al. (2017) reported RP δ15N in root and rhizomes across a 2-yr

study ranging from -0.73 to -1.34‰, for Arblick and Florigraze, respectively.

δ13C and C3:C4 Proportion in Roots and Rhizomes

There was a treatment effect (P <.0001, SE = 0.9507) for root and rhizome δ13C

(Figure 3.8). Bahiagrass monocultures were less depleted (-14.61 ± 0.9‰, average),

while RP monocultures were more depleted (-28.21 ± 0.9‰, average). Differences

between δ13C in C3 and C4 plants is well known in the literature and it is associated with

their photosynthetic pathways (Farquhar et al., 1989). Because of internal fractionation,

δ13C varies according to the fractions of the plant. For example, leaf and root δ13C in

ryegrass (Lolium perenne) were reported as -28.5 and -26.9‰, respectively

(Fernandez, 2003). Mixtures did not differ between each other (-18.76‰, average), and

Ecoturf-Argentine (-17.55‰) and Q6B-Argentine (-17.64‰) also did not differ from

bahiagrass monocultures (Figure 3-9). By utilizing the root and rhizome δ13C in plots

growing in monocultures, it was possible to estimate the contribution of bahiagrass and

rhizoma peanut in the belowground biomass in mixed plots. Nevertheless, there was no

significant difference among treatments (P > 0.4301; SE = 0.09994) for the proportion of

bahiagrass or RP in the belowground material of the mixtures (Figure 3-9), and there

was no significant difference (P = 0.1283) for the orthogonal contrast (Argentine

73

mixtures x DF9 mixtures). The proportion of grass belowground biomass in the mixtures

ranged from 58.8 to 78.8% (41.8 and 21.2% of RP), for Q6B-DF9 and Q6B-Argentine,

respectively.

Conclusions

Nitrogen fertilization lead to an increase in belowground biomass and

belowground N and C content in bahiagrass entries. Bahiagrass-RP mixtures had as

much belowground biomass as bahiagrass monocultures. In the second year, root and

rhizome C:N ratios for the mixtures were not different from those of RP monocultures

and N-fertilized bahiagrass monocultures. The proportion of RP in belowground

biomass ranged from 21.2 to 41.8%, and did not differ among treatments. Results

indicated that mixing legumes and grasses is a good strategy to improve the storage of

belowground N in root and rhizome tissues, even when compared with bahiagrass plus

90 kg N ha-1 harvest-1. Long-term implications include the potential re-utilization of this

stored N after root and rhizome decay over time. This might be a significant source of N

in grazing systems, where most N is recycled via cattle excreta and litter turnover.

74

Figure 3-1. A) Rainfall (mm), B) temperature (°C), and C) solar radition (W m-2) in Quincy – FL, during 2015 and 2016.

0

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Figure 3-2. Belowground biomass of bahiagrass-rhizoma peanut mixtures in contrast with their monocultures. Treatment ˟ year effect (P = 0.0053, SE = 1536.21), according to PDIFF procedure adjusted by Tukey (P < 0.05).

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Argentine Ecoturf Eco/Arg Eco/DF9 DF9 Q6B Q6B/Arg Q6B/DF9

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Figure 3-3. Root and rhizome N concentration of bahiagrass-rhizoma peanut mixtures in contrast with their monocultures. Treatment ˟ year effect (P = 0.0223, SE = 1.004), according to PDIFF procedure adjusted by Tukey (P < 0.05).

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Figure 3-4. Root and rhizome N content of bahiagrass-rhizoma peanut mixtures in contrast with their monocultures. Treatment ˟ year effect (P = 0.0245, SE = 25.76), according to PDIFF procedure adjusted by Tukey (P < 0.05).

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Figure 3-5. Root and rhizome C pool of bahiagrass-rhizoma peanut mixtures and monocultures during 2 yr. Year effect (P = 0.0003, SE = 299), according to PDIFF procedure adjusted by Tukey (P < 0.05).

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ten

t (k

g C

ha-1

)

79

Figure 3-6. Root and rhizome C/N ratio of bahiagrass and rhizoma peanut growing in mixtures or monoculture. Treatment ˟ year effect (P <.0001, SE = 6.5462), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0

20

40

60

80

100

120

2015 2016

Ro

ot

and

rh

izo

me

C/N

rat

io

Argentine Ecoturf Eco/Arg Eco/DF9 DF9 Q6B Q6B/Arg Q6B/DF9

80

Figure 3-7. Root and rhizome δ15N of bahiagrass and rhizoma peanut growing in

mixtures or monoculture. Treatment ˟ year effect (P = 0.0063, SE = 0.328), according to PDIFF procedure adjusted by Tukey (P < 0.05).

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

2015 2016R

oot

and r

hiz

om

e δ

15N

, ‰

Arg ET ET/Arg ET/DF9 DF9 Q6B Q6B/Arg Q6B/DF9

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Figure 3-8. Root and rhizome δ13C of bahiagrass and rhizoma peanut growing in mixtures or monoculture. Treatment effect (P <.0001, SE = 0.9507), according to PDIFF procedure adjusted by Tukey (P < 0.05).

-35

-30

-25

-20

-15

-10

-5

0

Arg ET ET/Arg ET/DF9 DF9 Q6B Q6B/Arg Q6B/DF9R

oo

t an

d r

hiz

om

e δ

13 C

, ‰

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Figure 3-9. Contribution of bahiagrass and rhizoma peanut (RP) to belowground biomass of mixed stands (P > 0.05, SE = 0.09994), according to PDIFF procedure adjusted by Tukey (P < 0.05).

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Ecoturf/Argentine

Ecoturf/DF9

Q6B/Argentine

Q6B/DF9

Bahiagrass RP

83

CHAPTER 4 NITROGEN LOSSES IN BAHIAGRASS-RHIZOMA PEANUT MIXTURES AND

MONOCULTURES

Introduction

Efficient N utilization by warm-season grasses improves herbage accumulation

and overall forage quality in intensive ruminant production systems (Stewart et al.,

2007). Excessive N can also act as a source of pollution to the atmosphere and to

groundwater when not well managed. It is estimated that from 20 to 70% of the N lost

from grasslands is the forms of dinitrogen (N2), nitrous oxide (N2O), ammonia (NH3),

and N leaching (Li et al., 2013). In order to reduce these N losses, concepts related to N

management on grasslands are changing with the goal of creating a more sustainable

system while maintaining adequate food production.

Agriculture, forestry, and other land uses (AFOLU) are responsible for 21-24% of

the greenhouse gasses (GHG) emitted annually (IPCC, 2014; FAO, 2016). Excess of N

in a grassland can be lost from the system as nitrous oxide (N2O), whether this source

comes from organic (Lessa et al., 2014) or inorganic (Mosier et al., 1991; Tilsner et al.,

2003; Bremer, 2006) N fertilization. Nitrous oxide is a potent GHG with a warming

potential 298 times greater than carbon dioxide (CO2) and 12 times greater than

methane (CH4; Solomon et al., 2007). Additionally, the manufacture, storage, and

transportation of N contribute to CO2 emissions to the atmosphere (Lal, 2004).

The loss of N to the atmosphere through ammonia (NH3) volatilization (Ferm,

1998; Jantalia et al., 2012) also represents a source of pollution. Ammonia is the most

reactive form of N found in the atmosphere, and it can be oxidized to N2O or react with

acidic gasses and form hygroscopic salt particles containing (NH4)2SO4 and NH4NO3

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(Ferm, 1998), forming acid rain. This loss can be influenced by N fertilizer type and

farming method (Ferm, 1998; Jantalia et al., 2012; Monteagudo et al., 2012).

Nitrogen can leach as nitrate and reach the groundwater, potentially causing

health problems in humans and animals when found in high concentrations in drinking

water. Currently, the maximum contaminant level (MCL) of nitrates present in drinking

water allowed by the Environmental Protection Agency is 10 mg N L-1 (USEPA, 2016),

in order to avoid the blue baby syndrome that may result in neonates death. Farming

methods and cropping management affect nitrate leaching and concentration (Eriksen

et al., 2015; Hansen and Eriksen, 2016).

In Florida, bahiagrass (Paspalum notatum Flügge.) pastures cover more than 1

million hectares, making it the most common forage species planted in the state and

serving as the basis for the calf-calf operation held on it (Chambliss and Sollenberger,

1991). Bahiagrass is commonly used for grazing animals or hay production, and in

order to have a greater herbage accumulation and nutritive value, it requires N

fertilization (Hanna and Sollenberger, 2007; Stewart et al., 2007).

Forage legumes can naturally fix atmospheric N2 through mutualistic association

with rhizobia bacteria (Russelle, 2008) and when growing in association with grasses

this N can be transferred to the non-fixing species (Heichel and Henjum, 1991; Haby et

al., 2006; Frankow-Lindberg and Dahlin, 2013) and the fixation from forage legumes

can be also stimulated (Nyfeler et al., 2011). Rhizoma peanut (RP: Arachis glabrata

Benth.) is a rhizomatous warm-season perennial forage legume (Ball et al., 1996b) well

adapted to Florida climate with good productivity and persistence across a variety of

management practices (Ortega-S. et al., 1992b).

85

Biologically fixed N2 from legumes-rhizobia symbiosis, however, is not free from

losses. It can also be lost to the environment by different pathways. Combination of

grasses and legumes might enhance N utilization and diminish N losses. Adding RP

into bahiagrass pastures appears to be an option to reduce industrial N fertilizer use

and create a more sustainable long-term production system, decreasing environmental

impact, and increasing farmer’s profitability. This study aimed to evaluate and contrast

N losses through N2O emissions, NH3 volatilization, and NO3- leaching on bahiagrass-

RP mixtures in contrast with monocultures of RP and N-fertilized bahiagrass in North

Florida.

Materials and Methods

Experimental Site

The study was conducted at the North Florida Research and Education Center,

Quincy – FL (30°32' N 84°36'W) during 2015 and 2016. Soils at the experimental site

are classified as Orangeburg loamy sand (fine-loamy, kaolinitic, thermic Typic

Kandiudults). Soil analysis in 2013 reported pH 6.04 and Mehlich-1 extractable P, K,

Mg, Ca, S, B, Zn, Mn, Fe, Cu of 60, 51, 45, 365, 7.6, 0.4, 3.6, 45, 93, and 0.8 mg kg-1,

respectively. Total rainfall for 2015 and 2016 was 1379 and 2304 mm, respectively.

Average, minimum, and maximum daily temperature for 2015 and 2016 were 20.1, 7.1,

30.8; and 19.7, 7.4, and 30.9°C, respectively. Daily rainfall, temperature, and relative

humidity (RH) during the experimental days are displayed in Figure 4-1.

Treatments and Experimental Design

There were eight treatments with three replications (24 experimental units),

arranged in a randomized complete block design. Treatments consisted of two

bahiagrass entries (Argentine and DF9), two RP entries (Ecoturf and Q6B), and the

86

combinations of each entry of bahiagrass with each entry of RP, i.e., Argentine-Ecoturf,

Argentine-Q6B, DF9-Ecoturf, and DF9-Q6B. Grass monocultures were fertilized with 90

kg N ha-1 harvest-1 as recommended by Mylavarapu et al. (2013) for standardized

fertilization in bahiagrass hay fields. Both DF9 and Q6B are experimental lines,

therefore have not been officially released by the UF-IFAS.

Plot Establishment and Management

Plots were established in 2011 in a fallow field previous planted to bahiagrass.

Glyphosate (N-[phosphonomethyl] glycine) plus 2.2 kg N ha-1 as (NH4)2SO4 (ammonium

sulfate) was applied at 12 L ha-1 in order to eradicate all vegetation. The land was tilled

to remove roots and rhizomes from bahiagrass, which can penetrate deeply into the

soil. In order to complete the eradication, two additional applications were performed.

Plots were 3-m wide by 3-m long with 1.2-m alleys between. The alleys were covered

with a black plastic mulch to prevent alley weeds from spreading into the experimental

units. Argentine and DF9 were broadcast seeded in July 2011; both grass monoculture

and grass-RP plots were seeded with the grass component. The grasses did not

establish well because 2011 was a droughty year. To fill gaps in the stand, 90 rooted

plants were inserted in each plot in late summer 2011. Rhizoma peanut monoculture

plots were planted using 7.5-cm potted plants (plugs) at a density of 1 plant per 0.09 m2,

in the same period as the bahiagrass. The goal was to allow the bahiagrass to establish

before plugging the RP into the mixed treatments, in early April 2012. The plots were

mowed once in 2012 and twice in 2013 and 2014, and the forage mass was left in

place. Plots were weeded by hand twice per year.

Once evaluations started in 2015, weeds were manually removed every 14 d as

needed. The plots were harvested staged three times in 2015 (July, August,

87

September) and four times in 2016 (April, May, July, and August). After each forage

harvest, plots were staged at 7.5-cm stubble height using a push mower (Husqvarna

HU 700F). All plots were fertilized with 224 kg ha-1 of 0-5-20 (5 kg P ha-1, 37 kg K ha-1)

and 224 kg ha-1 of Kmag (37 kg K ha-1, 20 kg Mg ha-1, and 45 kg S ha-1) following IFAS

recommendations for hayfield maintenance (Mylavarapu et al., 2013), after plots were

staged and then after each harvest, except for the last harvest of the year. Grass

monocultures were fertilized with 90 kg N ha-1 after plots were staged and then after

each harvest, except for the last harvest of the year, summing up a total of 270 kg N ha-

1 in 2015 and 360 kg N ha-1 in 2016. Two different types of N fertilizer were used. On

11 July and 10 Aug. 2015, a commercial formula 34-0-0 (340 g kg) was applied; in 20

Sept. 2015, 11 Apr., 21 May, 5 July, and 13 Aug. 2016 a commercial formula 34-0-0

(248 g Urea-N kg-1, 92 g ammoniacal-N kg-1, and 100 g S kg-1) was applied (Table 4-1).

Response Variables

The response measured include NH3 volatilization per sampling day, NH3

cumulative volatilization, NO3 concentration in leachate, and N2O flux emission and

concentration. All the plots had static chambers for capturing N2O emission and NH3

volatilization, and lysimeters to estimate NO3- concentration. Samples were taken every

14 d. On days that the plots were fertilized, samples were taken prior to fertilization.

Sampling days and N fertilization according to date and day of study are detailed in

Table 4-1.

Ammonia Volatilization

A semi-open static chamber based on the methodology described by Araujo et

al. (2009) and then by Jantalia et al. (2012) was used to measure the ammonia

volatilization from the soils. The chamber consisted of a polyethylene terephthalate

88

bottle (PET, 2-L bottle) divided into two components, the base and the cap. The bottom

part was removed and painted outside, with a silver reflective aerosol paint, and used

upside down to serve as a cap and protect from rain and thermal radiation. The

funneled part of the bottle was also painted with a metallic silver paint. A small, plastic,

triangle-shaped support was attached by duct tape in the bottle mouth. The support and

the cap were connected by Velcro. Two wire weed cloth stakes were affixed with duct

tape to opposing sides of the bottle and the base of the bottle placed snug against the

soil surface.

A fishing line (nylon, 0.3mm, 4.5-kg weight resistance) equipped with a metal

hook was used to hang an 88-ml plastic cup from the bottle mouth to the center of the

bottle base. A 60-ml plastic bottle containing a sulfuric acid solution (30ml; H2SO4, 1 mol

dm-3 + glicerine, 0.02 v v-1) was placed inside the cup. A polyester wick was kept

saturated by hanging one end inside the 60-mL bottle, and the other end hung from the

bottle mouth, via aluminum wire. Ammonia trapped by the acid-saturated wick,

converted to NH4-N. When sampled, the wick was dropped into the bottle and a new

wick/bottle combination installed. The bottles were replaced every 14 days and taken to

the laboratory, where they were filtered and washed three times with a KCl solution.

Then, samples were frozen until analyzed with a continuous flow diffusion and

conductivity cell N analyzer (Timberland, Boulder, CO, USA).

Nitrate Concentration in Leachate

Soil water samplers (lysimeters; 1900L Near Surface Sampler, Soilmoisture

Equipment Corp., Goleta, CA) were installed in each plot. Lysimeters consisted of a

PVC pipe with a porous ceramic cup attached with epoxy at the bottom shaft, and

Santropene (SantropeneTM) stopper placed at the top shaft, with a hose coming from

89

the bottom cup to the top stopper, and passing through a hole (at the stopper) until

reach the soil surface. The porous cup lysimeters were installed using a hydraulic soil

coring machine (Giddings Machine Co., Windsor, CO, USA). Silica flour was mixed with

water (to provide good hydraulic contact between cup and soil) and poured into the

holes made by the Giddings Rig. Lysimeters were inserted in holes, gently tamped to

provide good contact, then soil from hole placed back into hole above the lysimeter. Soil

was tamped to provide good contact and prevent cave-ins.

Sampling pressure of -70 KPa was applied to each lysimeter 2 d prior to sample

collection. Samples were collected with an Erlenmeyer Extractor Kit (1000 ml,

Polypropene, for use with 1,900 or 1,920 samplers, Soilmoisture Equipment Corp.,

Goleta, CA), placed in 60-ml cantillation tubes and carried out to the laboratory, filtered,

and then frozen until the day of analysis. Nitrate concentration in leachate (mg NO3- L-1)

was determined with a continuous flow diffusion and conductivity cell N analyzer

(Timberland, Boulder, CO, USA).

Nitrous Oxide Emissions

Nitrous oxide was estimated by utilizing the static chamber method described by

Hutchinson and Mosier (1981; Mosier et al., 1986, 1991; Bremer, 2006). The chambers

were made of polymerizing vinyl chloride (PVC) and divided into base and cover. The

base was open and fixed in the field for the whole experimental time, and measured 10-

cm height by 20-cm diameter. Out of the 10-cm height, 5 cm were buried into the soil.

The cover was 8-cm tall by 20-cm diameter and covered by an aluminum tape to reflect

the radiation. In addition, the cover had a vent (0.25-cm diameter) on the side with a

copper hose (25.5-cm long) on the edge and going to the center to maintain the

ventilation inside the chamber. The silver tape and vent had the purpose of equilibrating

90

the temperature and pressure inside the chamber with the ambient temperature. A

rubber stopper (20-mm butyl) was installed in the top of the cover and served as the

sampling point.

Samples were taken every 14 d from 9:30 to 10:15 am using a 60-ml syringe

(Luer-LokTM). The first sample was taken outside the chamber after placing the cover

(time 0); subsequent samples were taken through the rubber stopper, 15, 30, and 45

min after time 0. Syringes were pulled in and out three times to homogenize the sample

before taking it. The gas collected was inserted in a 20-mL glass vial where it stayed

until the analysis. Samples were analyzed for N2O in a gas chromatography (Agilent

7820A, Agilent Technologies, Inc.). Soil moisture and temperature were taken

individually per plot right after the sampling using a SDI-12 Xplorer probe (StevensR,

Water Monitoring Systems, Inc.).

Statistical Analysis

Data were analyzed using PROC MIXED from SAS (SAS for Windows V 9.4,

SAS Institute, 2009, Cary, NC, USA). Fixed effects included treatment, evaluation, and

treatment × evaluation interaction. Blocks and the interaction treatment × blocks were

considered as random effects. The LSMEANS were compared using the PDIFF

procedure adjusted for Tukey’s test. Differences were declared significant at P ≤ 0.05.

Results and Discussion

Ammonia Volatilization

There was a treatment ˟ evaluation effect (P < 0.0001, SE = 0.8383) for NH3-N

volatilization per sampling day (Figure 4.2). On Day 85, both grass monoculture

treatments (with 90 kg N ha-1 harvest-1) were significantly different from other

treatments. In addition, DF9 had a greater NH3-N loss than Argentine (15.75 and 8.24

91

kg N ha-1, for DF and Argentine, respectively). Rhizoma peanut monoculture and

mixtures did not differ among sampling days and averaged a NH3-N loss of 0.13 kg N

ha-1 day-1. The combination of the mixed urea-N plus ammonium sulfate, high

temperature, rainfall, and relative air humidity, contributed to a rapid increase in NH3

volatilization on Day 85.

Cumulative NH3-N loss (kg ha-1) was also greater for DF9 (Figure 4-3). After 278

d of study, DF9 NH3-N cumulative loss was 29.2 kg N ha-1 and was different from all the

mixtures and the RP monocultures (P < 0.0001, SE = 3.6). On the other hand,

Argentine had a NH3-N cumulative loss of 20 kg N ha-1 and was intermediate among

DF9 and the other treatments. Rhizoma peanut monoculture and mixtures did not differ

among each other, and they averaged a NH3-N cumulative loss of 2.6 kg ha-1.

Urea losses from NH3 volatilization have been reported in the literature (Vaio et

al., 2008; Araújo et al., 2009; Jantalia et al., 2012). Jantalia et al. (2012) evaluated the

volatilization of different industrial N fertilizers utilizing open chambers (similar to the

ones used in this study). Treatments included granular urea (46%N), liquid urea

ammonium nitrate (UAN 32%N), and two controlled release N fertilizers, SuperU (46%)

and ESN (44%). The sources of N were applied 10 cm apart of recently emerged corn

on the soil surface at a rate of 200 kg N ha-1. The study evaluated the ammonia

volatilization for a period of 27 d in 2010 and 68 in 2011. At the end of the study the

authors reported a cumulative NH3-N loss of ≈ 6 (27 days) and ≈ 11 kg N ha-1 (68 days).

Nitrogen loss when applying granular urea was 2.3%. In this study, N fertilizer was

applied seven times during the 440-d period, summing to 630 kg N ha-1. We estimate a

NH3-N volatilization cumulative loss for Argentine and DF9 equal to 3.2 and 4.6%,

92

respectively. Jantalia et al. (2012) used the 15N tracer technique to calibrate the

chambers, which was not performed in this study.

One of the main factors driving the sudden increase on cumulative NH3-N

volatilization was the replacement of urea (34% urea-N) with a combined urea plus

ammonium sulfate (24.82% urea-N, and 9.18% ammoniacal-N), due to these

compounds have a different critical relative humidity (CRH). Critical relative humidity

determines whether the fertilizers absorb moisture or not. When the relative humidity

(RH) is greater than the CRH, the fertilizer will absorb moisture; when the RH is below

the CRH, the fertilizer will not absorb moisture (Clayton, 1998). The values of CRH vary

according to the temperature and fertilizer material. Urea CRH is reported as 72.5%, in

favorable conditions, while the combined urea plus ammonium sulfate CRH is reported

as 56.4% (Clayton, 1998; EFMA, 2006). Average RH during the experimental period

was 83%, which probably affected most the urea plus ammonium sulfate, compared to

sole urea, used at the beginning of the study. Vaio et al. (2008) evaluated the ammonia

volatilization of three urea-based fertilizers (Urea, UAN, and Nitamin®) on tall fescue

(Festuca arundinacea Schreb.) pastures. The authors concluded that urea lost more

NH3 than the other two N fertilizers. In addition, the authors reported that conditions

favoring NH3 volatilization were high temperatures with RH > CRH for urea, in

conjunction with low water contents, which was a limiting factor for urea diffusion into

the soil.

Nitrate Concentration in Leachate

There was no significant difference (P > 0.05) for nitrate concentration in

leachate (mg NO3--N L-1). Treatments averaged 0.1 mg NO3

--N L-1 (Table 4-1). This

concentration is 100 times lower than the value stipulated by the Environmental

93

Protection Agency (EPA) for drinking water, in order to avoid methemoglobinemia (blue

baby syndrome) in neonates (USEPA, 2016). Concentration of NO3- in leachate was not

affected by N fertilization or stand composition. Bahiagrass belowground biomass may

have contributed to avoid N losses due to NO3- leaching. Argentine bahiagrass root and

rhizome mass in low input systems with limited N fertilization ranged from 2.8 to 3.1 Mg

ha-1 (Vendramini et al., 2013). Developed root systems play an important role in

reducing N total amount and concentration of NO3- leached (Bowman et al., 1998).

Nitrous oxide concentration

There was no significant difference for N2O fluxes (P <0.05), however, there was

an evaluation effect (P < 0.0001, SE = 0.019) for N2O concentration (Fig. 4-4). By Day

42 of the study, N2O emission (in mg L-1) was greater than any other evaluation. The

effect probably occurred due to greater rainfall events a few days before the sampling

day, which resulted in low soil O2. Nitrification and denitrification are the main processes

occurring in soils responsible for N2O emission. Nitrification is the microbial oxidation of

ammonia to less reduced forms, mainly NO2- and NO3

- (Robertson and Groffman,

2015). Ammonia oxidizers are able to produce NO via NO2- reduction, which results in

emission of N2O to the atmosphere (Robertson and Groffman, 2015). Denitrification is

the continuous process where NO3- will become N2, sequentially being reduced to NO2

-,

NO, N2O, and N2 (Li et al., 2013). At any step of denitrification, its products can be

exchanged with the environment, making the process an important source of NO2- in the

soil solution and important sources NO and N2O in the atmosphere (Robertson and

Groffman, 2015). Regardless no difference between treatments have been found, timing

and sampling frequency may have contributed to not detecting an effect. Bouwman et

al. (2002), reported that longer measurement periods yield more of the fertilization effect

94

on N2O emission, and intensive measurements (≥1 per day) yield lower emissions than

less intensive measurements of 2 to 3 measurements per week. Greater emissions

could occur right after fertilization following rainfall events (Bouwman et al., 2002). The

sampling frequency may have contributed to the inability to detect differences.

Conclusions

Fertilized monocultures of bahiagrass had greater N losses than RP and

bahiagrass-RP mixtures due to NH3-N volatilization. Replacement of N fertilizer source,

rainfall, and temperature, most likely increased NH3 volatilization. Neither bahiagrass,

rhizoma peanut, or mixed stands had NO3- concentration in leachate greater than 10 mg

N L-1, a safely limit proposed by the Environmental Protection Agency. Nitrous oxide

concentrations were greater when sampling dates were closer to rain events. In this

work, sampling timing may have contributed to failure in detecting differences for N2O

emission and NO3- leaching, as NH3 static chamber were always measuring the

volatilization, it was not affected by frequency. Further work is needed to find out the

influence of sampling frequency and rainfall events on N2O emission and NO3- leaching

of monocultures of RP and N-fertilized bahiagrass in comparison with their mixtures.

Yet, planting mixed stands of bahiagrass-RP contributes to attenuate indirect

greenhouse gas emission through manufacture and handling of N fertilizer.

95

Table 4-1. Nitrogen fertilization type and date, according to date and day of study. Date Day of Study Fertilization N Fertilizer

7/11/2015 0* Yes Urea-N

7/25/2015 14 No

8/8/2015 28 Yes Urea-N

8/22/2015 42 No

9/5/2015 56 No

9/20/2015 71 Yes Urea plus ammoniacal-N

10/4/2015 85 No

10/18/2015 109 No

10/31/2015 112† No

4/11/2016 275*‡ Yes Urea plus ammoniacal-N

4/23/2016 287 No

5/7/2016 301 No

5/21/2016 315 Yes Urea plus ammoniacal-N

6/4/2016 329 No

6/19/2016 344 No

7/5/2016 360 Yes Urea plus ammoniacal-N

7/19/2016 374 No

7/30/2016 385 No

8/13/2016 399 Yes Urea plus ammoniacal-N

8/26/2016 412 No

9/9/2016 426 No

9/23/2016 440 No

* No ammonia traps were sampled. Instead, they were placed after fertilization. † Last harvest in 2015. There was a 162 d break before resuming the evaluations in spring 2016 on day 275. ‡ Static chambers for N2O were not sampled. Instead, they were placed in the plots.

96

Table 4-2. Nitrate concentration in leachate.

Treatment mg NO3--N L-1

Argentine 0.02

Ecoturf 0.48

Ecoturf-Argentine 0.03

Ecoturf-DF9 0.04

DF9 0.03

Q6B 0.09

Q6B-Argentine 0.08

Q6B-DF9 0.05

P value 0.40

SE 0.14

97

Figure 4-1. Daily rainfall, relative humidity, and temperature at the NFREC, Quincy - FL, during the experimental period. † Last harvest in 2015. There was a 162 d break before resuming the evaluations in spring 2016 on day 275.

0

20

40

60

80

100

120

0

20

40

60

80

100

120

140

160

0 9

18

27

36

45

54

63

72

81

90

99

10

8

27

9

28

8

29

7

30

6

31

5

32

4

33

3

34

2

35

1

36

0

36

9

37

8

38

7

39

6

40

5

41

4

42

3

43

2

Rel

ativ

e H

um

idit

y (%

)Te

mp

erat

ure

(°C

)

Rai

nfa

ll (m

m)

Days of Study

Rainfall Temperature Relative Humidity

†

98

Figure 4-2. NH3-N (kg N ha-1) loss per day from N-fertilized bahiagrass in contrast with bahiagrass-rhizoma peanut (RP) mixtures and monocultures of RP. * Indicate the first sampling after N fertilization. † Last harvest in 2015. There was a 162 d break before resuming the evaluations in spring 2016 on day 275. ‡ Significant difference among treatments, according to PDIFF procedure adjusted by Tukey (P < 0.05).

99

Figure 4-3. Cumulative NH3-N loss from N fertilized bahiagrass (90 kg N ha-1 harvest-1) in comparison with rhizoma peanut (RP) monoculture and mixtures of bahiagrass and RP.* Indicate the first sampling after N fertilization. † Last harvest in 2015. There was a 162 d break before resuming the evaluations in spring 2016 on day 275. Different letter indicate significant difference among treatments (P<.0001, SE=1756) at the end of the study, according to PDIFF procedure adjusted by Tukey (P < 0.05).

100

Figure 4-4. Soil N2O emission on bahiagrass and rhizoma peanut monocultures or in their mixtures. Evaluation effect (P < 0.0001, SE = 0.019). Different letters mean significant difference among evaluations, according to PDIFF procedure adjusted by Tukey (P < 0.05).

101

CHAPTER 5 FINAL REMARKS

The adoption of legumes into warm-season grasses is still not a common

practice in Florida. The main obstacles for researchers and producers is to find a

competitive legume and adequate management practices for mixed pastures. In our

study, rhizoma peanut has proven to be a competitive legume. After 5 yr, RP

aboveground biomass contributes from 33 to 57% and RP roots and rhizomes represent

21 to 42% of the total belowground biomass. Contribution of legumes to total forage

production, however, needs to meet producers’ expectations. We have seen mixtures

producing as much biomass as fertilized bahiagrass in many harvests along the study;

however, that was not always true. When Argentine was fertilized with N, it had a

greater herbage accumulation then the other treatments during the early and middle

season of 2016. Nonetheless, further investigations on bahiagrass-rhizoma peanut

mixtures utilizing some N fertilization (e.g., 50% of what is applied in the grass

monocultures) are needed to determine whether the combination of bahiagrass +

rhizoma peanut + N, would outyield Argentine bahiagrass. However, entries of

bahiagrass behaved differently. Argentine had greater yields than the mixtures at some

times, while DF9, even fertilized aggressively, was never greater than the mixture of

Q6B-DF9. This leads us to believe that the most common entries of bahiagrass and RP

should be tested in association under different management practices. The effect of N

fertilization on herbage accumulation has been reported before and it is clear, however

we did not take into account the price of fertilizer or RP establishment cost. Therefore,

even if the establishment cost of RP is greater than applying N in the first 2 yr, the long-

term response would compensate for the initial investment.

102

Another question we tried to answer in this thesis was if the association of RP

and bahiagrass would stimulate the biological N2 fixation in the RP. We did find mixed

stands with a greater proportion of %Ndfa than Q6B, however they were not different

from Ecoturf. Thus, the associations behaved differently and answers to this question

were specific to different bahiagrass-rhizoma peanut mixtures.

Belowground responses were mainly stimulated by N fertilization. Argentine and

DF9 biomass increased greatly from 2015 to 2016, however, they were not different

from the mixtures. Thus, mixtures, without industrial N fertilizer, proved to accumulate

as much below ground biomass as N-fertilized bahiagrass. This effect was also

reflected in the C and N content of the belowground biomass. In addition, C:N ratios of

the mixtures were comparable to N-fertilized bahiagrass and RP monocultures. We can

infer here that mixtures are capable of produce as much HA and belowground biomass,

as N-fertilized bahiagrass. Furthermore, N losses caused by ammonia (NH3)

volatilization were greater for N-fertilized bahiagrass.

Thus, besides the yield parameters, mixtures can be an option to increase

farmers’ profitability. Although, we assume that costs of implementing RP and N

fertilization overlap each other, environmental benefits should be considered. Even

though production cost and outputs are the same, we may mitigate environmental

damage caused by manufacturing, transportation, storage, and utilization of industrial N

fertilizer. In this study, we did not observe differences among treatments of nitrous oxide

(N2O) concentration or nitrate (NO3-) concentration in leachate, as we did for NH3

volatilization. Meanwhile, timing of sampling may have underestimated N losses via N2O

emission or leaching. Further studies evaluating N2O losses within a shorter time after

103

fertilization are needed. In the same way, NO3 losses can be greater after rainfall

events; sampling lysimeters after these events could approach better the N leached

from the system. An important finding in this study was the changing in δ15N signal from

negative to positive in bahiagrass monocultures, which occurred before, and after N

fertilization. That may indicate the potential of bahiagrass to fix atmospheric N2.

However, further studies are needed to understand the reason for this change in the

isotopic signal. In conclusion, the adoption of RP in bahiagrass may be an option to

produce as much forage as N-fertilized bahiagrass, reducing industrial N inputs,

decreasing N losses, and attenuating environmental impact.

104

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BIOGRAPHICAL SKETCH

Erick R. S. Santos was born in Recife, PE – Brazil. In 2009, he started his BS in

Animal Sciences at the Federal Rural University of Pernambuco. Since 2010, he has

worked with Forage Management as an undergraduate researcher. Before completing

his BS in Brazil, he was come twice to the University of Florida. The first time, as an

exchange student, sponsored by the CAPES/FIPSE scholarship, and the second time to

develop an internship at the UF/IFAS North Florida Research and Education Center. He

obtained his BS degree in 2014, and started a MS at the UF Agronomy Department in

2015.