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2008

Evaluation of Nutrient (Protein) – Organism(Fish) Relationship Using a Saturation KineticModelZainab Sa'ad Beiruti

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Recommended CitationBeiruti, Zainab Sa'ad, "Evaluation of Nutrient (Protein) – Organism (Fish) Relationship Using a Saturation Kinetic Model" (2008).Theses. 596.https://scholarworks.uaeu.ac.ae/all_theses/596

United Arab Emirates University Deanship of Graduate Studies

M. Sc. Program in Environmental Science

EVALUATION OF

NUTREINT (pROTEIN) - ORGANISM (FISH)

RELATIONSHIP USING A SATURATION

KINETIC MODEL.

By

Zainab Sa'ad Beiruti Bachelor in Science (Biology)

College of Science, Baghdad University (2003-2004)

A Thesis Submitted to

United Arab Emirates University

In partial fulfillment of the requirements

For the Degree ofM.Sc. in Environmental Sciences

2008

United Arab Emirates University Deanship of Graduate Studies

M.Sc. Program in Environmental Sciences

EVALUATION OF NUTREINT (pROTEIN) -ORGANISM (FISH) RELATIONSHIP USING A

SATURA TION KINETIC MODEL.

Thesis Submitted to

United Arab Emirates University In partial fulfillment of the requirements

For the Degree ofM.Sc. in Environmental Sciences

By Zainab Salad Beiruti

200670310 Bachelor in Science (Biology)

College of Science, Baghdad University (2003-2004)

Supervisor

Dr. Ibrahim EI Shishtawy Hassan Belal Chairman of Aridland Agriculture Department

College of Food and Agriculture United Arab Emirates University

2008

TO MY BELOVED PA'RENTS}

TO THE SOUL OF MY AUNT (NIDAL) WHO STILL EMBRACES ME AND GIVES ME THE STRENGTH TO CONTINUE IN MY LIFE.

And to all the members of my family whom, I lost during the preparation of this

work; Uncle Dr. Usama, My dear grandfather and my missing uncle Dr. Oday, I dedicate this work.

KNOWLEDIIE

Acknowledgment

In the name of Allah \ hom with His grace I was able to complete this work.

I acknowledge with gratitude the upport and the guidance offered to me by my supervisor

Dr. Ibrahim Belal (Head of the Department of Arid land Agriculture

College of Food and Agriculture, UAEU) who helped me to pass the difficult times with a lot

of patience and tolerance.

I will ahvay be grateful to Dr. Tarek Youssef,(Direclor of the Environmental Science

Program, College of Science, UAEU) he is him who built the confidence in my self, the pride

of being a biologist and ga e me all the assistance as a boss and a director of the

environmental science program.

I appreciate the continuous motivation of Professor Waleed Hamza (Head of Biology

Department, College of Science, UAEU) who helped me to keep my momentum and taught

me how to be brave.

Much gratitude to Mr. Mamdouh Kawanna (Fish Lab Specialist), he made things easy for me

with his continuous help in my practical part of the work.

Many thanks to Professor L. P. Mercer (University of South Florida, Polytechnic) for

teaching me the statistical part, to Mr. Adel Al-awad (Lab Specialist) for helping me in the

chemical analysis, to the Arid land Agriculture Department and the biology department in

UAEU for their generous hospitality, to all the faculties and the science I learn from them, to

miss Huda, Latifa ,Wafa and Jumaa for their helps and guidance, to Dr. Noshad Mohammed

and all the fish lab staff you were marvelous, to Mr.Abdulkarim Sadiq and Mr. Mohammed

AI- Kayali and all the bus drivers whom I burden them too much.

To my parents, it is more than words

To my big family, to my brothers, Muammer, Ahmed and Zaid, to my sisters Subh, Arnina

and Shaimaa, to my friends Asil, Rhadwa, Samarra, Abeer, Anfal, Marwa,Suzan,Sameera,

Houssam and Haider, to all my colleagues and friends in the hostel, I apologize for the hard

moments I had given to you while preparing this work.

And last and not least, Dr. Hazem Kataya God blesses his soul I carry for him a lot of respect

and admiration.

I

The Thesis of Zainab aad Bei rut i for the Degree of Master of Science in n ironmental i appro ed.

qq qq C q 767k qC_ . . � ................... .

Examining Committee Member Dr. Ibrah i m Bela)

. . . . . . . . , . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

E amining Committee Member, Dr. Khad ija Zainal

.................................................. :.��� ......... ... .

Examining Committee Member, Dr. Waleed Hamza

H I � • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • , • • • • • • • • • • • • • • • • • • • • • • • • • • • • • 0 • • • • • • • • • • • • • , • • ,

Assistant Chief Academic Officer for Graduate Studies, Prof. Ben Bennani

United Arab Emirates University 2008/2009

STRA

Abstract

The primar objecti e of thi s thesis was to demonstrate that the net

nutrient (protein) deposition and weight gain as a function of nutrient

(protein) intake fits the aturation Kinetic Model and utilize the model

parameters to describe and predict protein intake-deposition relationship.

Groups of ile tilapia, Oreochromis niloticus, fry (0.0 1 g) and small

fingerlings (0. 1 5 g) were each separately fed twelve semi purified diets in

triplicates to the fingerling and duplicate to the fry trial . Each test diet

contains a percentage of protein. Protein levels were (0%, 5%, 1 0%, 1 5%,

20%, 25%, 30% 3 5% 40%, 45%, 50% and 54%). Each group of fish was

randomly assigned a test diet. Fingerlings were fed at a rate of 1 0% their

body weight per day seven days a week for 8 weeks while the fry were fed at

a rate of 25% of their body weight per day for 4 weeks. The mathematical

model (the four parameter saturation kinetics) was used to analyze the

relationships between dietary crude protein intake and each of growth rate

and protein depositions.

It was found that tilapia protein-response (deposition) and weight

gain as a result of feeding the test diets fit the saturation kinetic model . 0.

niloticus weight gain and net nutrient (crude protein) deposition were

described as a function of the protein intake graphically and numerical ly.

Maximum efficiency and protein requirements were calculated from the

model for the fries and the smal l fingerlings. Dietary protein requirements

for fry and fingerlings were calculated and compared to other estimation

using different models techniques.

II

List of Contents

Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ' " . . . . . . . . . . . . . . . . . . . . . . I

Ab tract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II

Li t of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III

Li t of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI

Introduction . . . . . . . . . . . . . . . . . . . " . . . . . . . . . . . . . . . . . . . . . . " . . . . . . . . . . . . . . . . . . 1

Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

1 . Review of the evaluation methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1 . 1 . Digestibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

1 .2 . Metabolizability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1 .3 . Energy Budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.4. Net Nutrients Deposition or growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

1 . 5 . The Saturation Kinetic ModeL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 0

2 . The Experimental Organism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1

2 . 1 Tilapia Oreochromis niloticus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1

2 .2 . Tilapia utrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2 .2 .1. Protein Requirement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2 .2 . 1 .2 . Protein Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2 .2 .2 . Lipid Requirement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2 .2 .3 Essential Fatty Acid Requirement . . . . . . . . . . . . . . . . . . . , . . . . . . . . 33

2.2.4 Carbohydrate Utilization . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . 34

2.2.5 Vitamins Requirement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

2.2.6 Mineral Requirement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Material and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

1 . Culture Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

2. Experimental Diet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3 . Feeding Trial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

4. Chemical Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

4. 1 . Crude Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44

4.2. Crude Fat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

III

4.3. Total h . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

5 . Mathematical and statistical analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

ppendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

IV

List of Tables

Table (1): Protein requirement of ile tilapia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Table (2); Essential amino acid requirements of ile tilapia as % of dietary protein and of total diet. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Table (3): Vitamin Requirement of ile Tilapia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Table (4) : Mineral Requirement of Nile Tilapia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Table (5) : Experimental Diets Composition and their Proximate Analyses as a percentage of the dry

weight. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Table (6): Mortality rate of Oriochromis niloticus in both trials fingerlings and fries experiments as

a result of feeding the different semi -purified diets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Table (7) : Moisture, Protein and fat as percentage of fingerlings' body

composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , ..... 54

Table (8) : The calculated parameters by SYST AT for the relationship between daily protein intake

and fingerling daily weight gain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Table (9) : The calculated parameters by SYSTAT for the relationship between daily protein intake

and fries daily weight gain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Table ( 1 0) : The calculated parameters by SYSTAT for the relationship between daily protein intake

and daily fingerlings protein deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Table ( 1 1 ): The calculated parameters by SYSTAT for the relationship between daily protein intake

and fries daily protein deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Table ( 1 2): The calculated parameters by SYST AT for the relationship between daily protein

intake and daily fat deposition. (fingerlings) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

v

List of Figures:

Figure (1): Utilization of a nutrient in the production of a physiological respons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure (2): The s-curve of the saturation kLnetic model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 8

Figure (3): iew of the semi closed. recirculating indoor systelTI . . . .. . .. . . . . . ....... .. . .. . . . . . . . . . .. .... .. . . . . .. . . . .. . . . . . . ... .. . . . ... . . . ... .. . 41

Figure(4): A iew of the semi closed, recirculating indoor system showing the Aquafme U V disinfection . . . . . . . . . . . . . . . . . . '" .. . . .. .... . . . .. . . . . ..... '" ........... ... ... . . .. .. . '" ... ...... . .. 42

Figure (5) : Fish weighting method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

Figure (6) : Fingerlings growth (response) as a result of feeding (intake) the experimental diet. X axis represents daily protein intake and Y axis represents daily weight gain. The four parameters of the saturation kinetic models are

ind icated . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . 63

Figure (7) : Fries growth (response) as a result of feeding (intake) the deferent semi-purified experimental diets. X axis represents daily protein intake and Y axis represents daily weight gain. The four parameters of the saturation kinetic models are indicated . . . . . ... . . . . . . . . . . '" . . . .... .... . '" .. . ... . ...... . . . . .. .. . . .... ... ...... .. . . " . .... . .. ... . 64

Figure (8) : Dietary protein deposition of tilapia fingerlings bodies (response) as a result of feeding (intake) the experimental diet. X axis represents daily protein intake and Y axis represents daily protein deposition. The four parameters of the saturation kinetic models are indicated. in the graph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Figure (9): Dietary protein deposition of til apia fries bodies (response) as a result of feeding (intake) the

experimental diet. X axis represents daily protein intake and Y axis represents daily protein

deposition. The values of the four parameters of the saturation kinetic models are indicated. in the graph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Figure (10): Protein efficiency curve for the growth response of Nile tilapia fingerlings as a result of

feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the

efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Figure (11): Protein efficiency curve for the growth response of Nile tilapia fries as a result of feeding

(intake) experimental diets. X axis represents daily protein intake and Y axis represents the

efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Figure ( 1 2) : Protein efficiency curve for the protein deposition of Nile tilapia fingerlings as a result of

feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the

efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

VI

Figure (13): protein efficiency curve for the protein deposition of ile tilapia fries as a result of feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the efficiency . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . .. ..... . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

VII

IRDIIGTIO

INTRODUCTION

Fish nutrition science started 70 years ago; many researchers since this

time have been trying to use parameters which are used in worm blooded animals

such as poultry, sheep, cows, etc. These parameters were digestibility,

metabolizablity energy budget and growth (net nutrient deposition) (Belal,

2004). Though fish live in a different environment in addition to being cold­

blooded animals some of these techniques (digestibility, metabolizablity, and

energy budget) could not be done without accepting a level of significant error.

Therefore, the above parameters are non-additive and meaningless. (Belal, 2004)

Thus, net nutrient deposition and/or growth are the only preClse

measurement left to evaluate dietary nutrients intake in fish. Several

mathematical models such as (1) the simple linear equation, (2) the logarithmic

equation, and (3) the quadratic equation are generally used for understanding and

predicting dietary nutrient intake-growth response relationship.

While it is generally acknowledged that the relationship between the

response (i.e., Weight gain, Protein Deposition) and nutrient intake of test

animals is not truly linear, most bioassays for protein quality use a linear model

to express this relationship and bound experimental points to the region of

approximate linearity.

1

Linear and nonlinear equations that describe the intake-response

relationship were the main interest of Morgan (1975) and Mercer (1980) who did

lots of experiments and discussed the relation ship between the nutrient intake

and the organism. With their colleagues they projected a model based on the

enzyme kinetic equation in order to fit data to a relationship based on saturation

kinetics. There are also some limitations in the mentioned mathematical models

that they can not describe a full range of growth and they have no biological

meaning while the saturation kinetic model which has a biological meaning (the

law of mass action and the enzyme kinetic), can describe a full range of the

growth curve.

Dixon- Phillips (1982) defined the concept of this model which is based

on that the efficiency of nutrient utilization decreases as the requirement is

approached based on some rate limiting step. The model is used by the following

equation:

In which r ; is animal's response, I; is nutrient intake, b ,. is the ordinate intercept,

Rmax. is the asymptotic or maximum value olr , n; is the apparent kinetic order,K] =

nutrition constant and ko.s ; intake ote Rmax - b).

2

This study aimed to use the saturation kinetic model in initiate new

parameters to evaluate nutrient utilization in addition to intake response curve

that pro ide full predictive description of nutrient (protein) utilization.

The experimental fish was tilapia (Appendixl). The fresh water fish as it

is the most cultured fish in the world. its wider acceptability comes from their

ability of growing fast depending on low protein diets ( in comparison with other

cultured fishes), their efficiency in utilizing poor quality natural food such as

blue green algae, their wide range tolerance of environmental conditions like

temperature and dissolved oxygen levels (El Sayed , 2006). In addition to that,

they can give under intensive culture a production as higher as 70-100

kg/hectare/day without a loss of food conversion. This is related to their excellent

utilization of artificial feed and natural food.

3

RATUREREII

Literature Review

1. Review of the evaluation methods

1.1. D igestibility

As defined in Belal (1987, 2004), it is one of the classical methods that used

for the evaluation of nutrients in animal nutrition studies, plays a role in the

scientists' researches of evaluation of fish feed. They depend on the absorption

factors (digestibility coefficient and/or metabolism.). The perceptible digestibility

can be determined in vivo by two methods. The first method is called the "direct

method" (the total collection technique). This technique relies on quantitative

measurement of the ingested (feed) and egested (feces) materials used in the

equation:

(/ - E) D% = x 100 /

Where D% represents the percentage of apparent digestibility; I represents

amount of nutrient ingested; E represents amount of nutrient egested.

Indirect technique is the second method for measuring the apparent digestibility

coefficient. It also called "indicator method". There are two types of indicators:

external and internal. The external one is an indigestible substance that is added to the

test diet in a small quantity (1-2%). Belal (2004) mentioned some examples of the

4

external indicator such as; chromic oxide ( Riche et aL 1995_; Anderson et al. , 1991),

acid washed sand ( Tacon and Rodrigues, 1984), Celitelrn (Atkinson et al. 1984)'

Sipernat ( Rodehutscord et al. , 1996); polyethylene ( Tacon and Rodrigues, 1984),

barium oxide ( Riche et al. , 1995), Yb, Ti, 5- 0: cholestane (Sigurgisladottir et al. ,

1990); and microtracer Fe-Ni ( Kabir et al. , 1998) in addition to using mixed markers

( Hillestad et al. , 1999; Sugiura et al. , 1998). While the internal is a naturally

occurring non-digestible component in a diet in a constant proportion (Kurmaly et al. ,

1990). Both of the indicators types should not affect digestion or palatability of the

test diet.

In addition to that their concentration should be easily determined. The

percentage of the indicator is measured in the feed and a sample of the feces to

estimate the digestibility coefficient by the equation:

100 x % indicator in food Digestability % = 100 -----------­% indicator in feces

Belal (2004) explained that the major sources of under or over estimation of the

digestibility coefficient is related to errors in quantitative fecal collection. There is

also a fear about using some of the indicators because of analytical variability and

poor recovery (Riche et al., 1995). Accepting a level of significant error should be

always kept in mind when the quantitative measurements of egested materials, is

calculated under aquatic environmental conditions. Thus, related to fecal leaching in

the water and/or fish stress, depending on the collection technique. (Appendix 2).

5

1.2. Metabolizability

According to Belal (2004) metabolizability is a method of measurement in

which we collect fishes' gill excretion and urine using the metabolic chan1ber (permits

separate and quantitative collection of feces, urine and gill excretions).

Metabolizable energy (%) = Eintake - Ereces - EUTine - Egi/l X 100 Eintake

Emtake represents energy intake; Efeces represents fecal energy; Eunne represents

energy excreted from urine; EgllI represents energy excreted from gills.

Problems of this method are also related to the ways of collecting gill secretion

and urine which accompanied by confinement, anesthesia, and force-feeding that

result in fish stress.

Fish stress leads to many troubles, it inhibits absorption which may cause

hyperglycemia, elevates muscle blood lactate, serum cholesterol, skin mucus

secretion and oxygen consumption. Smith suggested that stress was reduced to

"normal" levels by injecting pure oxygen into the metabolic chamber to reduce blood

lactate. Nevertheless, blood lactate is not a reliable indicator of confinement stress

since lactic acidosis results from anaerobic muscle glycolysis ( Wedemeyer, 1976).

6

1.3. Energy Budget.

Another method in fish nutrition introduced by mith in 1976 used a modified

adiabatic calorimetry. In this method smith utilized the direct calorimetry procedure

that based on measuring heat production using a thermal equivalent. He reported that

the direct calorimetry method is less sensitive to metabolic fluctuation than indirect

calorimetry using the oxygen consumption method. The indirect calorimetry method

measures the amount of oxygen consumed during a specified period multiplied by an

oxy-calorific equivalent (Belal, 2004). Brafield, (1985) suggested that Application of

this method assumes that dietary nutrients such as carbohydrates, lipids, and proteins

are being digested and metabolized in the same proportion, in which they occur in the

diet. This is related to the difficulties of measuring faecal, urine, and gills excretion.

In addition to that this method completely ignores anaerobic metabolism.

Improvement of the indirect calorimetry method can be done by measunng

oxygen carbon dioxide and ammonia as developed by Brafield and Llewellyn in

1982.

Kutty (1968) mentioned that the application of this method is based on accurate

measurements of the oxygen consumption, ammonia production, and carbon dioxide

production. Unfortunately, large amounts of carbon dioxide can be present in the

water (especially hard water), which in turn, suppresses the release of carbon dioxide

from fish.

In addition to that Gold-stein et al. (1982) found that the concentration of

ammonia in the water will also effect on the ammonia excretion of the fish. Therefore,

7

this method still not sufficient for fish nutrition and fish still need different parameters

for dietary evaluation.

1.4. Net Nutrients Deposition or growth .

Belal (2004) mentioned that there are several mathematical models used to

predict the optimum feed (nutrient) intake and growth (net nutrients deposition

response relationship). The quantitative relationship between dietary nutrients intake

and growth responses is studied using appropriate models, in which growth data fit

well result in the prediction of optimum intake-response relationship.

Belal (2004) mentioned that the most common and applied model used ill

evaluation of fish diet is the linear model or straight-line.

Y = ao + a1X . . . . . . ... . . . . . . . . . . . . . . . . . . . .. . . . . . . .. 1

Where Y is the response (weight gain and/or the net nutrients deposition); ao is

the intercept (the response at zero intake level)' a1 is the slope of the line; X is

amount of nutrient intake.

In spite of the fact that this model is easy to use and valuable in describing the

nutritional response over a linear range of responses to nutritional intake, the growth

response is not linear over a wide range of nutrient intake levels. Thus, the

logarithmic form of the linear equation (1) is used to describe the curvilinear

relationship over a wide range of nutrient intake levels ( Eq. (2)):

Y = ao + allogX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

8

Here Y is the response (weight gain and/or the net nutrients deposition); aois the

intercept (the response at zero intake level); a1 is the slope of the line; X represents

the logarithm amount of nutrient intake.

Almquist (1953) indicated that the biological response appears to deviate from

the principle (the hyperbolic shape of grovvth response) at very low levels of nutrient

intake.

Belal (2004) mentioned that Hegsted and Neff (1970) observed that a linear

equation is sufficient for the middle range of the response curve. They also added that

at higher nutrient inputs an extra parameter forming a quadratic model becomes

significant ( Eq. (3)):

Y=ao+a1X+a2X2 . . . . . . . . . . . . . . . ... . . . . . . .. . . . . . .. 3

Where Y is the response (weight gain and/or the net nutrients deposition); ao is

the intercept (the response at zero intake level); a1 and az is the slopes of the line; X

represents the logarithm amount of nutrient intake.

The quadratic model is still inadequate in describing the lower end of the

biological curve. If another parameter is added to Eq. (3), the equation will not satisfy

the criteria of a mathematical or biological significance (Mercer, 1980; Belal, 2004).

9

1.5. The Saturation Kinetic Model

When the nutrient intake inter the body, a series of processes will take place

inside the body it self. These processes are:

1. Digestion: the act or process of converting food into chemical substances that

can be absorbed and assimilated.

2. Absorption: the uptake from the intestinal lumen of fluids, solutes, proteins,

fats and other nutrients into the intestinal epithelial cells, blood, lymph, or interstitial

fluids.

3. Distribution.

4. Metabolism.

5. Excretion.

Those processes will lead to a nutrient-macromolecular interaction which directs

the body to give a physiological response like (weight gain, serum albumin,

hemoglobin, total serum of protein, tissues enzyme levels, serum B 12, folate, tibia

femur ash, mg DNAIg liver and total food intake.) (Mercer, 1980; Belal, 2004).

Morgan et al.(197S) developed a model based on Enzyme kinetic equation that

was developed by Michaelis and Menten (1913) and Hill in (1913). The theoretical

derivation of the Morgan model was developed by Mercer (1982), who reported that

the effect of a nutrient in a physiological system may be regarded as the result of

physio-chemical interaction between the nutrient and various micro molecular

components of the organism. This specific interaction may use an organized function,

which collectively are described as the metabolic activity or responses of the

organisms. (Belal, 2004).

10

Belal (2004) explained Figure (1) shows how it is possible to conceptualize a

sequence of events by which a nutrient elicits its characteristics response.

Furthennore, Mercer (1982) suggested that a specific interaction with a

macromolecule such as an enzyme mediated almost every aspect of nutrient

utilization. The magnitude of a response would be a function of the rate-limiting step,

if we assume that there is a rate limiting step in the sequence. A rate limiting step like

this has been postulated by Almquist (1953).

The interaction of the nutrient with a specific site on the macromolecule

(receptor) would give rise to a physiological response and the magnitude of the

response would be directly proportional to the number of receptors occupied by the

nutrient (Mercer, 1982; Belal, 2004).

According to this concept, the law of mass action (equilibrium constant to a

simple chemical reaction) can be applied to the system and derived an appropriate

equation governing the quantitative relation ship between nutrient and response as

mentioned in Morgan, et al. (1975).

11

utrient Intake

"- ��

Dige lion Ab orplion Di tribution Metabolism Eurelion

Nutrient macromolecular interaction

I Physiological Response

Figure (1): Utilization of a nutrient in the production of a physiological response (Adopted from Mercer (1982)) (Belal, 2004).

The following model derivation was adopted from Belal (2004) with the author

perrrusslOn.

Mercer (1982) illustrated the mathematical derivation of the saturation kinetic

model as follows:

Nutrient intake + Organism � Nutrient - macromolec ular interactio n

t Pysiologic al response.

If we agreed:

utrients = substrate

Organism = Groups of enzymes (receptors, digestion, absorption, metabolism,

excretion, and deposition).

12

""

Actually this is biochemical equilibrium when a nutrient (I) combines with a

receptor, eM) to yield the complex M1 which produces the physiological response pr

in a manner proportional to concentration of M1:

KI [1]+ [M] ¢:> [MJ]

K2

Where K1J KZJ K3 are constant and [] denotes concentration at equilibrium.

[M][I] _ K2 = K 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

[MI] Kl

Where K[ is also a constant.

Next, if Mt is defined as a total enzyme receptor concentration or the total

number of enzyme, so that:

[Mt]=[M]+[MI]J Then;

13

[Mt-MIJ[I)

[MIl = KI

···

. . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

. . . . . . . . . . . . . . . . . ..

. . . . . . . . . . . . . . . . . . . . . . . . 2

Rearrangement will give:

[Mll _ _ Ql_

[Mtl - Kl +Q) ················································· . . . .

.. . . . . . . . . . . . . .

..

. . . . . . 3

Then;

� _ [MI]

PRmax [Mt]

And;

PRmaxQ] pr = K,+ [I] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Belal (2004) mentioned that this equation is identical to Michaelis-Menten

equation according to Hegested and Neff (1970) and could be useful in describing

physiological responses to nutrients, according to the model. It meets the criteria of

observed phenomena that are a continuous response to graded levels of intake and the

law of diminishing returns (Almquist 1953). The Michaelis-Menten equation is

expressed here as:

14

Vmax + [5] v=----=---::.. Km + [5]

Where

Km = Michaelis-Menten rate constant.

[ ] = substrate concentration.

= initial rate of production of the product.

V max = maximum initial rate of production of the product.

However, equation 4 has two limitations which do not match with observed

responses. First, the equation only describes a hyperbola, while many responses are

found experimentally to be sigmoidal (n > 1) in nature (Allison 1964). This problem

may be defeated by adding the parameter n (the apparent kinetic order) or the slope

factor to the equation:

PRmax[I)n 5 pr= . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

KI+[I)n

The above equation named Hill equation (Hill 19 13), this approach has been

utilized in enzyme kinetics and it can vary from hyperbola to a sigmoidal (n> 1) curve

as n increase above 1.

15

But, equation 5 has also a limitation that the equation describe a curve which pass

through the point (0, 0) of an (x,y) coordinate system, which does not allow the

prediction of responses such as weight loss. And if we consider [M] as the organism

(which is a group of enzyme) so the curve could not pass through (0, 0) point because

the enzyme level in the organism could not reach to the level zero. To solve this

problem, another parameter has been added by Mercer ( 1982) to the above equation,

the new parameter is b which represents x intercept.

pr= PRmax[I]D +b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . · · · · · · · · · · · · · · . . . . . . 6

K,+[I)D

Rearrangement will give;

PRmax[J]+bK,+bln 7 pr=

K,+[I)n . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . • . .

Mercer ( 1982) suggested that if we let;

16

And simplify pr to r; we will have the four parameters for the physiological

response.

b K/+Rmax(1)n r = -�--=..:.::=-::....!...-K/+(I)n

. . . . . . . . . . . . . . . . . . . . . . . . . . . '" .. .. . .. . . . . . .. . .. . . ... . ... . .... . .. ... 8

This can be more conveniently written;

bKJ+Rmax[I]n r = [K.s)n+[I)n . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

When;

r =physiological response.

J =nutrient intake or concentration in the diet.

b= intercept on the x axis.

K/ = nutrient constant

Rmax = maximum response.

n = apparent kinetic order.

1 ko.s = intake of 2' (Rmax - b)

The data points 0, r) for the standard and test proteins are read into the

computer using the program SYSTAT, which calculates the above parameters (

17

Thi model sati factorily explains all parts of the biological response curve over a

wide range of nutrient intakes.

We can see this clearly in a hand drawn response s-shape that result when the

organism will be fed with graded levels (i.e., dietary nutrient concentrations) of an

essential nutrient over a range from zero to levels which surpass maximum dietary

response levels.

4.5

I 4() • T I • I

h D A- I r d I i i ,

I 0 8 t .. .e I s I + .q x 11 I � u

I I) t , .c I

t t I I I � " i .- I

10 I 1 t I a I

t I • 0 �

1 2 3 � B @ 1 8 10 11 �rrt 1�

Figure (2): The s-curve of the saturation kinetic model (adopted from Mercer

( 1982)).

18

The various sections of the curve have been recognized by Mercer (1982) and

have been adopted in this thesis from Belal (2004) with the author permission.

1. Threshold-the lower range of nutrient concentrations, which produce zero or

negligible responses by the organism. A positive response (b>O) with a zero slope at a

low dietary nutrient level implies endogenous stores of that nutrient.

2. Deficient-the range in which the slope of response increases, but the genetic

potential of the animal is not fully expressed.

3. A dequate-the portion of the curve at which the slope moves from positive towards

zero (or a plateau). The genetic potential (assuming no other limiting nutrient) is fully

expressed but no "margin of safety" exists for stress, pathology, etc.

4. Optimal-the range (rather than the point) of maximal responses.

5. Toxic-the intake level at which the response is diminished. An excessive dietary

level of a nutrient can lead to displacement of other essential nutrients and/or

impaired metabolism.

From this curve we can also understand the application of the saturation kinetics

model:

1. It satisfactorily explains all areas of the biological response curve over a wide range

of nutrient intake.

2. It could be used to determine the nutrient necessities of animals (fish).

3. The model is useful in comparing other nutrients.

19

4. The model was used to predict the dietary nutrients toxicity utilizing daily weight

gain as an indicator.

For these reasons lots of experiments have been done with the model tested on

different organisms with different ecological factors to get specific physiological

response as summarized in the followings:

1. Organisms such as (rats mice, chicks, swine, and even man).

2. utrient (protein, amino acid, selenium, mercury, cadmium, vitamins, and etc).

3. Predictive Response (weight gain, serum albumin, hemoglobin, total serum of

protein, tissues enzyme levels, serum B12, folate, tibia femur ash, mg DNAIg liver

and total food intake.) (Mercer 1980).

20

2. The experimental Organism

2.1. Tilapia Oreochromis niloticus

Tilapia is cichlid fish with high economic value. As tilapia are native to Africa,

The origin of the name tilapia is derived from the African bushman word meaning

"fish". Belal (1987) mentioned that during the second half of the 20th century, tilapia

were introduced into many tropical, sUbtropical and temperate regions of the world

according to their importance as food sources, recreational fishing, aquatic weed

controller and in research purposes. They play a significant role in tropical aquatic

ecosystems because of that their introduction must be done very carefully or it will

lead to several bad ecological impacts.

Belal (1987), Al-Mohsen (1998) and El-Sayed (2006) mentioned that Tilapia has

many characteristics that make them favorable for aqua cUlturing especially in

developing countries. These characteristics can be summarized as: (These

characteristics led me to choose tilapia as my experimental organisms).

1. They grow fast.

2. They can tolerate a wide range of environmental conditions (temperate,

salinity, low dissolved oxygen, etc.)

3. They show a good resistance to disease and stress.

4. They have a great ability to reproduce in captivity and short generation time.

5. They feed on low trophic levels and accepting artificial feeds immediately

after yolk-sac absorption.

21

This fresh water species is widely introduced out side its range may be because of

its high economic value. It has a wider acceptability than other species by consumers

and fish fanners and it continues to be considered as one of the most popular and

important aquaculture species in the gulf countries despite of its darkish gray

coloration that is often considered as undesirable unattractive characteristics by

consumers.

2.2. Tilapia Nutrition

A great deal of interest has been paid to aquaculture nutrition in latest years. The

development of commercial, cost effective tilapia feeds using locally obtainable, low­

priced and alternative resources is the challenge that faces tilapia fanners in general

and tilapia nutritionists in developing countries in particular.

The requirements of farmed (experimental) tilapia for the five classes of dietary

nutrient, (protein, lipids, carbohydrates, vitamins and minerals) discussed and

abbreviated as follows:

2.2.1. Protein requirements

Proteins, the large, complex molecules are composed typically of carbon,

hydrogen, oxygen and nitrogen, as well as small amounts of sulphur and some times

phosphorus. They are essential for the structure and function of all living organisms.

22

It is interested that protein requirements for the maximum performance fish is rugher

than terrestrial animals (EI- ayed, 2006) thus, special attention is paid for to studying

dietary protein requirements for aqua culture farming. Tilapia requirements of Protein

depend, among other things, on fish size or Age protein supply and the energy

content of the diets. Generally speaking, protein requirements diminish with

increasing fish size.

During the larval stages, tilapia (especially Nile tilapia) necessitates about 35-

45% dietary protein for maximum growth performance ( Siddiqui et al.. 1988; EI­

Sayed and Teshima 1992)Some researches reported higher values (>50%) (Winfee

and Stickney 1981; Jauncey and Ross, 1982) but these values appear not practical

conditions.

On the other hand, tilapia broodstock require 35-45% dietary protein for best

possible reproduction, produces efficiency and larval growth and endurance

(Gunasekera et al,. 1996a, b;Siddiqui et al. 1998, EI-Sayed et aI., 2003)(Table1)

23

Specie a n d Weight (g) Protein sou rce Req u irem e n t Reference l i fe tage. (%)

Fry 0.0 1 2 FM 45 EI-Sayed and Teshima 0.51 FM 40 ( 1992). 0.56 Casein/Gelatin 35 Al Hafedb (1999).

Teshima et al. ( l 985a).

Fingerlings 1 .29 Casein 40 Teshima et al. ( 1982).

2.40 Casein/ gelatin 3 5 Abdelghany (2000a).

3.50 Casein 30 Wang et al. ( 1985).

Adults 24 FMl SBMl BM 27.5 Wee and Tuan ( 1988)

40 FM 30 Siddiqui et al. ( 1988)

45-264 FM 30 AI Hafedb ( 1999)

Table (1); Protein requirement of Tilapia, Oreochromis niloticus.

Adopted from El-Sayed (2006)

24

The main components of proteins are known as amino acids, of which about 25

commonly happen in food protein. These amino acids are divided into two groups:

� Essential amino acids (EAA),

Ami no acids that cannot be synthesized by l iving orgarusms and must be

presented in the diets are cal led essential amino acid. They are Arginine(Arg),

lysine(Lys) histidine(His), threonine(Thr), valine(Val), leucine(Leu), isoleucine(Iso),

methionine(Met), phenylalanine(phe) and tryptophan(Try).

� Non-essential amino acids (NEAA),

Amino acids that can be synthesized by the orgarusms, in the presence of

suitable starting materials including EAA, are called Non-essential amino acids.

Tilapia requires the same ten EAA, like other fish. But the definite EAA

requirements of the most farmed tilapias have not been detennined. (El-Sayed, 2006)

The EAA requirements of tilapia differ by species and amino acid source

.Neutralizing AA-based diets to a PH of 7-7.5 would recover their quality for tilapia

(Mazid et al., 1 979) Lots of efforts should be done in this area, since other studies

indicated that lowering food PH improved the appetite of Tilapia zilli for food

(Adams et al. , 1 988) (Table 2)

25

Table (2); .Esse�tial amino acid requirements of Nile tilapia as % of dietary protein and of total diet

Ammo aCIds Oreochromis niloticus • J Oreochromis niloticus*b

Lysine (Lys) 5. 1 2( 1 .43) Arginine (Arg) 4.20( 1 . 1 8) Histidine (His) 1 .72(0.48)

Threonine (Thr) 3 . 75( 1 .05) Valine (Val) 2.80(0.78)

Leucine (Leu) 3.39(0.95) Isoleucine (Iso) 3 . 1 1 (0.87)

Methionine (Met) 2.68(0.75) Cysteine (Cys) 0.53

Phenylalanine (phe) 3 .75( 1 .05) Tyrosine (Tyr) 1 .79

Tryptophan (Try) 1 .00(0.28)

* 1 Santiago and Lovell ( 1 988);*2 Fagbenro (2000) Adopted from (El-Sayed, 2006)

-

4 . 1 1 .5 3 .3 3.0 4.3 2.6 1 . 3 2. 1 3 .2 1 .6 0.6

Lots of studies were done about protein and amino acids requirements of Nile

tilapia, fIrst Quadros, et al. (2007) did an experiment about the effect on protein and

nitrogen efficiency ratios of Nile tilapia by feeding diets different in their methionine

plus cystine and threonine to lysine ratios. In the same laboratories another related

study about methionine plus cystine requirement was done by BornfIm et al. (2007)

The threonine requirement was the focus of a study by Lanna et al . (2007) in another

place, the lysine requirement of Nile tilapia was modeled by Liebert and BenKendroff

(2007). Another experiment was done by Nguyen and Davis (2007) conducted

research on the sulfur amino acid requirement and ability of cystine to replace

methionine in diets fed to Nile tilapia.

26

In addition to that, Gaye- iessengger et al . (2007) fed diets differing only in the

composition of their non essential amino acids to the Nile tilapia. The experiment

indicated poor uti lization of synthetic amino acids by the fish, thus the author

concluded that they are important to growth performance.

2.2. 1 .2. Protein Sources

El Sayed (2006) mentioned that Purified and semi-purified protein sources are

not recommended for ti lapia under commercial culture condition, but in other

conventional and unconventional, locally available dietary protein sources should be

reco gnized (chosen) carefully.

Researches have evaluated many such sources for different species of tilapia,

with varying results. It is appropriate to highlight these protein sources for tilapia,

with emphasis on the sources that have economic potential and are locally available,

especially in developing countries (EI-Sayed, 2006). Protein sources can be

mentioned briefly as fol lows:

A) Animal protein sources (FM)

a) Fish meal

Fishmeal has been traditionally considered as the main protein source in the aqua

feed industry, according to its high protein content and balanced EAA profile. In

addition FM is also an admirable source of essential fatty acids (EF A), digestible

energy, minerals and vitamins. The increased demand for FM, coupled with a

27

ignificant shortage in global FM production has created sharp competition for its use

by animal feed industry.

As a result, FM has become the most expansive protein commodity in animal

aqua culture feeds in recent years (El-Sayed, 1 998, 1 999a). For this reason, many

efforts have been done to partially or total ly replace FM with less expensive, locally

available protein source.

b) Fishery by-product

Large amounts of fishery by-product and by-catch are produced annually in the

world, thus, the attention to use them commercially and experimentally for tilapia

must be increased (El-Sayed, 2006).

El-Sayed (2006) mentioned that several studies have been done on the fish silage

(FS) and shrimp meals, considering their use as an FM replacer in tilapia feeds. The

results point toward that between 3 0 and 75% fish silage can be successfully included

on tilapia feed, depending on fish species and size. Example, (grow-out Nile tilapia

responded better to FS than fry or fingerlings).

c) Terrestrial animal by-products

El-Sayed (2006) discussed the terrestrial animal by-product which includes

poultry by-products meal (pBM), blood meal (BM), hydrolyzed feather meal (HFM)

and meat and bone meal (MBM), have been extensively used as protein sources for

tilapia, according to their high protein content and good EAA profiles. However, they

may be diffident in one or more of the EAA. Example ( lysine PBM and HFM),

28

isoleucine(BM) and methionine (MBM, BM and HFM) (NRC, 1 983 ' Tacon and

Jackson, 1 985)

uccessful experiments used terrestrial animal by-product si lage, as a source of

protein for tilapia. (Belal et al ., 1 995) fed O niloticus fingerlings ( 1 0.8g) test diets

containing 0-20% chicken offal si lage (GOS), made from chicken viscera, as a

replacement of FM. Results proved that the growth and body composition of fish fed

GOS up to the 20% level were similar to those of fish fed an FM-based diet. Final ly

for the determination of the proper inclusion level, high inclusion levels of GOS

should be tested. (EI-Sayed,2006)

d) Maggot

House fly Maggot meal is considered as a good alternative protein source for

tilapia fingerlings according to cost effectiveness, availability and crude protein

content, in a study by Ogunj i et al . (2006) a multi-dimensional biological approach

was used to evaluate the suitability of House fly Maggot meal as an alternative protein

source.

B) Plant protein sources

a) Oilseed plants

SOYBEAN MEAL

It contains the highest protein content and has the best EAA profile among plant

protein sources, and it can be used as a total or partial protein source for farmed

tilapia, depending on fish species and size.

29

BM is deficient in sulphur-containing amino acids (Met, Lys cystine (Cys»

and contains endogenous anti-nutrients, including protease (trypsin) inhibitor,

phytohaemagglutinin and anti-vitamins. Some of the factors can be destroyed or

inactivated during thermal processing (El-Sayed et al. , 2000, EI-Sayed, 2006).

COTTON SEED MEAL/CAKE

EI-Sayed (2006) defined CSM as one of the most obtainable plant protein sources

in tropical and sub tropical regions. In developing countries, CSM is also one of the

best protein candidates according to high availability, low price, good protein content

(26-54%, depending on processing methods) and amino acid profile. But it contains

relatively low levels of Cys, Lys, Met in addition to a high content of gossypol (a

phenolic anti nutrient), which may limit the use of CSM 10

tilapia feeds. Finally, lots of studies should focus on using oilseed by-products in

tilapia nutrition such as (Groundnut, sunflower rapeseed, sesame seed, macadamia,

coca cake and others) and they have to understand the effects of phytase

supplementation that related to the high levels of phytic acid in plant protein which

binds with divalent minerals such as Ca, P, Zn, Mn, Mg and Fe to form water­

insoluble salts, rendering the minerals unavailable.

b) Aquatic plants

EI-Sayed (2006) discussed the use of aquatic plants as a source of protein in

tilapia feeds, he mentioned that it should be involved in the study of Tilapia. A plant

named duckweed (fami ly :Lemnaceae.) is an excellent food source for tilapia, it

30

contains about 3 5-45% crude protein with good amino acid and mineral profiles and it

can be used as a single food. ( kil licom et al. 1 993)

Other aquatic plants, including Hydrodictyon reticu/atum, coontail

(Ceratophyllum demersum), chuut-nuu (Eleocharis ochrostchys) and Potamogeton

gramineus, can be second-hand as a partial replacement of standard protein for

different tilapia species. However these sources must be carefully looked at, since

some other aquatic plants, such as Elodea trifoliate and Muyriophyllum spicatum,

ha e been reported to reduce tilapia performance (El-Sayed, 2006).

c) G rain legumes

A lot of leguminous or cereal plants and by products can be used as

fractional protein sources for tilapia. For examples, (leucaena leaf meal (LLM, 30%

crude protein), brewery wastes, maize products, cassava leaf meal, green gram

legume, l ima bean and leaf protein concentrates are of prime value.

C) Single cell protein

Single-cell proteins (SCP) are defmed as a group of microorganisms,

including unicellular algae, fungi, bacteria, cyanobacteria and yeast. Using (SCP) in

tilapia's nutrition has attracted attention in latest years. Producing (SCP) is simple,

cheap and effective way of natural fish food production (El-Sayed, 2006).

3 1

Example, if a carbon source (ex, wheat bran) is sprayed on the surface of

pond water with continuous aeration, at the optimum carbon: nitrogen ratio ( 1 5 : 1 ), bacterial growth will increase (Chamberlain and Hopkins, 1 994). The bacteria

consume the carbon source as energy and reduce the ammonia concentration

through nitrification, while the fish feed on the bacteria (El-Sayed, 2006). Efforts

should focus on using (SCP) in tilapia nutrition especial ly in developing countries.

2.2.2. Dietary Lipid Requirements

EI-Sayed (2006) considered that like other vertebrates, tilapia necessitate

dietary lipids for several physiological responses such as,

1 . A supply of essential fatty acids (EF A) .

2. Energy production.

3. Normal growth and development.

4. Carrying and supporting in the absorption of fat-soluble vitamins.

5 . Structure and repairs of cell membrane integrity and flexibility.

6. Originators of steroid hormones.

7. Improving the surface and taste of the diet and fatty acids composition of the

fish.

Tilapia has been identified to utilize dietary l ipids very efficiently. Dietary lipids

may unused more protein for growth than do carbohydrates (Teshirna et al . , 1 985b,

El-Sayed and Garling, 1 988) Lipid requirements of tilapia, is stil l in need for more

studies. Tilapia requirements for l ipids depend on lipid source, dietary protein and

energy contents in addition to tilapia species and size. In general tilapia lipid

32

requirement is about ( I O ta 1 5) % dietary lipids for maximwn growth performance.

However. tilapia farmers often use lower lipid values (6to 8) % (El-Sayed, 2006).

2.2.3. E sential Fatty Acid Requirements

The word essential in nutrition refers to the necessary components the organism

needs and can not be synthesized by its body. Essential fatty acids for tilapia are

polyunsaturated fatty acids (n-3PUF A and n-6 PUF A).

According to (Kanazawa, et.aI, 1 980a, Stickney et.aL, 1 982 and Stickney and

McGeachin 1 983) cold-water fish and marine fish require n-3 polyunsaturated fatty

acids (n-3PUF A), while freshwater fish inhabiting warm water environments tend to

require (n-6 PUPA). This lead to suggestion that tilapia would utilize plant oils (rich

in n-6 fatty acids) more efficiently than fish oils (rich in n-3 fatty acids).

Several studies supported this fact that Tilapia requires n-6 EFA rather than n-3

EF A. The growth of Nile tilapia fed on a fish oil-containing diet (rich in n-3 EF A)

was significantly reduced as compared with one containing soybean oil or maize oil

(rich in n-6 EFA) (Takeuchi et aI . , 1 983) S imilar results were reported for Nile tilapia

broodstock, where fish fed with fish oil-containing diets had a significantly poor

reproductive performance compared to those fed soybean oil diets (Santiago and

Reyes, 1 993)

33

Other studies found that tilapia may require both n-3 EFA and n-6 EFA. An

experiment was done by tickney and McGeachin ( 1 983) resulted in that 1 0%

soybean oil or 1 0% fish oil produced similar growth of blue tilapia. Chou and Shiau

( 1 999) found that both n-3 and n-6 highly unsaturated fatty acids (HUF A) are

required for maximum performance of tilapia hybrids (0. niloticus x o. aureus). (El­

Sayed et al .,2005a) recently found Nile tilapia broodstock reared in brackish water

required n-3 HUF A for optimum spawnin g performance, while the reproductive

performance of fish reared in fresh water was not affected by dietary lipid source. It is

evident that the requirements of tilapias for EFA are species-specific. Lots of studies

should be on this fields to answer all the questions and doubts about the requirements

of tilapia to essential fatty acids under different culture systems and in different water

environments.

2.2.4. Carbohydrate Util ization

El-Sayed (2006) defmed Carbohydrates as the most available and the

cheapest source of dietary energy for human, fish and domestic animals, could be

utilized efficiently by the mainly herbivorous fish tilapia. Traditionally, wheat

bran, maize and rice bran have been used as a major dietary carbohydrate source

for tilapia.

El-Sayed (2006) discussed carbohydrate utilization of tilapia which IS

affected by several factors like (their fiber content and the daily feeding

frequency). On the other hand, attention should be attracted to the amount of

34

amylase inhibitors or other anti-nutrients in the carbohydrates that may reduce

their uti l ization by tilapia.

2 .2.5. Vitamin Requ irements

Vitamins are defined as organic compounds that are general ly required in small

quantities in animal diets. They act as cofactor or substrates in nonnal metabolic

reactions (El-Sayed, 2006).

Vitamins are either not synthesized by the organisms or synthesized at rates

not enough to meet the needs of the organisms. They are critical for the

maintenance of nonnal metabolic and physiological functions in spite of fonning

a minute fraction of the diet.

They are subdivided into water soluble (macro vitamins, based on the levels

required) and fat-soluble groups. It has been reported that tilapia may not

necessitate definite vitamins, since the fish are able to manufacture them. But

vitamins deficiency in general may result in nutrition-related disease, poor growth

or increased susceptibility to infections (El-Sayed, 2006) (Table 3)

35

T bl (3 ) a e : Vitamin Requirement of Nile Tilapia. v i tamin Requ i rement (mg/kg) References Deficiency Symptoms

A 5000ru Saleh et al. ( 1 995); Low growth, restless, abnormal movement, blindness,

exophthalmia, haemorrhage, pot-belly syndrome, reduced

mucus secretion, high mortality.

C 420 (ascorbic acid) Soliman et al. ( 1994).

E 50- 1 00 (5% lipid) Satoh et al. ( 1 987). 500 ( 1 0 - 1 5% lipid)

Adopted from (El-Sayed, 2006)

2.2 .6. Mineral Requirements

Minerals are defmed as inorganic elements that are necessary by animals to

preserve many of their metabolic functions that can be summarized as follows

(Jauncey, 1 998) :

1 . Structure of hard skeleton such as bones and teeth.

2. Osmoregulation.

3 . Structure of soft tissue.

4. Nerve impulse and transmission and muscle contraction.

5. Body acid -base equilibrium and regulation of the PH of the blood and other

fluids.

6. Cofactors in metabolism, catalysts, and enzyme activators.

7. Minerals serve as components of many enzyme, vitamins, hormones and

respiratory pigments.

36

tudies should be done on mineral requirements of tilapia because their

response to dietary minerals is not fully understood.

There have been some difficulties in determining mineral requirements of the

fish because of their ability to absorb ions from the external environment (Al­

Darmaki, 2003) . It is not easy to formulate diets and maintain a culture

environment free of minerals to conduct requirements or deficiency studies. Ion

exchange across the gills and skin greatly complicates the quantitative

determination of mineral requirements (Lal I , 1 979). Also, the supplementation of

the dietary minerals may not be essential, except in the case of those that are

required in relatively high concentration, mainly in fresh water fish.

Fish size and the source of dietary P and Ca, are determining the availability

of P and Ca in the diets. A study by Robinson et al. ( 1 987) found that the best

growth of 0. aureus fed casein diets supplemented with graded level of Ca and P

was founded at 0 .7% (7 glkg) dietary Ca, though bone mineralization was not

significantly affected by dietary Ca. Then again, about 0.3% (3 glkg) P

supplementation was sufficient for good growth, as 0 .5% (5g1kg) was necessary

for normal bone mineralization. The available phosphorus requirement is nearly

similar to those reported for other fish species.

The requirements of zinc of 0. niloticus are studied by Eid and Ghonim

( 1 994). They found that the zinc requirement was 30 mglkg dry weight for

frngerlings fed purified diet. General zinc deficiency signs l ike reduced growth

rate and high mortality have been noticed in rainbow trout, common crap and

37

channel catfish, while a high occurrence of cataracts has been associated with zinc

deficiency in rainbow trout and carp. (Table 4)

Table (4)' Mineral Requirement of Nile Tilapia. M inerals Requ i rement References

(mg/kg) Magnesium 600-800 Dabrowska et al. ( 1 989)

linc 30 Eid and Ghonim (1994) 79 do Carmo e Sa et al. (2004)

Manganese 1 2 Watanabe et al. ( l 988a)

Iron 60 Kleemann et al . (2003)

Adopted from (EI-Sayed, 2006)

38

M a terial and Method

1. Culture Cond it ion

This study was prepared in The Fish Lab. of Arid Land Agriculture

Department, College of Food and Agriculture, DAE University, At Al Ain, UAE. Nile

Tilapia, 0. niloticus was selected as the experimental organism. The origins of the

fish used in this study were the Philippine. The study was composed of two

experiments, the same concept but with different growth stages of fish (Fries and

small Fingerl ings) . In both experiment, fish were fed twelve semi-purified diets

containing graduated levels of nutrient (protein). Three replicate per feed were used

for the fingerl ings and two replicate were used for the fries (because of the limited

number available) . Feeding levels were based on percentage of the fish wet body

weight adjusted weekly . 25% for fry experiment and 1 0% for the fmgerlings

experiment. A sample of fish were weighed, sacrificed, ground and stored frozen at -

20Cfor later chemical analyses at the beginning of the both experiments, while al l fish

from each tank had similar treatment at the end period of the experimental duration.

The four parameters of the saturation kinetic model were used to analyze the results of

the dietary protein intake and the fish responses.

Fries experiment used tilapia fries at swim-up fry stage which is exactly after the

yolk sac absorption, the fry were counted and weighed to the nearest 0.0 1 g and the

average initial weight (g per fish) was calculated. While in fingerlings experiment

fingerlings weighed to the nearest 0. 1 5 g and the average initial weight (g per fish)

were calculated. Fries were randomly stocked into 1 8L fiberglass tanks while

fingerl ings were stocked 70L fiberglass at a stocking density of 1 2 fry per tank and 1 0

39

fingerlings per tanle Tanks were part of two semi-closed water recirculation systems

( one for fry and the other for fingerl ings) consisting of a four settling tanks to remove

solids smal l pieces of plastic tubes for nitrification, UV tube, Aquafllle U V

disinfection made in the USA (Aquafine corporation), for disinfection and an elevated

head tank to provide water to each tank. De-chlorinated tab water was used for fil l ing

tanks and replace make-up water that was lost due to evaporation and system

maintenance. Water was heated using a High Watts Liquid heater unit made in

England (E.Braud Limited). The aeration was regulated by small l ine from the main

Lab 5 Hp Air Blower in each tank in addition to the presence of thermostat that keeps

the temperature at 24 + _ 3c . Fries were fed at 25% of their weight per day while

fingerlings were fed 1 0% of their weight per day. The system was similarly exposed

to 1 4 h i l lumination using fluorescent l ightening. Water quality parameters (DO,

temperature, total ammonia, and pH) were measured once a week using Dissolved

Oxygen Meter, YSI Model 52 (YSI Instrument Co. Inc . , Yellow spring, Ohio, USA),

Digital pH ,Jenway ion meter, Jenway Limited cat no. 3205, England, total ammonia

ORION Photometer, Orion Research; INC . Aquafast, USA.

40

Figure (3): A view of the semi closed, recirculating indoor system

41

Figure(4): a view of the semi closed, recirculating indoor system showing the Aquafme U V

disinfection

42

r--- ----

.------� 01< • U

2 . Experimen tal Diet

Twelve semi purified rations with 0%, 5%, 1 0%. 1 5%, 20%, 25%, 30%, 35%,

40, 45%, 50%, and 54% protein powder (on dry weight basis) were formulated

(Table 5) .

The diets were prepared as fol lows : a l l feed ingredients were weighed and mixed

in a kitchen mixer. Distilled water (60°C) was slowly added while mixing until the

mix began to clump. Then, the diet passed through a kitchen meat grinder and dried

for 72 h at 80°C in an air blowing drying oven. The dried diet was chopped into

pel lets in a blender and then passed through laboratory test sieves (mesh 2 and 0.02

43

nun) to ensure homogenous particles size and stored at -8°C until used for both fry

and fingerl ings of sinking pellets. Small particles were used for fry experiment and

larger ones for the fingerl ings test.

3. Feed ing trial

Each feed was fed on a dry weight basis to triplicate tanks of fish three times a

day. Fish from each tank were weighed every seven days. The trial i s continuing for a

period of four weeks for fry and eight weeks for the fingerlings. At the end of the

experiment all the fish from each tank were separately weighed. Then fish were

kil led, ground in a commercial blender and stored at _8°C for subsequent body

composition analysis.

4. Chemic al Analyses

4.1. Crude P rotein

The kjeldahl method was used for nitrogen! protein determination.

1 . 0.5 g of ground samples digested in concentrated sulfuric acid (95-98%) with

a catalysts potassium sulphate and selenium), which results in a conversion of

nitrogen to ammonia by using Tecator digestion system 40.

2 . Distillation of ammonia into trapping solution of 4% boric acid by using

Vabodest®

3 . Quantification of ammonia by titrating with a 0 . 1 N standard solution.

44

The results were calculated using the following equation :

% Pr olein = %N X 6.25

% (dry matter bases) = VA X N Hcl X 1 .007/w X Lab DM/ I OO

VA = Volume, in mI, of standard Hcl required

N Hcl = ormality of standard Hcl

1 .007 = milli equivalent weight of nitrogen X 1 00

W = Sample weight in g

4.2. Crude Fat

Tecator, Soxtec system HT6 were used to determine crude fat . Dried ground

sample 0 .5 g were weighted into thimbles and inserted into the extraction unit.

Diethyl ether was used as an extraction solvent. After solvent addition to the

extraction cup, the material was extracted into the solvent in two stage processes

fol lowed by a solvent recovery cycle. The resulting residue were weighed and

referred as ether or crude fat.

4.3. Total Ash

A dried ground sample 2g was weighed in a pre-weighed crucible and ashed in

a furnace at 600°C for 1 6 hours. The crucible were removed and transferred to

desiccator to cool . The final weight was recorded and the percentages of ash

were calculated.

45

5. Ma thematical and Statistical Ana lysis

The mathematical and statistical analyses were the same as in Belal ( 1 987). The

four parameters of the saturation kinetic model were used to analyze the data similar

to the following example :

utrient intake (1) N utrient response (ro) :observed response

[unitlgfishldayJ (g response/ fish/day)

Diet #1 0.75 0.03 1

1 .20 0.095

1 .90 0. 1 76

2.60 0.230

3.30 0.24 1

Nutrients included: protein.

(bk, +Rma J r (Kj + r)

I .The equation above was rearranged to :

So the multiple l inear regression programs were applied to determine the three

independent variable at a given en).

46

2 . The theoretical values of ( r ) were calculated at the specific n (theoretical

response).

3 . The sum of squares of errors between the observed and the theoretical

response (rt, ro) were calculated.

(Residual sum of squares) RSS = ", N ro - rJ 6o-J

4. Steps 1 -3 were repeated using different values of N until the minimum value

of RSS was gained.

5. The four independent parameters of the nutrient response was used to plot the

predictive curve.

6. the nutrient intake at half-maximal response was calculated from the

equation:

1 k0 5 = (K, }1i

7 . Depending on the four parameters and the specific curve for each protein

level, each diet was compared.

8 . The dietary protein intake required for maintenance of the original weight (the

dietary response is equal to zero), Ir=O was calculated from general equation.

47

9. Mercer ( 1 982) developed an efficiency parameter that can measure the

greatest response with smal lest intake value. By calculating the intake at

maximum response from the followed equation :

1 1 enu = ko 5 (n - 1 )"N

The response at Ime was calculated from general equation. The maximum

efficiency was calculated as:

Another efficiency parameters was used m this study III measuring protein

efficiency at half maximal response (E) .

1 0. The confidence l imits for each parameter were estimated by using the analysis

of variance for Multiple Regression Techniques (Draper, 1 966).

1 1 . The parameters were calculated by computer program SYSTAT. (Appendix

3).

48

Results

Water quality parameters namely DO pH, water temperature and the total

ammonia nitrogen indicated were within the following ranges DO 1 0±. 1 mg L - 1 , pH

7.9± . l and total ammonia.0.05 ±. l mg L- 1 •

Crude protein composition o f the test diets agreed wel l with the calculated semi­

purified diets (Table 5) . Test diets with variant levels of dietary protein had significant

effect on fry and fingerlings survivals (Table 6)

Body composition analyses of Oriochromis niloticus fmgerlings are shown in

(Table 7). Percentages of body fat were found to increase with increasing dietary

protein in the test diets.

Survival was significantly higher in fish fed diets ranging from 40% to 54%

crude protein than in fish fed diets containing zero to 30% crude protein. However, no

significant difference (P > 0.05) exists within these groups. Survival was much lower

in fry stage trial as compared to fingerlings stage one.

Application of the four parameters saturation kinetic model in the fingerlings and

fries trials indicates that the model satisfactorily describes all areas of the growth

response curve over a wide range of nutrient intakes. The four parameters for

physiological responses (weight gain, protein deposition and fat deposition) were

calculated by SYSTAT (Table 8, 9, 1 0, 1 1 ). A hand drawn response s-shape curve is

observed.

49

The arious sections of the curve have been identified in (Figures 6, 7, 8, and 9)

showing the slope of the line for semi purified diet protein intake and their

depositions (responses) in 0. niloticus fry and fingerlings bodies for both

experiments. Each point on the curves represents the mean of three and observations

of the fmgerlings and fry trials respectively. The confidence limit of the four

parameters is 95%. These curves demonstrate the characteristics of protein intake­

response relationships of each trial (fry and fmgerlings) . Each observation represents

steady state equilibrium. This was achieved by the fish based on limiting nutrient

(protein) represented by the intake level . All points above the intake axis are in

positive balance with the environment. Parameters generated from the fry trial were

different from those of the fmgerling trial . Fries were much more efficient (lower Ko 5

value) than fingerlings. However the maximum theoretical response values ( Rrnax )

were much lower during fry stage than that of fingerling stage. Dietary protein intake

and deposition in 0. niloticus fry and fmgerlings bodies followed the same pattern of

weight gain (responses) of fry and fingerlings bodies for both experiments. Each point

on the curves represents the mean of three and observations of the fingerlings and fry

trials respectively. The confidence l imit of the four parameters was 95%. These

curves demonstrate the characteristics of protein intake-response relationships of each

trial (fry and fmgerlings).

Slope factor (0)

The kinetic order resulted in a sigmoidal (n > 1 ) shaped curves for both trials .

50

Ordinate intercept, b

The dietary nutrient (protein) response to zero feed intake level demonstrated that fish

was sti ll growing (depositing protein from other source). The only protein source was

microorganisms from the culture water.

a) 1r=0

This parameter represents the nutrient (protein) intake at zero response, the

maintenance intake level . 1 r=O value was not present in both trails because fry and

fingerlings grew at zero protein intake level . That was because presence of micro­

organisms in water, low stocking density and fish were eating parts of the dead fish as

a protein sources.

b) Emax

Emax represents the highest dietary protein (nutrient) converted to fish flesh. It

occurs at specific nutrient (protein) intake level which was lower level for the fry than

for the fmgerling. (Figures 1 0, 1 1 , 1 2, and 1 3) .

5 1

Table (5): E perimental Diets Composition and their Proximate Analyses as a percentage of the dry weigh

Component Diet Diet Diet Diet Diet Diet Diet Diet Diet Diet Diet Diet 1 2 3 4 5 6 7 8 9 10 11 12

asein 0.00 3 .75 7 .50 11.25 15.00 18.80 22.50 26.30 30.00 33 .75 37.5 40.5 elatin2 0.00 1.25 2.50 3 .75 5.00 6.25 7.500 8.75 10.00 11.25 12.50 13.50 extrin3 34.00 34 .00 3 4.00 34.00 34.00 34.00 34.00 34.00 34.00 34 .00 34.00 34.00

ish oil 6.00 6.00 6.00 6.00 6.00 6.00 6.00 6.00 6.00 6.00 6.00 6.00

inerals mix 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4 .00 4.00 4.00

�itarnins mix 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00

Ipha cellulose 54.00 49.00 44 .00 39.00 34.00 29.00 24.00 19.00 14.00 9.00 4.00 0.00

otal 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1 00.00

roxirnate analyses

'rude Protein 0 .00 4.12 8.30 12.00 17.02 2 l .05 25.86 27.07 33 .00 38.52 45.44 48.33 r�d fat 3 .81 4 .00 4.01 5 .84 5 .99 6.36 6.16 6.78 4.69 6.29 5 .58 6.75 otal Ash 7.09 7.02 6.73 7.48 7.60 7.83 7.31 8.29 7.36 8.41 8.89 8.47

1 • Casein soluble in alkali, Loba Chemie. India. Art 2570 2 .Gelatin powder for bacteriology, Loba Chemie. India. Art 3920

3 . Dextrine white, Loba Chemie. India. Art 3 164

52

Table (6): Mortality rate of Oriochrom is niloticus in both trials fmgerlings and fries experiments as a result of feeding the different semi -purified diets.

Dietary Percentage Percentage treatments of mortality of mortality Protein% III in fries

fingerlings trial trial

0 93 .3 79.2 5 66.7 95 .8 1 0 30 .0 70. 8 1 5 1 6 .7 29.2 20 6 .7 1 6 .7 25 0.0 8.3 30 3 .3 1 6 .7 35 6 .7 1 6. 8

40 1 0 .0 0.0

45 3 . 3 0 .0

50 1 3 .3 4 .2

54 20.0 4 .2

53

Table (7) : Moisture. Protein and fat as percentage of fmgerlings' body composition.

Protein in Diet % Moisture % Protein % Fat %

0 80.4 69.6 -

5 74.2 66.3 -

1 0 8 1 .3 63.9 7 . 1

1 5 79.7 69. 1 1 0 .5

20 79.2 68.4 1 3 .0

25 78 .6 65 .8 1 6.6

30 79. 1 64.7 1 7 .5

35 79.3 68.9 1 5 .3

40 77 .9 65. 1 22.0

45 78 .5 66.2 2 1 .7

50 77 .7 66.3 2 1 . 1

54 78 .2 62. 1 26.6

54

Table (8) : The calculated parameters b) YST AT for the relationship between daily protein intake and fingerling daily weight gain. (Fingerlings)

Iteration H istory No Loss is �RMAXiK iN o 20.66�0.00Q50.00Q5.00Q1 .00C ....... ·· · · ····· · ····; · · ··· · · · · ·· i··· · · ···· ·· · · ·i· ··· ·· · · ·· ·; ........ � .;, 1 1 2 .856:'O.531 40.88�3. 1 5611 . 1 O;.J 2····· :;·1·:·8S·1·�·

.·9713·9·

.·745h .. :;·1· 1h : ·1 ·S�1 3····· :;·1· : ·85�o·:9·1·614·o·.·650'i·234H·

: 1·6� . . . . .. . . . . . . . . . . . . . . . } . . . . . . . . . . . ( ....... .. . . . .. , ..... ..... . ( ....... . . . . . 14 1 1 .868P.92T,'40.46�3.2 1CJ,1 1 7q • • • . . . • . . . . . . . . . . . . . . , . . . . . . . . . . . ! ....... · ·· · · · · I ·· ······· ··�··· ....... . .

5 1 1 .868�0.92440.53�3.21 S.1 . 1 681 5

···· :;·1·:·86·8,h .. 925i4·0:·5·1·�i·2·1·�1

·:1·6� : :i···· :;·1··.·86·�h .. 92;Mo·

.·52d,i2·1·i1·:1·681 ....... ·· ··· · · ·· ·· · · ·1·· · ····· ···,······· ·· · · · · · 1 · · · ........ ( ..... .. . . . . .

8 1 1 .86@.924'40 5 1 8�3.2 1 7:1 . 1 681 · · · · · · · · · · ···· · ·· ····j··········.i ......... . . . . . j ........... , .. . . . . . . . . ;,1 9 1 1 .868p.924140.5 1 9\3.2 1 7]1 . 1 681

Iteration History Dependent Variable : F INGE_G

F INGE_G means weight gain of the fingerlings

Isum of Squares and Mean Squares Source iSs �df lMean Squares Regression 12589.0034 1647.251 Residuai···· · · · ······ · 1··1··S68·····1s··11·:4s·4··· · · · ............. .

iT·ot·ai······················1250o:8i�1·�······· · ·· · · · · .......... ...... .

M·ea�··co·r·re·ctec 856486··

:1··11

········ · · · · ···················

Sum of Squares and Mean Squares R-squares

R-squares

Raw R-square ( 1 -ResidualfTotal) : 0.995 Mean Corrected R-square (1 -ResiduaIlCorrected) : 0.986

R-square(Observed vs Predicted) : 0.986

Parameter Estimates Parameter Estimatel ASE iParameter/ASEWald 95% Confidence Interval

l ! r········

Lower········r········iJ"ppe·r··········

B 0.924 � 0.975 � 0.948 - 1 .324 . 3. 1 72

· ••• ��� ••• ·. �":?�'tl��8n··.···· ••• lni ••••• • r �jir ••••••• i Y{il ... Parameter Estimate

55

Table (9): The calculated parameters by Y TAT for the relationship between daily protein intake and fries daily weight gain. (Fries).

Iteration History No. Loss B RMAX K j N

. . . ... . . . 9. .... . . .. . .. . . .. . . �:.�§� . . . . . . .. . 1 . . . . . . . . . 9 ... q9..9. . . . . . . . .. i .. . . . . . . .... �.:9.9.9 ........ . . . . . i . . . . ... . . g:?g.g . . . ....... �. : .q9.9. 1 0.695 : 0.694 : 3 .425 � 0 .51 0 �1 .46 1 •••• ·.· E .· ].���.. I ··.1��F [ ••••• ]·��� •••• • ••• ·.·.I · • • ·. �;;�� !1 •• ��; 4 0.669 � 0.668 : 3 .2 1 3 � 0 .451 �1 .402 .... . ... . . . ..... . . .. . .. . . . ... . . .. . . .. ... . . ......... . ) . . .. ........... . ..... . . ....... . . ) . . . . . . . .. . . . ...... . . . . . . ... .......... ( . . . . . . . . . . . . ............ . . . . ... . , ............ . 5 0.669 : 0.676 : 3. 1 52 : 0 .436 :1 .453

:::::::::�:::::::: :::::::::9.;���::::::::T::::::::9.;���:::::::::I::::::::::::�;?9.f.::::::::::::C::::: ::q:·:�F�::::::::::lj:;�9.� 7 0.669 : 0.675 � 3. 1 59 : 0.438 :1 .448 · · · · · .. ··8········ .. ·· · · · ..

0:669 .. ·· · .. ··

1· .. ··· · ..

0:6·70

··· · · .. ··1· .. ···· · · · · ·

3·:20j

····· .. ·· · · ·j· · · · · · · · · ·

6 .. 44·8···· · · · · ·

j1·:4·1·3

;9� � li! l � !�� I ]lJ[ 1 � ;U ji �i� ........ � ·� ...... ·I ...... · .. 6:��� . . . .. . . . ·t .. . . . . . . ·6��i} ...... ·t .......... ·}�·i} . . . . . . . . . . T ........ ·6·�11� .......... 1·�·�:j� ::::::::i�::::::: :::::::::9.;���:::::::::I:::::::::9.;�j:f::::::::r::::::::::�j:��::::::::::::r:::::::::q: .. ��:$::::::::::jj:;�?? ........ �.? . . . . .. . ... . . . . . . . 9.:.?§� .......... ; ....... .. . 9.:§?� ... . . . . . . J. . . . . . . . ... . . �.: .�.?? . . . . . . . .. l . ........ g:.�.�.? . . . . . . . .. . l.�.:��?

1 6 0 .669 : 0.67 1 � 3. 1 9 1 � 0.446 �1 .424 ··· .... ·1·7·· · · · · · · · .. · .. · · ·

0:669 .. ·· · · · · ·

1· · · · · · · · ·

0:673··· · · .. ··

1·· · · · · · · ....

3·:·1·78

···· · · · · · · · ·)' · · · .. ·· .. 6 ..

44·2 .. · .. ·· · ..

h:434 ···· .. ··1'fj

·· .... · · .. ·······0:669

.. ··· · · · ·1·· · · · · · · ·

0:672·········

1· · · · · · · · · · · ·

j:·1·89

··· · · · · .... ·r··· · · · · · ·

ii44·S· ...... ···

)1·:425

::::::::):�::::::: .::::::::9.;���:::::::::r::::::::9.;�j�:::::::::I::::::::::::�:;:�:!�::::::::::::l::::::::::q:;���::::::::::!};��� 20 0 .669 : 0.672 : 3. 1 88 : 0 .445 :1 .426 · · · . . ···2·1· .. · .. ·· . . ·· · · · · ·

0:669··· · · · · · ·

1·· . . ··· · ·

0:' (373

····· · ···1 . . · .. ··· .. ··

3·:·1·80

· .. · · · · .... ·j· · . . ···· . .

6 .. 443·· .. ······

j1·:432 • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • 0) • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • ) • • • • • • • • • • • • • • • • • •• • • • • • • •••••••••••• c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ( . . . . . . . . . . . . .

22 0 .669 : 0.672 � 3. 1 87 : 0.445 : 1 .427 · · · · · · · ·2·3··· · . . · ··· ·· · · · ·

0:669···· · · · · ·

1· · . . ··· · ·

0 :6·73

······ · ··1·· · · · · · · · · · ·

3·:·1·8·1"'

···· · · .... :-········ ·

6 .. 443···· ......

]1·:43

·1·

::::::::?�::::::: :::::: : : :9.;���:::::::::I::::: : : : :9.;�!?:::::::::r::::::::::::�:;I�(::::::::::r::: : : : :::q:;��A:::::::::lj:;�?! 25 0.669 � 0.673 � 3. 1 82 � 0.443 �1 .431 · · · · · .. ·26

· · .. · · · ·· .. ··· ··0:669

···· .. · .. 1· · .. · · . . ·

0:672 .. ··· · · · ·

j· · · .. ··· · · · ·

3·:·1·86

· .. ··· · · · .. ·1'· · · · · · ·· ·

0' .. 44

·4· .. · .... ··

)1·:428 .. ... .... . ... ....... .. . . . . . . .. . . . . . .. . . . . .... . ..... . 0) • • • • • • • • • • • • • • • • • • • • • • ··· · · · · ·· ·) · · · · · · · · · · · .. • • • • • .. • • • • • • • • • • • • • • .. ·c .. ········ · · · · · · · · · · · · · · · · · · · · · ·c ·· .. ··· · · · · · ·

27 0.669 : 0.672 : 3. 1 82 : 0 .444 :1 .431 :::::::�:�::::::: :::::::::�:���::::::::T:::::::�;���:::::::::F:::::::::f�:��::::::: : :: :+::::::::�:j:::::::::::::l{1�� ....... '

3'0 ....... ·········

0:669·· · .. ··· ·

1· · · · · · .. ·

0:672··· · · .. · ·

r· ...... ·····

3:·1·85

···· · · · · .... r·· · · · · · · ·

6 .. 44·4··· · · · · · · ·

j1·:428 .................. . . . . . ... . . .. . . .... .. . . .... . . . .. .. . 0) ... . . . . . . . . . ..... . . . . .. . . . . ..... ) ............................. ········c· · · · ······· · · · · · · · · · · ·. ·········c· .... ······ ..

31 0.669 : 0.672 : 3. 1 83 � 0 .444 �1 .430 · · . . · · · '32

·· .. · · · · · · . . ·· . . ·0:669

···· · · · · ·1"· · · . . ··

0:672···· ......

[·· .. ······· ·

3·:·1·85

··· · · · · · · · · ·:- · · · · · · · · ·

6 .. 444··· .. ·· · · ·

]1·:429

: .. ::::.�� ... :. :. :: ::: : :·:��;,;,[::: ::I . : ::::l;,;r: .::I: . .

··: : .:::�:�}��:.: .. ...... I·

: . . :]:�;;;.:.:: . . -]{;�� 35 0.669 : 0.672 : 3. 1 83 : 0.444 :1 .430 .................... ....... .. .................. ..... ;-........................ ···· ·· ·.,.····· · · · · · ·· · · · · · · · ·· · · · · · ·· · · · · · · .. ·c········ .......... . . . . . . . . .. . . . . { ............ . 36 0.669 � 0.672 j 3. 1 85 : 0.444 :1 .429

::::::: :�:�:::: : :]:::::::::�; ���::::::::r:::::::� :���::::::::r::::::::: :�: �:�:�f:::::::::T:::::: ::�:j1f::::::: lr1�� ::::::::�:$.::::::: .:::::::::9. ;���::::: ::::I::: : :::::9. ;�j?:::::::::!::::::::::::�:3�{:::::::::::r::: : ::::§;���::::::: : :: lj:;�?�

40 0.669 � 0.672 : 3. 1 84 � 0.444 �1 .429 ·

: ... ::.�{::·· .... :::: ::

·

� ·;,;,�::::::::T::: .. : :�·;,;�:::: ... . :F:::::: .. I}�;.:: .. :: .. J .. . . . :.:J.;;;: . . : .. :J{;�� 56

Iteration History No. Loss B RMAX K N 43 0.669 i 0.672 3 . 1 84 0 .444 11 .429

· · · · · · ··1:::::::: ,:::::::::�����:::::::::r::::::::�����:::::::::1::::::::::::ft�f:::::::::T::::::::�:j11::::::::::rri�� . . . . . . ... . .... . . . . . . . . . . . . . .. . . . . .. . . . . . . ... .. . . . . . ..... . .. ... . . . . . . . . . . . . . . . . . . . . . . . . -> . . . . . . . . . . . . . . . • . • • • . • . • • . . . . . . . . . . . • ( . . . . . . ......•... . . . . . • . . . . . . . . . . , • • . • . . . . . . . . .

�i l � iii t lit� l i jii l tm \jm :: .. ::::�:Q::::::: :::::::::9.;§§�::::::::T::::::::9.;§j?:::::::::I::::::::::::j;:�:��:::::::::::T::::::::q:;��A:::::::::n:;�?� Maximum number of iterations exceeded . Current estimates suspect.:

Iteration History Dependent Variable: Fries Response Weight Gain.

Zero weights, missing data or estimates reduced degrees of freedom

Sum of Squares and Mean Squares Source SS id(Mean Squares

.... ��.�:.�.��!?� .... �.�:.�.��j.�.l . . . . . . . . . �.�.:�.�.� .. . . . . ..

Residual 0.669 [ 7 1 0.096 · · · · · · ·· . . T�tai .. · · · · · . . · f46

.

·s·6711·11 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·

Me�·n · ·co;�e�tec · ·5:437'11·0,· · · · · · · .... · · · · · · · · · · · · .. · · · · ..

Sum of Squares and Mean Squares R-squares

Raw R-square ( 1 -Residual(fotal) : 0.984 Mean Corrected R-square ( 1 -ResiduaI/Corrected) : 0 .877

R-square(Observed vs Predicted) : 0.877

Parameter Estimates Paramete�Estimat� ASE iParameter/ASEiWald 95% Confidence Interval

j j f . ....... Towe·,:· · · · .... T · . . . . . . ·U'p·per · . . . . · · · ·

B 0.672 �0.285. 2.350 . -0.004 . 1 .349

:::::�:��:::: ::::��:�:��::::1�:;�:�:q:::::::::::#.;:�:�:�:::::::::::l::::::::::��;���:::::::::l::::::::::�f��:::::::::: K 0.444 !0 .41 O, 1 .084 [ -0.525 � 1 .41 3

.. · · · · · · · ·N .. · .. · · · · · .. ·1 ·

.

. 429· · · ·11· .. 1·2�· · · · · · .. · · · ·1· :26·9· · · · · · · · · · ·i· · · · · · · · · ·�·1·:23·3 · · · · · · · .. ·[ · · · · · · · · · ·4:0·9·1· · · · · · · · · · ·

Parameter Estimates

57

Table ( 1 0) : The calculated parameters by Y TAT for the relationship between dai ly protein intake and dail) protein deposition.(Fingerlings)

Iteration H istory No Loss is iRMAXiK iN o 0.31 3P.000j4.000 �3.20Oj1 .00C 1···· ·· 0:"365Io"."i:i25.3":S·62·Y2 :S441··.·'·OC � . . . . . oj6210·.·08d2·:s·i2·1·'·:74·i�'·jss 3····· 0:'1'!�j4�':1'07�':S'32'f1':94'�1':'57E' � . . . . . 0:·1·9·3i0·.·1·0�i·:i8S·h:8S·i,1·.·64·(· 5·· ··· 0:·,·g·310·.·1·01�·:s·'·4·F:91·�'·:·6·1·S � .. . . . 0:·'·9316.·1·0�·"S·02··'f'·:96311·:·62·g 7·· · · · 0:','g'3[0" 1'02!2'''S'07'h:968[1':'624 8···· · 0:·,·g·3iO·.·1·02�·"S·05·h:966i1· ·.·62E g"'" 0:·,·g·3i0·.·1·021i .. s·06·F:96f1··.·62·5 1'0" 0:·,·g·310·.·1·02�· .. s·06·h:96�1".·62·E 1" ,'" 0: ·,·g'3!0.·1·02!2·"S·06· I,':96i[1':'62E 1'2" 0:·,·g'310·.·1·02�· .. S·06·r,·:9o·i11·:·62·E 1'3" 0:·,·g·3i0·.·1·0�· .. S·06·F:90·f1··.·62·E 1'4" 0:-1'g·31i:i· .. 1·02�· .. s·06·f'·:9o·�1 .... 62·E

Dependent Variable: Fingerlings Deposition.

Sum of Squares and Mean Squares !source ss �d(Mean Squares

�.��.�.��.���.� . . . . . ... �.�:.�.�� . . . l�:.!�! .. . . . . . . . . . . . . .... . . Residual 0. 1 93 �8 �0.024 rroi�'i " " " " " " " " " '" 23'.

·182!1·21 .. ····· .... ·· · · · ······ ···· .. ···

Mea·n·co·��·ecte� 8:600 .. 1'1·1·:· .. ··· · ·· · · · · · · · · · · · · · · · · ···· · ·

R�quares

Raw R-square ( 1 -ResidualfTotal) : 0 .992 Mean Corrected R-square ( 1 -ResiduaI/Corrected) : 0.976 R-square(Observed vs Predicted) : 0.976

Parameter Estimates Parameter EstimateEASE iParameter/ASElWald 95% Confidence Interval

1 1 (Cowe';:"""'"''''''''''iUpp'er''''''''''''''''''' B 0. 1 02 !0. 1 0ao.939 �0. 1 48 \0.352

���:::::::::�:.:�?�:::::::!�:.:�:!.��;��:�:::::::::::::::::::::H::��:�::::::::::::::::: ::::F::�:�:�::::::::::::::::::::: K 1 .907 !0.583.3.272 :0.563 !3.251

N·· . . ·· . . ··· .... · . . · 1· .. 626··· ·····b .. s·0$3:219·· .. ··· .... · ···· · . . ···10·.461 ···· · · .... ······· · · · · ·(2:·ig·0 .. ··· · ····· ···· · .....

Parameter Estimates

58

Table ( 1 1 ) : The calculated parameters by Y TAT for the relationship between daily protein intake and tries daily protein deposition.

� istory No. Loss �B iRMAX �K iN

q .................. q·:9.�}········· .. ·······p:9.9.9. ... . . . . . . . . . . ......... i?:99.q ....................... j�:.�9.q .... . . . ............ !.�.:.q9.9. J . . ..... . . ..... .. . 6·��6�··········· .... ·· .. 16:66� ····· .... ··············:6

�·l-��·· .. · .... ····· .. ········ !6·

:�6i ········ ··········l�·

:·�6�

1 1 !li io�J! il!I ]I III I! 111 s·· .. · .... ··· .. ····

iio01 .. ·· .. ······· .. ·· ..

1�6:01·fi· .... · .. · .. ···· .. · ..

ro:j4·9 .. ·· .. · .. ······· ........

16:'272······· ...... ·· ....

1'1':959

ri •••• · •• ·· •• �.��r •• ······•· •• t��n •••••• · · •••• ··.�.m •••• · ·· •• · •••• ·· ••••• �.n� ••••• 11 11� . . . . . . . . . .. . . . . . . . . . � . .. . . . ... . .... . ...... . . . . . .... ( ................................... .: . ... . . . . . . . . . . . . . ····················1········· ...................... ; . .. . .. .. .. . . . 1 2 0 .001 1-0 . 020 10 349 :0.272 �1 .958 .. . ...... .......... . .. ..... .. .. . .... . .... . ...... ... , ...................... ............. � . . . ................................. , . . . .. ........... . . . ... .... . .... ( ... . . .. .. .. . . 1 3 0 .001 1-0 .020 �0 .349 �0.272 11 . 957

�}.:.: .. :: : .:: : �·���F:::·:::: : :·

·

:J�]�{ .:·. : :.::::::::·]��:�;:r·:·: ::: : .. :::::::.J���n::::: .. : .. ::: . . ']�]�;,

1 6 0 .001 �-0 .02 1 !0 . 349 10 .271 !1 .956 1·1'· .... · · . . · . . ··

6:001·············· . . ···

�6:02·1' .... ·· . . · ........ ···

fo·.'34

·9· .... ·· ...... · .. ······ ..

:6:'271··· .. ··············

11':955

1·8········ .. ·····

6:001···················

1�6:62·2·················· .. ·

ro·.'34

·9············ .. · .. ·······

16:'271···················

]1·:955

�:�::::::::::::::: q:;9.9.I::::::::::::::::::t.q:·:9.??:::::::::::::::::::::lq;:���::::::::::::::::::::::::lq:;?!�:::::::::::::::::::r�:;��� �O 0 .00 1 1-0.022 !0 .349 10 .271 11 .954 .............. . . .... ············· ·· .. ·· .... ······ .. f·········· ....... . . . ........... . . .. y .. . ......... ... . . . ...... .. . . . . . . . . . . I . ... .......... . ........ . .. . .... c . . . . . . . . . . . .. � 1 0 .001 �-0 .022 10 .349 !0.271 11 . 953 �f.· ••••••• · • •• §. ��F ••••• ·.. n ��f ·.·. ] •• ��� ••• ··· • •• · •• • • • · ••• ·.··.I§..��� ••••••• �. ]H�� 124 0 .001 �-0 .023 �0 .349 �0.270 �1 .952 2·5···············

6:001 .. ·· .. ·· .. ···· .. ···

1�6:02·3· .. · .. ············ .. ·

ro:'3·s·o·········· .. ········ ····

:0:270·· .... ········ .. ·'

1'1·:·95

·1·

�·r·::. : :

·

::.:. �: ·��F .. ·

: .. :: .. :::J�.·��·f: ::

·

::::·

.:·

: :·::::�. :�:�·� .. ·:·

::·:·

: : : .. ::: .. :.J� .. �;�.: .. :· : .. ::.::::Jr��t 28 0 .001 �0.024 �0. 350 !0 .270 �1 . 950 �.' ................. ............................... , .. . ......... .... . .. . .. .. . .... . . . . . . " .. .. . . . . . . ....... . . .. . .. .......... . . , . . . . .. . . ... ... ..... . . . .......... . ........ . . . . 29 0 .00 1 �-0.024 !0. 350 �0 .270 !1 . 949 �.' . . . . . . . .......... . . . . . . . . . ...................... I . ............. . . ....... .... . . ...... (, .......................... ........ ··1·· .. •••·····• .. •·· ·•• • · .. ······(···· .. ••••••• 30 0 .00 1 !-0.024 10. 350 !0.269 �1 . 949

li ] ��1 1� ��� : �U[ !� 11I !1 i;; 34 0 .001 1-0 .025 10 .350 10.269 �1 . 947

Ir J��j J� �[[ J� li� �m lj i�! 3'9'" 0.001 1-0 . 025 10 .350 !0.269 �1 .945

��::::::::::::::: g;��F:::: ... :· : : .. ·J� .. ���·:·

.... : :·:::::::·

]�::�·�·�·:·:·: :.:::: .:: .. :::·J�:·�;.r . ::::·:::: .. J{·�;;, . . ·2· .. · ... . · ......

0"001 LO.026 !0. 350 !0.268 �1 . 944

�E ·· §. ��1 .·: 1�;��� •••••••••••••••• ]� �;� ••••••• • ••••••••• • •••••• �.��t·· ...... · . . · ...... :1.�;� 59

History No. Loss [8 �RMAX \K \N 45 0.00 1 �0.026 \0.350 [0 .268 h .942 �'6 .. . . ... . .. . . . . 15:001· · · · · · · · · · · · · · · · · · ·�15 ·02·6· · · · · · · · · · · · · · · · · · · ·"f(i ·j·s·o· · · · · · · · · · · · · · · · · · · · · · · ·1o·268· · · · · · · · · · · · · · · · · ·\"1·: ·942 �'7 .... ... . . . . . . 6 ·001 · · · · · · · · · · · · · · · · · · ·�·15 ·02·6 · · · · · · · · · · · · · · · · · · · ·rCij·s·o· · · · · · · · · · · · · · · · · · · · · · · ·l15:268 · · · · · · · · · · · · · · · · · ·\"1": ·942 �:�::::::::::::::: �:����:::::::::::::::::T�:���r::::::::::::::::::r��:�:��::::::::::::::::::::::J�::���::::.:::::::::::::l{�:� 5'15 · . . . . . . . . . . 6 ·061 · · · · · · · · · · · · · · · · .. \15:02·i· · · · · · · · · · · · · · · · · · · ·To·

.

"3·s·0· · · · · · · · · · · · · · · · · · · · · · · ·\6:268· .... · · · · · · · · · · · · ·\1·: ·94 ·1·

Max·fmum· ·nu·mbe;. .. of· ·fi�ri3t"io·n ·s·exc·eed�d·: .. C"�·rren·t . . e·sti·�ai·es· ·sus·p·ecd· · · · · · · · · · · · ·

Dependent Variable :Fries _Deposition Zero weights, missing data or estimates reduced degrees of freedom

�um of Squares and Mean Squares !source SS \<!f,Mean Squares Regression 0.578�3 D. 1 93 .J. R·es·

i·du·ai· · · · · · · · · · · · · · 0·:0"0 ·114·\0:000· · · · · · · · · · · ·· · · · · · · 1

ffota·{ · · · · · · · · · · · · · · · · · · · · · 0":5·i�i ·\· · · · · · · · · · · · ·· · · · · · · · · · · · · · · · · ·] Me·a�· ·correct·ec 0":0"1·016 '1' · · · · · · · · · · · · · · · · . . · · · · · · · · · · · ·1

Sum of Squares and Mean Squares

R-squares

Raw R-square ( 1 -ResidualfTotal) : 0.998 Mean Corrected R-square (1 -ResiduaI/Corrected) : 0.907 R-square(Observed vs Predicted) : 0.907

Parameter Estimates ParameteriEstimat�ASE �Parameter/ASEWald 95% Confidence Interval

1 1 [Cowe·;: . . . . . . . . . . . . . . . . . . ·[upper· . . . . . . . . . . . . . . . . ..

B 0.027 [0.429-0.063 �1 . 2 1 9 \1 . 1 65

lli�: •••••••• i-in ••• r�!l?��§": .·· ••• ··.··... �o�IE ••••• · ••• ···��!.� ·.· .•...••••••••... Parameter Estimates

60

Table ( 1 2) : The calculated parameters by SY TAT for the relationship between daily protein intake and daily fat deposition. (fingerlings)

Iteration History No Loss l B lRM� K N

o 0.31 Z 0.000 : 2.000 :4.500.1 .000 ....... · · · · · · · · · · ·:············· :· · · · · · · · · · · · ·i· · · · · · · · · · ·� . · ... . . � .;;

1 0.065.-0.0n 2.940 :9.71 n . ool. " 2" 0·

.. 02':�·0:·067l·2j)4Ci\s·:S·7�·1·:26·4· • • • • • • • · · · · · · · · · · · ,······ ••••••• 1 ••••••••••••••••••••••••• .,:. ••••••• � .;...

3 0.0 1 9j-0.023: 2.935 j8 .87311 .20::; . ..... . . ... . . . .... , . ....... .. . . . , . . . . ... . . .... ( ........... * .... . . . � .;:., 4 0.0 1 9j-0.026i 2 .776 j8 .301 j1 .20l:l

" 5" 0:·0·1·i.·O:O:;·�·2j76·ls·:2·0g;1·:2·3·6 " 6" 0· .. 0·1·��·0:02·�·2· .. 62i\7:6·92j·1·:23·6 " j" O·:0·1·�:·0:·0:;·�·2· .. 62i1i:6·22h:26·2 " s" O· .. 0·1·��·0:O:;·�·2· .. 50i;7·:2·1·d,1·:26·2 . . . . . .. . . . . . . . . . .. , . . . . . . . . . . ... , . . . ..... . . . . . , . . . . . . . . . . . � . . . . . . . ; .;. .

.. � . . �:.�.�.�.�:.?�.�.?:.��!..?:�.��1�.: 3.�.�. 1 0 0.01 &-0.01 3i 2.262 16.245.1 .321 . .... . . . . . . .... . . . : ........ . . ... : . . . . ..... . . . . ; ........... � ..... . . ; .;: 1 1 0.01 8:-0.007: 2 .259 :6 .245:1 .340 .. .. . . . . . . . . . . . ... , . . . . . .. . . . .. . , . . . . . . . ... . . . ( . . . . . . . . . . . � .. · · · · · r ·;; 1 2 0.01 8�0.0071 2 . 1 1 5 j5. 725,1 .37,j

······· · · · · · · · · · · · , . . · · · · · · · · · · · , · · · · · · · · · · · · · 1 · · · · · · · · . . . -:- ... . . . . :.;;..:

1 3 0.01 8:-0.00Z 2 . 1 1 3 :5.725.1 .391. ....... · · · · · · · ···· ; ············· ; · · · · · · · · · · · · · i · · · · · · · · · · ·�· · · · · · · i ·;; 1 4 0.0 1 8:-0.00Z 1 .927 :5.075.1 .43J ':;'5' O'

''O'1'S\'O'

''00s'\','''S33'\4:i77i1':49'S

':;'6' 0'"0'1'8:'0'''00g'1','''8'1'6'14:7'2711':5:;''' . . . . . . . · · · · · · · · · · · . · · · · · · · · · · · ·· , · · · · · · · · · · · · · ( · · · · · · · · · · · 0 · · ........ . 1 7 0.0 1 8: 0.009 : 1 .809 :4.704.1 .5 18

....... ···········; ·············; ·············i· · · · · · · · · · ·�·· . . . . . ; .;; 1 8 0.01 &. 0.009 : 1 .808 :4. 70t1 .5 1 l:l . . .. ... . ... ... . . . . ; .. . ... . . . . . . . ; . . . . ... . . .... : . . . . . ... . . .. : . .. . . . . . ; .;: 1 9 0.01 8: 0.009 : 1 .808 4.701 :1 .5 1 ;: . ... . . . . . . . .. . . ... : . . ... . . . ..... : . . . ... . . . .... , . . . ... . . . . . :. .. ..... ; .;; 20 0.0 1 8j 0.009 � 1 .808 ?4 .70!Y,1 .5h '2'1" iO'''0'1'8;'O'''oOg'1','''8'os'14:iod,1': '5,'E' ....... · · · · · · · · · · · j · · · ......... . J . ...... . . .... t ........... ':' . . ..... ; ';.: 22 0.01 81 0.009 j 1 .808 14 .700,1 .51 ;:

Dependent Variable :F I NG_FD Zero weights, missing data or estimates reduced degrees of freedom

Sum of Squares and Mean Squares Source SS �df�Mean Squares

Regression 2.597j 4 j 0.649 ... . . . . .. . . .... ... . . . .... . ..... . . .... . . . . . . , . . . . . ) .... . . . . . . .... .. . . . ......... . . . Residual 0.01 a: 6 : 0.003

............................... . . . . . . . . . . . . j • . . . . ; .. . . . .... . . ............. . . . . .. . Total 2 .6 1 5j1 Oj

�iea�··co·��e·cte·c 0 :941 : ·9· ·[ ··

· · · · · · · · · · · · · · · · ·············

Sum of Squares and Mean Squares

R-squares

Raw R-square ( 1 -Residualrrotal) : 0.993

Mean Corrected R-square (1 -ResiduaI/Corrected) : 0.981

R-square(ObseNed vs Predicted) : 0.98 1

6 1

Parameter Estimates

Parameter Estimatel ASE �Parameter/AS�Wald 95% Confidence Interval � � r····· .. "[ow·er········r·······Uppe·r··· · .. ····

.......... � .... . . . . . .. . . �.:�.�� ... !.�:g.?:.� . . . . . . . . . . . �:.:�� ........... : .......... ��:.�.�� .. . . . . . ... : ........ . . g:.�.�.� ... . . . . . . . . RMAX 1 .808 � 1 .265 � 1 .429 � - 1 .288 � 4.903 I

··········K········· ·· .. 4·:ioo···j4·.·046·j·· · · · · · · · · ·1·

.

·1·62····· · ····1··· · · · · · · ·�5·:1·99 .... ·····r······· ··1·4:60o···· · · · · ·1

.. · .. ·· · · ·N .. ······· ·· ··1···S·1·9· .. rO:·6·S·S!···· .. ··· ·i:·3·1··9· · .... ····r·······�·O·.·68·4·········I·· · · · · · · ·3:·1·i·1···········1

Parameter Estimates

62

45 r-------r-------r-------.-----�

36

o

R rn ax - - - - - - - - - - - - - - - - - - - - - - - -�� .,..---

.,.,-----

// • Data

5

Rrnax = 4 0 .5 1 9

K . 5 = 3 .2 1 7

n = 1 . 1 68

b =0 .924

1(j I ntake

1 5 20

Figure (6): Fingerlings growth (response) as a result of feeding (intake) the experimental diet. X axis represents daily protein intake and Y axis represents daily weight gain. The four parameters of

the saturation kinetic models are indicated.

63

4r-------�1--------,1--------�1--------� R rn ax

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

3 f-

Data -

R rn ax = 3 . 1 84 K . S =0 .444 n = 1 .429 b = 0 . 6 7 2 -

OL-------�I---------L-I------�I--------� 0 . 0 0 . 5 1 . 0 1 . 5

I ntake 2 .0

Figure (7): Fries growth (response) as a result of feeding (intake) the deferent semi-purified experimental diets. X axis represents daily protein intake and Y axis represents daily weight gain. The four parameters of the saturation kinetic models are indicated.

64

4 r-------.-------.-------�------�------� R rn ax

3

o 1

R rn ax = 2 .806 K . 5 = 1 .907 n = 1 .626 b = 0 . 1 02

2 3 I ntake

4 5

Figure (8): Protein deposition of tilapia fingerlings bodies (response) as a result of feeding (intake) the experimental diet. X axis represents daily protein intake and Y axis represents daily protein deposition. The four parameters of the saturation kinetic models are indicated in the graph.

65

2 .0 r-------.------,.-------�

1 5

0 . 5

R rnax

Data R rn ax = 0 .3 50

K .5 = 0 . 26 8

n = 1 .94 1 - - - - - - - - -�A - - - - - - ""6 -=-=--0 .027

O O LL--------�-----------L--------� o 2 3

I ntake

Figure (9): Protein deposition o f tilapia fries bodies (response) as a result of feeding (intake) the experimental diet. X axis represents daily protein intake and Y axis represents daily protein deposition. The values of the four parameters of the saturation kinetic models are indicated in the graph.

66

1 0 r------,�------,�-------�1-----�1----�

2 - -

o L-____ �I _______ L_I ____ �I _______ �I ____ � o 2 3 4

F I NG E_I T 5

Figure ( 1 0) : Efficiency curve for the growth response of Nile tilapia fingerlings as a result of feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the efficiency .FINGE _IT means the intake of fingerlings.

67

6 r-------r-I------.-l------r-I----�

O � ______ L-I ______ L-I ______ L-I ____ � 0 0 0 .5 1 0 1 .5 2 .0

I ntake F R_

Figure ( 1 1 ) : Protein efficiency curve for the growth response of Nile tilapia fries as a result of feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the efficiency. Intake FR_I means the intake of fries.

68

� u C

.� (,J IE

LU

6 r-----T�-----.�------�I----�I----�

4 r- -

2 f- -

//�� I I I O �----�------�------�----�----� o 2 3 4

I ntake F l t�G E 5

Figure ( 1 2) : Protein efficiency curve for the protein deposition of Nile tilapia fmgerlings as a result of feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the efficiency. Intake FINGE means intake of fmgerlings.

69

4 r---------.-�--------'�--------�

3 r- -

� <.> c <l> ' - 2 I­(,) -

IE w

- -

(�---------l -----·�--:--------I o I I

0 1 2 3 I ntake F R I E

Figure ( 1 3 ) : Protein efficiency curve for the protein deposition of N ile tilapia fries as a result of feeding (intake) experimental diets. X axis represents daily protein intake and Y axis represents the efficiency. Intake FRlE means intake of fries.

70

ISCUSSIO

Discussion

With regard to the experiments culture conditions it was found that the values

water quality parameters namely DO, pH, water temperature, and the total ammonia

nitrogen were within the recommended range for best growth rates (Boyed, 1 990).

Proximate composition values of the experimental feeds agreed well with the

estimated values. The basal part of the semi-purified diets agrees with the

recommended for 0. niloticus by Jauncey ( 1 998). Additionally, detenmned values of

crude protein content of the test diets agreed well with our dietary formulation.

Fish survival rates were affected by the dietary protein level . Lower levels of

protein especially below reduced survival rates. Survival was significantly lower in

fish (both fry and fingerlings) fed diets with lower protein levels especially those with

proteins from 20% to 0% protein. Generally, fry had lower survival rates than

fmgerlings. These results agreed well with Fiogb' et al. ( 1 996). Survival was lower

than 35% when fingerlings fed diets with 0% and 5% protein diet and fries fed diets

with 0%, 5%, and 1 0% dietary protein. High variability of survival at first-feeding is

frequently reported : e .g. 1 8-32% in perch and trout with low protein diets. (Falk­

Petersen et aI ., 1 999; Nankervis and Southgate 2006).

Body composition of fries and fmgerlings tend to accumulate more body fat with

higher dietary protein intake. The percentages of body fat were increased with

increasing body protein. This is in agreement with Dias et al. (2005) when they used

European sea bass as an experimental animal . Fish utilizes part of their dietary protein

as an energy source and reserve in a form of body fat. In other words the more dietary

protein in fish diets the higher the body fat. Additionally, each species of fish needs a

certain ration of protein to fat in their diet (Table 7).

7 1

G rowth a n d P rote in Req u i rements

Rmax Or the maximum theoretical response values were higher in fingerlings trail

as compared to the fries trai l . That is because fingerlings (larger fish) grow larger

whi le fries (smaller fish) grow faster. While calculation of dietary protein

requirements for both sizes (dietary protein intake at 95% of the R level indicated max

that fries require 48% protein while small fingerlings require 42% protein. To my

knowledge, no study used the saturation kinetic model to calculate dietary protein

requirements for tilapia 0. niloticus. All studies used broken-line technique to

estimate the requirements which has inaccurate prediction of the requirements at

which the two straight lines meet. The saturation kinetic model, on the other hand,

estimates the most accurate protein requirement value. EI-Sayed and Teshllna ( 1 992)

used the broken l ine model to estimate dietary protein requirements for 0. niloticus

fry. They found it to be 45% for tilapia fry which is 3% less than that of our results.

On the other hand, AI Hafedh ( 1 999) and Teshima et al. ( 1 985a) using same broken

l ine technique showed that tilapia five times larger fry than that of our study to have

dietary protein requirements of 35%. This result is stil l inaccurate due the error from

the technique. Same thing happen to tilapia fingerlings protein requirements.

Teshllna et al . ( 1 982) showed that dietary protein requirements for tilapia fmgerlings

to 40% while our results using the saturation kinetic model to be 42%. Other studies

(Abdelghany 2000a and Wang et aI . 1 985) showed much less dietary protein

requirement for tilapia fingerlings (35% and 30% respectively). That was probably

because they used much larger fmgerl ings than that of our study.

72

As dietary protein requirements changes with fish time (fish size and/or age), an

accurate prediction of dietary protein requirement at any age or size could be achieved

using the saturation kinetic model by using nutrient (protein) intakes of the

requirement levels at their specific age and its responses. Then the non l inear curve

would be generated with the four predictive parameters and the dietary protein

requirements could be calculated for the specific fish species at any age.

K0 5 is an efficiency parameters. It is known that, the lower value of Ko 5 the

higher efficiency. Our results indicated a relatively lower K05 value for the fry than

the fingerlings. (Figures 6 and 7) This indicates that dietary protein utilization

efficiency for fry was as expected much higher than that of fingerlings. Our maximum

efficiency parameters indicate that very c learly (Figures 1 0 and 11). As fish grow in

size their feed utilization efficiency is gradually reduced (Azevedo et al. 2004).

Protein intake and deposition

Rmax The maximum amount of protein deposited (response) in 0. niloticus fries and

fmgerlings as a result of feeding graded levels of dietary protein. The fingerlings and

the fries were different in terms of their Rmax of protein deposition value (P <0.05).

Fingerlings had higher Rmax than that of the fry. This is because fmgerlings are larger

than the fries and can consume more protein intake and deposit more than that of the

fry. This is supported by Ko 5 values which indicate tilapia fries and fingerlings

protein intake at half maximum deposition was higher in fingerlings compared to that

of the fry (P <0.05). K05 is considered an efficiency parameter (the less it's value the

higher the efficiency). Therefore, the fmgerlings were less efficient in utilizing protein

73

than the fry. That was supported by the maximum efficiency values in figures (8 9

1 2 and 1 3 )

Restriction of an essential dietary component causes impairment of normal

physiological responses. If this component is added to the diet in graded level the

range of responses can often be predicted by the four parameter mathematical model

equation. The primary goal of this study was to show that the saturation kinetic model

(Morgan et al. , 1 975) can be used to describe 0. niloticus fry and fingerlings weight

gain and net nutrient (protein) deposition (Figures 6,7,8 and 9). These results

demonstrated that the physiological responses tested (dietary crude protein deposition,

weight gain) could be predicted by the saturation kinetics model . The response could

be calculated at any intake level using the model equation after estimating the four

parameters (b, KO.5, N, Rmax);

The second goal of thi s study was to use the model parameters to evaluate the

semi-purified Tilapia diets obtained from the U.S .A and Panama. There are several

possible methods of nutrient comparisons based on the four parameters of the

saturation kinetic model :

( 1 ) A ratio of response for specific nutrient source to the response for standardized

diet, at the same food intake level (Since there is no standard). 0. niloticus diet

and feed ingredients can vary in quality and composition.

74

(2) Comparison based on individual parameters such as Rmax. (the maximum

theoretical response) and/or Ko s (the feed or nutrient intake at half maximal

response)

(3) Comparisons based on derivatives of the model such as the maxlffiUlll

efficiency ( Emu ), the food (nutrient) intake at maintenance level on zero response

]r=O (Mercer et al. , 1 978).

The experiment provided model parameters for fry and growing small fingerlings

for further application. The model parameters are of fundamental importance to

continue studies and subsequent modeling for requirement for other individual

nutrients which is important for commercial diets for fish feeding. They can use the

method practically in making comparison of using different protein sources l ike fish

meal, cotton seeds and others with the semi purified diet used as standards. So the

method will have lots of applications in aquaculture farms since it is not expensive

and can give us standard values within short period.

75

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86

PEIIICE

A ppendix 1

About Tilapia

The name 'tilapia' was derived from the African Bushman word meaning 'fish'

(Trewavas 1 982). The word tilapias represent a great munber of fresh water fish

species within the fami ly Cichlidae. The genus Tilapia was first described by smith

( 1 840)(EI- sayed 2006). Later, it was split according breeding behavior and feeding

habits into two subgenera:

1 . Tilapia ,(substrate spawners).

2. Sarotherdon, (,brush-toothed')(mouthbrooders) .whlch incubate the fertilized

eggs and hatched fry in the mouth of the male or female parents or both male or

female. (El-sayed,2006).

The subgenus Sarotherodon, then raised to a genus and further subdivided into

two subgenera, Oreochromis(mountain cichlids) and Sarotherodon, according to

whether parental females (Oreochromis), males (Sarotheredon) or both parental

Al- Mohsen ( 1 998) mentioned that In spite of all revisions and changes in the

taxonomic classification of ti lapia, the confusion does not be eliminated. Because of

that, researchers stil l favor to use the old genus Tilapia for all tilapia species.

87

A ppendix 2

Feces and urine co l lection methods.

No Method Reference: Problem. P roblems' Causes

1 Dissecting the fish Belal,1987 Underestimation l . Mixing of incompletely gut after digested materials with

sacrificing the fish the body fluid, intestinal and collecting its epithelium and excess

fecal material enzymes. 2. Force feeding affects the

gastric motility. 2 Manual striping of Belal, 1 987 Underestimation 1 . Mixing of incompletely

live fish from the digested materials with abdominal cavity the body fluid, intestinal

to get a fecal epithelium and excess sample. enzymes.

2. Force feeding affects the gastric motility

3 Anal Suctioning. Windell et a1. Underestimation 1 . Mixing of incompletely 1978 digested materials with

the body fluid, intestinal epithelium and excess enzymes.

2. Force feeding affects the gastric motility

4 Collecting feces Windell et a1. Over estimation Leaching of dissolved materials deposited in 1 974 into the water.

aquarium using a fine dip net.

5 Siphoning the Buddington, 1 980 Over estimation Leaching of dissolved materials

feces using a into the water.

specially desighned aquarium.

6 Settling columns Cho et at., 1975 Over estimation Leaching of dissolved materials

attached to the into the water.

aquarium drain system.

Leaching of dissolved materials 7 The mechanically Choubert et aL Over estimation

rotating filter 1982 into the water.

screen. 8 The metabolism Smith, 1 97 1 Not accurate Stress caused by confinement,

chamber anaesthesia and force feeding leading to inhibition of absorption in addition to being the causes of hyperglycemia, elevates muscle blood lactate, serium cholesterol , skin mucus secretion, and oxygen consumption.

Adopted from (Bela1, 1 987)

88

A ppendix 3 Ho\ to apply aturation Kinetic Model in SY TAT. Figure (1 ),(2).(3)

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Appendix 4

Table 1 Daily weight gain and daily protein deposition of 0. niloticus as responses to daily protein deposition in trials fingerl ings experiments as a result of feeding the different semi -purified diets. In mg

Treatments Daily Daily weight Daily protein Daily fat (% of protein gain. deposition deposition

protein) intake 0 0 1 .68 0. 1 4 -

5 0.09 0 .72 0.08 -

1 0 0.28 2 .54 0. 1 5 0 .02 1 5 0.49 5 .07 0 .4 0 .06 20 0 .86 8 .54 0.78 0. 1 5 25 1 .07 9 .91 0 .94 0.24 30 1 .63 1 3 .67 1 . 1 9 0 .32 3 5 1 8 1 1 2 .99 1 .22 0.27 40 3.56 24.34 2.38 0 .80 45 3.24 1 9.89 1 . 95 0 .64 50 3 .38 20.36 2 . 1 2 0.68 54 4 .94 25.22 2 . 1 4 0 .92

Table 2 Daily weight gain and daily protein deposition of O. niloticus as responses to dai ly protein deposition in trials fries experiments as a result of feeding the different semi -purified diets. In mg

Protein Daily Protein Daily weight Daily protein

percentage in Intake gain deposition

d iet.

0 0 0.82 -

5 0.07 0 .39 -

1 0 0. 1 5 1 . 70 -

1 5 0.24 1 . 1 6 -

20 0 .36 1 .63 0 .2 1 25 0.47 1 . 1 0 0.26 30 0.58 2 .25 0.28 35 0.66 2.29 0.30 40 0.82 2 .36 0.30 45 0.88 2 .64 0 .34 50 1 .0 1 2 .53 0 .3 1

92

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