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United Arab Emirates UniversityScholarworks@UAEU
Theses Electronic Theses and Dissertations
2008
Evaluation of Nutrient (Protein) – Organism(Fish) Relationship Using a Saturation KineticModelZainab Sa'ad Beiruti
Follow this and additional works at: https://scholarworks.uaeu.ac.ae/all_theses
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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 [email protected]'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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89
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9 1
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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