Growth Modelling as a Tool for Predicting Amino Acid Requirements of Broilers12

01994 A p p l i i Poultry Science, tnc

GROWTH MODELLING AS A TOOL FOR PREDICTING AMINO ACID REQUIREMENTS OF BROILERS'J MILAN HRUBY, MELVIN L.HAMRE, and CRAIG N.COON3 Depattment of Animal Science, Universityof Minnesota, Saint Paul, MN 55108 Phone: (612) 6246263 FAX;.(612) 625-5789

Primary Audience: Nutritionists, Researchers, Broiler Producers

The growth and body composition of a broiler are affected by feed, feeding regimes, environmental conditions, stocking density, diseases, and other factors. Black [l] suggested that the factors affecting animalgrowth and the interactions among these factors make it impossible for the human mind to account for the potential variables. Production decisions to be made by a poultry enterprise regarding optimum management and nutrition

practices may be greatly supported by the use of simulation models. A simulation model predicts the behavior of a system as a response to a given treatment [2]. Before researchers produce a model, important decisions to be made include the choice of the system (eg., the flock of birds), the treatments to be simulated (e.g., environmental temperature, stocking density, and composition of diet), and the responses to be predicted (e.g., average body weight, amino acid requirements, etc.). The

1 Published as Paper Number 21,598, Scientific Journal Series, Minnesota Agricultural

Experiment Station Presented at the 1994 Poultry Science Association Informal Nutrition Conference Symposium: Poultry Modelling - Theoretical and Practical Evaluations 3 To whom correspondence should be addressed 2

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INTRODUCTION

404

EMPIRICAL AND MECHANISTIC MODELS TO DESCRIBE GROWTH Empirical models that can be used to describe growth are usually accurate and relatively easy to construct. They are easily incorporated into least cost linear programming systems to determine optimum diets for

feeding. The disadvantage of using empirical models is that the model describes only a mathematical relationship between a dependent variable and an independent variable without further explanation of the biological processes involved [16]. The Gompertz function and the logistic function are two frequently discussed empirical models [17,181. The logistic or autocatalytic [19] curve has the relative growth rate declininglinearly with increasingweight and is symmetrical around the point of inflection (POI). The POI is the place on the curve where the growth rate (dW/dt) is maximum [20]. The Gompertz curve is asymmetricaland inflecting at W = N e or 0.368A [191, where A is mature body sue, W is a weight at POI, and e stands for an exponential parameter. The Gompertz function is easy to use and fits data well for the posthatching growth of poultry to 0.8 of maturity [12]. In its pure form the Gompertz curve is empirical as it shows what maximum growth will be at any point in time with the provided nutritional and environmental conditions. Figure 1 shows the fit of the Gompertz, the logistic, and the polynomial function to body protein data [21]. The Gompertz function produced better results for the 19-wkbroiler study as determined by comparing the size of the residuals and coefficients of determination P11Because they combine the affects of dietary and environmental factors with knowledge about growth physiology [16], mechanistic models may help more than empirical models in our understanding of animal growth. Emmans [13] concluded that the Gompertz function is frequently chosen in mechanistic models for its mathematicalproperties, biological meaning of parameters, and its reasonable fit.

GROWTH OF BIRD Zoons et al. [16] described growth as a very complex phenomenon determined by both genetic and environmental factors. Emmans [13] mentioned that growth is made up of two components: normal growth (protein, ash, water, and some minimum amount of lipid) and fat growth (storage of lipid above the minimum). Emmans [22] stressed some difficulties in describing feather growth primarily because shed feathers are not present at slaughter

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validity of the model concepts should be tested by comparing predicted and experimental data. One of the first partition models developed was from the University of Reading as described by Curnow [3]. Fisher et al. [4] utilized the model to describe the expected flock response of laying hens to amino acid intake. Since the concepts of the model were reported, the model has also been utilized by Clark et al. [q and Gous and Morris [6] to determine the amino acid requirements of broiler chicks. The amino acid requirements determined by the "Reading model" are optimum flock requirements that maximize profits and are based on amino acid cost in relation to both product value and standard deviations of response parameters for buds in the flock. The initial modelling papers from Israel also focused on the amino acid requirements for laying hens [q;however, Hurwitz et al. [8] also developed a formula for predicting the daily metabolizable energy and amino acid requirements of growing chicks. In a later experiment Hunvitz et al. [9] validated the amino acid model by improving the performance of chicks fed diets formulated with model-predicted requirements compared to NRC formulations. In two experiments Tdpazet al. [lo, 111 continued the work of the Israeli group and combined Gompertz growth curves with previous coefficients utilized for amino acid and energy requirements. The Edinburgh growth model [12,13] was the first model to utilize projected Gompertz growth curves for broilers and partition the response to dietary energy and amino acid requirements. The FORTEL" models [14] for both broiler and turkey growth were built on the theory of the Edinburgh growth model. Most recently, Novus International, Inc. has developed a broiler growth model [15] called the Ivey Growth Model (IGM").

BROILER GROWTH MODELLING

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AGE (Wk)

FIGURE 1. Total protein weight of bled, plucked male broilers from 21.1"C treatment fitted to three growth functions [21]

and genotypes of birds may differ in feather OF growth. To solve this problem, Emmans suggested, based on data of Hurwitz et al. [B], that feather weight should be related to body The genetic potential variables of each protein in male turkeys. However, feather broiler genotype important to predict growth weight is not a simple power function of are the mature size of the bird and the rate at body protein of the growing bird [24]. llvo which the bird achieves this mature size [2q. phases of feather growth occur for turkeys Emmans [ 131 characterized a "genetic potenwith the change in slope at about u = 0.25 tial'' as a level of performance which will be [24], where u = coefficient of maturity. in a non-limiting environment. Thus, achieved Fisher [24] further suggested that a threeat maturity or final equilibrium state the aniphase model should be used for broilers. The mal seeks a rate of change of zero [14]. Table three-phase feather growth model derived 1 shows a description of maturity in terms of by Fisher [24] from data of Hakansson et al. chemical components of the empty body [14]. [25] was used to describe feather growth The mature protein weight (Pm) and the shown in Figure 2 [XI. Using these formulas Epidprotein ratio (LPRm) are variables degave an underestimation of feather growth scribing the maturity. from the Minnesota data; however, using Both Gous [27] and Emmans [13] advised proposed [24] shedding adjustments (+5%, that the components of the body at different 3-5 wk; +lo%, from 5 wk of age and up), stages of growth should be measured - not just the prediction of feather growth fit the body weight or body protein weight. The readata closely. Gous [27] described another forson for using chemical components is that the mula for feather protein weight of chicken composition of the lipid-free dry matter does broilers as: not change during development, but the lipid FPB = 0.250 BPm0.67 content of the growing chicken can be affected BPm = body protein at maturity where: by the composition of the diet. Furthermore, the water content of the lipid-free empty body

GROWTH PREDICTION BODY COMPONENTS

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data *Fitted

*Fitted

adjusted for sheding

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AGE (Wk) FIGURE 2. Male broiler feather growth (real data fitted, and adjusted for shedding. Equations for the feather ~~0.20, growth prediction are: u >0.65, F = 0.25(~*Pm)”~’;u0.20, F = (0.25(0.65*Pm)~0.23)*0.9 F = (0.25(0.65*Pm)0.23)*(0.20*Pm)0.5)*Pm1.4; where u = coefficient of maturity, and Pm = protein weight at maturity [24].

w (kg)

COMPOSITION

COMPOSITION VARIABLES

Ash Water

Ash,

APR, = A s h a ,

Warn

WaPR,,, = Wa,JPm

Lipid

Lm

LP%, = w

decreases systematically during development, and the lipid content of the empty body increases systematically during development [Z].Assuming that growth of other components in the carcass can be explained using the Gompertz function, Emmans [22] concluded that these nutrients can be estimated via allometric relations with body protein growth. An allometric relationship occurs when the weight of one component can be explained through a simple power function of the weight of another. If the body protein weight is known, the estimated allometric relationship

m

There are problems of using an allometric relationship of describing feather growth with a power function of broiler protein weight as

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0.5 0

-0.5 -1 -1.5 -2

-2.1

-1.8

-1.5

-1.2

-0.9

-0.6

-0.3

0

Protein weight (kg) log scale FIGURE 3. Fielationshi of body protein to bod fat, water, and ash in male broilers. Equations for the responses are: Ash = 0.239*P0.8'; Water = 3.259*P0.&; Fat = 1.538*P'.'ga.

allometric relationships that exist between broiler protein weight and weights of the ash, water, and fat [XI. Figure 4 records the fitted body composition for a male broiler and allometric relations for protein, lipid, water, and ash [%I. The differences for Pm and LPRm in Table 2 are probably caused by different broiler genotypes, environmental conditions, feeding regimes, and diets. Emmans and Fisher [28] noted that 1)at a particular degree of maturity in body protein, a particular kind of chicken seeks a particular tipid-to-protein ratio, 2) this lipid-to-protein ratio is a simple power function of degree of maturity in body protein, and 3) lipid-to-protein ratios can differ at any particular degree of maturity for different kinds of chickens. Gous [27] has suggested that free-choice feeding systems need to be applied in modelling experiments so that the lipid-to-protein ratio will not be influenced by diet. Gous [27] recommended offering two feeds - one high in protein, the other low - containing the same concentrations of all other nutrients, including energy.

MAINTENANCE

AND

PRODUCTION REQUIREMENTS FOR PROTEIN AND ENERGY The growingbird has a number of requirements for different functions. The energy requirement in a thermally neutral environment consists of the separate requirements for maintenance and for protein and lipid growth. The ash and water retention either take no energy or the energy needed for these is taken into account in the other terms. Additionally, the protein requirement is the sum of the maintenance and the protein growth requirements [2]. Brody [29] found that maintenance requirements of animals at maturity was proportional to mature size raised to the power of 0.73. Brody's scaling rule, using body protein weight (P,) as a measure of mature size is: where:

MN = ME * Pm0.73* u MJ/day MN = the effective energy requirement for maintenance u = P/Pm is the degree of maturity in body protein [14]

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+Bled carcass-fitted *Fat MProtein *Feathers *Ash +Body water

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AGE (Wk) FIGURE 4. Fitted body composition for a male broiler. The quantity of mature weight com onents related to mature protein weight are: Pm -1.09 kg; LPR,,, (1ipid:protein ratio) 1.56; Fm 0 . 2 5 P m 0 ~ 6 ~ ~- h0.236Pm; m Water, 3.23Pm [26].

-

-

FJSHER [a]

COMPONENT

-

UNIVERSITY OF MN [21] 1.09 kg males, 0.75'kg females

Pm

1.3 kg males, 0.85 kg females

LP%,

0.7 males, 1.1 females

156 males, 2.11 females

Fm

0.25Pm0.67

0.25Pm0.67

h h m

0.210Pm

0.237Pm,0.239Pm

Water,,,

3.25Pm

3.23Pm,3.20Pm

The value of ME for maintenance has been estimated for broilers from maintenance heat production at a level of 1.63MJ/unit with 1 unit equal to Pm0.73 * u [30].Emmans [30] mentioned that the maintenance scaling rule implies that no energy is needed to maintain body lipid. The "effective energyll requirements for protein retention have been estimated as 60.3 MJ/kg [B]for chickens and at 56 MJ/kg [B, 301 for both turkeys and chickens for lipid retention. Emmans [31] suggested that an "effective energyll system for both feed evaluation and requirements would be more accurate than using only AME, because there needs to be consideration for the energy loss or heat increment associated with nitrogen

excretion, defecation, and tissue deposition. Fisher [24] recommended that the "effective energy" content of a specified feed (DEE, MJ/kg) be used to predict the energy requirement of each bird on a daily basis (EER, kJ/day). Feed intake can then be calculated as EERDEE @day and feed formulations adjusted to provide daily requirements of nutrients such as amino acids. Emmans [30] suggested that the effective protein requirements for maintenance should be 8 dmaintenance unit (Pm0.73 u day), 1.25 kgkg protein growth. Requirements would be 0.0 kg for fattening when utilizing an ideal dietary protein source. Figure 5 shows the effective energy needed (kcaVday/bird) for male broilers [26]

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AGE W) FIGURE 5. The effective energy required for maintenance and growth of a male broiler

partitioned into energy necessary for protein accretion, fat gain, feather growth, and maintenance. Figure 6 shows the effective protein needs for male broilers in the same University of Minnesota study. Hruby et al. [%I used 1.15 kg ideal digestible proteinikg protein gain for day 1 to 14 and 1.33kg ideal digestible protein/kg protein gain from day 15 to 19 wk of age. The 1.15 and 1.33 units are reciprocals of 0.87 and 0.75, respectively, which were used as amino acid utilization coefficients. It is apparent that the maintenance part of the protein and energy requirement does not play a major role in a broiler reared to 6 wk of age. Male broiler growth in the Minnesota study demonstrates that broilers at 10 wk and older need more dietary energy for maintenance than for protein or fat gain and at 15 wk of age broilers need more dietary protein for maintenance than for the protein retention requirement. Zoons et al. [16] published another energy requirement formula for maintenance: MEm = a Wb (kJ/day), where W stands for body weight. According to Kirchgessner et al.

[32], the values of "a"and "b"in this formula are 450 and 0.75, respectively.

AMINO ACIDREQUIREMENT CALCULATIONS Emmans [22] suggested that the problem of amino acid requirements could be solved by analyzing the amino acid content of the protein of the body and the feathers and then utilizing proper coefficients for dietary amino acid efficiency. Fisher and Scougall [33] reported that 0.68 (0.75 * 0.9, where 0.9 stands for digestibility of amino acids and 0.75 for utilization) is a proper coefficient of efficiency for turkeys. Fisher [34] suggested that the coefficient of efficiency, "the ratio between amino acid deposited in the body or egg and feed amino acids,'' can incorporate a number of issues. The coefficient of efficiency is probably between 0.65 and 0.85, but within this range there is uncertainty, especially for growing birds. For example, in the "Israeli model" amino acid deposition is divided by 0.85 to convert to dietary total amino acids and there-

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AGE (Wk) FIGURE 6. The ideal protein required for maintenance and growth of a male broiler

ments (g digestible amino acid/h4cal ME) for male broilers in the study by Hruby et al. [26] are presented in Figures 7 and 8 using Emmans and Fisher [28] amino acid profiles and the number 0.75 as an efficiency coefficient. The predicted requirement of lysine and

fore combines both digestibility and efficiency of utilization into one coefficient. The comparisons of essential amino acid composition of protein in feathers and carcasses and their need for maintenance [lo, 281 appear in Table 3. Lysine and TSAA require-

Met Met

+ Cys

Thr

1.9

2.5

os

0.6

2.3

2.4

4.3

3.6

7.0

7.6

2.7

4.8

3.4

4.2

4.7

4.4

5.1

3.6

LRU

65

7.1

8.5

7.0

3.4

4.8

Ile

3.9

4.0

6.4

4.0

2.9

3.6

4.4

4.4

8.9

6.0

2.7

4.2

V~al_

_

ATalpaz

_

_

_ ~

~

~

~

d.[101

BEmmansand Fisher [28] ‘Numbers in bold show maior disaereement between the mblications.

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AGE (Wk) FIGURE 7. The comparison of digestible lysine requirements for a broiler

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+U of MN (19%) +NRC ( 199.4) +Fisher (1987)

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requirements predicted by Hruby et ai. [26] and NRC [35]. The increase in predicted TSAA requirements for male broilers between weeks 3 to 5 in Figure 8 shows the advantages of modelling for actual body components such as feather growth. The predicted weekly digestible amino acid requirements per Mcal ME as determined by Hruby et ai. [26] are listed for broilers from 1 to 19 wk of age in Table 4.

FEED INTAKE AND ENVIRONMENTAL TEMPERATURE The desired feed intake for broilers is based on the premise that birds will consume

0.78 0.79

1.54

1.40

253

1.38

0.33

1.55

16

152

1.37

2.45

1.33

0.33

1.50

19

0.78

153

1.34

2.39

1.27

0.33

1.45

13

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TSAA described by Fisher [24] and NRC [35] are also presented for comparison. Figures 7 and 8 express requirements as dietary digestible amino acids per Mcal of dietary ME (dietary energy concentration). The NRC requirements [35] were multiplied by 0.90 to reflect digestible amino acids instead of total amino acids. Fisher [24] suggested that amino acid requirements can also be expressed on a daily basis as a percentage of the diet if feed intake is also predicted. The advantage of using a growth modelling technique is the dynamic prediction of amino acid requirements compared to the step-by-step method of NRC [35]. The daily predicted lysine and TSAA requirements (g digestible amino acid/Mcal ME) by Fisher [28] are generally higher than the amino acid

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SEX

I

weight of broilers reared at 21.1"C with the mature protein weight for broilers reared in hot environments [26]. The number in parentheses gives the percentage of the potential growth. Increasing the temperature to 26.7"C and higher for both male and female broilers caused substantial reductions in mature protein weight. Figure 9 shows the lysine and TSAA requirements for broilers housed at 21.1"C and 32.2"C [XI.The amino acidenergy ratio as an expression of requirement did not change for the high ambient temperatures compared to the thermoneutral temperature. The research demonstrates the futility of formulating diets with an additional concentration of protein and amino acids to compensate for less feed intake in hot temperatures. The inability of broilers to dissipate adequate body heat in hot temperatures is the problem. Trying to increase daily intake of dietary protein and amino acids decreases performance.

MALE (kg)

FEMALE (kg)

I

POTENIlAL

I

2.934

I

5.056

FEED PROTEIN (gkg)

12.6"C

22.7-c

12.6"C

22.7-c

234

2.988 (1oo)A

2.716 (91)

4.067 (100)

3.557 (87)

155

2.156 (84)

2.090 (70)

3.185 (78)

2.517 (62)

TABLE 6. The broiler mature body protein weight as influenced by sex and temperature 1211

SEX

FEMALE(g)

MALE (9)

POTENTIAL

792

1085

Temperature Actual

21.1"C

26.7-C

32.2"C

21.1"C

26.7-C

32.2"C

792 (loo)*

583 (73.6)

508 (64.1)

1085 (100)

958 (88.3)

819 (75.5)

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feed at a rate which provides the requirement of the first limitingnutrient needed to produce the daily potential body protein gain [13]. The definition by Emmans is compatible with the concept that birds primarily consume a balanced feed at a rate to supply adequate dietary energy needed for maintenance and production. Emmans [30] reported that feed bulk and the ability to lose body heat are the two main constraints that control feed intake for poultry, but imbalanced feed and toxins are also important. Howlider and Rose [36]reported that the ability of a broiler to lose body heat is dependent upon the environmental temperature. Table 5 shows the limitations of body protein weights for turkeys as affected by dietary protein level and environmental temperature [22]. The turkeys reared at 12.6"C compared to 22.7"C had a greater ability to lose body heat; therefore, the bird consumed more feed and gained higher body protein weights. Table 6 contrasts the mature protein

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*Lysine 21.1C t T S A A 21.1C +Lysine 32.2C fTSAA 32.2C

a 2

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AGE (Wk) FIGURE 9. Digestible lysine and TSAA requirements for a broiler under different temperature treatments

CONCLUSIONS AND APPLICATIONS 1. The Gompertz function seems to fit actual broiler growth data the best. The prediction of the ash, water, and lipid content of broilers using allometric relations with body protein should be acceptable since a linear relationship exists between these. The lipid gain predictions can be a problem because the carcass lipid is greatly influenced by feed. 2. Research is needed to determine the mature protein weight, rate of protein gain, and mature lipid/protein ratios for the continually changing genotypes being used in the broiler industry. 3. Research is needed to determine accurate coefficients of efficiency (including digestion and utilization) for dietary amino acids. Efficiency of utilization may be different for each amino acid and may be influenced by the broilers’ stage of maturity. 4. Growth modelling techniques allow researchers to predict dynamic amino acid requirements, a process which seems more natural than using the starter, grower, and finisher requirements published by NRC. 5. Hot environmental temperatures limit the ability of broilers to lose body heat, a situation which decreases feed intake and body weight gain. Rearing different broiler genotypes in a thermoneutral environment w ill be important for determining the potential Gompertz growth functions. 6. The ability to formulate diets for predicted amino acid requirements on a percentage basis will depend on accurately predicting feed intake. Further research is needed related to dietary energy evaluation, utilization, and requirements in order to predict feed intake under various environmental conditions.

REFERENCES AND NOTES 1. Black, J.L, 1994. The evolution of animal models. Pages 1-9 in: P m . of Growth Modelling ence, Wageningen, The Netherlands.

3. Curnow, RN., 1973. A smooth population response cuwe based on an abrupt threshold and plateau model for individuals. Biometrics 291-10.

2. Emmans, G.C., 1990. Problems in modellin the gr&xvth of p o u l t y . Pages 1-21 in: Proc. Georgia kutr. nf., Atlanta, GA.

4. Fisher, C., T.R Morris, and RC. Jcnnings, 1973. A model for the description and prediction of the response

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Hruby et al. of layin hens to amino acid intake. Br. Poultry Sci. 14469-834. 5. Clark, F.A, RM. Gous, and T.R Morris, 1982. Response of broiler chickens to well-balanced protein mixtures. Br. Poultry Sci. 2 3 4 3 M 6 .

6. Gous, RM. and T.R Morris, 1985. Evaluation of a diet dilution technique for measuring the response of broiler chickens to increasing concentrations of b i n e . Br. Poultry Sci. 26:147-161. 7. Humitz, S. and S Bornsteln, 1973. The protein and amino acidrequirements of laying hens: Suggested models for calculation. Poultry Sci. 521124-1134. 8. Humltz, S., D. Sklan, and I. Bartov, 1978. New formal approaches to the determination of energy and amino acid requirements of chickens. Poultry Sci. 5 7 197-205.

12. Emmans, G.C., 1981a. Corn uter simulation in ultry nutrition. Pa es 91-104 in: froc. 3rd European G p a s i u m Poultry Tfutr., Peebles, Scotland. 13. Emmans, G.C., 1981b. A model of the growth and feed i n t a k e o f & u f e d animals,particularlypoultry. Pages 103-110 in: Computers in Animal Production, Occ. Publ. No. 5, Brit. Soc. of Anim. Prod., Edinburgh, Scotland. 14. Emmans, G.C., 1991. The idea behind the models. Pages 17-23 in: Proc. FORTEL- Modelling Seminar/Workshop, London, England.

15. Harlow, H.B. and FJ. Ivey, 1993. Improvements in broiler roduction throu the use of the Novus-lvey Growthhodel (IGMn). g g e s 21-31 in: Proc. Nutr. and Tech. Symposium, Springdale, AR 16. Zoons, J., J. Buyse, and E Decuypere, 1991. Mathematical models in broiler raising. World’s. Poultry Sci. J. 47243-255. 17. Thornley, J.H.M. and 1.R Johnson, 1990. Plant and Crop Modelling. A Mathematical A proach to Plant and Crop Physiology. Oxford Science gublication, Oxford, England. 18. France, J. and J.H.M. Thornley, 1984. Mathematical Models in Agriculture. A Quantitative Approach to Problems in Agriculture and Related Science. Buttenvorths, London, England. 19. Richards, FJ., 1959. A flexible growth function for empirical use. J. Exp. Botany 10(29):290-300. 20. Parks, J.R, 1982.ATheoryof Feedin and Growth of Animals. Springer-Verlag, New York,

&.

22.Emm~ns,C.C,1989.The wthofturkeys.Pages 135-166 in: Recent Advances in g k e y Science. C. Nixey and T.C. Grey, e&. Buttenvorths, London, England. 23. Humitz, S., I. Piavnik, I. Bengal, H. Talpaq and I. Bartov, 1983b.The amino acid requirementsof growing turkeys. 2. Experimental validation of model-calculated requirements for sulfur amino acids and lysine. Poultry Sci. 62~2387-2393. 24. Fisher, C, 1987. Formal methods of calculating amino acid requirements of growing oultry. Pages 1-16 in: Proc. Heartland Lysine Avian d r u m , Fayetteville,

AR. 25. Hakansson, J., Eriksson, S., and S. A Svensson, 1978. The influence of feed energy level on feed consumption, growth, and develo ment of different organs of chicks. Report Numbers SPand 59. Swed. Univ. Agr. Sci., Department of Animal Husbandry, Uppsala, Sweden. 26. Hruby, M., M.L. Hamre, and C.N. Coon, (In Press). Amino acid prediction for broilers reared under 21.1”C and 32.2”C. J. Appl. Poultry Res. 27. Gous, RM., 1990. Future research goals in broiler nutrition identified b means of computer simulation modelling. Pa es 1 2$ in: Proc. Arkansas Nutr. Conf., Little ~ o c k , 28. Emmans, G.C. and C. Fisher, 1986. Problems in nutritional theory. Pages 9-38 in: Nutritional Re uire ments and Nutritional Theory. C. Fisher and K.N. man, eds. Butterworths, London, England.

af,

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