©2009 Poultry Science Association, Inc.
Impact of dietary amino acid and crude protein
levels in broiler feeds on biological performance
G. M. Pesti1
Department of Poultry Science, The University of Georgia, Athens 30602-2772
Primary Audience: Nutritionists, Researchers, Executives
SUMMARY
The concept of a requirement for dietary protein has been controversial since it was discovered that proteins are composed of amino acids and that some amino acids are dietary essentials
for maximum growth and performance. In addition to the 10 essential amino acids and 3 that
can be accreted only from limited substrates, poultry need a quantity of amino acids to synthesize the other 8 that are needed to synthesize body proteins. Adding purified amino acids or
amino acid precursors has been known for more than 50 yr to allow for reduced levels of intact
proteins to provide adequate levels of essential and nonessential amino acids (CP). It has been
recognized that individual essential amino acid requirements are functions of the total CP level.
Increasing the total CP level while maintaining ideal ratios of essential amino acids increases
growth, feed utilization efficiency, and carcass yields (i.e., decreases carcass fat). A published
data set is used here to demonstrate 1) that potential problems arise from analyzing combined
data sets inappropriately; 2) that in the overwhelming majority of studies, there is a positive
response in growth (P < 0.0002) and feed utilization efficiency (P < 0.0002) to increasing dietary protein levels; 3) that the relationships are much stronger in faster growing broiler strain
birds; and 4) that there is no clear break point or “requirement” for CP in the range of dietary
protein levels typically studied. Regardless of whether it is called “CP level” or “essential +
nonessential amino acid level,” there is no clear requirement, only a smooth response curve that
approaches maxima at lower levels for growth, and then feed utilization efficiency, and then
lean meat yield, and finally the minimum for carcass fat. As a result, decisions on feeding levels
for essential and nonessential amino acids should depend on the input-output relationships and
costs.
Key words: broiler, amino acid, crude protein, requirement, model
2009 J. Appl. Poult. Res. 18:477–486
doi:10.3382/japr.2008-00105
DESCRIPTION OF PROBLEM
The use of dietary CP level in feed formulation has been controversial since it was recognized that protein is merely the sum of amino
acids in the feed ingredient, which may or may
not be essential themselves. Before purified
1
Corresponding author: [email protected], [email protected]
methionine was available, a typical corn- and
soybean meal-based broiler starter feed had to
contain approximately 71% soybean meal and
14% corn to supply minimal levels of the essential amino acids. The feed had to contain 35.6%
CP to supply all the essential amino acids at recommended levels [1]. When synthetic dl-meth-
JAPR: Research Report
478
ionine became available, adding merely 0.23%
dl-methionine to the feed allowed soybean meal
to be decreased to approximately 34% and the
protein level to 21.6% while still satisfying
the essential amino acid requirements. Table 1
shows the composition of feeds formulated to
meet essential amino acid but not CP requirements using the NRC [1] nutrient requirements
and ingredient composition tables.
Chickens fed low-protein feeds, despite having enough of each essential amino acid (to support excellent growth), failed to thrive and were
excessively fat. It was realized that chickens require the essential amino acids plus some other
amount of nonessential amino acids to synthesize protein at acceptable rates. Therefore, it was
clear that chickens require not only the essential amino acids but also some other quantity of
amino acids, which have been referred to as the
“nonessential” amino acids. Clearly, some quantity of these nonessential amino acids is needed
(essential) for growth. The sum of the essential
and nonessential amino acids may also be re-
ferred to as the CP requirement. The 1994 NRC
[1], for instance, set the CP requirement for 0- to
3-wk-old broilers at 23%.
It was recognized that the amino acid requirements of the bird are proportional to the CP
content of the diet [1, 2]. The ratios of amino
acids in muscle and other tissues in the body of
the bird are constant. Birds consuming lower
protein levels synthesize smaller amounts of
protein and so need less of each amino acid, and
vice versa. Amino acids are needed in direct proportion to the dietary protein level [3–8]. One
of the factors determining feed consumption in
published studies [3–8] is the dietary protein
level. With higher protein levels, some genetic
strains maintain consumption levels but grow
more, resulting in improved feed utilization efficiency, whereas other genetic strains consume
less feed but maintain growth levels, resulting in
improved feed utilization efficiency [9–13].
The concept that amino acids are required
in proportion to one another to synthesize body
proteins (or in proportion to the total essential
Table 1. The influence of synthetic amino acid level on the protein level of corn- and soybean meal-based diets1
Item
Ingredient, %
Corn, grain
Soybean meal, 48%
Poultry fat
Limestone
Defluorinated phosphorus
Common salt
Vitamin premix
Mineral premix
CuSO4
Coccidiostat
dl-Methionine
l-Threonine
l-Lysine hydrochloride
Composition (calculated), %
ME, kcal/g
Protein, %
Calcium, %
Total phosphorus, %
Available phosphorus, %
Valine, %
Isoleucine, %
Methionine, %
Methionine + cysteine, %
Threonine, %
Lysine, %
1
UA = the amino acid was unavailable.
Unsupplemented
+Met
+Met +Lys
+Met +Lys +Thr
14.01
70.86
12.22
0.61
1.48
0.40
0.25
0.08
0.05
0.05
UA
UA
UA
57.21
33.91
5.46
0.64
1.73
0.40
0.25
0.08
0.05
0.05
0.23
UA
UA
59.47
31.94
5.10
0.64
1.74
0.40
0.25
0.08
0.05
0.05
0.25
0.03
UA
62.42
29.29
4.62
0.64
1.76
0.40
0.25
0.08
0.05
0.05
0.27
0.07
0.09
3.20
35.60
0.90
0.74
0.45
1.63
1.54
0.50
1.04
1.37
2.13
3.20
21.61
0.90
0.68
0.45
0.98
0.88
0.55
0.90
0.80
1.15
3.20
20.89
0.90
0.68
0.45
0.95
0.85
0.56
0.90
0.80
1.10
3.20
20.00
0.90
0.67
0.45
0.90
0.80
0.58
0.90
0.80
1.10
Pesti: AMINO ACIDS AND CRUDE PROTEIN
and nonessential amino acids) has been referred
to as the “ideal amino acid balance” [14]. The
concept of the ideal balance usually refers to ratios of amino acids to one another and often uses
lysine levels as the anchor or reference. Amino
acid requirements are determined in reference to
lysine without regard for the need for nonessential amino acids or the total essential and nonessential amino acids (CP).
Not only are growth rate and feed utilization
efficiency dependent on dietary protein and energy levels, but the amount of carcass and, especially, abdominal fat are as well. The order of
“requirements” (i.e., the maximum responses
to CP levels) is as follows: 1) maximum live
BW; 2) maximum feed utilization efficiency; 3)
maximum carcass lean mass; and 4) minimum
carcass fat. The changes in carcass yield (weight
of salable product/live BW) caused by changing
the dietary protein level may be on the order of
4%, which is enormous from an economic perspective [12, 13].
Ideally, amino acids would each be determined as a function of the total essential plus
nonessential amino acids in the feed. The total
of essential plus nonessential amino acids in the
feed is usually estimated by determining the nitrogen content and by assuming that CP contains
16% nitrogen. The CP that maximizes profits can
be chosen by maximizing the difference between
the cost of feed consumption and yields of salable product minus any costs for waste disposal.
Note that the cost of waste disposal may be negative if there is value in the wastes for fertilizer,
fuel, and the like. The use of this approach was
best illustrated in Ross technical bulletin 00/39
[13] (Figure 1). The important economic factors
influenced by CP level are represented by nonlinear functions, which may be used to calculate
profit-maximizing functions. Protein level, in
this case, is actually a function of the digestible
lysine level and all essential amino acid minima
are kept in proportion to the digestible lysine
level. The term, “percentage of Manual,” refers
to the standard nutritional requirements or feeding levels that Ross Breeders [13] was recommending at the time.
It is very important to recognize that when
nonlinear models (as in Figure 1) are fitted to
the data,
479
• No obvious break point or requirement
is defined by the model. No declaration
of a protein requirement results in maximum technical performance. The goal is
maximum economic efficiency, and nutrient levels must be chosen as a function of
economics.
• Each response value (y, gain, consumption, yield, etc.) is implicitly assumed to
be different for each level of protein intake (x), unless the slope of the line is
equal to zero.
An inherent challenge with this approach is that
results are dependent on choosing an appropriate model and in the error associated with the
parameter estimates of the model.
A second approach to determining appropriate CP levels in broiler diets is to supplement essential or nonessential amino acids while reducing CP levels and to test the hypothesis that the
response to one combination of amino acids and
CP level is different from another. This approach
is fundamentally different from the approach in
Figure 1 because 1) it is based on attempting to
determine differences in response points, not fitting curves through them; and 2) the goal is to
determine the minimum protein level that results
in maximum performance. Maximum technical
performance may or may not result in maximum
economic efficiency. An inherent challenge with
this approach is that small but very important
differences in responses may not be declared
as significant because of inadequate replication
and inherent variation in the responses between
individuals.
Payne [15] assembled a data set from experiments conducted using the second approach,
comparing responses from combinations of amino acid and CP levels. Payne [15] concluded, “It
seems that the CP levels in broiler diets can be
reduced by 3 to 4 percentage points without sacrificing performance provided that free amino
acids are supplemented in the diet to equal the
amino acid levels in a conventional diet.” Payne
[15] presented bar graphs showing that within
experiments, there were few detectable differences between lower CP diets with higher purified amino acid supplementation and higher
CP with lower amino acid supplementation. The
480
data set compiled by Payne [15] should be ideal
to test the hypothesis that there is no response
to CP level if adequate purified amino acids are
supplemented (at least in the ranges studied),
using the regression approach. The experiments
included were all based on the hypothesis that
CP levels could be decreased by supplementing
synthetic amino acids.
The objective of this research was to determine the influence of CP level on growth and
FE by fitting simple linear models to the broiler
data set compiled by Payne [15–38]. When it
JAPR: Research Report
was recognized that CP levels fed were dependent on age, and were therefore also a function
of growth rate, the data set was divided into
halves (faster and slower growing) and was reanalyzed.
MATERIALS AND METHODS
The data set compiled by Payne [15] (Table
2) was entered into Microsoft Excel for graphing and was transferred to SAS [39] for statistical analysis. The statements used with SAS [39]
were as follows:
Figure 1. The response of Ross 308 broilers to dietary protein at 42 d of age, indexed to performance on manual
feeds (Ross recommendations). The fitted curves have the formula {y = k0 + k1 × [1 − exp(k3 × digestible lysine)]}.
The response curve for eviscerated yield is linear. The axis is expressed as deviation of the dietary protein level
from the recommended level. Abd. fat = abdominal fat; Evisc. yield = eviscerated yield.
Pesti: AMINO ACIDS AND CRUDE PROTEIN
Table 2. Data used in the analyses1
Exp. no.
12
12
22
22
32
32
42
42
52
52
6
62
7
7
82
82
9
9
122
122
142
142
152
152
162
162
172
172
182
182
192
192
202
202
212
212
22
22
232
232
242
242
25
25
26
26
27
27
282
282
292
292
302
302
312
481
Table 2 (Continued). Data used in the analyses1
CP, %
Gain, g/d
G:F, g of gain/g
of feed
22.2
19.2
22.2
16.2
22.2
16.2
22.2
16.2
22.2
16.2
22.8
20.9
22.3
18.6
22.0
20.0
26.4
21.9
23.0
21.0
24.0
17.0
23.0
20.0
23.0
17.0
23.0
17.0
23.0
21.0
23.0
20.3
23.0
20.1
23.0
19.7
23.0
17.8
23.0
17.4
23.0
16.5
23.2
18.6
24.0
18.5
23.4
20.6
23.0
19.0
23.0
19.0
23.0
19.0
23.0
29.97
28.04
29.27
28.32
28.70
28.50
26.50
25.91
28.98
29.60
33.86
34.50
41.50
40.76
37.60
36.20
37.70
36.50
28.60
26.50
33.30
29.60
36.50
33.80
36.50
31.80
37.00
35.10
32.30
32.30
25.30
27.80
28.90
31.30
28.90
31.00
36.70
38.00
33.00
34.60
33.90
36.60
46.70
44.30
52.20
46.90
43.90
42.60
20.70
20.80
20.70
20.60
20.50
21.10
19.70
0.817
0.759
0.797
0.807
0.766
0.801
0.808
0.791
0.800
0.797
0.873
0.876
0.764
0.756
0.709
0.694
0.758
0.714
0.694
0.640
0.691
0.613
0.712
0.680
0.712
0.630
0.703
0.690
0.630
0.617
0.559
0.595
0.541
0.585
0.541
0.571
0.654
0.617
0.654
0.617
0.637
0.625
0.739
0.679
0.762
0.710
0.753
0.723
0.675
0.660
0.675
0.672
0.671
0.687
0.682
Continued
Exp. no.
312
322
322
332
332
342
342
35
35
36
36
37
37
38
38
39
39
40
40
41
41
42
42
43
43
45
45
46
46
47
47
48
48
49
49
50
50
51
51
52
52
53
53
54
54
55
55
3B2
3B2
1
CP, %
Gain, g/d
G:F, g of gain/g
of feed
19.0
23.0
19.0
23.0
19.0
23.0
19.0
23.0
19.0
20.9
17.1
18.3
15.9
19.0
16.6
19.0
16.6
19.4
16.4
19.4
16.4
22.0
19.0
22.0
16.0
22.0
19.0
22.0
16.0
17.6
13.5
20.6
18.2
21.5
16.5
19.0
17.0
19.4
18.2
19.4
16.7
17.2
15.9
17.2
14.7
15.6
11.7
22.2
16.2
19.90
19.30
19.40
19.10
18.90
19.10
19.30
45.40
44.90
41.18
37.49
42.30
38.90
50.10
47.60
50.10
47.00
44.00
43.90
44.00
44.70
61.00
60.60
61.00
59.80
62.00
60.60
62.00
57.00
73.73
68.09
81.00
78.80
90.60
86.40
75.10
73.60
81.60
80.60
81.60
80.20
79.00
76.00
79.00
73.30
69.69
64.90
28.70
27.79
0.680
0.675
0.696
0.675
0.661
0.697
0.694
0.776
0.771
0.790
0.690
0.487
0.463
0.494
0.469
0.494
0.474
0.458
0.437
0.458
0.466
0.487
0.478
0.487
0.466
0.538
0.511
0.538
0.488
0.560
0.520
0.490
0.500
0.479
0.427
0.433
0.431
0.478
0.478
0.478
0.470
0.379
0.372
0.379
0.366
0.420
0.440
0.766
0.806
From Payne [15].
The half of all data sets used showing the least growth.
2
JAPR: Research Report
482
Table 3. Comparison of ANOVA results for gain and feed utilization efficiency (g of gain/g of feed) from different
models
Source of variation
df
ADG as a function of CP level (CP, %)
Intercept
1
CP
1
Error
102
ADG as a function of CP level (CP, %) and experiment
Intercept
1
CP
1
Experiment
51
Error
52
Feed utilization as a function of CP level (CP, %)
Intercept
1
CP
1
Error
102
Feed utilization as a function of CP level (CP, %) and experiment
Intercept
1
CP
1
Experiment
51
Error
52
Parameter
estimate
SE of
estimate
Pr > |t|
92.7689
−2.51556
12.5099
0.62610
<0.0001
0.0001
30.0526
0.2918
2.0625
0.0725
<0.0001
<0.0001
<0.0001
0.2029
0.0211
0.0816
0.0041
0.0145
<0.0001
0.6371
0.0041
0.0287
0.0010
<0.0001
0.0002
0.0037
R2
0.137
0.997
0.208
0.987
1
Pr = probability.
PROC GLM; model BWG FE = CP, and
PROC GLM; class EXPT; BWG
FE = CP EXPT,
where BWG is daily BW gain (g/d), FE is feed
efficiency (g of gain/g of consumption), CP is
dietary CP level (%), and EXPT is experiment.
RESULTS
If the gain data are analyzed as a simple collection of data points from the literature without regard for the individual experiments from
which they came, CP is a very highly significant
contributor to the variation in BW gain (Table
3 and Figure 2), and CP has a negative effect
on BW gain (it is toxic). If each experiment
from which the data came is also included in the
analysis, CP is again a significant contributor to
the variation in BW gain, but the coefficient is
positive (Table 3 and Figure 3). Each unit (percentage) of protein increased daily BW gain (g)
by 0.2918 ± 0.0724. A total of 71.2% of the data
sets had positive slopes for BW gain as a function of dietary CP level.
If the FE data are analyzed as a simple collection of data from the literature without regard
for the individual experiments from which they
came, CP is a very highly significant contributor to the variation in FE (Table 3 and Figure 4),
and CP has a positive effect on FE (G:F). If each
experiment from which the data came is also included in the analysis, CP is again a significant
contributor to the variation in FE, and the coefficient is again positive (Table 3). Each unit
(percentage) of protein increased FE by 0.0041
± 0.0010. A total of 75.0% of the data sets had
positive slopes for FE as a function of dietary
CP level.
Figure 2. The relationship between ADG and dietary
protein level (PL). Holistic analysis of data from 52 experiments. Model: ADG = f(PL).
Pesti: AMINO ACIDS AND CRUDE PROTEIN
483
DISCUSSION
ining whether 2 points in each experiment can
be declared as significantly different at P < 0.05.
The problem is that each experiment should
come with a disclaimer stating that “because of
variability in the data, differences smaller than
some percentages could not reliably be detected.” Finding no significant differences should
not be taken to mean that no differences existed.
By pooling the data as in Table 3, it becomes
clear that CP level really is having some significant effect overall (P < 0.0001 for gain, and P =
0.0002 for feed utilization efficiency). Whether
that effect is important is an economic question:
Is the cost of additional protein offset by the increased BW, breast meat yield, and so forth?
That is not to imply that all the experiments
listed in Table 2 would have shown significant
responses to BW and feed utilization efficiency had there been adequate replication. Body
weight gain and FE slopes, for instance, approach zero in the interval from 110 to 120% of
manual CP recommendations in Figure 1. Had
the experiments been conducted in this range,
certainly it would have been extremely difficult
to declare any differences as significant with the
resources most researchers have to provide replication. Breast meat and eviscerated yield for
both sexes and abdominal fat for females, however, still showed linear changes in the manual
CP recommendations at 110 to 120% and need
to be considered even though BW and FE are
not changing in any detectable amounts.
Whether significant differences can be detected depends on several factors, including 1)
These results make it clear that CP level is
still a significant contributor to variation in both
broiler growth and FE, even when purified amino
acids are added to the lower CP feeds (from the
collection of data in Table 2). The BW responses
in Figure 3 are still increasing, similar to the BW
responses in Figure 1 (between 100 and 110%
of manual recommendations). Similarly, the FE
responses in Figure 4 are increasing, similar to
the FE responses in Figure 1 (between 90 and
100% of manual recommendations). The overall
conclusion from the data set compiled by Payne
[15] should be that both amino acid supplementation and CP levels are important in determining growth responses of broilers (at least in the
ranges studied). The conclusions of Payne [15]
are quite correct from the perspective of exam-
Figure 4. The relationship between FE and dietary protein level (PL). Holistic analysis of data from 26 experiments with the highest daily gains. Model: FE = f(PL).
Figure 3. The relationship between ADG and dietary
protein level (PL). Holistic analysis of 52 experiments
(EXP). Model: ADG = f(PL, EXP).
When only the data from the 26 research trials
with birds with the lowest BW gains were considered, no significant effects of protein level on
BW gain (P < 0.2830) or FE (P < 0.1693) were
observed. However, when only the data from the
26 research trials with birds with the highest BW
gains were considered, highly significant effects
of protein level on BW gain (P < 0.0001) and
FE (P < 0.0001) were observed (the independent
variable “experiment” was included in the models). Each unit (percentage) of protein increased
daily BW gain (g) by 0.6061 ± 0.1063 and FE
by 0.0072 ± 0.0120. A total of 82.8% of the data
sets had positive slopes for BW gain as a function of dietary CP level.
484
the growth rate of the birds, 2) the quality (digestibility) of the ingredients, 3) the magnitude
of the CP reduction, 4) the amount of experimental variation, and 5) the number of replicates
per treatment. The more imbalanced a feed is to
begin with, because of the individual ingredients and their qualities, the greater will be the
detectable differences in protein level. When
more is known about ingredient quality, such as
individual amino acid digestibilities, then better
amino balances can be achieved and more of the
essential amino acids will be incorporated into
body protein and less will be oxidized and metabolized.
The approach taken in the experiments whose
results are summarized in Table 3 and Figures 2
to 4 does not directly address the questions of
1) what the ratio of essential to nonessential
amino acids should be, or 2) what the response
is to total essential and nonessential amino acids (CP). Collectively, the results suggest little
response to dietary protein level in the younger
and slower growing birds. This is consistent
with recommendations of relatively high protein levels when birds are young and growing at
slow (absolute g/d) rates. However, when birds
are older and growing at faster rates, the protein
levels fed were limiting growth and feed utilization efficiency in the majority of cases, resulting
in very high probabilities that the observed differences were not due to chance. In experiments
showing the responses to protein level (despite
the lower protein diets being better balanced),
the real consideration should be, “Is the cost of
the additional protein at least offset by the additional returns from increased growth rate or less
feed per unit of salable product?”
These analyses illustrate several potential
problems that may occur when analyzing data
sets made from a collection of results from experiments with many design differences. The
initial analysis simply relating all ADG = f (CP)
(Table 3 and Figure 2) suggests that CP is toxic
in the range studied (note the negative coefficient for CP in Table 3). This apparent relationship may simply be due to the different experimental conditions used: younger chicks tend to
be fed higher CP levels but naturally have lower
ADG.
Including “experiment” in the regression
model (Table 3) lowers error degrees of free-
JAPR: Research Report
dom from 102 to 51. However, 51 df is still adequate to show that ADG and CP are related
(less than 2 chances in 10,000 that observed
effects are due to chance). The R2 values, the
amount of variation described by the experimental model, increases from 0.137 to 0.997
when the effect of experiment is accounted for.
Clearly, most of the variation in the ADG data
in this data set is due to experimental variables
other than dietary CP level. When differences
in experiment are accounted for in the statistical model, ADG appears to be directly proportional to percentage of CP (positive coefficient
for percentage of CP; Table 3 and Figure 2) in
the ranges studied.
The slower growing birds may not have
shown responses to CP for several reasons: 1)
they may simply have been younger and so may
have responded differently physiologically; 2)
their environmental (growing) conditions may
have been such that they were not near their
genetic potential; or 3) they may have been of
specific genetic stocks that showed little growth
response to dietary CP level in the ranges being
studied.
The NRC [1] emphasized the increasing importance of developing comprehensive models:
Generally, as dietary protein level increases, essential amino acid requirements (expressed as a percentage of the
diet) increase, although when expressed
as a percentage of the protein, essential
amino acid requirements are little affected. . . . These observations demonstrate
the importance of maintaining a balance
among the concentrations of essential and
nonessential amino acids in poultry diets.
Optimal balance is important for efficient
utilization of dietary protein. The protein
and amino acid concentrations presented
as requirements herein are intended to
support maximum growth and production.
Achieving maximum growth and production, however, may not always ensure
maximum economic returns, particularly
when prices of protein sources are high.
If decreased performance can be tolerated, dietary concentrations of amino acids
may, accordingly, be reduced somewhat to
maximize economic returns.
Pesti: AMINO ACIDS AND CRUDE PROTEIN
Clearly, it is becoming more important not to
waste dietary CP from both cost and environmental waste perspectives. Amino acid supplementation is one key factor in reducing CP levels
in practical broiler feeds (Table 1). Optimizing,
and not minimizing, CP levels is another. The
idea of comparing low CP plus nonessential
amino acids with some higher standard implies
that the goal of feed formulation is merely to
achieve some standard performance. However,
it is just as clear that feed formulation should
have as its goal achieving a compromise between diet cost and performance. Performance
increasingly means optimizing eviscerated and
breast meat yields, not just maximizing BW and
FE. The emphasis of amino acid and protein research should be on developing equations that
can be used to relate inputs (costs) and outputs
(performance) to maximize profits under various environmental conditions with each genetic
stock.
CONCLUSIONS AND APPLICATIONS
1. The choice of the appropriate statistical
model is critical to making appropriate
conclusions about the relationship between dietary protein level, amino acid
supplementation, and broiler performance.
2. Although individual experiments may
seem to show no “significant” response
to dietary protein level (even with amino
acid supplementation), when the data are
pooled with an appropriate regression
model, clear responses to dietary protein
are obvious and are highly significant.
3. Essential amino acid balance and total
amino acid levels (CP or essential plus
nonessential amino acids) should be
considered to optimize growth and to
maximize profits. Simply lowering CP
levels by supplementing amino acids
may not result in maximum performance
or profits.
REFERENCES AND NOTES
1. NRC. 1994. Nutrient Requirements of Poultry. 9th
rev. ed. Natl. Acad. Press, Washington, DC.
2. Almquist, H. J. 1947. Evaluation of amino acid requirements by observations on the chick. J. Nutr. 34:543–
563.
485
3. Almquist, H. J. 1952. Amino acid requirements of
chickens and turkeys—A review. Poult. Sci. 31:966 –981.
4. Boomgaardt, J., and D. H. Baker. 1971. Tryptophan
requirement of growing chicks as affected by dietary protein
level. J. Anim. Sci. 33:595–599.
5. Boomgaardt, J., and D. H. Baker. 1973. The lysine requirement of growing chicks fed sesame meal-gelatin diets
at three protein levels. Poult. Sci. 52:586–591.
6. Morris, T. R., K. Al-Azzawi, R. M. Gous, and G. L.
Simpson. 1987. Effects of protein concentration on responses to dietary lysine by chicks. Br. Poult. Sci. 28:185–195.
7. Mendonca, C., and L. S. Jensen. 1989. Influence of
protein concentration on the sulfur-containing amino acid
requirement of broiler chickens. Br. Poult. Sci. 30:889–
898.
8. Leclercq, B. 1983. The influence of dietary protein
content on the performance of genetically lean or fat growing chickens. Br. Poult. Sci. 24:581–587.
9. Leclercq, B., and G. Guy. 1991. Further investigations
on protein requirement of genetically lean and fat chickens.
Br. Poult. Sci. 32:789–798.
10.Alleman, F., J. Michel, A. M. Chagneau, and B.
Leclercq. 2000. The effects of dietary protein independent of
essential amino acids on growth and body composition in genetically lean and fat chickens. Br. Poult. Sci. 41:214–218.
11.Smith, E. R., G. M. Pesti, R. I. Bakalli, G. O. Ware,
and J. F. M. Menten. 1998. Further studies on the influence
of genotype and dietary protein on the performance of broilers. Poult. Sci. 77:1678–1687.
12.Smith, E. R., and G. M. Pesti. 1998. Influence of
broiler strain cross and dietary protein on the performance
of broilers. Poult. Sci. 77:276–281.
13.Aviagen. 2000. Broilers, Protein and Profit. Ross
Tech. 00/39. Aviagen, Newbridge, Midlothian, Scotland,
UK.
14.Emmert, J. L., and D. H. Baker. 1997. Use of the ideal
protein concept for precision formulation of amino acid levels in broiler diets. J. Appl. Poult. Res. 6:462–470.
15.Payne, R. L. 2007. The potential for using low crude
protein diets for broilers and turkeys. Degussa AminoNews
8:2–13.
16.Aletor, V. A., I. I. Hamid, and E. Pfeffer. 2000. Low
protein amino acid-supplemented diets in broiler chickens:
Effects on performance, carcass characteristics, whole-body
composition and efficiencies of nutrient utilization. J. Sci.
Food Agric. 80:547–554.
17.Bregendahl, K., J. S. Sell, and D. R. Zimmerman.
2002. Effect of low protein diets on growth performance and
body composition of broiler chicks. Poult. Sci. 81:1156–
1167.
18.Brooks, S. E., H. M. Allen, and J. D. Firman. 2003.
Utilization of low crude protein diets fed to 0–3 wk broilers.
Poult. Sci. 82(Suppl. 1):37. (Abstr.)
19.Cabel, M. C., and P. W. Waldroup. 1991. Effect of
dietary protein level and length of feeding on performance
and abdominal fat pad content of broiler chickens. Poult.
Sci. 70:1550–1558.
20.Corzo, A., M. T. Kidd, D. J. Burnham, and B. J. Kerr.
2004. Dietary glycine needs of broiler chicks. Poult. Sci.
83:1382–1384.
21.Fancher, B. I., and L. S. Jensen. 1989. Dietary protein level and essential amino acid content: Influence upon
female broiler performance during the grower period. Poult.
Sci. 68:897–908.
486
22.Fancher, B. I., and L. S. Jensen. 1989. Male broiler
performance during the starting and growing periods as affected by dietary protein, essential amino acids, and potassium levels. Poult. Sci. 68:1385–1395.
23.Ferguson, N. S., R. S. Gates, J. L. Taraba, A. H. Cantor, A. J. Pescatore, M. L. Straw, M. J. Ford, and D. J. Burnham. 1998. The effect of dietary protein and phosphorus on
ammonia concentration and litter composition in broilers.
Poult. Sci. 77:1085–1093.
24.Ferguson, N. S., R. S. Gates, J. L. Taraba, A. H. Cantor, A. J. Pescatore, M. L. Straw, M. J. Ford, and D. J. Burnham. 1998. The effect of dietary crude protein on growth,
ammonia concentration and litter composition in broilers.
Poult. Sci. 77:1481–1487.
25.Fritts, C. A., A. Corzo, and M. T. Kidd. 2004. Chick
responses to diets differing in essential and nonessential
amino acids. Poult. Sci. 83(Suppl. 1):443. (Abstr.)
26.Han, Y., H. Suzuki, C. M. Parsons, and D. H. Baker.
1992. Amino acid fortification of a low protein corn and soybean meal diet for chicks. Poult. Sci. 71:1168–1178.
27.Heger, J., and M. Pack. 1996. Effects of dietary
glycine + serine on starting broiler chick performance as
influenced by dietary crude protein levels. Agribiol. Res.
49:257–265.
28.Kerr, B. J., and M. T. Kidd. 1999. Amino acid supplementation of low-protein broiler diets: 1. Glutamic acid and
indispensable amino acid supplementation. J. Appl. Poult.
Res. 8:298–309.
29.Kerr, B. J., and M. T. Kidd. 1999. Amino acid supplementation of low-protein broiler diets: 2. Formulation on an
ideal amino acid basis. J. Appl. Poult. Res. 8:310–320.
30.Mack, S., D. Bercovici, G. de Groote, B. Leclercq, M.
Lippens, M. Pack, J. B. Schutte, and S. vanCauwenberghe.
JAPR: Research Report
1999. Ideal amino acid profile and dietary lysine specification for broiler chickens of 20 to 40 days of age. Br. Poult.
Sci. 40:257–265.
31.Parr, J. F., and J. D. Summers. 1991. The effect of
minimizing amino acid excesses in broiler diets. Poult. Sci.
70:1540–1549.
32.Pesti, G. M., and C. F. Smith. 1984. The response
of growing broiler chickens to dietary protein, energy and
added fat contents. Br. Poult. Sci. 25:127–138.
33.Pinchasov, Y., C. X. Mendonca, and L. S. Jensen.
1990. Broiler chick response to low protein diets supplemented with synthetic amino acids. Poult. Sci. 69:1950–
1955.
34.Robbins, K. R. 1987. Threonine requirement of the
broiler chick as affected by protein level and source. Poult.
Sci. 66:1531–1534.
35.Schutte, J. B., W. Smink, and M. Pack. 1997. Requirement of young broiler chicks for glycine + serine. Arch.
Geflugelkd. 61:43–47.
36.Si, J., C. A. Fritts, P. W. Waldroup, and D. J. Burnham.
2004. Effects of tryptophan to large neutral amino acid ratios
and overall amino acid levels on utilization of diets low in
crude protein by broilers. J. Appl. Poult. Res. 13:570–578.
37.Si, J., C. A. Fritts, P. W. Waldroup, and D. J. Burnham.
2004. Effects of excess methionine from meeting needs for
sulfur amino acids on utilization of diets low in crude protein
by broiler chicks. J. Appl. Poult. Res. 13:579–587.
38.Waldroup, P. W. 2000. Feeding programs for broilers: The challenge of low protein diets. Pages 119–134 in
Proc. 47th Annu. Maryland Nutr. Conf. Maryland Feed Ind.
Counc. Inc., College Park, MD.
39.SAS Institute. 2001. SAS User’s Guide: Statistics.
Version 8.02 Edition. SAS Inst. Inc., Cary, NC.