Note: Descriptions are shown in the official language in which they were submitted.
CA 02320687 2000-09-21
6 INTRODUCTION
'7 There has been increasing interest in quantitatively studying the effect of
different levels of
8 feed enzymes (inputs) when added to a diet on the performance (outputs) of
chickens (Friesen et
9 al., 1991; Bedford and Classen, 1992; Marquardt et al., 1994; and Zhang et
al., 1996; 2000). The
primary objectives of the former studies were ( 1 ) to estimate the optimal
level of feed enzyme
11 addition required to obtain maximal chick performance (Friesen et al.,
1991; Bedford and
12 Classen, 1992), and (2) to evaluate the efficacy of feed enzymes added to a
diet (Rotter et al.,
13 1989; Zhang et al., 1996; 2000). Frequently, the experimental designs and
statistical procedures
14 have only provided trends on the effects of enzyme treatment but have not
provided precise
prediction values that can be obtained when a given enzyme is added to a given
diet. Therefore, it
16 has been impossible to accurately estimate the relationship between inputs
(enzyme or cereal) on
17 outputs (chick performance), or to establish the most profitable
combination of inputs for a
18 specified output. In addition, researchers in nutrition have generally been
concerned only with
19 biological rather than economic criteria to evaluate and make
recommendations on the effects of
feed enzymes. The criteria that have been used for the evaluation of
performance often were the
21 treatments yielding the largest weight gain or the lowest feed to gain
ratio per unit of enzyme
22 addition (Friesen et al., 1991; Bedford and Classen, 1992). However, these
maxima or minima
3
CA 02320687 2000-09-21
have seldom been utilized to estimate the most profitable output or optimal
input. Even where
2 the objective was the prediction of the physical maxima or minima, the exact
values could only
3 be accurately estimated by use of a prediction equation (Zhang et al.,
1996).
4 Recently, we have developed a simple log-linear model to accurately predict
the response of
chickens to dietary enzymes (Zhang et al., 1996). The model equation was able
to predict the
6 performance of chickens fed diets containing different amounts of an enzyme
and different
7 proportions of two cereals. Simple but accurate log-linear equations were
derived from many
8 previous dose response studies with feed enzymes, even though they were not
designed for this
9 purpose. In addition, the efficacy of any enzyme preparation for a
particular cereal or class of
poultry with regards to any index of animal performance such as weight gain or
feed to gain ratio
11 could be assayed from a single value of B, the slope of the model equation
(Zhang et al., 1996;
12 Marquardt and Bedford, 1997). Therefore, it should be possible, using this
equation along with
13 other analyses, to correctly estimate the maximum economic return obtained
when a feed enzyme
14 is added to a diet. A requirement is that accurate input data be available.
The objective of this
1 S study was to develop a Multi-purpose Enzyme Analyzer (MPEA) for estimating
the profitability
16 of using enzymes in poultry feeds. Three main applications of the Enzyme
Analyzer were to: ( 1 )
17 evaluate the effects of different enzyme preparations when they are added
to a cereal-based diet
18 using maximal profit as a standard, (2) determine the amounts of an enzyme
preparation and/or a
19 substituted cereal that should be used in a diet to obtain maximal profit,
and (3) to establish the
relationships among the price of an enzyme preparation, the price of the
substituted cereal, and
21 the economic return. Therefore, the use of the modelling method in
conjunction with nutrition
4
CA 02320687 2000-09-21
1 knowledge and computer technology should provide researchers and managers
that use feed
2 enzymes a powerful new approach for the analysis and interpretation of their
data.
3
4 MATERIALS AND METHODS
Sources of Data
6 The data used in this study were obtained from four previous studies: Rotter
et al. (1989),
7 Bedford and Classen (1992), Marquardt et al. (1994), Zhang et al. (1996).
The data for the first
8 study was obtained from Rotter et al. (1989) and Zhang et al. (1996). In
experiment 3 of the study
9 from Rotter et al. (1996), one-day-old Single Comb White Leghorn chicks were
fed a
commercial starter crumble for a 7 d pre-experimental period. A barley-based
diet was fed to
11 birds from 7 to 14 d of age in a completely randomized design. The diet
consisted of the
12 following ingredients: 65.50% barley, 23.07% soybean meal, and 11.43% other
ingredients. The
13 calculated metabolizable energy (MEn) of the diet was 12.20 MJ/kg. Five
enzyme preparations
14 used in the study were: Cellulase Tv concentrate (T. viride)3, Celluclast
(Trichoderma ressei)4,
SP249 (Aspergillus niger)4, Finizym (A. niger)4, and Cereflo (Bacillus
subtilis)4. The enzyme
16 activities as determined by manufacturer were: Cellulast, 1633 NCU/g;
SP249, 11240 PGU/g;
17 Finizym, 217 FBG/g; Cellulase Tv concentrate 23880 CU/g; and Cereflo, 67.5
KNU/g. All of the
18 enzymes at amounts of 0.003125, 0.00625, and 0.0125 % were added to the
experimental diet for
19 the dose response study. Performance per chick was recorded at 14 d of age.
3 Miles Laboratories Inc.
4 Novo A/S Denmark.
5
CA 02320687 2000-09-21
1 Another data set used in the first study was obtained from Zhang et al.
(1996). In this
2 experiment, one-day-old Single Comb White Leghorn cockerels were fed a
commercial starter
3 diet for a 7 d pre-experimental period. The experimental diets were fed to
birds from 7 to 21 d of
4 age. The diet consisted of the following ingredients: 60% rye, 8.25% wheat,
24.5% soybean
S meal, and 6.75% other ingredients. The calculated MEn of the diet was 12.34
MJ/kg. Rye grain
6 (Prima) was selected as the substituted cereal for wheat in the diet as it
contains high levels of
7 viscous arabinoxylans. The arabinoxylans in rye grains are primarily
responsible for its
8 antinutritive effects (Antoniou et al., 1981 ). They greatly reduce chick
performance but are
9 efficiently hydrolysed by enzyme preparations containing xylanase activity
(Fengler et al., 1988;
Fengler and Marquardt, 1988; Marquardt et al., 1994; Zhang et al., 1996,
1997). Two enzyme
11 preparations, RM1 (T. longibrachiatum)5 and NQ (T. ressei)6, were used in
this study (Zhang et
12 al., 1996). The xylanase activity of RM1 and NQ was 389 and 778 U/g of
enzyme preparation as
13 assayed by the azo-dye method (McCleary, 1992) using dye-labelled
arabinoxylan as the
14 substrate. Different amounts of RM1 (0, 0.25, 0.75, 2.75, 6.75, 20.25 g/kg)
and NQ (0, 0.1, 0.3,
0.9, 2.7, and 8.1 g/kg) were added to the diet, at the expense of rye, for a
total 12 different
16 treatments. Bird weight and feed consumption based on six birds were
recorded 4 h after removal
17 of feed at 21 d of age.
18 The data for the second study were obtained from experiment 2, Marquardt et
al. ( 1994). In
19 this experiment, one-day-old Single Comb White Leghorn chicks were fed a
commercial starter
diet for a 7 d pre-experimental period. The experimental diets were fed to
birds from 7 to 21 d of
5 Finnfeeds International Ltd., Wiltshire, UK.SN8 1XN.
6 Nutri-Quest, Chesterfield, MO, 63017.
6
CA 02320687 2000-09-21
1 age in a factorial arrangement of treatments: 4 (cereals) x 4 (enzyme
doses). The cereals used in
2 four diets were 63% corn (unknown variety), 67% wheat (Katepwa), 66% hulless
barley (Scout),
3 and 64 % rye (Prima), respectively. The calculated MEn of the four diets
were 12.66, 13.37,
4 12.46, and 12.01 MJ/kg. The diets were supplemented with different
concentrations (0, 0.5, 1,
and 2 g/kg) of a crude enzyme preparation, Kyowa Cellulase (T. reesei)5. The
xylanase and
6 cellulase activities as determined by the Japan Food Laboratory were 1500
and 1000 U/g,
7 respectively. The chick performances based on a bird basis were recorded at
21 d of age.
8 The data for the third study was obtained from Bedford and Classen (1992).
In this
9 experiment, one-day-old male broiler chicks were fed four diets supplemented
with different
amounts of a pentosanase preparation (experimental product6 from T.
longibrachiatum) in a 4 x 6
11 factorial arrangement of treatments from 1 to 19 d of age. The diets
consisted of the following
12 proportions of rye (Musketeer) and wheat (unknown variety): 0:60, 20:40,
40:20, and 60:0 each
13 with 32.05% soybean meal, and 7.95% other ingredients. The calculated MEn
of the four diets
14 were 12.85, 12.50, 12.15, and 11.80 MJ/kg, respectively. The enzyme
preparation added to each
1 S of the four diets was 0, 1, 2, 4, 8, and 16 g/kg. The xylanase activity of
this enzyme preparation
16 was 21 SO U/g as determined by the reducing sugar method when assayed on
oat spelt xylan
17 (Seeta et al., 1989). Chick performances, based on six birds, were recorded
at 19 d of age.
18 For demonstration purposes, the price range for enzyme preparations was
assumed to be from
19 $ 3 to $ 7 per kg. The price for corn, wheat, barley, and rye was assumed
to be $ 0.13, $ 0.12, $
0.08, $ 0.08 per kg, respectively. The barley and rye were used as substituted
cereals for wheat in
21 the diet, therefore, their price was assumed to be less expensive than that
of wheat. The average
7
CA 02320687 2000-09-21
1 price of other ingredients in a diet was $ 0.08 per kg and the price of
chickens was $ 1.23 per kg.
2 Other prices can be inserted into the equations as desired as outlined
below.
3 Outline of a Multi purpose Enzyme Analyzer (MPEA)
4 Recently, we have developed a log-linear model equation to predict the
performance of
chickens fed a cereal-based diet supplemented with different concentrations of
a feed enzyme.
6 The model can estimate maximal economic return when a feed enzyme is added
to a diet. Based
7 on the log-linear model, we have further developed a software package, a
Multi-purpose Enzyme
8 analyzer (MPEA). The MPEA consists of two parts: a modelling and application
part (Figure 1).
9 The modelling part has revenue, production cost, and profit functions. The
MPEA has three
applications. The first application evaluates the profitable efficacy of
different enzyme
11 preparations added to a specific diet and determines the most profitable
cereal for a specific
12 enzyme preparation based on maximal economic returns. The second is to
determine the optimal
13 amount of a feed enzyme and a cereal used in a diet to obtain maximal
profit. The third is to
14 determine the alternate price that should be paid for a given enzyme
preparation and a cereal.
Principle of the MPEA: Maximal Profit with the Optimal Inputs
16 From the dose response of study with varying the levels of a feed enzyme
added to a diet, the
17 log-linear model equation was selected to fit the data of the output or
chick performance and the
18 input or amount of enzyme. The general model as proposed by Zhang et al.
(1996) for weight
19 gain (Equation 1 ) and feed intake (Equation 2) was:
Y=A+Blog(CX+1) [1~
21 F = a + b log (c X + 1 ) [2]
8
" CA 02320687 2000-09-21
' 1 where, X was the amount of an enzyme (percentage of diet), Y and F were
weight gain (g) and
2 feed intake (g), A, B, C and a, b, c were the corresponding coefficients of
the two regression
3 equations, respectively. Based on the two equations, we have developed a
profit function
4 (Equation 3) in general:
II=PrY'F~(P;X;)
[3]
6 where, II is the profit, Py is the price of chickens, P; is the price of
ingredients in a diet and X; is
7 the amount of the i-th variable such as rye, wheat, or enzyme preparation in
a diet. The maximal
8 profit can, therefore, be calculated when the partial derivatives of
Equation 3 are equal to zero
9 (Heady and Dillon, 1961 ). A more detailed profit equation can be deduced
when other variables
are utilized (Equation 4). For example, the optimal amounts of a feed enzyme
and a substituted
11 cereal (rye or barley) for wheat or corn in a diet, that will yield maximal
profits, can be
12 determined using parameters and equations outlined below.
13 Suppose: Y = weight gain (kg), Py = price of chicken per kg,
14 F = feed consumption (kg), (PF = price of feed per kg,)
XE = % of diet (enzyme), PE = price of enzyme per kg,
16 XR = % of diet (rye or barley), PR = price of rye per kg,
1 ~ XW = % of diet (wheat), PW = price of wheat per kg,
18 Xo = % of diet (other ingredients), Po = price of other ingredients per
19 kg~
Constrains: XR + XW = 0.60 0 ~ XR s 0.60
21 XE + Xo = 0.40 0 s XE s 0.05
22 XR+XW+XE+Xo= 1.00
9
CA 02320687 2000-09-21
1 Then II = Py Y - F (PEXE + PRXR+ PWXW + Pte) (4]
2 Where Y = A + B log (C X + 1 )
3 F = a + b log (c X + 1 )
4 Since XW = 0.60 - XR
Xo=0.40-XE
6 When 8II ~ 8XE = 0 [5]
7 8II ~ 8XR = 0 [6]
8 The amounts of XE and XR that will yield the maximum profit can be
calculated when the XE and
9 XR are inputted into Equation 4.
Analyses of Data
11 The coei~'icients (A, B, C or a, b, c) for the log-linear model for weight
gain or feed
12 consumption for the data from the first and second study were calculated
using a program
13 developed by Zhang et al. (2000). A multiple regression analysis was used
for the data from the
14 third study to establish the response of chick performances, such as weight
gain (Y) and feed
intake (F), to the amount of enzyme (XE) and the proportion of rye (XR) in the
diet. The general
16 regression equations are shown in the following equations (Equations 7 and
8).
17 Y = (Ao + A,XR + AZXRZ + A3 XR3)
18 + (Bo + B,XR + BzXR2 + B3 XR3) log (C X + 1 ) [7]
19 F - (ap + aIXR + a2XR2 + a3 XR3)
+ (bo + b,XR + b2XRZ + b3 XR3) log (C X + 1 ) [8]
21 These models were an extension of the models used in our previous research
(Zhang et al., 1996).
22 The coefficients of the two regression equations, with the two variables
such as the amounts of
, CA 02320687 2000-09-21
1 enzyme and the amount of rye relative to wheat in the diet as the inputs of
the equation, were
2 calculated by the stepwise regression method (SAS, 1994) where the C values
of the log-linear
3 equation were assumed to be 2150. The data for the third study were also
analyzed using Sigma
4 Plot (Kuo and Norby, 1992) to determine the level of profit that was
obtained with different
amounts of an enzyme and different proportions of a substituted cereal, such
as rye substituted
6 for that of wheat, in a diet.
7 The standard error of means for all of the data are given in the original
studies. The residual
8 standard deviations of regression for the log-linear model equations are
listed in Table 1.
9
RESULTS AND DISCUSSION
11 Evaluating the Effect of Different Feed Enzymes
12 One of the problems encountered by nutritionists in the feed industry is
how to select a feed
13 enzyme that would be most effective for a particular feed. The effect of
different feed enzymes
14 are generally evaluated by biological criteria such as their effect on
chick performance,
digestibility of feed nutrients, and degree of reduction of the viscosity of
digesta or the diet
16 (Bedford and Classen, 1992; Joroch et al, 1995; Zhang et al, 1996). In most
studies, comparisons
17 among different enzyme preparations has been often carried out using the
same amount of
18 different enzyme preparations in a cereal-based chick diet as determined by
an enzyme activity
19 assay or the levels of inclusion in the diet as recommended by the
manufacturers (Rotter et al.,
1989; Guenter 1997; Boros et al., 1998; Zhang et al., 2000). However, it is
difficult to correctly
21 evaluate different enzyme preparations based on their activities, since
many enzyme preparations
22 are from different sources. Therefore, they often contain a different
spectrum of enzymes with
11
CA 02320687 2000-09-21
1 different catalytic properties. In addition, the selection of the proper
assay conditions such as pH,
2 especially when comparing the activity of different feed enzymes, is
essential because the
3 selected pH will bias results in favour of an enzyme whose optimal pH is
closest to the select
4 selected pH, which in turn may not be the optimal pH in vivo (Marquardt and
Bedford, 1997;
Ziggers, 1999, Zhang et al, 2000). Recently, we have developed a new approach
to accurately
6 evaluate the effects of different enzyme preparations. The approach uses a
new concept for
7 estimating the efficacy of a feed enzyme, the slope of a log-linear model
(Zhang et al., 1996).
8 This evaluation, although very useful, is only based on the biological data.
However, the goal of
9 many studies is often to select an enzyme preparation that will yield the
greatest profit.
The objective of the first study was to determine if the effects of different
feed enzyme
11 preparations on maximal profits could be evaluated using the MPEA. The
profit functions (Table
12 1 ) were readily derived using Equation 4 from the production (Equation 1 )
and feed consumption
13 (Equation 2) functions. The maximal profit and the optimal amount of an
enzyme that should be
14 added to a diet was calculated using Equations S and 6. The results in
Table 2 indicated that the
maximum profit per 1000 birds when given the optimal amount of each of the
five enzyme
16 preparations, Cellulase Tv, Cellulast, Finizym, Cereflo, and SP249 were $
67.29, $ 61.27, $
17 51.91, $ 49.27, and $ 46.79, respectively. In this analysis, the assumed
price of the enzymes were
18 the same. The sequence of these values also agrees with that of the B
values for the feed to gain
19 ratio as determined from the log-linear equation ( rz = 0.99, P < 0.0005).
The same trend was also
observed in this study using data from Zhang et al. ( 1996). These results, in
contrast to
21 subsequent results with different cereals or cereals plus enzymes, suggest
that both the B values
22 and the maximal profit provided similar indices for the evaluation of
different enzyme
12
CA 02320687 2000-09-21
1 preparations. This relationship, however, would not necessarily be the same
if the price of the
2 different enzyme preparations was different. In addition, the advantage of
the two methods,
3 especially for the method using maximal profit, is that they do not require
a knowledge of
4 enzyme activity, the combination of enzymes used in a preparation, and the
site of action of the
enzymes in the gut. The information required for latter method (the maximal
profit) is that (1) the
6 model equations be used to establish the influence of different
concentrations of different enzyme
7 preparations on chick performance and (2) the price of the major ingredients
used in a diet. The
8 method proposed in this study therefore provides a simple way to evaluate
the collective effect of
9 different enzyme preparations when incorporated into chick diets based on
maximal economic
returns.
11 Identifying the Most Profitable Cereal When Used l~th a Feed Enzyme
12 On the basis of the proposed method (Zhang et al., 1996), the most suitable
cereal for a target
13 enzyme preparation can be determined from the slope of a log-linear model.
In this study (study
14 2), the B values for the feed to gain ratio were calculated from the data
of Marquardt et al.
(1994). The sequence of cereals producing the greatest response to an enzyme
preparation in
16 decreasing order were rye, barley, wheat, and corn (negative control)
(Table 3). However, the
17 sequence of the cereals that yielded the maximum profit following enzyme
addition was
18 different. The maximal profits obtained when the enzyme preparation was
added to a barley-,
19 corn-, wheat-, and rye-based diet were $ 135.00, $ 134.45, $ 133.55, and $
123.96 per 1000 birds,
respectively when the price of all cereals were the same (Table 3). Therefore,
under these
21 conditions, the relationship between the magnitude of the B values for feed
to gain ratio and the
22 maximal profit was low ( rz = 0.61, P = 0.2171). This disagreement was also
observed in the third
13
CA 02320687 2000-09-21
1 study ( rz = 0.59, P = 0.2340). The reason for this discrepancy is
attributed to the fact that the B
2 values reflect the overall response of chicks to different amounts of an
enzyme added to different
3 cereal-based diets while the maximal profits are not only affected by the
efficacy of the enzyme
4 (B value) but also by the response of chick when fed different cereal-based
diets without enzyme
addition (A), and by the cost of the feed and the enzyme. The results
therefore demonstrate that
6 the latter method (maximal profit) is more useful than the former procedure
(B value) for the
7 feed or enzyme industry in determinating which cereal should be used with a
given feed enzyme
8 to obtain the maximum profit. In addition, if the prices of wheat and corn
were assumed to be $
9 0.12 and $ 0.13 per kg, wheat yielded a greater profit than corn and the rye
grain at $ 0.08 per kg
becomes a competitive cereal with wheat or corn ( $123.96 per 1000 birds for
rye vs. $ 126.00 or
11 $ 126.73 per 1000 birds for corn or wheat). These results demonstrate that
the price of a cereal
12 also influences profitability when a special feed enzyme is added to the
cereal-based diet.
13 Therefore, an acceptable price for a substituted cereal such as rye, when
used with an enzyme,
14 could be determined by comparing its maximal profit with that obtained by
the use of the
standard cereal such as wheat.
16 Optimal Amounts of Enzyme and Cereal That Should be Used in a Diet
17 One of the important applications of MPEA is to determine the amounts of an
enzyme and a
18 cereal that should be used in the diet to obtain a maximum profit.
Generally, the performance
19 response of chicks fed a diet with increasing amounts of an enzyme is a
hyperbolic saturated
response pattern. It is well known that equal incremental amounts of enzyme
when added to a
21 diet results in diminishing incremental changes in chick performance
(Friesen et al., 1991;
22 Bedford and Classen, 1992; Marquardt et al., 1994, Zhang et al., 1996).
However, this study
14
CA 02320687 2000-09-21
1 demonstrates that the dose response of profit obtained with the addition of
a feed enzyme yields a
2 quadratic rather than a hyperbolic pattern. The results, as shown in Figures
2 and 3, indicate that
3 the profit obtained with increasing amounts of a feed enzyme was increased
to a certain point.
4 After that, the profit decreased with increasing amounts of the enzyme
(Figures 2 and 3). This
point can be readily calculated using the MPEA. The results demonstrated that
the optimal
6 amounts of different enzyme preparations that should be added to a diet
(Table 2) were
7 considerably different for a given feed enzyme when added to different
cereal-based diets (Table
8 3), and for a feed enzyme when added to a diet with varying the proportions
of two cereals (Table
9 4). These results, however, demonstrated that there was the high correlation
between the values
of B for feed to gain ratio and the optimal amount of an enzyme that should be
used in a diet ( rz
11 = 0.99, P < 0.0005 for the first study, Table 2; rz = 0.92, P < 0.05 for
the second study, Table 3; rz
12 = 0.89, P < 0.06 for the third study, Table 4). Therefore, the amount of an
enzyme that should be
13 used in a diet to obtain maximal profit increases with an increasing B
value for the feed to gain
14 ratio. In addition, the optimal amounts of the two inputs to obtain maximum
profit can also be
determined by the MPEA. This is shown by the arrows indicated in Figure 4. The
two variables
16 used in this study were variable amounts of enzyme and variable proportions
of rye and wheat.
17 Profct Contours or Isoquants
18 The objective of obtaining maximal profit by enzyme addition to a given
diet may not be the
19 only goal for a feed company or poultry farm. In some cases, the question
that has to be asked is,
does the enzyme and substituted cereal, used at various levels and in
different combinations, give
21 the expected profit? The relationships among amounts of enzyme added to the
diet, the relative
22 concentrations of two cereals (rye vs. wheat), the cost of the enzyme
preparation, and the
CA 02320687 2000-09-21
1, resulting profit are illustrated in Figure 4. The two-dimensional figures
on the right side of Figure
2 4 represents the contour of response associated with horizontal slices of
the figure on the left.
3 These lines, called profit contours or isoquants, provide a useful tool to
determine any
4 combination of inputs such as amounts of an enzyme and rye used in a diet
for any fixed level of
profit. For example, if the price of enzyme was $ 5 / kg (middle figure), it
is possible to obtain $
6 65 (line labelled 65) of profit per 1000 birds with various combinations of
rye (levels from 7 to
7 3 8 %) and an enzyme (levels from 0 to 1.6 %). The arrows ( 1 ) in the
figures indicates the amount
8 of enzyme that should be used to yield maximal profits. For example, maximum
profits of $
9 71.72, $ 71.27, or $ 70.98 per 1000 birds was obtained when the enzyme
content was 0.27, 0.16,
or 0.11 %, the rye content was 0, 0, or 0 %, and enzyme cost was $ 3, $ 5, or
$ 7 per kg,
11 respectively. Different combinations of these inputs represent the optimal
amounts of the enzyme
12 and the rye that should be used in the diet to obtain maximum profits.
13 Decision Maker for Price of Enzyme and Cereal Used
14 There are many factors that influence the profit obtained when a feed
enzyme is added to a
diet. They included the amount of enzyme added, the type and amount of
cereals, the efficacy of
16 the feed enzyme, and the price of enzyme and cereals used. Once the profit
function is
17 established, any variable in the equation can be calculated and analyzed
provided other variables
18 are fixed. Therefore, the price that should be paid for an enzyme and a
substituted cereal can be
19 determined. This can be illustrated by the comparison of two enzyme
preparations, Cellulase Tv
concentrate (CT) and Celluclast (CC). The results in Table 2 indicated that
the maximal profits
21 per 1000 birds for CT and CC were $ 67.29 and $ 61.27 per 1000 birds when
the price of both
22 enzyme preparations was $ S per kg. If the maximal profit of $ 67.29 per
1000 birds was the
16
CA 02320687 2000-09-21
1 target for both enzyme preparations, the price of CC should be reduced from
$ 5 to $ 0.9 (Figure
2 2). The result suggest that the competitive price of CC can be determined by
comparing its
3 maximal profit with that of CT. Let us assume that CC was an enzyme
preparation being
4 developed to compete with CT for rye-based diets. Two possible methods could
be used for CC
in order to obtain the same maximal profit as that of CT. The first would be
to reduce its price
6 and the second would be to improve its efficacy (B value). The results
indicated that an 82%
7 decrease in the price of CC ($ 5 to $ 0.9) would be required to yield the
same maximal profit ($
8 67.29 /1000 birds) as obtained with CC at $ 5 / kg. However, the same
results could be obtained
9 with a 17 % improvement in the efficacy of CC, an increase in its B value
for the feed to gain
ratio from -0.211 to -0.247. This suggests that an improvement in the
ef~'icacy of an enzyme is a
11 much more effective means of increasing profitability than that obtained by
reducing its price. In
12 some cases, it is not possible to obtain an equivalent maximal profit by
changing the price of a
13 feed enzyme. For example, the only way that Finizym could yield the same
maximal profit as
14 CT would be to improve its efficacy, i.e. improvement of its B value from -
0.172 to -0.247 as
shown in Table 2.
16 In addition, the maximal profit is also influenced by the price of the
cereal used in a diet. As
17 indicated in Table 3, rye grain cannot compete with wheat when the price of
these cereal are the
18 same. However, when a higher price of wheat was used, rye grain could yield
a similar maximal
19 profit to that obtained with wheat. This strategy could also be used by a
feed industry to
determine the expected price of a target cereal in order to obtain a certain
level of maximal profit.
21 In conclusion, the MPEA that was developed in this study can be used by the
enzyme and feed
22 industries to evaluate different enzyme preparations based on their
profitability, to determine the
17
CA 02320687 2000-09-21
1_ maximal economic return that can be obtained with the optimal inputs of
feed ingredients such as
2 type and amounts of cereals and enzymes, and to analyze the relationship
between the price of a
3 feed enzyme or a cereal and the economic return. This study demonstrates
that a knowledge of
4 nutrition in combination with computer technology and the modelling method
can provides
nutritionists and managers in the enzyme and feed industry with useful
information for their
6 research activities and business decisions.
7
8
9
11
12
13
14
16
17
18 ACKNOWLEDGMENTS
19 The authors would like to thank the supports the Natural Science and
Engineering Research
Council of Canada, Ottawa, ON, Canada, K 1 G 1 FS and University of Manitoba,
Winnipeg, MB,
21 Canada, R3T 2N2. The authors also thank M. Popp for his invaluable
assistance.
22
18
CA 02320687 2000-09-21
1 REFERENCES
2 Antoniou, T.C., R.R. Marquardt, and P. E. Cansfield, 1981. Isolation,
partial characterization,
3 and antinutritional activity of a factor (pentosans) in rye grain. J. Agric.
Food Chem.
4 29:1240-1247.
Bedford, M. R., 1997. Reduced viscosity of intestinal digesta and enhanced
nutrient digestibility
6 in chickens given exogenous enzymes. Pages 19-28 in: Enzyme in Poultry and
Swine
7 Nutrition. R.R. Marquardt, and Z. Han, ed. International Development
Research Centre,
8 Ottawa, ON, Canada.
9 Bedford, M. R., and H. L. Classen, 1992. Reduction of intestinal viscosity
through manipulation
of dietary rye and pentosanase concentration is effected through changes in
the
11 carbohydrate composition of the intestinal aqueous phase and results in
improved growth
12 rate and food conversion e~ciency of broiler chicks J. Nutr. 122:560-569.
13 Boros, D., R.R. Marquardt, and W. Guenter, 1998. Site of exoenzyme action
in gastrointestinal
14 tract of broiler chicks. Can. J. Anim. Sci. 78:599-602.
Fengler, A. L, and R.R. Marquardt, 1988. Water-soluble pentosans from rye: II
Effects on rate of
16 dialysis and on the retention of nutrients by the chick. Cereal Chem. 65:
298-302.
17 Fengler, A. L, J. R. Pawlik, and R. R. Marquardt, 1988. Improvements in
nutrient retention and
18 changes in excreta viscosities in chicks fed rye-containing diets
supplemented with fungal
19 enzymes, sodium taurocholate and penicillin. Can. J. Anim. Sci. 68:483-491.
Friesen, O.D., W. Guenter, B.A. Rotter, and R.R. Marquardt, 1991. The effects
of enzyme
21 supplementation on the nutritive value of rye grain (Secale cereale) for
the young broiler
22 chick. Poultry Sci. 70:2501-2508.
19
CA 02320687 2000-09-21
1 Guenter, W., 1997. Practical experience with the use of enzymes. Pages 53-62
in: Enzyme in
2 Poultry and Swine Nutrition. R.R. Marquardt, and Z. Han, ed. International
Development
3 Research Centre, Ottawa, ON, Canada.
4 Heady, E. D., and J. L. Dillon, 1961. Economic applications. Pages 31-72 in:
Agricultural
S production functions. E.O. Heady, and J. L. Dillon, ed. Iowa State
University Press,
6 Ames, Iowa.
7 Kuo, J., and J. Norby, 1992. Sigma Plot~, Scientific Graphing Software,
User's manual. Jandel
8 Scientific, San Rafael, CA.
9 Marquardt, R. R., 1997. Enzyme enhancement of the nutritional value of
cereals: role of viscous,
water-soluble, nonstarch polysaccharides in chick performance. Pages 5-17 in:
Enzyme in
11 Poultry and Swine Nutrition. R.R. Marquardt, and Z. Han, ed. International
Development
12 Research Centre, Ottawa, ON, Canada
13 Marquardt, R. R., and M. Bedford, 1997. Recommendations for future research
on the use of
14 enzymes in animal feeds. Pages 129-138 in: Enzyme in Poultry and Swine
Nutrition. R.R.
Marquardt, and Z. Han, ed. International Development Research Centre, Ottawa,
ON,
16 Canada.
17 Marquardt, R. R., D. Boros, W. Guenter, and G Crow, 1994. The nutritive
value of barley, rye,
18 wheat and corn for young chicks as aRected by use of a Trichoderma reesei
enzyme
19 preparation. Anim. Feed Sci. Technol. 45:363-378.
McCleary, B. V., 1992. Measurement of endo-1,4-~i-D-xylanase. Pages 161-170
in: Xylans and
21 xylanases. V. J. Beldman, G. Kusters- Van, M.A. Someren, and A.G.J.
Voragen, ed.
22 Elsevier Science Publishers, Amsterdam.
CA 02320687 2000-09-21
1 Rotter, B.A., M. Neskar, R.R. Marquardt, and W. Guenter, 1989b. Effects of
different enzyme
2 preparations on the nutritional value of barley in chicken diets. Nutr. Rep.
Int. 39:107-
3 120.
4 SAS., 1988. SAS/STAT'~ Users' Guide (Release 6.03). SAS Inst. Inc., Cary,
NC.
Seeta, R., V Deshpande, and M. Rao, 1989. Role of (3-xylosidase in
hemicellulose hydrolysis by
6 xylanase from Penicillium funiculosum. Biotechnol. Appl. Biochem. 11:128-
132.
7 Zhang, Z., R. R. Marquardt, and W. Guenter, 2000. Evaluating the efficacy of
enzyme
8 preparations and predicting the performance of Leghorn chicks fed rye-based
diets using a
9 dietary viscosity assay. Poultry Sci. (accepted).
Zhang, Z., R. R. Marquardt, W. Guenter, and Z. Han, 1997. Effect of different
enzyme
11 preparations supplemented in a rye-based diet on the performance of young
broilers and
12 the viscosity of digesta and cloacal excreta. Chinese J. of Animal Sci. 34
(1): 3-6.
13 Zhang, Z., R. R. Marquardt, G Wang, W. Guenter, G H. Crow, Z. Han, and M.
R. Bedford,
14 1996. A simple model for predicting the response of chicks to dietary
enzyme
1 S supplementation. J. Anim. Sci. 74: 394-402.
16 Ziggers, D. 1999. Enzymes: hidden catalysts come out of the dark. Feed
Tech. 3(6):23-33.
21
CA 02320687 2000-09-21
FIGURE 1. Principle and Application of the Multi-purpose Enzyme Analyzer for
Use of
Enzymes in Poultry Feeds
FIGURE 2. Estimated effect of price of enzymes and the amounts of enzymes
added to a barley-
based diet on the profit per 1000 birds in a one-week feeding study. The
enzyme preparations
used in this figure were CC (Celluclast ) from Novo A/S Demark and CT (
Cellulase Tv
concentrate) from Miles Laboratories Inc. Data used for the calculations were
from Rotter et al.,
1989.
FIGURE 3. Profit as affected by cereal price and amounts of an enzyme added to
the cereal-based
diets. Different (A) and the same (B) price of cereals were used to calculate
profit ($/bird). The
assumed cost of the enzyme was $ 5 / kg. Data used for the calculations were
from Marquardt,
1994. C, corn; W, wheat; B, barley; and R, rye.
FIGURE 4. Effect of different combination of two variables, amounts of enzyme
(XE) and rye
(XR) added to diets on the profit of chickens fed diets from 1 to 19 d of age.
Cereals in the diet
were wheat plus rye (60 %). The profit function were: II = Py Y - F ~ ( Pi Xi
), where Y = (404 -
2.04XR+ 5.25 X 1 O-3XRZ - 3.20X I O~XR3 ) + (9.78 + 3.49x 1 OXR - 1.29 x 1 O-
'XRZ + 1.06X 10~ XR3) log
(2150 X + 1 ), and F = (648 - 8.52 X 10-ZXRZ + 8.33 x 1 O~XR3) + (2.64 + 2.27
x I O-ZXRZ - 2.10 X 10~
XR3) log (2150 X + 1 ); II = profit ($/1000 birds), Y = weight gain (g), F =
feed consumption (g),
Py and Pi represented the price of chickens and the price of the i-th
ingredient (Xi) in a diet. The
22
CA 02320687 2000-09-21
plots on the left gives the three-dimensional relationship for relative amount
of rye in the diet
(the balance is wheat), the amount of enzyme added to the diet, and the
profits obtained assuming
wheat and rye costs are $ 0.12 and 0.08 per kg, respectively, and that of
enzyme is $ 3, S, or 7 per
kg. The figures on the right are the profit contours of two-dimensional slices
of that on the right
for diets containing different amounts of enzyme and different percentage of
rye in the diet. The
number in each line represents the fixed profit that can be obtained by
feeding different amounts
(%) of rye and enzyme. The arrow indicated the amount of enzyme that should be
used to obtain
maximal profits. Data used for the calculations were from Bedford and Classen,
1992.
23
CA 02320687 2000-09-21
Table 1. The production and feed consumption functions established from a log-
linear model for
the data from Zhang et al. ( 1996, study 1 ), Rotter et al. ( 1989, study 1 ),
Marquard et al.( 1994, study 2),
and Bedford and Classen (1992, study 3)
Cereal' Y = Weight gain (g)2 r SD3 F = Feed intake (g)Z r SD3
(Enryme)
Barley 31.4 + 7.68 log 0.99 2.03 80.2 + 7.27 log 0.99 1.67
(CT)" ( 105 X +1 ) ( 105 X +1 )
Barley 31.0 + 6.79 log 0.99 0 80.1 + 7.72 log 0.99 0.66
(CC) ( 105 X +1 ) ( 1 OS X +1 )
Barley 30.8 + 4.99 log 0.99 1.06 79.9 + 5.75 log 0.99 0.28
(FZ) ( 105 X +1 ) ( 105 X +1 )
Barley 30.3 + 4.49 log 0.92 3.21 79.3 + 4.61 log 0.93 3.28
(CF) ( 105 X +I ) ( 105 X +I )
Barley 30.6 + 4.00 log 0.96 1.91 79.5 + 4.63 log 0.94 2.94
(SP) ( 105 X +1 ) ( 105 X +1 )
Rye(RM1)B536+45.61og(10'X+1)0.99 7.3 1309+45.61og(10~X+1)0.98 13.4
Rye (NQ)549 + 52.2 log 0.98 13.1 1317 + 59.6 log 0.94 26.2
( 10' X +1 ) ( 10' X +1 )
Corn 135 - 1.67 log 0.96 0.9 275 - 1.16 log -0.83 4.3
(KC)~ (IOaX +1) (10'X +I)
Wheat 125 + 0.81 log 0.98 0.8 248 + 0.43 log 0.9 1.1
(KC) (10' X +1) (10'X +1)
Barley 113 + 2.26 log 0.99 2 220 + 4.87 log 0.99 0.3
(KC) ( 10' X +I ) ( 10~ X +1 )
Rye (KC)97 + $.76 log 0.99 0.3 220 + 9.09 log 0.99 2
( 10 X +1 ) ( 10 X +I )
0% rye (PP)° 399 + 3.55 log (10'°X +1) 0.81 11.4 664 + 13.1 log
(l0 X +1) 0.52 10.7
20% rye (PP) 359 + 6.28 log (10' X +i) 0.99 2.5 622 + g.01 log (10° X
+1) 0.57 20.1
40% rye (PP) 306 + 21.6 log (105 X +i) 0.98 9.2 561 + 30.8 log (10° X
+I) 0.93 21
60% rye (PP) 232 + 54.4 log ( 10' X +1 ) 0.98 13.7 530 + 63.7 log ( 1 Oz X +I
) 0.94 20.6
' Data from four studies were used to develop the prediction equation for
weight gain, Y = A + B log
(CX +1 ), and feed consumption, F = a + b log ( cX + 1 ), where Y and F are
weight gain (g) and feed
consumption (g), X is the amount of an enryme (%) added to a cereal-based
diet, A, B, C and a, b, c are
the coeffcients of the log-linear equations for weight gain and feed
consumption, respectively. The
performances of chicks predicted by the equations were the values per bird
when Leghorns were fed from
24
CA 02320687 2000-09-21
7 to 14 d (A: Rotter et al., 1989) and from 7 to 21 d (C: Marquardt et al.,
1994), and the values per 6
birds when Leghorns were fed from 7 to 21 d (B : Zhang et al., 1996), and when
broilers were fed from 1
to 19 d (D: Bedford and Classen, 1992). The relative proportion of rye and
wheat in the different diets
were: 0, 60; 20, 40; 40, 20; and 60, 0.
2 The enzyme preparations used in the studies were RM1 and PP (a pentosanas
preparation) from
Finnfeed International Ltd; NQ and KC (Kyowa Cellulase) from Nutri-Quest; CT
(Cellulase Tv
concentrate) from Miles Laboratories Inc.; and CC (Celluclast), FZ (Finizym),
CF (Cereflo), and SP
(SP249) from Novo A/S Denmark.
' SD represents the residual standard deviation of regression for the log-
linear equations.
CA 02320687 2000-09-21
TABLE 2. Effect of different enzyme preparations added to a barley- or rye-
based diet on the
efficacy of enzyme (B values), the optimal amounts of enzymes and the maximal
profits obtained
from Leghorn chicks in a one-week (Rotter et al., 1989) or two-week (Zhang et
al., 1996) feed
study (study 1 )'
Source of Enzyme B Value3 Optimal Enzyme4 Maximal Profit
Data Preparation2 (%) ($/1000 birds)
Rotter et Cellulase -0.247 0.656 67.29
al., Tv
1989 Celluclast -0.211 0.56 61.27
Finizym -0.172 0.452 51.91
Cereflo -0.171 0.439 49.27
SP249 -0.139 0.3 85 46.79
Zhang et RM 1 -0.0943 0.31 S 1 O 1.19
al.,
1996 NQ -0.0963 0.348 104.38
' The assumed price for enzyme preparations used in the two studies was $ 5
per kg.
z The enzyme preparations used in the study of Rotter et al.( 1989) and Zhang
et al. ( 1996) were
Cellulase Tv concentrate (Trichoderma viride) from Miles Laboratories Inc. and
Cellucast (T.
ressei) Finizym (Aspergillus niger), Cereflo (Bacillus subtilis), and SP249
(Aspergillus niger)
from Novo A/S Demark; and RM1 (T. longibrachiatum) from Finnfeeds
International Ltd. and
NQ (T. reesei) from Nutri-Quest.
3 The B values were the slope of log-linear model equation calculated from the
feed to gain ratio
data. The values are the indexes of the efficacy of a feed enzyme added to a
diet (Zhang et al.,
1996; 2000).
26
CA 02320687 2000-09-21
4Amounts of enzyme to yield a maximum profit.
27
CA 02320687 2000-09-21
TABLE 3. Effect of cereal prices on optimal amounts of an enzyme added to
different cereal-
based diets and their maximal profits.
Value Same OptimalMaximal DifferentOptimalMaximal
Cereal of Pricez Enzyme Profit Price2 Enzyme Profit
B'
($/kg) 3 ($/1000 birds)($/kg) 3 ($/1000 birds)
(%) (%)
Corn 0.01 0.08 0 134.45 0.13 0 126
Wheat -0.03 0.08 0.0339 133.55 0.12 0.0335 126.73
Barley -0.04 0.08 0.0815 135 0.08 0.0815 135
Rye -0.0900.08 0.3419 123.96 0.08 0.3419 123.96
' The B values are the slope of log-linear model equation calculated from the
feed to gain ratio
data (Zhang et al., 1996; 2000). The values are indices of the efficacy of a
feed enzyme when
added to different diets.
ZThese values represent the price of the cereals. The assumption was that the
enzyme (Kyowa
Cellulase, Finnfeeds International Ltd.) cost was $ 5 per kg.
3The optimal amount of enzyme calculated is that amount of enzyme that yield
maximal profits.
28
CA 02320687 2000-09-21
TABLE 4. Effect of price of an enzyme and cereals on the maximal profits and
the optimal
amounts of an enzyme added to diets with different proportion of rye
Price of Enzyme ($/kg) $ 3 $ 5 $ 7
Price Difference of Cereals $ 0.02 $ 0.04 $ 0.02 $ 0.04 $ 0.02 $ 0.04
( o $ / kg)'
Rye in B value' Optimal enzyme (%)
diets2
0 % -0.0323 0.273 0.273 0.159 0.159 0.113 0.113
20 % -0.0482 0.461 0.462 0.27 0.271 0.191 0.192
40 % -0.0544 0.738 0.742 0.435 0.438 0.309 0.311
60 % -0.1867 1.262 1.272 0.748 0.754 0.537 0.537
Maximal profit ($/1000 birds)
0 % -0.0323 71.72 71.72 71.27 71.27 70.98 70.98
20 % -0.0482 68.15 68.59 67.4 67.83 66.91 67.34
40 % -0.0544 65.21 66.07 64.01 64.86 63.23 64.08
60 % -0.1867 63.27 64.58 61.19 62.48 59.85 61.13
' This price presents the net difference between the price of wheat and the
price of rye that was
assumed as a cheap and substituted cereal for wheat in diets.
Z The corresponding amount of wheat in the four diets was 60, 40, 20, and 0 %,
respectively.
3 The B values were the slope of log-linear model equation calculated from the
data of feed to
gain ratio. The values are indexes of the efficacies of a feed enzyme when
added to a diet with
different levels (Zhang et al., 1996; 2000).
29
CA 02320687 2000-09-21
'+ Introduction
World feed production for industrialized farming currently tops 575 million
tonnes
6 annually with about 57 % of the production being for pigs and poultry
enterprises (Dunn, 1999,
7 Hofinan, 2000). However, only about 6% of manufactured animal feed contain
enzymes. The
8 worldwide feed enzyme business is now estimated to be worth about $100
million, more than 20
9 times greater than the 1990 value. The potential is even greater (McCoy,
1998). Currently most
of the enzymes that are used in feeds are xylanases for wheat- and rye-based
diets and (3-
11 glucanases for barley- and oat-based diets. The target of these enzymes are
the non-starch
12 polysaccharides (NSPs) that are found in cereals; they include xylanases
for xylans and ~i-
13 glucanases for (3-glucans. Phytase is also widely used (Marquardt, 1997;
Ziggers, 1999). The use
14 of NSP enzymes in the animal feed industry has greatly expanded in the past
ten years especially
in countries like Canada that utilizes large quantities of cereals such as
barley, wheat, triticale,
16 and rye in poultry and pig diets. As biological catalysts, NSP enzymes are
able to neutralize the
17 negative effects produced by certain viscous NSP in these cereals. These
enzymes when added to
18 diets, especially for poultry, have been shown to improve the efficiency of
feed utilization,
19 increase the rate of growth, improve the health of the gastrointestinal
tract, and reduce
environmental pollution due to a decreased output of manure and gases such as
ammonia
21 (Marquardt, 1997; Choct, 1997; Bedford, 1997b). However, many unseen
benefits of exogenous
22 enzymes will gradually be explored in the future. The exogenous enzymes as
feed additives has
3
CA 02320687 2000-09-21
~1 considerable potential since they are efficient in their catalytic
functions and safe in applications.
2 Although feed enzymes have been proven to be highly beneficial, the use of
enzymes has
3 many problems that must be solved before their full potential is reached.
One of the problems
4 that has to be solved is how to accurately determine the efficacy of a feed
enzyme added to a diet.
S Most feed enzymes are primarily derived from different bacteria (e.g.
Bacillus spp) and fungi
6 (e.g. Aspergillus and Trichoderma spp). The major enzymes contained in many
commercial
7 enzyme preparations (i.e., ~i-glucanases) are often intended for certain
target-cereals (i.e., barley).
8 Although enzymes are labeled as if they all have the same effect on selected
cereals, they often
9 have different pH optimums, substrate preferences, temperature optimums and
thermal
stabilities. In addition, the reaction conditions where exogenous enzymes act
in the gut are
11 determined by the nature of condition in the intestine with very limited
possibilities for
12 modification (Classen, 1996; van de Mierop and Ghesquiere, 1999). Also, the
structure and
13 contents of the target substrates within and between cereals for enzymes
are complex and vary in
14 nature. Consequently, the efficacy of most enzyme preparations varies
considerably.
World markets are becoming less insular and subject to increasing
international competition.
16 Faced with the rapid expansion of feed enzyme markets, nutritionists in the
feed industry often
17 do not know how to select an enzyme preparation that is the most effective
for their products.
18 Currently, comparison among different enzyme preparations has been often
carried out on the
19 basis of the same amount of different enzyme preparations added to a diet.
The amount of
enzyme preparations that are added to a cereal based diet is often determined
on the basis of an
21 enzyme assay in a laboratory or by the level that is recommended by the
manufacturer (Boros et
22 al., 1999; Guenter, 1997). However, it is difficult to correctly evaluate
different enzyme
4
CA 02320687 2000-09-21
~1 preparations based on their activities, since many enzyme preparations are
from different sources,
2 contain a different spectrum of enzymes with different catalytic properties.
The selection of the
3 correct assay conditions such pH, especially when comparing the activity of
different feed
4 enzymes, is essential because the selected pH will bias results in favor of
an enzyme whose
optimal pH is closest to the selected pH. In addition, enzyme assay conditions
vary considerably
6 among laboratories and they often do not reflect conditions at the site of
action of exogenous
7 enzymes in the gastrointestinal tract. Therefore, the successful development
of a method that
8 accurately evaluated the efficacy of a feed enzyme is highly important. This
would not only
9 greatly assist the feed industry in the selection of an enzyme preparation
having the highest
efficacy, but would also establish a standard to evaluate the effect of a new
generation of enzyme
11 preparations (a cocktail vs. a single type of enzyme), recombination DNA
enzymes (a
12 modification enzyme product vs. a natural enzyme preparation), and the
processing of enzymes
13 (a dry mix vs. a liquid spray).
14 Another problem is how to accurately predict the response of a feed enzyme
when added to a
diet. There has been increasing interest in quantitatively studying the effect
of the input into the
16 diet of different levels of feed enzymes on the outputs or the performance
of chickens (Bedford
17 and Classen, 1992; Friesen et al., 1991; Marquardt et al., 1994; Rotter et
al., 1989). The primary
18 objectives of these studies has been to estimate the optimal level of feed
enzyme addition
19 required to obtain maximal performance in chickens (Bedford and Classen,
1992; Friesen et al.,
1991 ). Frequently, the experimental designs and statistical procedures have
only provided trends
21 on the effects of enzyme treatment but have not provided precise prediction
values that can be
22 obtained when a given enzyme is added to a given diet. From this
standpoint, it has been
5
CA 02320687 2000-09-21
'1 impossible to conduct refined studies on the relationship between inputs
(enzymes) on outputs
2 (chick performance), or to establish the most profitable combination of
inputs for a specified
3 output. In addition, researchers in nutritional fields have generally been
concerned only with
4 biological rather than economic criteria to evaluate the effects of feed
enzymes and to make their
recommendations. The largest weight gain or the lowest feed to gain ratio per
unit of enzyme
6 addition have often been the criteria used for evaluation of
performance(Bedford and Classen,
7 1992; Friesen et al., 1991). However, the most profitable output or optimal
input has seldom
8 been the same as these maxima or minima. Even where the objective was
prediction of physical
9 maxima or minima, the exact values can only be accurately estimated by a
prediction equation
where the experimental data are used to estimate this equation.
11 Recently, we have applied a log-linear model to predict the response of
chickens to dietary
12 enzymes (Zhang et al., 1996). The model was able to accurately predict the
performance of
13 chickens fed diets containing different amounts of an enzyme and different
proportions of two
14 cereals. Data from many dose response studies of feed enzymes, although not
designed for these
purposes, confirmed that the simple log-linear equation was accurate. In
addition, the efficacy of
16 any enzyme preparation for a particular cereal or class of poultry with
regards to any index of
17 animal performance such as weight gain or feed to gain ratio can be
determined from a single
18 value of B, the slope of the model equation (Marquardt and Bedford, 1997;
Zhang et al., 1996).
19 Therefore, it is possible to correctly evaluate the efficacy of a feed
enzyme and to accurately
predict the response of chickens to an enzyme when it is added to a diet using
this new approach,
21 the log-linear model.
22 This review will mainly discuss our recent research on the use of the log-
linear model to
6
CA 02320687 2000-09-21
1 evaluate and predict the response of chicks when a feed enzyme is added to
the diet. It will cover
2 the following topics: hypothesis and the development of the log-linear
model, evaluating the
3 efficacy of a feed enzyme using the model, predicting the response of chicks
to a feed enzyme,
4 evaluating and predicting the profitable effect of a feed enzyme, and
finally the use of an in vitro
assay to predict in vivo response to an enzyme.
6
7 Hypothesis and the Log-linear Model
8 Dose Response Studies
9 Several dose response studies in our laboratory (Rotter et al., 1989;
Friesen et al., 1991;
Marquardt et al., 1994) have determined the level of a feed enzyme required to
obtain maximal
11 growth performance in chicks fed cereal-based diets. In a study by Friesen
et al. (1991), a crude
12 xylanase preparation with different levels of the enzyme was added to a 60%
rye-based diet. The
13 results indicated that the performance response of the growing chicks to
increasing amounts of
14 enzyme was a typically hyperbolic pattern. The results from other studies
also supported this
observation (Bedford and Classen, 1992; Marquardt et al., 1994; Rotter et al.,
1989; Zhang et al.,
16 1996). In addition, the efficacy of different enzyme preparations, as
determined by their effect on
17 the performance of Leghorn chicks when they were added to barley-based
(Rotter et al., 1989)
18 and rye-based (Zhang et al., 1996) diets, was evaluated. Marquardt et al.
(1994) established the
19 dose response effect of a feed enzyme when added to different dietary
cereals (such as corn,
wheat, barley, and rye) on the performance of Leghorn chicks. Bedford and
Classen ( 1992) also
21 studied the dose response effect on chick performance and viscosity of
digesta of an enzyme
22 preparation when added to diets containing different proportional rye and
wheat. Three basic
7
CA 02320687 2000-09-21
1 characteristics of the dose response were observed.: ( 1 ) the response
pattern was typically a
2 hyperbolic curve, (2) each additional increment of enzymes that was added to
the diet produced
3 diminishing incremental responses, and (3) different maximal improvements
and diminishing
4 incremental responses were obtained with different enzyme preparations and
different cereals.
The ability to accurately predict the effect that different amounts of an
enzyme preparation have
6 on the performance of chickens would be of considerable value to the
nutritional research
7 scientist and the livestock producer. This, however, is not a simple matter
since there is not a
8 direct proportionality between the two factors, enhanced performance and
amount of added
9 enzyme.
A Log Model and its Modification
11 The hyperbolic dose response curve reflects a common biological phenomenon,
the "Law of
12 Diminishing Returns". The curve can be generated by several non-linear
models, including
13 polynomial, exponential, or logarithmical models (Almquist, 1952; SAS,
1988), or other models
14 such as segmented or logistic models (Remmenga et al., 1997). However, for
feed enzyme
research, only a few authors have used these models to fit their data. For
example, in the study of
16 Friesen et al. (' 1991 ), the exponential model was applied to estimate the
maximal effective dose
17 of a feed enzyme when added to a 60% rye-based diet. In another study,
Hesselman et al. (1982)
18 applied the polynomial model (linear and quadratic model) to predict the
effect of different doses
19 of a (3-glucanase preparation on the productive response of chick s fed
diets containing barley
harvested at two stages of ripeness.
21 Recently, Zhang et al. (1996), based on the results of two dose response
studies and some
22 published data, first applied the log model to predict the response of
chicks fed diets containing
8
CA 02320687 2000-09-21
1 enzymes. The criteria for developing this model were: ( 1 ) there must be a
good fit (high rz)
2 between the observed and predicted data (SAS, 1988), (2) the model should be
simple to
3 interpret, and (3) the model should provide useful information. The general
form of the log
4 model is written as follows:
Y=A+B logX [OJ
6 where, Y is the estimated performance value [for example, weight gain (g)],
X is the
7 concentration of an enzyme (unit per kilogram of diet or percentage of
diet), B is the slope of the
8 equation (performance change per log unit of an enzyme in the diet), A, the
intercept (Y axis),
9 theoretically represents performance without an enzyme added to the diet.
However, this value is
not readily obtained as there is no value for the log of zero (the value
without enzyme
11 supplementation, i.e., when X = 0). In order to obtain an A value, Zhang et
al. (1996) developed
12 a modified log model, Equation 1.
13 Y=A+Blog(X+E) [1J
14 In the model, an amount of enzyme (E) was selected which was very small and
close to zero. The
s value was shown to be essentially constant as it was not affected by the
concentration of
16 enzyme for a given diet.
17 The intercept, A, in Equation 1 represents chick performance when a
preselected and
18 substituted value for zero (s) is used. As such A = Y - B log g may not
yield an accurate estimate
19 of chick performance for diets that do not contain an exogenous enzyme. In
turn, the selected E
may also affect the slope B of Equation 1 [B = ( Y-A ) / log ( X + ~ )]. These
are some of the
21 weaknesses of Equation 1. In addition, the introduction of an g value into
Equation 1 not only
22 influences the accuracy of certain parameters, such as A and B, but its
value is difficult to
9
CA 02320687 2000-09-21
1 calculate, therefore an arbitrary s value must be selected (Zhang et al.,
1996). Therefore, the
2 model was further modified, as outlined below, to overcome these weakness.
In this approach s,
3 in Equation 1, was assigned a value of 1 ($ = 1) and X was amplified several
fold by use of a
4 constant (C). Therefore, the new modified equation was as follows:
Y=A+Blog(CX+1) [2]
6 The intent of this modification was the same as that obtained with the s
treatment in Equation 1;
7 that is, the value of 1 relative to CX should be very small as is E relative
to X. Equation 2, when
8 X = 0 ( i.e., without enzyme addition), therefore became:
Y=A+Blog(C X 0+ 1 ) [3]
Since C x 0 = 0, and B log 1 = 0, then
11 yo = A [4]
12 The value of A in Equation 4 clearly indicated that it represents the
predicted performance of
13 chicks without addition of an enzyme preparation (Yo). In addition, based
on the same criteria for
14 selection of s (Zhang et al., 1996), a computer program using BASIC
language was developed
based on a least squares procedure and a stepwise technique to calculate the
different parameters
16 ( A, B, and C) of equation 2. In this program A, B and C values were
selected when these values
17 yielded the highest coefficient of correlation (rz ).
18 The results from Zhang et al. (2000b) clearly demonstrated that in all
cases, the A value as
19 determined by use of Equation 2 provided a better measure of observed
performance values (Yo)
than that of Equation 1. The results also indicated that Equation 2 in
conjunction with the
21 developed computer program was a more suitable equation than Equation 1 as
it not only
22 provided a more accurate estimate of the A value than Equation 1 as
discussed above but also
CA 02320687 2000-09-21
~l overcame the main shortcoming of Equation 1 (i.e., an arbitrary s value
used to calculate the log
2 zero value).
3 Efficacy of a Feed Enzyme and Hypothesis
4 One of the important characteristics of the log model is that the model is a
non-linear model
when X (the amount of enzymes added to a diet) is the input but is a simple
linear model when
6 log X (log percentage of enzyme) is the input. These characteristics
suggested that a hyperbolic
7 or non-linear relationship between the response of chicks (i.e., chick
performance) and the
8 amount of enzyme added to a diet could be simply converted to a linear
relationship by the log-
9 linear model. In addition, Almquist ( 1952) in the study of vitamin
metabolism in the gut
demonstrated that a logarithmic method for evaluating data was extremely
useful in many
11 diversified applications of biology since these relations were merely
expressions of the Law of
12 Diminishing Returns, a common biological phenomenon. A particular valuable
feature of the
13 logarithmic method of expressing the relationship between intake and
biological response was
14 the fact that it provided a simple but accurate estimation of the slope of
the response line. The
slope of the line in the Almquist study was mainly associated with the
magnitude of the
16 conversion rate constant for a provitamin to vitamin in the intestinal
wall. The constant was
17 dependent upon many dietary and physiological factors in an absolute sense,
but was relatively
18 constant within any one bioassay. Therefore, we hypothesized that the feed
enzyme, in a manner
19 similar to the conversion of a provitamin into a vitamin, would convert a
nutrient from an
unavailable, because of anti-nutritive NSPs in the digesta, to an available
nutrient through the
21 degradation of the anti-nutritive NSPs. The magnitude of the rate of
conversion should be a
22 reflection of the ability of an enzyme to perform this task. Therefore, the
B values can be used to
11
CA 02320687 2000-09-21
1 evaluate the efficacy of a feed enzyme when added to a diet.
2
3 Evaluating the Efficacy of a Feed Enzyme
4 Comparing the Efficacies of Different Feed Enzymes
As hypothesized, the slope of the log-linear model can be used to evaluate the
efficacy of a
6 feed enzyme. This in turn can be used to compare the effects of different
enzyme preparations
7 when added to a diet, determine the suitable target cereal for a feed
enzyme, evaluate the effect of
8 a newly developed enzyme preparation and even the effect of processing on
the feed enzyme.
9 Zhang et al. (2000c) have recently tested the hypothesis using data from
Zhang et al. (1996) and
Rotter et al. ( 1989). In the study of Zhang et al.( 1996), two enzyme
preparations, RM 1 and NQ,
11 with similar xylanase activity were used to compare their effect on the
performance of chicks
12 when the enzyme was added to a rye-based diet. The results indicated that
the B values of NQ
13 compared to RM1 in the first week for weight gain and the feed/gain ratio
were 22.3 vs. 18.0 g
14 weight gain per log unit of enzyme added and -0.13 vs. -0.09 g gain/g feed
intake/ log unit of
enzyme added, which agrees with the trend seen for the corresponding overall
net improvements
16 in chick performance (Ym - Yo, the maximal response related to the control)
[i.e., 112 vs. 88 (g),
17 and -0.58 vs. -0.55 (g/g)) during the same period. Although the
relationships between the B
18 values and the Ym - Yo values during wk 1 and wk 2 were high ( r = 0.99, P
< 0.001 ), they did
19 not change proportionately. Similar relationships were also obtained when
the data from Rotter et
al. (1989) were analyzed (Zhang et al., unpublished data). In their study of
dose response, five
21 enzyme preparations, Cellulase Tv concentrate (CT), Celluclast (CC),
Finizym (FZ), Cereflo
22 (CF), and SP249 (SP), were used to compare the efficacy of these enzymes on
the performance
12
CA 02320687 2000-09-21
1 of Leghorn chicks fed a barley-based diet. The results indicated that the
relative B values for
2 weight gain and feed to gain ratio from for chicks 7 to 14 d of age were
7.68, 6.79, 4.99, 4.49,
3 and 4.00 (g per log percentage of enzyme) and -0.2470, -0.2113, -0.1716, -
0.1713, and -0.1386
4 (g/g per log percentage of enzyme), respectively. This trend agreed with
that of the corresponding
overall net improvements (Ym - Yo) that were obtained. The net improvements
for the five
6 enzyme preparations, CT, CC, FZ, CF, and SP, were 22, 21, 16, 16, 14 in
weight gain and -0.71,
7 -0.64, -0.54, -0.58, and -0.45 in feed to gain ratio. There were high
correlation between the B
8 values and the net improvement in weight gain ( r2 = 0.98, P < 0.0016) and
feed to gain ratio ( rz
9 = 0.96, P < 0.0041 ). These two studies clearly indicated that the B values
accurately reflected the
ability of a feed enzyme when added to a diet to improve the performance of
chicks. Therefore, it
11 is a measure of the efficacy of an enzyme.
12 Evaluating the Suitable Target Cereal for a Feed Enryme
13 The structures and contents of NSPs varies in different cereals (Marquardt,
1997). Therefore,
14 the efficacy of a feed enzyme on different cereal-based diets was different
and could also be
evaluated by the slope of the log-linear model. The dose response study of
Marquardt et al.
16 (1994) was used to test the hypothesis. In their study, different
concentrations of a feed enzyme
17 (high in both xylanase and (3-glucanase activity) were added to corn-,
wheat-, barley-, and rye-
18 based diets. The effect of the enzyme on the different cereals was then
evaluated to determine the
19 suitable target cereal for the enzyme. The results demonstrated that the
effect of the enzyme on
chick performance and the B value as calculated from Equation 2 were similar
in trend. For
21 example, the observed weight gain values (Ym - Yo) for the corn, wheat,
barley, and rye diets
22 were -6, 7, 22, and 29 g, respectively, while the B value calculated from
Equation 2 were -1.67,
13
CA 02320687 2000-09-21
1 0.81, 2.26, and 8.76 g/log of percentage enzyme added to the diet,
respectively. The correlation
2 between the two sets of data was high ( r = 0.90, P < 0.001 ). The results
suggested that the B
3 values of the log-linear equation can be used to assess the efficacies of a
feed enzyme when
4 added to different cereal-based diets. Part of the reason is the NSPs in
these cereals are different.
These relationships were also supported by the data from Bedford and Classen
(1992). In this
6 study, a dose response experiment of a feed enzyme was carried out using 4
different ratios of
7 two cereals (i.e., wheat to rye, 0:60, 20:40, 40:20, 60:0) and 6 doses of
enzyme (0, 0.1, 0.2, 0.4,
8 0.8, and 1.6 %). Their results demonstrated that the net performance
response of chicks to an
9 enzyme preparation that was high in xylanase activity increased dramatically
as the proportion of
rye was increased. The relevant B values for weight gain and feed to gain
ratio during the two
11 week experimental period for diets containing 60, 40, 20 and 0 % rye as
calculated by Equation 2
12 were 54.4, 26.1, 6.3, and 0.36; -0.103, -0.018, -0.016, and -0.013,
respectively. The B values, as
13 were the improvements in observed performance values (Ym - Yo), were
considerably higher for
14 diets containing a high compared to a low concentrations of rye which also
reflects the overall
efflcacies of an enzyme to degrade the different concentrations of its
antinutritional substrate
16 (i.e., arabinoxylan) in the diet. Again, the B values and Ym - Yo were
highly related ( r = 0.95, P <
17 0.001 ) but they did not change proportionality with the percentage of rye
in the diet.
18 Therefore, the slope of the log-linear model, the B value, is an index of
the efficacy of an
19 enzyme. This value not only provides the value which is a measure of the
efficacy of different
enzymes when the same diet is used but can also provide a measure of the
efficacy of an enzyme
21 when added to different diets or when different amounts of their target
substrates are present in
22 the diet.
14
CA 02320687 2000-09-21
1
2 Predicting the Response of Chicks
3 Accuracy of the Log-linear Model
4 Another important characteristic of the log-linear model is that the model
accurately predicts
the performance response of chicks (Zhang et al.,1996) and the viscosity
reduction of digesta in
6 the gut. In the study of Zhang et al. ( 1996), two dose response experiments
were conducted. The
7 data from Experiment 1 of the study were subjected to different types of
regression analysis
8 (Table 2). The amount of enzyme added to the diet was generally not
significantly correlated (P >
9 0.05) with chick performance during wk 1 when the data were subjected to
linear, quadratic, or
cubic regression analysis. However, when the dietary enzyme concentration data
were converted
11 into their logarithmic values and subjected to linear regression analysis,
all of the log-linear
12 values were significant (P s 0.005), with all rz values being greater than
0.88. The rz values for
13 the combined data of wk 1 and wk 2 for weight gain and feed to gain ratio
were 0.99 (P < 0.001 ).
14 In addition, the data also were subjected to other models such as the
polynomial, exponential,
and saturation models (Michaelis and Menten model), their rz values were all
less than that of the
16 log-linear model.
17 The predicted relationship between chick performance (data from Wk 1+2) and
amount of
18 enzyme added to a rye based diet (solid lines, Figure 1 ) as determined by
Equation 1 and actual
19 performance values (solid triangles or squares, Figure 1 ) demonstrate a
very close fit ( rz = 0.99,
P < 0.001 for weight gain and rz = 0.99, P < 0.001 for feed to gain ratio).
The inset of Figure 1
21 showed that there was a linear change in weight gain and feed to gain ratio
when the
22 concentration of enzyme was plotted on a logarithmic scale.
CA 02320687 2000-09-21
l General Applicability of the Model
2 The general applicability of the model was tested using data from Experiment
2 of Zhang et
3 al. (1996) and those from the literature. The objective of these analyses
was to determine whether
4 the log-linear model also yielded high rz values with these data when there
was a significant
S response to enzyme treatment. The results demonstrated that high r2 values
(0.88 to 0.999) were
6 obtained during wk 1 and during wk 1+2 of the experiment. The slope of the
lines (B) showed
7 that the response to enzyme was also higher in wk 1 and wk 1+2 but not in wk
2. Overall, the
8 data demonstrated that it is possible to predict the response to xylanase
supplementation in chicks
9 at different ages.
Data from literatures were used to determine whether a similar relationship
could also be
11 obtained between the log of the amount of enzyme added to the diet and
chick performance.
12 Among the 13 comparisons, nine yield rz values for weight gain greater than
0.91, with all but
13 one comparison being greater than 0.77 (Equation 1 ). Regression analysis
of the feed to gain ratio
14 also yielded similar trends. In addition, high rz values were obtained
under different feed
conditions [e.g., when enzyme was added to different cereals (rye, wheat, and
barley) and a grain
16 legume (lupins)] with different types of enzymes ((i-galactosidase, [i-
glucanase, and xylanase),
17 with different concentrations of two cereals in the diet (wheat and rye),
and with different ages
18 and types of chickens (Leghorn and broiler).
19 Response Surface
The model could be used not only to predict the response of a given diet to
different amounts
21 of one enzyme, but also to determine the response to different amounts of
any two dietary
22 components such as enzyme and the substituted cereal.1n order to achieve
this goal an
16
CA 02320687 2000-09-21
1 experiment must be carried out where different amounts of an enzyme is added
to diets
2 containing different proportions of two cereals. Such an experiment was
conducted by Bedford
3 and Classen ( 1992). They fed four different concentrations of rye each with
six different
4 concentrations of enzyme (xylanase) to broiler chicks from 1 to 19 days of
age. The diets
consisted of the following proportions of rye and wheat: 0:60, 20:40, 40:20,
and 60:0. The
6 amounts of the enzyme added to each of the different diets were 0, 0.1, 0.2,
0.4, 0.8, and 1.6%.
7 Mutiple regression (SAS, 1988) was used to relate the response in chick gain
(Y) to the
8 enzyme concentration (X) and the proportion of rye (Z) in the diet.
9 Y = Bo +B, log (X) + BZ Z + B3 Z log (X) [6]
This model was an extension of the models used previously in the sense that
chick performance
11 is regressed on the logarithm of enzyme concentration. The response surface
for the above model
12 is shown in Figure 2. Similar prediction equations can be generated for
feed to gain ratio or any
13 other variable that fits the model. The results suggested that the response
of chicks to an enzyme
14 supplementation can be accurately predicted not only the response to a
given diet but also to any
proportion of two cereals in diets supplemented with any given amount of an
enzyme preparation
16 (Zhang et a.,1996).
17
18 Evaluating and Predicting Efficacy of Feed Enzymes Based on their
Profitability
19 Development of a Multi purpose Enzyme Analyzer
The log-linear model we have developed provides a basis to estimate the
maximal economic
21 return when a feed enzyme is added to a diet. Based on the model, we have
further developed a
22 software package, a Multi-purpose Enzyme Analysis (MPEA) (Figure 3) for
predicting and
17
CA 02320687 2000-09-21
l evaluating the profitable effect of an enzyme in poultry feeds. The enzyme
analyzer has three
2 main applications: ( 1 ) to evaluate the effect of different enzyme
preparations added to a cereal-
3 based diet, (2) to determine the optimal amounts of an enzyme preparation
and /or a substituted
4 cereal to be used in a diet, and (3) to analyze the relationships between
the price of enzyme
preparation, and the price of the substituted cereal, and the economic return.
6 Evaluating Efficacy of Different Feed Enrymes Based on their Profitability
7 As discussed in the previous section, the slope of the log-linear model is
an index of the
8 efficacy of a feed enzyme. This evaluation, however, is only based on the
biological criteria. The
9 goal of many studies is usually to select an enzyme preparation that will
yield the greatest profit.
Zhang et al. (2000c) using the data selected from Rotter et al. (1989) and
Zhang et al. (1996)
11 demonstrated that it was possible to select an enzyme preparation, among
several different
12 enzyme preparations, that will yield a highest maximum profit when added to
a diet at a certain
13 concentration. The maximal profit per 1000 birds for the five enzyme
preparations when added to
14 the diet at the selected concentration would have been: Cellulase Tv,
Celluclast, Finizym,
Cereflo, and SP249 were $ 67.29, $ 61.27, $ 51.91, $ 49.27, and $ 46.79,
respectively (Table 3).
16 The sequence of these values also agrees with that of the B values for feed
to gain ratio from the
17 log-linear equation as indicated in Table 2 ( rz = 0.99, P < 0.0005). The
same trend was observed
18 using data from Zhang et al. (1996). The results suggested that the B
values and the estimated
19 maximal profit provided similar indices for the evaluation of different
enzyme preparations. In
addition, the advantage of the two methods, especially for the method using
maximal profit, is
21 that they do not require a knowledge of enzyme activity, the combination of
enzymes in a
22 preparation, and the best site of action of the enzymes in the gut. The
information required for the
18
CA 02320687 2000-09-21
1 method that estimates maximal profit is ( 1 ) the influence of different
concentrations of different
2 enzyme preparations on chick performance as estimated from the model
equations and (2) the
3 price of the major ingredients used in a diet.
4 Identifying the Most Profitable Cereal When Used With a Feed Enzyme
On the basis of the method that we have proposed (Zhang et al., 1996), the
most suitable
6 target-cereal for an enzyme preparation could be determined from the slope
of a log-linear model.
7 The B values for the feed to gain ratio of were calculated from the data of
Marquardt et al.
8 ( 1994). Based on the B values, the sequence of cereals producing the
greatest response to an
9 enzyme preparation in decreasing order were rye, barley, wheat, and corn
(negative control),
respectively (Table 4). However, the sequence of the cereals that yielded the
maximal profit
11 following enzyme addition was different. The maximal profit obtained by an
enzyme preparation
12 added to a barley-, corn-, wheat-, and rye-based diet was $ 135.00, $
134.45, $ 133.55, and $
13 123.96 per 1000 birds, respectively when the same price of the used cereal
was inputted (Table
14 4). The relationship between the magnitude of the B values for feed to gain
ratio and the maximal
profit values was low ( rz = 0.61, P = 0.217). This disagreement in the
sequence was also be
16 observed in the study of the data from Bedford and Classen ( rz = 0.59, P =
0.234). The results
17 suggested that the method of the maximal profit could be more useful for
the feed or enzyme
18 industry in determinating which cereal should be used with a given feed
enzyme to obtain
19 maximal profit. In addition, if the prices of wheat and corn were assumed
to be $ 0.12 and $ 0.13
per kg, wheat yielded a greater profit than corn and the rye grain at $ 0.08
per kg become a
21 competitive cereal with wheat or corn ( $123.96 per 1000 birds for rye vs.
$ 126.00 or $ 126.73
22 per 1000 birds for corn or wheat). These results suggested that the price
of a cereal also influence
19
CA 02320687 2000-09-21
1 profitability when a special feed enzyme is added to the cereal-based diet.
2 Determining Optimal Amounts of Enryme and Cereal in a Diet
3 One of the important applications of MPEA is to determine the optimal
amounts of a feed
4 enzyme and a cereal that should be used in a diet to obtain maximal profit.
Generally, the
response pattern with increasing amounts of a feed enzyme on the performance
of chicks fed a
6 diet is hyperbolic and not linear (Friesen et al., 1991; Bedford and
Classen, 1992; Marquardt,
7 1994, Zhang et al., 1996). However, the dose response pattern obtained with
the addition of a
8 feed enzyme yields a quadratic rather than a hyperbolic pattern of profit.
The results from the
9 study by Zhang et al. (2000c) indicated that the profit obtained with
increasing amounts of a feed
enzyme was increased to a certain point. After that, the profit decreased with
increasing amounts
11 of the enzyme. This point can easily be calculated using the MPEA. The
results demonstrated
12 that the optimal amounts of different enzyme preparations that should be
added to a diet, of a
13 given feed enzyme that should be added to different cereal-based diets, and
of a feed enzyme
14 added to a diet with varying the proportions of two cereals were
considerably different.
Profit Contours or Isoquants
16 The objective of obtaining maximal profit by enzyme addition to a given
diet may not bean
17 only business goal for a feed company or poultry farm. In some cases, the
question that has to be
18 asked is, does the enzyme and substituted cereal, when used at various
levels and in different
19 combinations, yield the expected profit? This question can be addressed by
use of the MPEA.
The relationships among amounts of enzyme added to the diet, the relative
concentrations of two
21 cereals (rye vs. wheat), the cost of the enzyme preparation, and the
resulting profit are illustrated
22 in Figure 4. The two-dimensional figures on the right side of Figure 4
represents the contour of
CA 02320687 2000-09-21
1 the response associated with a individual horizontal slice of the figure on
the left. The lines with
2 same numbers in the figure, called profit contours or isoquants, provide a
useful tool to
3 determine any combination of inputs such as amounts of an enzyme and rye
used in a diet for any
4 fixed level of profit. In there analyses, the assigned price of the enzyme
were $ 3, $ 5, and $ 7 /
kg (top to bottom, Figure 4) and the price of rye and wheat were $ 0.08 and $
0.12 / kg,
6 respevtively.
7 Expected Price of Enzyme and Cereal
8 There are many factors that influence the profit obtained when a feed enzyme
is added to a
9 diet. They include the amount of enzyme added, the type and amount of
cereal, the efficacy of the
feed enzyme, and the price of enzyme and cereals used. Once the profit
function is established,
11 any variable in the equation can be calculated and analyzed when other
factors are fixed.
12 Therefore, the price that should be paid for an enzyme and a substituted
cereal can be
13 determined. This can be illustrated by the comparison of two enzyme
preparations, Cellulase Tv
14 concentrate (CT) and Celluclast (CC). The results in Table 3 indicated that
the maximal profits
per 1000 birds for CT and CC were $ 67.29 and $ 61.27 per 1000 birds when the
price of both
16 enzyme preparations was $ 5 per kg. If the maximal profit of $ 67.29 per
1000 birds was the
17 target for both enzyme preparations, the price of CC should be reduced from
$ 5 to $ 0.9. The
18 result suggested that the competitive price of CC can be determined by
comparing its maximal
19 profit with that of CT. Let us assume that CC was an enzyme preparation
that was developed to
compete with CT for rye-based diets. Two possible methods could be used for CC
in order to
21 obtain the same maximal profit as that of CT. The first would be to reduce
its price and the
22 second was to improve its efficacy (B value). The results indicated that an
82% decrease in its
21
CA 02320687 2000-09-21
1 price ($ 5 to $ 0.9) would be required to yield the same maximal profit ($
67.290 /1000 birds) as
2 obtain with CC at $ 5 / kg. However, the same result could be obtained with
a 17 % improvement
3 in the efficacy of CC, an increase in its B value for the feed to gain ratio
from -0.2113 to -0.2470.
4 This suggests that an improvement in the efficacy of an enzyme is a much
more effective means
of increasing profitability than that obtained by reducing its price.
6 On the other hand, the maximal profit was also influenced by the price of
cereal used in a diet.
7 As indicated in Table 4, rye grain cannot compete with wheat when the price
of these cereal are
8 the same. However, when a higher price of wheat was used, the rye grain
could yield a similar
9 maximal profit to that obtained with wheat. This strategy could be used by a
feed company to
determine the expected price of a target cereal in order to obtain a certain
level of the maximal
11 profit.
12
13 From In Vivo Study to In Vitro Study
14 Background
Feed enzymes have been evaluated using both in vivo and in vitro procedures.
Chick
16 performance, AME, digestibility of feed nutrients, digesta viscosity
reduction for evaluating the
17 effect of a feed enzyme when added to a diet are generally classified as in
vivo evaluations. Most
18 criteria used in in vivo assays are directly related to productivity,
therefore, they are widely
19 accepted. The weaknesses of the in vivo assays are their high variation,
low sensitivity, cost, and
time requirements. On the other hand, in vitro methods for enzyme assays such
as reducing sugar
21 and viscosity assays, the dietary viscosity assay, and digestibility as
measured by various
22 incubation procedures, yielded low variation and high sensitivity, are
inexpensive and relatively
22
CA 02320687 2000-09-21
1 rapid. Therefore, they are also widely used for the evaluation of a feed
enzyme. However, there is
2 generally low correlation between the predicted values obtained from the in
vitro methods and
3 the performance of chicks that is obtained when an enzyme is added to the
diet.
4 Development of an In Vitro Dietary Enzyme Assay
Zhang et al. (2000a) have recently developed an in vitro dietary enzyme assay
to determine
6 the amount of feed enzymes that had been added to a rye-based diet and to
evaluate the efficacy
7 of enzymes. Rye was selected as a model cereal, because it contains high
concentrations of a
8 highly viscous NSP, arabinoxylans, that in turn can be effectively
hydrolyzed by preparations
9 high in xylanase. The principle of the assay was to allow the enzyme in the
diet to interact with
the substrates in a buffered suspension of the diet for an appropriate time
period followed by
11 centrifugation of the suspension and the measurement of the viscosity of
the solution. Therefore,
12 both bound and free exogenous enzymes could react with the soluble, and
insoluble NSPs of the
13 diet, similar to the condition in the gut. In this study, the relationship
between dietary viscosity
14 change and the amount of enzyme added to the diet was established (Figure
5). Viscosity was
expressed as its log value because this yields values that are equivalent to
the amount of substrate
16 hydrolyzed (Boros et al., 1993). The results demonstrated that there was a
linear relationship ( r >
17 0.99, P < 0.005) between log of the net viscosity change from the dietary
extracts and log of the
18 concentration of enzyme added to the diet for all three incubation times
(1, 2 and 8 h,
19 respectively). Using this relationship along with the appropriate
references (enzyme and diet) as
standards it should be possible to determine the amount of an enzyme in a diet
using the in vitro
21 viscosity assay. Other assays have not been able to successfully monitor
enzyme activity in the
22 diet.
23
CA 02320687 2000-09-21
1 Relationships Between Determined and Actual Enryme Activities in a Diet
2 Zhang et al. (1996) demonstrated that there was a linear relationship
between chick
3 performance and the log amounts of enzyme added to a diet. The results of
Bedford and Classen
4 (1992) indicated that there was a linear relationship between chick
performance and the log of
S intestinal viscosity. Therefore, we hypothesized that a linear relationship
exists between the log
6 of viscosity change as determined by the in vitro assay and the log amounts
of enzyme added to a
7 diet. Such a relationship was established in this study (Table 5, log CP vs.
log U/kg, r > 0.99,
8 Figure 5). The same trend was obtained for all of the different assay times
(1 to 8, data not
9 shown). The results shown in Table 3 further demonstrate that the in vitro
assay accurately
estimated the amount of enzyme in the diet when viscosity was converted into
its logarithmic
11 value but not when its arithmetic value was used ( r < 0.82, P > 0.05).
Collectively these results
12 demonstrate that when the viscosity values from the in vitro assay are
converted into their log
13 values, they can accurately predict amount of enzyme in a diet with highly
viscous compounds.
14 Prediction of Chick Performance by Use of the In Vitro Assay
The objective of this comparison was to determine if data from the in vitro
viscosity assay
16 could be used to accurately predict chick performance and to determine if
its predicted value was
17 as accurate as that obtained using known amounts of enzyme that were added
to the diet. The
18 data in Table 5 (chick performance vs. the enzyme activity added to the
diet, or measured enzyme
19 activity by the in vitro assay) demonstrate that both the in vitro assay
and the amount of enzyme
added to the diet (the input, X ) were highly correlated ( r > 0.95) with
animal performance (the
21 output, ~. In addition, the data in Figure 6 show that both amount of
enzyme added to the diet
22 (C and D) and the amount of enzyme as determined by the log of the in vitro
viscosity assay (A
24
CA 02320687 2000-09-21
1 and B) were linearly ( r > 0.99, P < 0.005) related to weight gain ( A and C
) and the feed to gain
2 ratio ( B and D). These data demonstrated that the degree of improvement
obtained when a given
3 enzyme is added to the diet is a linear function of the log of enzyme
activity which in turn is
4 directly related to the log of the net dietary viscosity change as
determined by the in vitro assay.
Therefore, the log of dietary viscosity change not only was able to estimate
the enzyme activity
6 added to the diet, but also was able to accurately predict the performance
of chickens when used
7 in conjunction with the modified log-linear model.
8 Evaluate the Efficacy of Feed Enzymes by the Assay
9 The ability of two enzyme preparations (RM1 and NQ) to improve the
performance of broiler
chicks fed a rye-based diet and to reduce the viscosity of the diet as
determined by the in vitro
11 assay were studied. The results showed that both enzyme preparations
improved chick
12 performance and decreased the dietary viscosity in a concentration-
dependent manner. Two
13 important trends were observed. First, the in vitro dietary viscosity assay
appeared to be a more
14 sensitive index for evaluating the effect of enzyme response than that
obtained from the feeding
trial. Second, the improvements in chick performance when comparing the
response of the two
16 enzyme preparations appeared to be more closely associated with the in
vitro dietary viscosity
17 change than the amounts of enzyme added to the diet. This effect may be
attributed to the
18 presence of different amounts of other viscosity reducing enzymes in the
enzyme preparations or
19 to a difference in efficacy of xylanases (i.e., the nature of an enzyme) in
the two preparations.
These data, therefore, suggest that the viscosity assay may provide a better
index of the efficacy
21 of an enzyme preparation than a standard calorimetric activity assay.
22 On the basis of these observations it was hypothesized that the in vitro
assay, when used with
CA 02320687 2000-09-21
1' the log-linear model, could also be used to accurately evaluate the
efficacy of an enzyme added to
2 a diet. The efficacy of the two enzymes (i.e., their B values) were
therefore calculated from the
3 model using the dietary viscosity changes as determined by the in vitro
assay, and the amount of
4 enzyme added to the diet. The results in Table 5 showed that the B value of
NQ was significantly
greater than that of RM1 (0.265 vs. 0.124, P < 0.05) when they were calculated
from log dietary
6 viscosity change as the output of the model and enzyme activity added to the
diet as the input.
7 This difference indicates that the enzyme, NQ, more effectively hydrolyzed
the viscous substrates
8 in the rye-based diet than RM1. However, there were no significant
differences ( P < 0.05)
9 between the B values of the two enzyme preparations ( RM1 vs. NQ) calculated
from the chick
performance and the enzyme added to the diet (Table 5). The inability of chick
performance data
11 to distinguish between the efficacy of the two enzymes in contrast with the
in vitro assay may be
12 caused by several factors, including a difference in relative sensitivities
or precision of the two
13 assays. In these studies, the relative standard error of means for the in
vitro dietary viscosity
14 assay was much lower than that of performance of chickens, and as a result,
it was a more precise
1 S indicator of the efficacy of the enzyme than chick performance.
16
1 ~ Implications
18 A log-linear model has been developed that it can be used to accurately
predict and evaluate
19 the response of chicks to a feed enzyme in both in vivo and in vitro
studies. The model and the
concept of efficacy proposed in these studies can be readily used to predict
and evaluate various
21 responses (i.e., performance, AME, digestibility of feed nutrients, or
reducing viscosity of digesta
22 or diets) of different animals (poultry or swine) to different feed enzymes
(xylanase, (3-glucanase,
26
CA 02320687 2000-09-21
1 ~i-galactosidase, or phytase) as well as other additives or nutrients (i.e.,
essential amino acids). In
2 addition, a refined level of output (chick performance) and inputs (feed
enzyme and substituted
3 cereal), or the most profitable combination of inputs for a specific output
can be evaluated by the
4 linear model when only two or three discrete enzyme dose treatments are
used. These studies
indicate the log-linear model when used in conjunction with a knowledge of
nutrition and
6 computer technology can be a considerable assistance to nutritionists in
their research activities
7 and business decisions.
8
9
11
12
13
14
16
17
18
19
21
22
27
CA 02320687 2000-09-21
1 Literature Cited
2 Almquist, H.J. 1952. Evaluation of vitamin requirement data. Poult. Sci.
32:122-128.
3 Bedford, M. R. 1997. Reduced viscosity of intestinal digesta and enhanced
nutrient digestibility
4 in chickens given exogenous enzymes. In: R. R. Marquardt and Z. Han (Ed.)
Enzyme in
Poultry and Swine Nutrition. pp 19-28. International Development Research
Centre,
6 Ottawa, ON, Canada.
7 Bedford, M. R., and H. L. Classen. 1992. Reduction of intestinal viscosity
through manipulation
8 of dietary rye and pentosanase concentration is effected through changes in
the
9 carbohydrate composition of the intestinal aqueous phase and results in
improved growth
rate and food conversion efficiency of broiler chicks J. Nutr. 122:50-569.
11 Boros, D., R. R. Marquardt, B. A. Slominski, and W. Guenter. 1993. Fxtr~ct
viscosity as an
12 indirect assay for water-soluble pentosan content in rye. Cereal Clo~~o.
70:575-580.
13 Boros, D., R. R. Marquardt, and W. Guenter. 1998. Site of exoenzyme actin
in gastrointestinal
14 tract of broiler chicks. Can. J. Anim. Sci. 78:599-602.
Classen, H.L. 1996. Enzymes in action: successful application of enzymes
relies on knowledge
16 of the chemical reaction to be affected and the conditions under w! ~ ah
the reaction will
17 occur. Feed Mix. 4(2):22-28.
18 Choct, M. 1997. Enzymes in animal nutrition: the unseen benefits. In: I',.
".. ~'~~rc~uardt and Z.
19 Han (Ed.) Enzyme in Poultry and Swine Nutrition. pp 45-51. Ir~t ~ ~~~~1
Development
Research Centre, Ottawa, ON, Canada.
21 Dunn, N. 1999. The impact of animal nutrition on the environment. Fc~~-' '
''~:. 7(s):8-11.
22 Friesen, O.D., W. Guenter, B.A. Rotter, and R.R. Marquardt. 1991. Tl~~ ~ .
; «,'~ enzyme
28
CA 02320687 2000-09-21
1 supplementation on the nutritive value of rye grain (Secale cereale) for the
young broiler
2 chick. Poult. Sci. 70:2501-2508.
3 Guenter, W. 1997. Practical experience with the use of enzymes. In: R. R .
1',1 a rquardt and Z. Han
4 (Ed.) Enzyme in Poultry and Swine Nutrition. pp 53-62. Inten~ at ~ ~ ~~ ~ ~'
Towel opment
Research Centre, Ottawa, ON, Canada.
6 Hesselman, K., K. Elwinger, and S. Thomke. 1982. Influence of incre~s~~~« '
v~-els of (i-glucanase
7 on the productive value of barley diets for broiler chickens. An i m . 1'-
v~ d S c i . Tech. 7:3 51-
8 358.
9 Hofinan, P. 2000. Market developments accelerate consolidation in feed
an~'~»trv. Feed Tech
4(1):15-19.
11 Marquardt, R. R. 1997. Enzyme enhancement of the nutritional value of c , I
;: role of viscous,
12 water-soluble, nonstarch polysaccharides in chick performance. T~~: ". n.
I\-'~~rquardt and
13 Z. Han (Ed.) Enzyme in Poultry and Swine Nutrition. pp 5-17. I~;; . .;ional
Development
14 Research Centre, Ottawa, ON, Canada
Marquardt, R. R., and M. Bedford. 1997. Recommendations for future r~ :v v:'~
on the use of
16 enzymes in animal feeds. In: R. R. Marquardt and Z. Han (Ed.) ? ~ = i n
Poultry and
17 Swine Nutrition. pp 129-138. International Development Resear ~' : re,
Ottawa, ON,
1 g Canada.
19 Marquardt, R. R., D. Boros, W. Guenter, and G. Crow. 1994. The n«tr~'~ v
~~'' h~rley, rye,
wheat and corn for young chicks as affected by use of a Trichnr' ~ ~~n~yme
21 preparation. Anim. Feed Sci. Technol. 45:363-378.
22 McCleary, B. V. 1992. Measurement ofendo-1,4-~3-D-xylanase. In: J. ~,''
"~~'~~man, M. A.
29
CA 02320687 2000-09-21
1 Kusters-Van Someren, and A. G. J.Voragen (Ed.) Xylans and Xylanases. pp 161-
170.
2 Elsevier Science Publishers, Amsterdam, The Netherlands.
3 McCoy, M..1998. Enzymes emerge as big ag supplement. C&EN, pp: 29-30.
4 Remmenga, M. D., G. A. Milliken, D. Kratzer, J.R. Schwenke, and H.R. Rolka.
1997. Estimating
the maximum effective dose in a quantitative dose-response experiment. J.
Anim. Sci.
6 75:2174-2183.
7 Rotter, B.A., M. Neskar, R.R. Marquardt, and W. Guenter. 1989. Effects of
different enzyme
8 preparations on the nutritional value of barley in chicken diets. Nutr. Rep.
Int. 39:107-
9 120.
van de Mierop. L., and H. Ghesquiere. 1998. Enzymes have a long life ahead.
Would Poul.-
11 Elsevier 14(11):16-18.
12 SAS., 1988. SAS/STAT~' Users' Guide (Release 6.03). SAS Inst. Inc., Cary,
NC.
13 Zhang, Z., R. R. Marquardt, and W. Guenter. 2000a. Evaluating the efficacy
of enzyme
14 preparations and predicting the performance of Leghorn chicks fed rye-based
diets using a
dietary viscosity assay. Poult. Sci. 97: (in press).
16 Zhang, Z., R. R. Marquardt, and W. Guenter. 2000b. Prediction of the effect
of enzymes on chcik
17 performance when added to cereal-based diets: use of a log-linear model.
Poult. Sci.
18 (accepted)
19 Zhang, Z., R. R. Marquardt, W. Guenter, and G. H. Crow. 2000c. Predicting
and evaluating the
profitable effect of enzyme in poultry feeds: use of a log-linear model in
application.
21 Poult. Sci. (submitted).
22 Zhang, Z., R. R. Marquardt, G. Wang, W. Guenter, G. H. Crow, Z. Han, and M.
R. Bedford.
CA 02320687 2000-09-21
1 1996. A simple model for predicting the response of chicks to dietary enzyme
2 supplementation. J. Anim. Sci. 74: 394-402.
3 Ziggers, D. 1999. Enzymes: hidden catalysts come out of the dark. Feed Tech.
3(6):23-33.
4
6
7
8
9
11
12
13
14
16
17
18
19
21
22
31
CA 02320687 2000-09-21
1 Figure 1. The predicted relationship between chick performance during the 1
st plus 2nd wk of
2 experiment, and the amount of crude xylanase (RM 1 ) added to a rye-based
diet as determined
3 from the equation Y= 517 + 45 IogX (rz = 1.00, residual SD = 3 g) or Y=2.46 -
.09 logX (r2 =
4 0.99, residual SD = 0.01 g) where X = units of enzyme in the diet and Y =
weight gain (g) or the
feed to gain ratio, respectively. Mean experiment values for weight gain (~)
and feed to gain
6 ratio (1) are also shown. Inset figure represents the same data except the
amounts of enzyme
7 have been transformed into their logarithmic values. (Source: Zhang et al.,
1996).
8
9 Figure 2. Effect of enzyme concentration (X) and rye content of diet (Z) on
chick gain (Y). Y =
436.11 + 7.58 log (X) - 0.63 Z + 0.75 Z log (X); all coefficents in the
equation were significantly
11 different from zero ( p < 0.001) with the exception of the coefficient for
log (X) (P < 0.1); rz =
12 0.94, residual SD = 12.56. (Source: Zhang et al., 1996).
13
14 Figure 3. Principle and application of the Multi-purpose Enzyme Analyzer
for Use of Enzymes in
1 S Poultry Feeds. (Source: Zhang et al., 2000c).
16
17 Figure 4. Effect of different combination of two variables, amounts of
enzyme (XE) and rye (XR)
18 added to diets on the profit of chickens fed diets from 1 to 19 d of age.
Cereals in the diet were
19 wheat plus rye (60 %). The profit function were: II = Py Y - F ~ ( Pi Xi ),
where Y = (404 -
2.04XR + S.2S X I O-3XR2 - 3.20X l0~XR3 ) + (9.78 + 3.49 X 1 OXR - 1.29 X I O-
3XR2 + 1.06X 10'~ XR3) log
21 (2150 X + 1), and F = (648 - 8.52X 1 O-ZXRZ+ 8.33X 1 O~XR') + (2.64 + 2.27x
10-zXRZ- 2.l OX 10'~
22 XR3) log (2150 X + 1); II = profit ($/1000 birds), Y = weight gain (g), F =
feed consumption (g),
32
CA 02320687 2000-09-21
1 Py and Pi represented the price of chickens and the price of the i-th
ingredient (Xi) in a diet. The
2 plots on the left gives the three-dimensional relationship for relative
amount of rye in the diet
3 (the balance is wheat), the amount of enzyme added to the diet, and the
profits obtained assuming
4 wheat and rye costs are $ 0.12 and 0.08 per kg, respectively, and that of
enzyme is $ 3, 5, or 7 per
kg. The figures on the right are the profit contours of two-dimensional slices
of that on the right
6 for diets containing different amounts of enzyme and different percentage of
rye in the diet. The
7 number in each line represents the fixed profit that can be obtained by
feeding different amounts
8 (%) of rye and enzyme. Data used for the calculations were from Bedford and
Classen, 1992.
9 (Source: Zhang et al., 2000c).
11 Figure 5. Log of viscosity changes [net log centipoises (log CP)] as
affected by the concentration
12 of the enzyme (% NQ, Nutri-Quest, Chesterfield, MO) in extracts prepared
from a rye diet
13 containing different concentrations of the enzyme. The extracts were
incubated using the dietary
14 viscosity assay for different time intervals (-0-, 1 h, -1-, 2 h and -~-, 8
h) at 40 C, and viscosity
values were converted to their logarithmic values and subtracted from the
control values (diets
16 with no enzyme supplementation) to yield net viscosity values. Overall
average standard errors
17 for thel, 2 and 8 h data were 0.009, 0.022, and 0.007 (log CP),
respectively. (Source: Zhang et
18 al., 2000a).
19
Figure 6. Prediction of weight gain (A and C) or the feed to gain ratio (B and
D) over a 7-d
21 period for Leghorn chicks fed a rye-based diet containing different
concentrations of an enzyme
22 preparation (RMI, Finnfeed International Ltd., Wiltshire, UK) by a log-
linear model equation
33
CA 02320687 2000-09-21
1 using either log of dietary viscosity change [log centipoise (log CP), A and
B] determined by
2 incubation of the diet at 40 C, pH 5.0 for 4 h or log of enzyme activity
(log U/kg, C and D) added
3 to the diet as the input of the equation. The linear regression equations
were: YA 198 + 69.5 log
4 ( 10 X+1 ) for weight gain (A) and YB 2.65-0.24 log ( 1 Oz X+ 1 ) for feed
to gain ratio (B) when the
input (X) was dietary viscosity change (centipoises, CP), and Y~ 195+18.0 log
(10 X+1) for
6 weight gain (C) and YD 2.64-0.091 log ( 10z X+1 ) for feed to gain ratio (D)
when the input (X)
7 was enzyme activity added to the diet (IJ/kg); r > 0.99; P < 0.005. (Source:
Zhang et al., 2000a).
8
9
11
12
13
14
16
17
18
19
34
CA 02320687 2000-09-21
Table 1. Evaluation of the performance of Leghorn chicks fed a rye-based diet
with different
concentrations of enzyme using different parameters calculated in model
Equations l and 2a
Enzyme RM 1 NQ
preparation (U~g) (LJ/kg) (%
Wk Wk 2 2 wk Wk Wk 2 wk Wk Wk 2
1 2 2 wk
1 1
WG (g)b
A 195 334 529 191 342 534 194 344 538
(A,) 187 329 515 184 334 519 278 378 656
Yo 196 345 541 196 345 541 196 345 541
B 18 11 30 22 9.3 32 28 12 40
Ym Yo 88 60 149 112 38 160 112 38 160
rz 0.99 0.64 0.91 0.91 0.94 0.94 0.930.97 0.97
(r,2) 0.96 0.74 0.98 0.93 0.97 0.97 0.920.98 0.97
C 10 10 10 10 10 10 10 10' 10'
3
F/G (g/g)b
A 2.64 2.35 2.45 2.65 2.31 2.43 2.652.31 2.43
(A,) 2.67 2.37 2.48 2.67 2.31 2.45 2.152.23 2.2
Yo 2.64 2.31 2.43 2.64 2.31 2.43 2.642.31 2.43
BX 10-2 -9.1 -3.4 -6.3 -12.7 -2 -6.1 -12 -2 -6
Ym Yo -0.6 -0.19 -0.32 -0.58 -0.1 -0.27 -0.6-0.1 -0.3
rz 0.99 0.62 0.94 0.92 0.66 0.96 0.920.66 0.95
(r,z) 0.93 0.76 0.99 0.89 0.62 0.93 0.910.65 0.95
C 102 10 10 10 10 10 10 10 104
4 4
aSource: Zhang et al., 2000b.
bA, B, and C are the parameters calculated from Equation 2, Y = A + B log ( CX
+ 1 ), using the
developed computer program, where Y is the chick performance [i.e., weight
gain (g), feed to
gain ratio (g/g)]; X is the enzyme preparation added to the diet (U/kg or %);
A, the intercept of
the equation, represents the chick perfromance without addition of an enzyme
preparation (g,
CA 02320687 2000-09-21
g/g); B, the slope of the equation, provides an index fro evaluating the
efficacy of an enzyme
added to the diet (g or g/g per log U/kg; g or g/g per log %), and C is an
adjusted factor used to
correct the X value when enzyme is not added to the diet. X in Equations is
the amount of
enzyme (U/kg or %) added to the diet. A, which are the bracketed values are
the A values as
estimated from Equationl, Y = A + B log ( X + a ), which were originally
reported by Zhang et
al (1996). Ym and Yo represent the respective observed performance values of
chicks [weight gain
(g) or feed to gain ratio (g/g)J for the indicated periods when either the
highest enzyme
concentration or no enzyme is added to the different diet. rz is the
correlation coefficient between
the observed experimental values and predicted values when either equation 2
(r2) or equation 1
(r,2) was used. WG and F/G represent weight gain and feed to gain ratio,
respectively.
- CA 02320687 2000-09-21
r ~
N ~' v1 o0 l~ O O O
O O O
O O O C O C
N
~~D0~0 ~0~10~1 p,
O O O O O O U
. ,..,
O
U
O O O O O O p
N C O C C O C
.b
O
N ~ ~ O~ O~ 0~0 ~
O O O O O O
'Lf t,"
U O
~O 00 00 O O M
O N M N O O O ~n
b ~ O O C O O O
U '~ r.,
bA
'~, O d: 00 ONE, Cy C1
O O O O O C
~r-... M T3
.-r .~
Na, o~M~ °0°00
o .-. ~ 0 0 0 ~ ~,
c o 0 0 0 0 ~ ;~
a~
o ~ "~., N t~~, o°°o, o°~,, o°y, ~ ~ ~'
m
0 0 0 0 0 0 ~ o
b
°' o
U ~~ ~ O O O O O O
b4 N
O O C O O C
3
0
3 ~ ~ ~ ~ ~, ~ ~ b
c o 0 0 o c
~~" r~ o
0 0 0
v ~t M w '.
n
Two d- o o c~ a~ ~ f~
~ N N O O O
O C O O O C
~ o, M ~ 00 00
d; ~n oo cv c, os ,~ ~ . ~b
0 0 0 0 0 0
.o i a ~
e~~' ~ ~ 3
Q '~ .~ ~ ,~ ~ ~ v ~ T3 ar
C" U
U p, U ~~ U ~ by dA dp G U
H ~' ~ a d v a a a
'_ CA 02320687 2000-09-21
Table 3. Effect of different enzyme preparations added to a barley- or rye-
based diet on the
efficacy of enzyme (B values), the optimal amounts of enzymes and the maximal
profits
obtained from Leghorn chicks in a one-week (Rotter et al., 1989) or two-week
(Zhang et al.,
1996)a
Source of Enzyme B Value' Optimal Enzyme Maximal Profit
Data Preparationb (%) ($/ 1000 birds)d
Rotter et Cellulase -0.247 0.656 67.29
al., Tv
1989 Celluclast -0.211 0.560 61.27
Finizym -0.172 0.452 51.91
Cereflo -0.171 0.439 49.27
SP249 -0.139 0.385 46.79
Zhang et RM1 -0.0943 0.315 101.19
al.,
1996 NQ -0.0963 0.348 104.38
aSource: Zhang et al.(2000c).
bThe enzyme preparations used in the study of Rotter et al.(1989) and Zhang et
al. (1996) were
Cellulase Tv concentrate (Trichoderma viride) from Miles Laboratories Inc. and
Cellucast (T.
ressei) Finizym (Aspergillus niger), Cereflo (Bacillus subtilis), and SP249
(Aspergillus niger)
from Novo A/S Demark; and RM1 (T. longibrachiatum) from Finnfeeds
International Ltd. and
NQ (T. reesei) from Nutri-Quest.
'The B values were the slope of log-linear model equation calculated from the
data of feed to
gain ratio. The values are the indexes of the efl'lcacy of a feed enzyme added
to a diet (Zhang et
al., 1996; 2000).
dThe assumed price for enzyme preparations used in the two studies was $ 5 per
kg.
CA 02320687 2000-09-21
Table 4. Effect of cereal prices on optimal amounts of an enzyme added to
different cereal-based
diets and their maximal profitsa
Value Same Optimal Maximal DifferentOptimal Maximal
Cereal of Price Enzyme Profit Price Enzyme Profit
Bb
($/kg)(%) ($/1000 ($/kg) (%) ($/1000
birds) birds)
Corn 0.005 0.08 0 134.45 0.13 0 126.00
Wheat -0.0280.08 0.0339 133.55 0.12 0.0335 126.73
Barley -0.0380.08 0.0815 135.00 0.08 0.0815 135.00
Rye -0.0900.08 0.3419 123.96 0.08 0.3419 123.96
aSource: Zhang et al. (2000c).
bThe B values were the slope of log-linear model equation calculated from the
data of feed to
gain ratio. The values are indexes of the efficacy of a feed enzyme added to
different diets.
Therefore, the suitable cereal for a feed enzyme can be determined by the
value (Zhang et al.,
1996; 2000).
CA 02320687 2000-09-21
Table 5. Use of a log-linear model equation to evaluate the efficacy of
enzymes added to the rye
based diet by in vitro dietary viscosity assay and predict chick performance
from the enzyme
activity expressed as the amounts added to the diet (AEA) or the viscosity
change determined by
an in vitro dietary viscosity assay (MEA)e
Outputb Input Parameters ed from
obtain prediction
equations
(~ (X) A B4 C r P <
Viscosity vs.
AEA'
MEA (log CP) RM1 (log -0.02 0.1248 10-2 0.99 0.005
U/kg)
NQ (log U/kg)-0.03 0.265" 10 -2 0.99 0.005
Performance vs.
AEAd
WG1 (g/6 birds) RM1 (log 195 18.08 10 0.99 0.005
U/kg)
NQ (log U/kg)191 22.38 10 0.95 0.005
FG1 (g/g) RM1(log U/kg)2.64 -0.0918 10 2 -0.99 0.005
NQ (log U/kg)2.65 -0.1278 10 -0.95 0.005
Performance vs. MEA
WG1 (g/6 birds) RM1 (log 198 69.58 10 0.99 0.005
CP)
NQ (log 198 72.28 10 0.97 0.005
CP)
FG1 (g/g) RM1 (log 2.65 -0.248 10 2 -0.99 0.005
CP)
NQ (log 2.65 -0.258 10 z -0.98 0.005
CP)
aSource: Zhang et al. (2000a).
bWGI and FG1 were actual weight gain and feed to gain ratio over a 7-d period
of a feeding
trail for chicks fed a rye-based diet containing different amounts of added
enzymes (RM1 or
NQ). The relationship between the outputs such as chick performances (WGl and
FG1) or log of
dietary viscosity change (log CP) and the inputs such as the amount of enzyme
in the diet (AEA
or MEA) was estimated from a prediction equation (Zhang et al., 1996; 2000b).
The equation is
Y = A + B log (CX + 1), where Y = outputs (WG1 and FG1 or MEA), and X =
inputs, i.e., the
amount of enzyme (xylanase) added to the diet (AEA) or its estimated activity
value (MEA). The
A is the intercept and represents performance without enzyme added to the
diet. The B, the slope
CA 02320687 2000-09-21
of the equation, represents the performance of chick per log unit of enzyme
(weight gain or feed
to gain ratio per log unit of enzyme for AEA, or weight gain or feed to gain
ratio per log
viscosity change for MEA, or log dietary viscosity change per log of enzyme
activity added to
the diet). The C is an adjusted factor that is required to calculate
performance of chicks when fed
diets without added enzyme. The data used to calculate the parameters of the
equations were
from Table 1.
°The outputs are log of dietary viscosity changes (log CP, centipoise)
obtained using the in
vitro viscosity assay during a 4-h incubation period and the inputs are the
log of the amount of
enzyme added to the diet (log U/kg).
dThe outputs are animal performances (Y) and the inputs are units of enzyme
activity (X)
added to the diet (AEA) or the enzyme activity as determined by in vitro
dietary viscosity
changes (MEA).
eB values for each comparison of the two enzymes not having the same
superscript are
significantly different (P < 0.05, t-tests).
fRMI (Finnfeed International Ltd., Wiltshire, UK) and NQ (Nutri-Quest,
Chesterfield, MO)
contained 389 and 778 U of xyalanase activity / g of original enzyme
prepasration (stock
enzyme), respectively, as determined at pH 4.7 by the colorimetric method of
McCleary (1992).
The stock preparations were added to the diets to give the indicated activity
values.
