Factors affecting ileal digestible energy of corn in poultry diets.

Abstract

151 Factors affecting ileal digestible energy of corn in poultry diets T.H. D'Alfonso Danisco Animal Nutrition, PO Box 777, Marlborough, Wiltshire SN8 1XN, UK tom.dalfonso@danisco.com Summary pericarp (P), which is the outer covering, or hull, that Broiler diets were formulated for 93 different corn protects the kernel from the environment, insects and batches, each divided in half. One was supplemented pathogens, although the tip cap (T) may provide access with xylanase, amylase and protease enzymes into the k ernel. The kernel is comprised of the (Avizyme 1502, Danisco Animal Nutrition) and fed endosperm (E) and the germ (G). The endosperm is the to male broilers to 28 d, and body weights and feed source of energy for the seed, and this energy comes intakes were recorded. Corn and digesta samples were mainly from starch, and some protein. The germ is the analysed for starch, protein, oil, and gross energ y living part of the kernel, and contains enzymes, vitamins, content, and ileal digestible energy (IDE) was computed. minerals and the genetic information for Feed conversion ratio (FCR) ranged the kernel to grow into a corn plant. between 1.43 and 2.67 (mean and SD Depending on the genetic variety, 1.81 � 0.30). The 28 d weight ranged approximately 25% of the germ is corn between 680 and 1301 g with mean 909 oil, high in linoleic acid. On average, the � 114 g. Enzyme addition improved FCR composition of corn dry matter is 68% to 1.73 ( P <0.01) a nd significantly starch, 8% protein, 4% oil, 2.5% cellulose, reduced its CV by 30%. The average corn and trace amounts of vitamins and IDE was 11.84 � 2.03 MJ/kg. Using minerals. leastsquare estimators, digestibility Starch as the major component of coefficients for starch, protein, oil and corn, and other grains, is the largest source other fractions (fibre etc.) were found to Figure 1 Corn kernel. of energy in the typical poultry cornsoy be 86%, 82%, 9 0% and 12%, diet. Regardless of its source in the diet, respectively. With enzyme addition, IDE starch is made up of glucose molecules amylose and was raised by an average of 5% to 12.45 MJ/kg. amylopectin. The amylopectin molecule is nearly Digestibility coefficients were raised to 91%, 83%, 91%, identical to amylose, except that amylopectin has an and 14% for starch (+5%), protein (+1%), oil (+1%) 16 glucose linkage that causes it to form branches. and other sources (+2%), respectively. Starch The branching structure (A, B) of a starch granule (C) digestibility was related to in vitro starch digestion formed by the 16 glucose linkage of amylopectin rate (P<0.01). (D) is illustrated in Figure 2. A global corn quality survey (DAlfonso and Keywords: poultry, ileal digestible energy, corn, maize, McCracken 2002) provided data on the variability of starch, enzymes, amylase, protease, xylanase corn composition. As shown in Figure 3, as starch level increases the protein and oil contents tend to decrease, especially oil; there is a less strong positive relationship Introduction between protein and oil contents. Gross energy values Corn quality is affected by genetics, growing and are relatively constant, 38.91, 17.36, and 22.97 MJ/kg harvesting conditions, drying process, and feed for oil, starch, and protein, respectively (Noblet 2000), manufacturing. Variability in composition and quality but these values could change if the corn is overheated a f fect the metabolizable energy content with and, for example, the starch is retrograded. consequential effects on poultry performance. Energ y The rate of starch digestion was measured in vitro comes from the protein, oil, and carbohydrate sources in a twostage process in which each of 93 samples of in the corn; however, not all of this ener gy is corn from various sources was incubated with a solution metabolizable. Corn (see Figure 1) is comprised of a of pepsin with HCl, followed by pancreatin digestion. Recent Advances in Animal Nutrition in Australia, Volume 14 (2003) 152 D'Alfonso, T.H. This process was designed to simulate digestion in the chicken (DAlfonso and McCracken 2002). The extent of digestion after 7, 15, 22, 30, 45, 60 and 120 minutes of incubation was determined (Figure 4). The purposes of this research are to quantify the sources of variation in corn quality, to predict the dietary energy of corn based on these factors, and to predict the improvement in dietary energy when appropriate enzymes are added to the feed. It is necessary to consider the proportion of corn in the diet which will determine the effect of corn quality on the performance of birds fed a cornbased diet. It is also necessary to use a method of measuring dietary energy that is closely related to poultry performance, namely the ileal digestible energy (IDE) of protein, oil and carbohydrates (starch and fibre) and the ef fect of enzyme supplementation on each value. Methodology Ninetythree commercial corn samples were obtained from 15 countries around the world (DAlfonso and McCracken 2002) and were ground, and one mash broiler diet was formulated with 55% corn for each corn batch, resulting in 93 diets that differed only in the batch of corn used. Diet formulation is shown in Table 1. Each diet was then separated into two portions and one was supplemented with a commercial enzyme blend of xylanase, amylase and protease (Avizyme 1502, Danisco Animal Nutrition). Each of these 186 diets was fed to 25 male broilers per pen from day 1 to day 28 and body weights and feed intake were measured. Digesta samples were collected at the terminal ileum from six birds per pen and digesta from each bird were analysed for energy content. Corn samples were analysed for starch, protein, oil and gross energy (GE). IDE was computed using the relative proportions of titanium dioxide marker in the feed and digesta. GE of the corn was partitioned into that coming from starch, protein and oil, and subtracting these amounts and moisture from 100% determined the contribution of other sources. The IDE of each source was calculated from its percent digestibility multiplied by the gross energy values of 38.91, 17.36, and 22.97 MJ/kg for oil, starch, and protein respectively. Improvements in IDE owing to the addition of the enzymes to the diets were portioned into improvements in the digestibility coefficients of starch, protein, oil and other sources. A m y lo p e c n ti Amylose Figure 2 Starch structure (A_D) and amylose and amylopectin molecules. Factors affecting ileal digestible energy of corn in poultry diets 153 12 Per cent in dry matter 7 6 Protein = -0.164x + 19.349 Protein = 20.164x + 19.349 r 2 = 0.161 R = 0. 161 10 P ercent oil i n dry m atter 8 6 4 2 0 64 5 4 3 2 1 0 Oil == 0.3335x ++ 1.7482 -0.3335x 1.7482 Oil 2 rR2= 0.1714 = 0.1714 Oi = 0. 2083x + 18.769 Oill = --0.2083x + 18.769 R2 = 0.4003 r2 = 0.4003 66 68 70 72 Pe rce nt starch in dry matte r 74 6.0 6.5 7. 0 7.5 8. 0 8.5 9.0 9.5 10.0 Pe rcent protei n i n dry m a tter Figure 3 Relationships among starch, protein and oil contents of corn. g Starch digested per 100 g ccm 70. 0 60. 0 50. 0 40. 0 30. 0 20. 0 10. 0 0. 0 0 20 40 60 80 Max 100 Average 120 Mi n 140 Tim e (mi nute s) Figure 4 Rate of starch digestion determined in_vitro among 93 corn samples. Table 1 Dietary composition and calculated nutrient levels. Composition of diets Ingredient and percent in diet Corn Soybean meal (49%) Fishmeal Lysine DL Methionine Soy Oil Dicalcium phosphate Limestone Salt Sodium bicarbonate Vitamin/Mineral mix Choline chloride Titanium dioxide 54.84 36.34 1.07 0.02 0.24 3.60 1.82 1.22 0.32 0.10 0.27 0.04 0.30 Protein % ME MJ/kg Fat % Fibre % Calcium % Total P % Available P % Na % Cl % K% Mg % S% Choline ppm Linoleic acid % Nutrients 23.0 12.93 6.2 2.6 1.04 0.78 0.49 0.16 0.25 0.97 0.21 0.19 1370 2.53 Amino acids (%) Met Cys Me+Cys Lys His Tryp Thr Arg Iso Leu Phe Tyr Val Gly Ser 0.60 0.37 0.98 1.29 0.62 0.27 0.89 1.55 0.98 1.99 1.12 0.83 1.08 0.95 1.09 154 D'Alfonso, T.H. Results The performance of broilers fed different sources of corn without enzymes was variable. Feed conversion ratio (FCR) ranged between 1.43 and 2.67 with a mean and SD of 1.81 � 0.30 (Table 2). One outlier with an FCR of 3.36 was removed from the analysis, this being a corn sample from France with 25% moisture. The weight gain ranged between 680 and 1301 g with a mean of 909 � 114 (an outlier of 375 g was removed). The addition of enzymes improved FCR (P <0.01) and reduced its CV by 30%. The variability in starch, protein, oil and gross energy composition among the samples on a dry matter basis is shown in Table 3. The relationship between measured GE of the corn samples and values predicted from their chemical composition and energy of the components was highly significant (P<0.0001, r2 > 0.92). The root mean square error of a predicted value was � 0.10 MJ/kg (� 0.5% of the mean) An example of a predicted GE for a sample with a measured 18.97 MJ/kg is shown in Table 4. Results from the analyses of many corn samples (Figure 5) show that starch contributes more than two thirds of the GE in corn. Protein and oil each contribute approximately the same percentages, although this is different for high oil corn. Fibre and other sources contribute approximately 20% of the GE, but these are not very digestible as shown by the IDE values. The mean of the measured IDE with SD was 13.58 � 2.04 MJ/kg DM. Using leastsquare estimators, digestibility coefficients for starch, protein, oil and other fractions were found to be 86.3%, 81.6%, 90.2% and 11.4%, respectively. With the addition of enzymes, the IDE was raised by an average of 5% to 14.25 MJ/kg DM (P<0.001). Digestibility coefficients were found to be raised to 91.3%, 82.4%, 90.7% and 13% for starch (+5.0%), protein (+0.8%), oil (+0.5%) and other (+1.6%), respectively. The average increase in digestibility of starch was significant at P<0.01 and for protein, oil and the other sources of energy at P<0.05. Digestibility of starch in vivo ranged from 84 to 90% with an average of 86% and was significantly related Table 2 Performance of 28_day broilers fed diets corn_based diets without or with enzymes. Enzymes Gain (g) No Yes Feed: Gain No Yes Mean 909 915 1.81 1.73 SD 114 114 0.30 0.20 CV % 13 12 16 12 Table 3 Major chemical constituents in the dry matter and the measured gross energy of 93 samples of corn obtained from various locations. Dry Matter (%) Mean SD Minimum Maximum CV% 89.1 0.9 87.4 90.7 1 Starch (%) 68.8 1.8 65.8 72.0 3 Protein (%) 8.1 0.7 7.1 9.7 9 Oil (%) 4.4 0.6 3.5 5.9 13 Gross energy (MJ/kg DM) 18.9 0.1 18.7 19.2 1 Table 4 The contributions of nutrients to the gross energy in a corn sample with measured 18.97 MJ per kg dry matter. Nutrient Starch Protein Oil Other Percent in corn DM 71.6 7.7 4.2 16.6 GE MJ/kg DM 17.36 22.97 38.91 18.16 Calculated MJ/kg DM 12.43 1.77 1.63 3.01 Total: 18.84 Factors affecting ileal digestible energy of corn in poultry diets 155 (P<0.01, r2 > 0.82) to the in vitro values for rate of starch digestion which ranged from 37 to 53% with an average of 42%. The addition of the enzymes increased starch digestion proportionately to the improvement in IDE. It is proposed that xylanase and protease act to increase accessibility of starch to digestion and that amylase increases the rate of digestion. There was an additional increase in IDE of approximately 0.02 MJ/kg that was not attributable to corn. In the type of diet used it is assumed that the IDE of soybean meal may have been improved, perhaps due to the protease. Figure 6 illustrates the percentage of IDE coming from corn components and other ingredients in the diets. Table 5 illustrates calculations of energy value for the corn sample with an estimated GE of 18.84 MJ/kg DM. The IDE of this sample was estimated to be 13.97 MJ/kg DM, and improved to 14.67 MJ/kg DM with the addition of enzymes (Table 5). In a diet containing 55% of this corn, the increase in IDE from the addition of enzymes due to corn alone is 0.38 MJ/kg DM (Table 6). Least square estimators were used to determine IDE of the other ingredients in the diet. Conclusion IDE and its improvement due to enzyme supplementation is predictable. A spreadsheet was developed to estimate: the IDE in corn based on starch, protein and oil composition; the IDE of a diet containing that corn and based on the inclusion level; Gr o ss En er gy Compositio n o f Cor n Other 19% Starch 66% Other Ingredients 45% ID E of the D iet Protein 7% Oil 8% Corn Starch 41% Corn Other 2% Corn Protein 6% Corn Oil 6% Figure 5 Sources of average gross energy in corn. Figure 6 Sources of ileal digestible energy (IDE) of a corn_soy diet containing 55% corn. Table 5 Calculated gross energy (GE) and ileal digestible energy (IDE) of a corn sample and the increase in IDE from the addition of enzymes. Energy digestibility (%) Nutrient Starch Protein Oil Other Total _Enzymes 86.3 81.6 90.2 11.4 74.2 +Enzymes 91.3 82.4 90.7 13.0 77.9 Ileal digestible energy (MJ/kg) _Enzymes 10.72 1.44 1.47 0.34 13.97 +Enzymes 11.35 1.45 1.48 0.39 14.67 Table 6 Calculated gross energy (GE) and ileal digestible energy (IDE) of a diet containing a corn sample (Table 5) and the increase in IDE from the addition of enzymes. Energy digestibility (%) Ingredient Corn (55%) Others (45%) Total _Enzymes 74.2 65.8 70.2 +Enzymes 77.9 65.9 72.2 Ileal digestible energy (MJ/kg) _Enzymes 7.69 6.09 13.78 +Enzymes 8.07 6.11 14.17 156 D'Alfonso, T.H. the improvement in IDE due to supplementation with the blend of enzymes used in this study. Practical benefits of this study include a more precise knowledge of corn energy for feed formulation, leading to reduced feed costs and reduced variability of dietary energ y. The optimal formulation of the blend of xylanase, amylase, and protease enzymes may be determined. The results form a basis to monitor corn quality by harvest year and geographic region, giving more information on commodity value. In vitro measures of starch quality at critical points in the feed manufacturing process may be used to make recommendations on temperature, moisture and time of processing related to the effects on corn quality. These measurements may also be used as a tool to monitor the efficiency of feed manufacturing equipment and to predict when work on the equipment may be required. References DAlfonso, T.H. and McCracken, K. (2002). Global corn quality variability. Proceedings of the Multistate Poultry Meeting, Indianapolis, Indiana, May1416, 2002. Noblet, J. (2000). Digestive and metabolic utilization of energy in swine: application to energy evaluation systems. Journal of Applied Animal Research 17, 113132.