Main factors affecting the nutritive value of poultry ingredients: cereals and soybean meal

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1 L7 Main factors affecting the nutritive value of poultry ingredients: cereals and soybean meal Gonzalo G. Mateos, G. Fondevila, G.G. Mateos, R.P. Lázaro Animal Science, Universidad Politécnica de Madrid, Madrid, Corresponding author: Keywords: amino acid digestibility, antintritional factors, energy evaluation, fat and fiber content, pelleting Summary Feeding represents 60 to 70% of the cost of production of eggs and poultry meat. Levels of apparent metabolizable energy (AMEn), standardized indispensable amino acids (Lys, Met+Cys, and Thr), and digestible P content of the diet are the main factors controlling the cost of poultry diets. In most countries, soybean meal, cereals and lipid sources are the main constituents of the diets, with increased interest for the use of crystalline amino acids and additives. Most feed companies formulate the diets based on the chemical composition and nutritive value provided by tables from different institutions throughout the world. In theory, values for key nutrients from all these tables should be similar and within a narrow range. However, this is not the case for many ingredients, including corn and soybean meal, the most traditional raw materials used in poultry diets. The reasons for the wide discrepancy observed among sources of information are not known but in most cases the differences reported, especially for AMEn content, are not justified. Introduction Poultry diets are based primarily in cereals and protein meals, with corn and soybean meal (SBM) as the main ingredients. Other raw materials used in practice are wheat, barley, sorghum and lipids as energy sources and sunflower meal, rapeseed meal, DDGS, and peas as protein sources. The world tends to globalization and consequently, the number of ingredients used in a given country and formal will increase. Numerous factors affect the nutritive value of ingredients for poultry. Many of these factors are related to the animal itself with energy utilization that varied among birds (i.e., pullets vs. chicks vs. layers vs. turkeys) and health status. Also, the ingredient composition and the characteristics of the diets affect of percentage of the gross energy that birds can utilize. In this respect, particle size of the ingredient (fine vs. coarse grinding), feed form of the diet (mash vs. pellets), antinutritional factor (ANF) content, inclusion level in the diet, proportion of fat and fiber, and the use of enzymes and other additives, are of interest. For example, particle size might influence the utilization of the energy of the starch with more pronounced benefits with fine grinding in ingredients with highly protected starch, such as peas (Pisum sativum) than in ingredients with less protected starch such as rice (Parera et al., ). Also, pelleting might be of more benefit for these ingredients in which a high percentage of the lipid fraction is inside the espherosomes, such as corn and toasted soybean meal (Irandoust et al., 202). The inclusion of moderate amount of insoluble fibers, such as oat hulls, might improve gizzard function and the utilization of nutrients and energy of the ingredients (Mateos et al., 202; JimenezMoreno et al., ). Moreover, fat supplementation reduces rate of feed passage which in turn might improve nutrient and energy utilization of the diet (Mateos and Sell, 980; Mandalawi et al., ). A key factor influencing the utilization of the nutrients and energy content of an ingredient is the content in ANF. In practice, trypsine inhibitor (TI) in soybean meal and peas, glucosinolate content in rapeseed meals, and non digested oligosaccharides in legumes and xylans and βglucans in small grains are the main factors to control. In this respect, the use of adequate technologies (i.e., heat processing for TI and inclusion of enzymes for non starch polysaccharides in grains) might solve at a high extent the problems encountered. Finally, the improvement in energy content of the ingredients of the diet might improve because of the inclusion of adequate enzymes (or other convenient additives) has been well documented (Lazaro et al., 2003). 30

2 Energy and protein evaluation of ingredients Different systems are available for evaluating the AMEn, and standardized ileal digestibility of the amino acids (AA). Moreover, numerous institutions (,, 202;, ; FEDNA, ;, ; Rostagno et al., ; Atlas, ; n Poultry Research Institute, ;, ) have edited comprehensive tables to evaluate the nutritive value of key ingredients in poultry diets. In practice, the three main approaches used to evaluate the energy content of ingredients in poultry diets are based on values obtained from a) tables, b) predictive equations (in vitro studies, wet chemistry, or NIR technology), and c) in vivo experiments (research farms). Each of them has advantages and disadvantages and at present time, it is not easy to make a fair recommendation on which one is best (Mateos et al., 205). Under practical conditions most feed companies will use table values often modified based on their practical experience or on analyses conducted in their labs by NIR technology. Consequently, this presentation will focus in this approach, using as examples determinations for SBM, cereals and grains in general. Protein sources SBM, rapeseed meal (RSM) and sunflower meal (SFM) are the main protein sources used worldwide. Usually, SBM will be the protein source of choice because of composition, protein quality and nutritive value (Van Eys, 202). The energy content of high protein SBM (47% CP), as recommended by different institutions, ranges from 2.2 Mcal/kg from () to 2.55 Mcal/kg for the () (Table ). The differences reported among s are difficult to understand and indicate the need for a better approach in the presentation of energy values by the s. As indicated by Frikha et al. (202), Ravindran et al. () and Garcia Rebollar et al. (), part of the differences might be due to differences in digestibility of the crude protein (CP) fraction as well as to the sucrose content among SBM samples. Garcia Rebollar et al. () in an extensive survey conducted during 8 consecutive years with SBM samples (n = 55) collected in Europe or in the country of origin of the beans, reported better uniformity and less fibre, more soluble sugars and higher indispensable AA content per unit of CP for the than BRA SBM, with SBM from ARG being intermediate. The SBM had higher TIA, KOH and PDI but lower HDI than the BRA SBM. In fact, SBM can be discriminated and classified by origin of the beans by NIR technology. These authors, reported different energy values for meals from the three major countries both in pigs, using the predictive equation developed by Noblet et al. (2003), and in poultry, using the predictive equation recommended by the WPSA (989). In fact, the values reported using the WPSA equation were 2,62, 2,605 and 2,576 kcal/kg (on DM bases) for the,, and Argentina meals respectively. These differences, although important, do not explain the high range of values for SBM among sources exposed in Table. Instit. Viçosa Rostagno et al. () Table. Energy content of soybean meal for poultry, Mcal/kg CP(%) AMEn(Mcal/kg) The variability in CP and AA content is also important among SBM samples with part of the differences depending on the processing conditions of the beans and the country of origin with lower CP content for Argentina meals than for or ian meals. Also, CP content is reduced when higher amounts of hulls are added to the meal after processing. The AA profile of the SBM varied with the country of or 3

3 igin and in general, the indispensable AA content was lower for the ian meals than for the Argentinean and meals (Ravindran et al., ). In Table 2 we offered the Lys content (per kg of meal or per unit of CP) of high protein SBM according to different sources of information. Again, the variability reported is not easy to explain. When the profile of the protein fraction is studied, the values change, with less but still important differences among countries. In fact, ian SBM showed a less convenient AA profile that the Argentina or meals. Table 2. Lysine content of the soybean meal (% of the meal or %CP) Lys (%) Viçosa Rostagno et al. () 2 To notice, that similar variability or even greater in energy and CP content and AA availability has been reported for RSM (Table 3) and for SFM (Table 4). In the case of RSM most differences in protein quality are due to processing conditions and glucosinolate content. For SFM, the main reason for the difference in AMEn and CP content are the amount of hulls added to the meal. Table 3.Energy content of rapeseed meal for poultry (Mcal/kg) Instit. EE (%) Table 4. Energy content of sunflower meal for poultry Viçosa PS Inst

4 Cereals When the AMEn of the cereals are compared, there is a lineal positive correlation between its nonstarch polysaccharide content (NSP) and energy content. The highest AMEn among cereals corresponds to rice, followed by corn with the lowest value for oats (Table 5). Within a given cereal, the energy and digestible protein content will depend on the proportion of starch and fiber (closely and negatively related) as well as on the amount of viscous carbohydrates, mainly βglucans and xylans. Consequently, one of the main reasons for the variability in nutrient content in samples from a given cereal, is its content in these complex oligosaccharides. Fortunately, the feed compound industry can utilize multiple enzymes complexes that permit to overcome this problem in all type of diets. In table 6 we include data on the variability in AMEn of corn according to different s, with values varying widely, from 3.20 Mcal/kg for () to 3.38 Mcal/kg for Rostagno et al. (). Again, these differences are difficult to understand and remained in many cases, even after removing the effects of moisture content. Similar type of problems are found for the energy evaluation of wheat (Table 7) and barley (Table 8). Rice is the cereal with the lowest ANF and the highest starch content. In addition, rice starch is easily digested because of the small size of the starch granule, simple protected matrix of the starch granules, and high relative content of amylopectin. As a consequence, rice is very easy to digest and contains more energy than any other cereal (Table 9). Table 5. Relative energy values of main cereals in poultry () () AME (kcal/kg) Relative value Corn 3, , Rice 3, , Barley 3, ,20 98 Wheat 3, ,50 96 Oats 2, , Sorghum 2, , Rye 2, , Table 6. Variability in energy content of corn for poultry Institut. Moist. (%) EE (%), , Viçosa Rostagno et al. () 33

5 Table 7. Variability in energy content of wheat for poultry Institut. Moist. (%) Starch (%) Viçosa Starch analyses? 2 Rostagno et al. () Tabla 8. Variability in energy content of barley for poultry (Mcal/kg) Moist. (%) Starch (%) AMEn (Mcal(kg) PS Inst Table 9. Comparative energy value of broken rice and corn (Mcal/kg) Corn Rice % Rostagno The crude protein content of the main cereals used by the industry, according to the different institutions, is shown in Table 0. Again, to notice the high variability in CP among sources for all cereals, with a range from 7.5 to % for corn. Usually, the variability in CP content is lower for corn than for the small grains, specially in those countries, such as, in which the small grain (wheat, barley, rye, triticale and oats) are produced in nonirrigated lands. As a consequence, the proportion of protein and starch (and fiber) of the seeds will depend on the raining conditions during the growing season. 34

6 Table 0. Crude protein content of major cereals () () () Vicosa () () () Corn Rice Barley Wheat Oats Sorghum Rye Conclusions In spite of the many years of research on the AMEn content and amino acid availability of the different ingredients used in poultry diets, still we do not have a simple method to evaluate with accuracy these values. Factors such as processing conditions, feed form and particle size, origin of the ingredient, diet characteristics, and use of additives will influence the energy and protein value of the ingredients and thus, tables values should be taken precaucioulsy. However, listed tables values, provided that the nutritionist applied sound information to existing tables and the use of predictive equations are useful tools to improve our knowledge on the nutrient content of ingredients. References, AMINODAT 5.0 () Amino Acid Analysis. Redshaw, M.S., Fickler, J., Fontaine, J., Heimbeck, W., Hess, V., Reinmann, I., (Eds.) Degussa GmbH, HanauWolfgang,. () Veevoedertabel (Livestock Feed Table). Centraal Veevoeder Bureau, Lelystad. The. DE COCASINOVA, A., VALENCIA, D.G., JIMÉNEZMORENO, E., LÁZARO, R., MATEOS, G.G. (2008) Apparent ileal digestibility of energy, nitrogen, and amino acids of soybean meals of different origin in broilers. Poultry of Science 87: FEDNA (Fundación Española Desarrollo Nutrición Animal) () Normas FEDNA de Composición y Valor nutritivo de Alimentos para la Fabricación de Piensos Compuestos, third ed. In: De Blas, C., Mateos, G.G., Rebollar, P.G. (Eds). FEDNA, Madrid,. FRIKHA, M., SERRANO, M.P., VALENCIA, D.G., REBOLLAR, P.G., FICKLER, J., MATEOS, G.G. (202) Correlation between ileal digestibility of amino acids and chemical composition of soybean meals in broilers at 2 days of age. Anim. Feed Sci. Technol. 78, 03 GARCIA REBOLLAR, P., CÁMARA, L., LÁZARO, R.P., DEPOZA, C., PEREZ MALDONADO, R., MATEOS, G.G. () Influence of origin of the beans on chemical composition and nutritive value of commercial soybean meals. Animal Feed Science Technology (In press). () Tables de composition et de valeur nutritive des matières premiers destinées aux animaux d elevage., Paris.. IRANDOUST, H., SAMIE, A.H., RAHMANI, H.R., EDRISS, M.A., MATEOS, G.G. (202). Influence of source of fat and supplementation of the diet with Vitamin E and C on performance and egg quality of laying hens from forty four to fifty six weeks of age. Animal Feed Science and Technology 77: JIMÉNEZ MORENO, E., DE COCA SINOVA, A., GONZÁLEZ ALVARADO, J.M. MATEOS, G.G. (). Inclusion of insoluble fiber sources in mash or pellet diets for young broilers. Effects growth performance and water intake. Poultry Science 95:452. LÁZARO, R.P., GARCÍA, M., ARANIBAR, M.J., MATEOS, G.G. (2003). Effect of enzyme addition to wheat, barley and rye based diets on nutrient digestibility and performance of laying hens. British Poultry Science 44: MANDALAWI, H.A., MALLO, J.J., MENOYO, D., LÁZARO, R., MATEOS, G.G. () Metabolizable energy content of traditional and reesterified lipid sources: effects of inclusion in the diet on nutrient retention and growth performance of broilers from high to 2 days of age. Animal Feed Science 35

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