Document Type : Research Paper
Authors
1 Department of Poultry Science, Tarbiat Modares University
2 Poultry Science, Tarbiat Modares University
Abstract
The goal of this study was to determine regression equations to predict metabolizable energy of wheat samples given their chemical compositions using meta-analytical approach. A database compromising chemical compositions and apparent metabolizable energy corrected for the nitrogen (AMEn) of 111 published sources of wheat strains was used. Sample information contains crude protein (CP), ether extract (EE), crude fiber (CF), ash and AMEn. Average values for AMEn was calculated as 2917.46 (kcal/kg), while for the CP, EE, CF, ash was calculated as 12.53, 2.12, 1.61and 1.56 (% dry matter), respectively. Meta-regression equations for predicting AMEn wheat based on chemical composition were developed and evaluated by means of provided database. Best equation obtained as: AMEn (kcal/kg)=
1648+45.8 %CP+175.8 %EE+ 185.4 %CF. This equation can be used for predicting energy of wheat variates in feed-factories and poultry farms.
Keywords
2. Ahmadi H and Rodehutscord M (2017) Application of artificial neural network and support vector machines in predicting metabolizable energy in compound feeds for pigs. Frontiers in nutrition 4: 27.
3. Ahmadi H and Rodehutscord M (2012) A meta-analysis of responses to dietary nonphytate phosphorus and phytase in laying hens. Poultry Science 91(8): 2072-2078.
4. Ahmadi H (2017) A mathematical function for the description of nutrient-response curve. PloS one 12(11): e0187292.
5. Barteczko J, Augustyn R, Lasek O and Smulikowska S (2009) Chemical composition and nutritional value of different wheat cultivars for broiler chickens. Journal of Animal and Feed Sciences 18(1): 124-131. 14.
6. Carré B, Lessire M and Juin H (2013) Prediction of metabolisable energy value of broiler diets and water excretion from dietary chemical analyses. Animal 7(8):1246-1258.
7. Del Alamo AG, Verstegen MWA, Den Hartog LA, de Ayala P and Villamide MJ (2009) Wheat starch digestion rate affects broiler performance. Poultry Science 88(8):1675-1666.
8. Firkins JL, Eastridge ML, St-Pierre NR and Noftsger SM (2001) Effects of grain variability and processing on starch utilization by lactating dairy cattle. Journal of Animal Science 79(suppl_E): 218-238.
9. Ghods Alavi B, Morovaj H and Shivazad M (2017) Determination and comparison of the estimating equations of some Iranian wheat cultivars with the equations and information of NRC based on the production performance of broiler. Livestock products 19(2): 455-466. (in Persian)
10. Minitab (2014) MINITAB Release 17: Statistical Software for Windows; Minitab Inc. State College, PA, USA 2019.
12. Noorghadimi J, Moraveg H, Ghaziani, F and Akbari R(2016) Prediction the metabolizable energy of most wheat cultivars of Alborz province with a multiple regression equation. Iranian Journal of Animal Science (Iranian Journal of Agricultural Sciences) 46(4): 379-388. (in Persian)
13. National Research Council. (1994). Nutrient requirements of poultry: 1994. National Academies Press.
14. Salar M and Golian1 A (2000) The use of sibbald method for determining the metabolizable energy of some poultry feedstuffs sued in Iran. Agricultural Science and Technology 13(2): 185-195. (in Persian)
15. Sedghi M, Ebadi MR, Golian A and Ahmadi H (2013) Prediction of digestible amino acid and true metabolizable energy contents of sorghum grain from total essential amino acids. The Journal of Agricultural Science, 151(5): 693-700.
16. Shakouri M and Kermanshahi H (2003) Effect of NSP degrading enzyme supplement on the nutrient digestibility of young chickens fed wheat with different viscosities and triticale: 105-112.
17. Scott, T (2002) Impact of wet feeding wheatbased diets with or without enzyme on broiler chick performance. Canadian Journal of Animal Science 82(3):417-409.
18. Sauvant D and Martin O (2006) Empirical Modelling through Meta-analysis vs Mechanistic
Modelling. Nutrient digestion and utilization in farm animals: modelling approaches 242.
19. Sauvant D, Schmidely P, Daudin J and St-Pierre N.R (2008) Meta-analyses of experimental data in animal nutrition. Animal 2(8):1203-1214.
20. Valdes E and S. Leeson (1992) Near infrared reflectance analysis as a method to measure metabolizable energy in complete poultry feeds. Poultry science 71(7): 1179-1187.
21. Yegani M and Korver DR (2012) Prediction of variation in energetic value of wheat for poultry. Canadian Journal of Animal Science 92(3): 261-273.
22. Yaghoubfar A, Mirzaei S, Valizadeh H and Safamehr A (2012) Determination of Non- Starch Polysaccharides (NSP) and Metabolizable Energy of Iran Wheat Varieties Fed to Poultry. Iranian Journal of Animal Science Research 4(1): 25-31. (in Persian)
23. Zobdeh M. R, Moravej H and Shivazad M (2018) Determination of prediction equations of 16 Iranian wheat cultivars with two methods and at two different ages in broilers. Journal of Animal Production (Journal of Agriculture) 20(1): 191-201. (in Persian)
)