Alvarenga R R, Rodrigues P B, Zangeronimo M G, Oliveira E C, Mariano F C M Q, Lima E M C, Garcia A A P, Naves L P, Nardelli N B S
Veterinary Medicine Department, Federal University of Lavras, Lavras, MG 37200-000, Brazil .
Exact Science Department, Federal University of Lavras, Lavras, MG 37200-000, Brazil .
Asian-Australas J Anim Sci. 2015 Sep;28(9):1335-44. doi: 10.5713/ajas.14.0339.
A set of prediction equations to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of individual ingredients and diets used in the poultry feed industry was evaluated. The AMEn values of three energy ingredients (maize, sorghum and defatted maize germ meal), four protein ingredients (soybean meal, maize gluten meal 60% crude protein, integral micronized soy and roasted whole soybean) and four diets (three containing four feedstuffs, complex diets, and one containing only corn-soybean meal, basal diet) were determined using a metabolism assay with male broilers from 1 to 7, 8 to 21, 22 to 35, and 36 to 42 days old. These values were compared to the AMEn values presented in the tables of energy composition or estimated by equation predictions based on chemical composition data of feedstuffs. In general, the equation predictions more precisely estimated the AMEn of feedstuffs when compared to the tables of energy composition. The equation AMEn (dry matter [DM] basis) = 4,164.187+51.006 ether extract (% in DM basis)-197.663 ash-35.689 crude fiber (% in DM basis)-20.593 neutral detergent fiber (% in DM basis) (R(2) = 0.75) was the most applicable for the prediction of the energy values of feedstuffs and diets used in the poultry feed industry.
对一套用于估算家禽饲料行业中单个成分和日粮的氮校正表观代谢能(AMEn)的预测方程进行了评估。使用代谢试验,测定了三种能量成分(玉米、高粱和脱脂玉米胚芽粕)、四种蛋白质成分(豆粕、粗蛋白含量60%的玉米蛋白粉、全脂微粉大豆和烤全大豆)以及四种日粮(三种含有四种饲料原料的复合日粮,一种仅含玉米-豆粕的基础日粮)在1至7日龄、8至21日龄、22至35日龄和36至42日龄雄性肉鸡中的AMEn值。将这些值与能量成分表中列出的AMEn值或根据饲料原料化学成分数据通过方程预测估算的值进行比较。总体而言,与能量成分表相比,方程预测能更精确地估算饲料原料的AMEn。方程AMEn(以干物质[DM]计)= 4164.187 + 51.006乙醚提取物(以DM计的百分比)- 197.663灰分 - 35.689粗纤维(以DM计的百分比)- 20.593中性洗涤纤维(以DM计的百分比)(R² = 0.75)最适用于预测家禽饲料行业中使用的饲料原料和日粮的能量值。