动物营养学报2011，Vol.23Issue(2)：250-257,8.DOI:10.3969/j.issn.1006-267x.2011.02.010
1～21 日龄黄羽肉鸡豆粕净能预测模型
Prediction Models for the Net Energy Value of Soybean Meal for Yellow-feathered Broilers Aged from l to 21 Days
摘要
Abstract
The study was conducted to establish reliable prediction models for net energy (NE) of soybean meals (SM) for yellow-feathered broilers aged from 1 to 21 days. NE value of SM was measured as the sum value of NE for maintenance (NEm) and NE for deposition (NEp). NEm and NEp were determined by regression method and substitution method, respectively. Proximate compositions of 21 SM samples were measured. Analyses of simple and multiple linear regression were carried out between NE and apparent metabolic energy (AME) values,and chemical composition. The moisture contents of 21 samples were adjusted to 11％, 12％ and 13％, respectively, and the model of Fourier near infrared spectroscopy (FNIRS) was established based on the three moisture and the global. The results showed as follows: 1 ) the NE value of 21 SM samples for broilers aged from 1 to 21 days were from 6.045 to 7.829 MJ/kg, and the conversion efficiencies of AME to NE were from 55. 24％ to 62.78％; 2) the correlation coefficients (R2) of the best regression equations based on chemical composition and AME combined with chemical composition were 0.96 and 0.98, respectively, and the relative standard deviations (RSD) were 0.114 and 0.079 MJ/kg, respectively; 3 ) the correlation coefficients in calibration (R2cal) of the FNIRS models were 0.96, 0.98, 0.97 and 0.94, respectively, and the root mean square errors of calibration (RMSEE) were 0.100, 0.072, 0.069, 0.105 MJ/kg, respectively; the correlation coefficients in cross validation (R2cv) were 0.92, 0.95, 0.95 and 0.93, respectively, and the root mean square error of cross validation (RMSECV) were 0.131, 0.096, 0.089 and 0.116 MJ/kg, respectively. The results indicate that a reliable and convenient NIRS model of NE value can be established by enlarging the sample size with the adjusting of moisture. The accuracy of FNIRS model is as high as the model based on chemical composition, but less than that of the model based on AME combined with chemical composition.[Chinese Journal of Animal Nutrition,2011,23 (2) :250-257]关键词
黄羽肉鸡/净能/傅里叶近红外光谱/全局校正模型Key words
yellow-feathered broilers/ net energy/ Fourier near infrared spectroscopy/ global calibration model分类
农业科技引用本文复制引用
张正帆,王康宁,贾刚,吴秀群..1～21 日龄黄羽肉鸡豆粕净能预测模型[J].动物营养学报,2011,23(2):250-257,8.基金项目
四川农业大学双支计划 （）
