中国农业科学2024，Vol.57Issue(10)：2035-2045,11.DOI:10.3864/j.issn.0578-1752.2024.10.014
基于体外仿生酶水解物能值和化学成分预测谷物饲料原料的鸡代谢能值
Prediction Equations of Chicken Metabolizable Energy Values for Grain Ingredients Based on in Vitro Simulated Enzymatic Hydrolysate Gross Energy Values and Chemical Composition
摘要
Abstract
[Objective]This study aimed to measure the enzymatic hydrolysate gross energy(EHGE)of chicken for wheat,paddy,and brown rice ingredients using a monogastric simulated digestion system,and it also aimed to correlate these measurements with the chemical composition of these ingredients.Moreover,the study sought to establish predictive equations for chicken metabolizable energy values based on the EHGE values and the grain ingredients'chemical compositions.The findings would provide a reference for the rapid prediction of the metabolizable energy value of grain ingredients for chickens.[Method]The EHGE values of nine samples from three sources of wheat,paddy,and brown rice ingredients were measured.Five replicates were set for each grain sample,with one digestion tube per replicate.The apparent metabolizable energy values(AME)and true metabolizable energy values(TME)of the same batch of ingredients were also measured by the free feeding method(FF)and the tube-feeding method(TF).A linear regression model was then used to establish predictive equations for AME and TME based on chemical composition and EHGE values.[Result](1)Based on dry matter basis,the EHGE values of wheat,paddy,and brown rice from the three sources were 14.46,14.63,and 14.80 MJ·kg-1;12.52,13.59,13.40 MJ·kg-1,and 14.74,15.10,15.23 MJ·kg-1,respectively.(2)Ash and neutral detergent fiber exhibited a negative correlation with AME(AMEFF and TMEFF)and TME(AMETF and TMETF)measured by both FF and TF methods(P＜0.01).EHGE exhibited a significant positive correlation with AMEFF,TMEFF,AMETF,and TMET measured by both methods(P＜0.01),with correlation coefficients of 0.801,0.864,0.807,and 0.866,respectively.(3)Compared with the metabolizable energy prediction equations established by EHGE,the prediction equations based on chemical composition had higher coefficients of determination(R2)and lower residual standard deviations(RSD).For AMEFF and TMEFF,Ash was the best predictor,with prediction equations:AMEFF=16.728-0.842×Ash(R2=0.809,RSD=0.826,P=0.001),and TMEFF=16.812-0.842×Ash(R2=0.816,RSD=0.806,P=0.001).On the other hand,for the AMETF and TMETF variables,NDF was identified as the best predictor.The prediction equations for AMETF and TMETF were AMETF=16.106-0.157×NDF(R2=0.907,RSD=0.523,P＜0.001),and TMETF=17.654-0.157×NDF(R2=0.903,RSD=0.534,P＜0.001),respectively.[Conclusion]The EHGE of wheat and brown rice was higher than that of paddy,and there was a good correlation between the EHGE values of the three grain ingredients and the metabolizable energy values measured by the in vivo method.The prediction model for the AME and TME of grains based on chemical composition was superior to the prediction model based on EHGE.关键词
鸡/代谢能/酶水解物能值/预测模型/谷物Key words
chicken/metabolizable energy/enzymatic hydrolysate gross energy/prediction equation/grain引用本文复制引用
李凯,白国松,滕春然,马腾,钟儒清,陈亮,张宏福..基于体外仿生酶水解物能值和化学成分预测谷物饲料原料的鸡代谢能值[J].中国农业科学,2024,57(10):2035-2045,11.基金项目
国家重点研发计划(2022YFD1300605)、公益性科研院所基本科研业务费专项(2023-YWF-ZX-03)、现代农业产业技术体系专项资金(CARS-41) （2022YFD1300605）
