CAJ | 학술논문

本试验旨在用析因法评定不同豆粕的天府肉鸭的净能( NE),并用表观代谢能( AME)结合化学成分建立其预测方程。豆粕NE的评定分为维持净能( NEm)与沉积净能( NEp)。试验共用天府肉鸭740只,先选100只随机分到自由采食及限饲20%、32%、44%、56%共5个组,采用回归法测定NEm；再选620只随机分到30个豆粕组和1个基础饲粮组,采用套算法评定豆粕的NEp；剩余20只鸭作为零对照组测定肉鸭初始能值。测定30种豆粕的常规化学成分,并根据测定的 NE、AME 和化学成分进行相关、回归分析。结果表明：天府肉鸭 NEm 为598.251 kJ/kg BW0.75,经套算法得到30种豆粕NE为(6.69±0.53) MJ/kg。用化学成分建立的最佳豆粕 NE 预测方程为 NE =0.412AME -0.126ADF +4.164( R2为0.931, RSD 为0.168 MJ/kg)；用AME 结合化学成分建立的最佳预测方程为 NE=0.230AME-0.132ADF-1.69CF+7.320(R2为0.942,RSD为0.156 MJ/kg)。由此可见,1)天府肉鸭的豆粕NE为(6.69±0.53) MJ/kg,不同豆粕存在较大差异；2)用豆粕化学成分和AME来预测天府肉鸭豆粕NE是可行的,且用AME结合化学成分建立的NE预测方程较好。
본시험지재용석인법평정불동두박적천부육압적정능( NE),병용표관대사능( AME)결합화학성분건립기예측방정。두박NE적평정분위유지정능( NEm)여침적정능( NEp)。시험공용천부육압740지,선선100지수궤분도자유채식급한사20%、32%、44%、56%공5개조,채용회귀법측정NEm；재선620지수궤분도30개두박조화1개기출사량조,채용투산법평정두박적NEp；잉여20지압작위령대조조측정육압초시능치。측정30충두박적상규화학성분,병근거측정적 NE、AME 화화학성분진행상관、회귀분석。결과표명：천부육압 NEm 위598.251 kJ/kg BW0.75,경투산법득도30충두박NE위(6.69±0.53) MJ/kg。용화학성분건립적최가두박 NE 예측방정위 NE =0.412AME -0.126ADF +4.164( R2위0.931, RSD 위0.168 MJ/kg)；용AME 결합화학성분건립적최가예측방정위 NE=0.230AME-0.132ADF-1.69CF+7.320(R2위0.942,RSD위0.156 MJ/kg)。유차가견,1)천부육압적두박NE위(6.69±0.53) MJ/kg,불동두박존재교대차이；2)용두박화학성분화AME래예측천부육압두박NE시가행적,차용AME결합화학성분건립적NE예측방정교호。
The study was conducted to determine the net energy ( NE ) of soybean meals using the factorial method, and was established prediction models for NE by chemical composition or apparent metabolizable en-ergy ( AME) . NE value of soybean meal was measured as the sum value of NE for maintenance ( NEm) and NE for deposition ( NEp) . A total of 740 Tianfu ducks were used in the experiment. NEm was measured by re-gression method with five groups used 100 ducks, which were ad libitum groups and restricted feeding 20%, 32%, 44%, 56% groups, respectively. NEp was measured by substitution method with 30 soybean meal groups and 1 basal diet group used 620 ducks. The other 20 ducks as a zero control group for measured initial energy values of ducks. Proximate compositions of soybean meal samples were measured, and analyses of sim-ple and multiple linear regression were carried out between NE and AME values, and chemical composition. The results showed that the NEm of ducks was 598.251 kJ/kg BW0.75, the NE value of 30 soybean meals were (6.69±0.53) MJ/kg. The optimum prediction model for NE of soybean meals by chemical composition was NE=0.412AME-0.126ADF+4.164 (R2=0.931,RSD=0.168 MJ/kg). The optimum prediction model for AME by chemical composition was NE=0. 230AME-0. 132ADF-1. 69CF+7. 320 ( R2 = 0. 942, RSD=0.156 MJ/kg). In conclusion, 1) the soybean meals NE of Tianfu ducks is (6.69±0.53) MJ/kg, and has greatly difference among different soybean meals. 2) It is feasible to using chemical composition and AME to establish prediction equations for soybean meal NE, and the best regression equation from AME combined with chemical composition is relatively good.