摘要
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 k J/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 M J/kg);用AM E结合化学成分建立的最佳预测方程为NE=0.230 AME-0.132 ADF-1.69 CF+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)M J/kg,不同豆粕存在较大差异;2)用豆粕化学成分和AM E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。
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 energy( 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 regression 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 1basal 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 simple 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 BW^0. 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( R^2= 0. 931,RSD = 0. 168 MJ / kg). The optimum prediction model for AME by chemical composition was NE = 0. 230AME-0. 132ADF-1. 69 CF +7. 320( R^2= 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.
出处
《动物营养学报》
CAS
CSCD
北大核心
2015年第10期3110-3117,共8页
CHINESE JOURNAL OF ANIMAL NUTRITION
基金
四川省科技支撑计划(2013NZ0054,科创饲料产业技术研究院)
四川农业大学双支计划
关键词
天府肉鸭
豆粕
净能
化学成分
预测模型
Tianfu ducks
soybean meal
net energy
chemical composition
prediction models