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1~21日龄黄羽肉鸡棉籽粕傅里叶近红外及化学成分净能预测模型研究

DOI: 10.3969/j.issn.1006-267x.2011.09.007

Keywords: 黄羽肉鸡,NE,预测,近红外,水分校正

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Abstract:

本试验在用比较屠宰法实测25个棉籽粕样品净能(NE)值的基础上,旨在研究用傅里叶近红外(NIRS)和化学成分2种方法建立的NE预测模型的可行性,并比较2种预测模型的预测效果。1)棉籽粕NE值的测定采用维持NE(NEm)+沉积NE(NEp)的方法。其中NEm用回归法测定,设自由采食及限饲20%、40%、60%和80%5个采食梯度,NEp采用套算法测定;每个梯度和棉籽粕样品均设6个重复,每个重复2只鸡。试验动物为382只平均体重为(62.20±0.64)g的7日龄末空腹康达尔黄羽肉公鸡,试验期为7d。2)分别建立自然状态和扩大水分背景的NIRS预测模型M1和M2。3)将25个棉籽粕样品的表观代谢能(AME)、粗蛋白质、粗脂肪、粗纤维、中性洗涤纤维、酸性洗涤纤维和灰分7种成分值与NE值进行一元和多元线性回归分析。结果如下:1)M1、M2的校正决定系数(R2cal)分别为0.999、0.985,校正标准差(RMSEE)分别为0.033、0.084MJ/kgDM,交叉验证决定系数(R2cv)分别为0.966、0.967,交叉验证标准差(RMSECV)分别为0.120、0.117MJ/kgDM,预测决定系数(R2val)分别为0.843、0.957,预测标准差(RMSEP)分别为0.260、0.136MJ/kgDM,2个模型预测值与实测值配对t检验结果均不显著(P>0.05)。2)用化学成分结合AME建立的最佳预测方程的R2和RSD分别为0.985和0.093MJ/kgDM。结果表明:1)应用NIRS和AME结合化学成分均能建立预测效果可靠的棉籽粕NE预测模型;2)NIRS所建M2模型的预测效果与AME结合化学成分所建模型相当。

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