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首页> 外文期刊>Animal Feed Science and Technology >The distribution of crude protein and amino acid content in maize grain and soybean meal
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The distribution of crude protein and amino acid content in maize grain and soybean meal

机译：玉米籽粒和豆粕中粗蛋白和氨基酸含量的分布

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This study examines the assumptions of normal distributions for crude protein (CP) and amino acid (AA) contents in feedstuffs. Data for maize grain and soybean meal (SBM) were collected from the Ajinomoto Heartland LLC laboratory analysis database between 2002 and 2008. Tests of normality for CP and selected AA were performed for both feedstuffs by using graphical methods (histogram and normal quantile-quantile plot) and numerical methods (skewness and Shapiro-Wilk procedure (W)). Relationships between CP and AA were also computed using linear and quadratic regression and W were used to test for normality of the internally Studentized residuals of the regression model. Results indicated that methionine (Met) and arginine (Arg) were not normally distributed in maize grain (P<0.05). In addition, CP, lysine (Lys), threonine (Thr), Met, isoleucine (Ile) and tryptophan (Trp) were not normally distributed in SBM (P<0.05). There were linear relationships between CP and most of the AA in maize grain and SBM, except for the relationship between CP and Thr, and CP and Ile in maize grain and CP and total sulfur amino acids (TSAA), and CP and Arg in SBM which were found to be non-linear (significant quadratic terms at P<0.05). The results indicate the need for normality testing of AA levels in feed ingredients prior to generating prediction equations for AA levels from CP. Assuming a normal distribution of CP and AA in critical feed ingredients may lead to an over or under estimated nutrient content in feed formulation.Even though the regression residuals are normally distributed in maize grain and SBM, other models beside linear and quadratic regression could be applied in order to accurately predict AA contents based on CP
机译：这项研究检验了饲料中粗蛋白（CP）和氨基酸（AA）含量的正态分布假设。玉米粒和豆粕（SBM）的数据是从Ajinomoto Heartland LLC实验室分析数据库中收集的，在2002年至2008年之间。使用图形方法（直方图和正态分位数图）对两种饲料的CP和选定的AA进行了正态性测试）和数值方法（偏度和Shapiro-Wilk过程（W））。 CP和AA之间的关系也使用线性和二次回归来计算，W用于检验回归模型的内部Studentized残差的正态性。结果表明，蛋氨酸（Met）和精氨酸（Arg）在玉米籽粒中分布不正常（P <0.05）。另外，CP，赖氨酸（Lys），苏氨酸（Thr），Met，异亮氨酸（Ile）和色氨酸（Trp）在SBM中未正常分布（P <0.05）。玉米籽粒和SBM中CP与大多数AA之间存在线性关系，除了CP与Thr，玉米籽粒中CP和Ile与CP和总硫氨基酸（TSAA）以及SBM中CP和Arg之间的关系被发现是非线性的（在P <0.05时有明显的二次项）。结果表明在从CP生成AA水平的预测方程之前，需要对饲料成分中AA水平进行正常测试。假定关键饲料成分中CP和AA的正态分布可能导致饲料配方中营养成分的估计过高或不足，即使回归残差正态分布在玉米籽粒和SBM中，也可以应用除线性和二次回归之外的其他模型为了基于CP准确预测AA含量

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