科研之友
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摘要
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.
- 出版日期2010-8-11
