Correlation analysis between the lean meat content and the carcass trait and live body in Guanzhong black pig
Hui Zhang
Abstract
Hui Zhang
Abstract
Data for this study were collected from 30 Guanzhong black pigs with a live weight around 90 kg.Assuming the final live weight ( x 1 ),body length ( x 2 ),dressed weight ( x 3 ),carcass length ( x 4 ),eye area ( x 5 ),ham joint weight ( x 6 ) and back fat thickness ( x 7 ) to be independent variables and the lean meat weight of carcass ( Y ) to be a dependent variable for path coefficient analysis,the correlation coefficients,path coefficients,determination coefficients and correlation indices ( R 2 ) were calculated.The results indicated that the correlation coefficients between the lean meat weight and respective independent variables were significant;the final live weight ( x 1 ) and the back fat thickness ( x 7 ) gave predominant direct effect ( P Yx 1 ,and P Yx 7 ) and determinacy on the lean meat weight( Y ).It is clear from the result of high correlation indices ( R 2 =0.939 8) that the path coefficient analysis could reveal the real relationship between the dependent variable and the independent variables.
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Data for this study were collected from 30 Guanzhong black pigs with a live weight around 90 kg.Assuming the final live weight ( x 1 ),body length ( x 2 ),dressed weight ( x 3 ),carcass length ( x 4 ),eye area ( x 5 ),ham joint weight ( x 6 ) and back fat thickness ( x 7 ) to be independent variables and the lean meat weight of carcass ( Y ) to be a dependent variable for path coefficient analysis,the correlation coefficients,path coefficients,determination coefficients and correlation indices ( R 2 ) were calculated.The results indicated that the correlation coefficients between the lean meat weight and respective independent variables were significant;the final live weight ( x 1 ) and the back fat thickness ( x 7 ) gave predominant direct effect ( P Yx 1 ,and P Yx 7 ) and determinacy on the lean meat weight( Y ).It is clear from the result of high correlation indices ( R 2 =0.939 8) that the path coefficient analysis could reveal the real relationship between the dependent variable and the independent variables.
Key concepts: Path coefficient, Mathematics, Path analysis (statistics), Correlation coefficient, Correlation, Carcass weight, Lean meat, Animal science