Fixing multicollinearity in modelling market body weight of Sudani ducks (Cairina moschata) from early age morphometric traits

Abstract

Morphometric parameters and their indices are central to characterization, selection and genetic improvement of farm animals. The present study was conducted to fix multicollinearity among predictors and to fit optimum regression model for prediction of 14-week body weight of 150 un-sexed Sudani ducks from early age (0, 2, 4 and 6 weeks of age) morphometric measurements (body weight, body length, breast circumference and keel length). Pairwise correlation between the 14-week body weight (BWT) and measured variables was the highest with 2-week BWT (r=0.934, P<0.001). Application of multicollinearity diagnostics (variance inflation factor, tolerance, eigenvalues and condition index) revealed collinearity among six variables. Stepwise regression equation identified 2-week BWT as the most important predictor accounting for 87.30% of the total variation of the response variable. However, the optimum regression model for prediction of adult body weight was fitted with 2-week BWT in quadratic model having the highest predictive power (Coefficient of determination /R2/=0.966 and least root mean square error /RMSE/=4.269). This result is applicable under field conditions for both researchers and duck farmers for early selection of 14-week market body weight of Sudani ducks at 2 weeks of age.

Measurement of some body parts of muscovy duck (Carina moschata) at age 3 weeks old fed by pellet feed under an intensive farming system

“…A distinctive feature of this duck lies in its sexual dimorphism, where the male exhibits significantly greater size compared to the female. Morphometric measurements and associated indices play a pivotal role in characterizing, selecting, and genetically enhancing farm animals [11]. Body weight is an economically important trait for livestock and is highly valued by farmers [12].…”