Development of Predictive Models for Egg Weight in Shika Brown Chickens Using Stepwise Regression
DOI:
https://doi.org/10.57038/usjas.v9i02.7843Abstract
Egg quality traits are essential indicators of productivity and commercial value in poultry breeding. This study evaluated egg quality characteristics of Shika Brown laying chickens and developed predictive models for egg weight (EWT) using stepwise regression. A total of 240 eggs, obtained from Shika Brown laying chickens, were analyzed for parameters including egg length (ELT), egg width (EWD), shell thickness (STK), shell weight (SWT), egg shape index (ESI), albumen weight (AWT), and yolk weight (YWT). Data were analyzed using statistical analysis procedures of Statistical Package for Social Sciences version 27.0 (IBM SPSS, 2020). Descriptive statistics and phenotypic correlations were computed to assess trait relationships. Stepwise regression analysis was employed to develop predictive models for EWT. Correlation analysis revealed significant relationships (p < 0.01) between EWT and external traits such as EWD (r = 0.256) and egg volume (EGV; r = 0.188), with a strong negative correlation between EWT and shell thickness index (STI; r = -0.763). Internal traits (albumen and yolk) showed weaker associations. The optimal predictive model was EWT = 57.271 - 19.030(STI) + 2.392(STK) + 4.080(EWD) - 0.125(ESI) - 0.155(ELT) with adjusted R² = 0.888 and RMSE = 1.813. External egg quality traits enable accurate EWT estimation, reducing reliance on direct measurement. These findings support optimized selection strategies in Shika Brown breeding programs, enhancing productivity and market value.
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