Estimation of egg weight from some external and internal quality characteristics in quail by using various data mining algorithms

Abstract

The objective of this study was to compare the predictive performance of some data mining algorithms implemented in the estimation of egg weight (EW), some egg quality traits measurements in quail. These quality traits are albumen weight (AW), yolk weight (YW), specific weight (SW), albumen index (AI), albumen height (AH), yolk index (YI), shell weight (SHW), shell thickness (SHT), Haugh unit (HU) and shape index (SI). For comparing the predictive performance of these algorithms in Model, goodness of fit criteria such as coefficient of determination (R2%), adjusted coefficient of determination (Adj. R2%), coefficient of variation (CV%), SD ratio, root mean square error (RMSE), relative approximation error (RAE), and Pearson correlation coefficient, between observed and predicted values were calculated. The heaviest average EW of 13.516 g was obtained from the subgroup of those having AW > 8 cm. The results showed that the analysis based on exhaustive CHAID might be useful for further researches linked with characterization of quail egg better than those provided by CART and CHAID algorithms.