Prediction Model of Albumen Index in Duck Eggs via External Egg Quality Characteristics in Case of Multicollinearity

Authors : Kadriye Kurşun, İsmail Gök

Pages : 525-532

Doi:10.47115/bsagriculture.1655436

View : 72 | Download : 94

Publication Date : 2025-07-15

Article Type : Research Paper

Abstract :This study used multiple regression analysis to estimate the relationships between duck egg albumen index and external quality traits of eggs. Egg albumen index was selected as the dependent variable, and egg weight, width, length, shape index and Haugh unit were determined as independent variables. In the multiple regression analysis, it was determined that the overall fit of the model was quite high, but there were multicollinearity problem among the independent variables. In order to solve this problem, Ridge regression method, which is widely used in the literature, was applied. In order to determine the albumen index, egg weight (X1), width (X1), length (X3), shape index (X4) and Haugh unit (X5) variables were used, R ̂=(+18.2029) ̂+(0.1362) ̂X_1-(0.5736) ̂X_2-(0.1596) ̂X_3+(0.0262) ̂X_4+(0.1921) ̂X_5+e ̂. The regression equation was obtained and found to be statistically significant (P<0.05). The model\\\'s fit was determined as R2=0.901, and Ridge regression method reduced the standard errors of the parameters, reduced the errors caused by multicollinearity problem and increased the accuracy of the model. The results show that Ridge regression method effectively solves the problem of multicollinearity and increases the accuracy of prediction, making it more reliable. This also reveals that Ridge regression method can be used effectively in poultry breeding and selection studies.
Keywords : Duck egg characteristics, Multiple regression, Multicollinearity problem, Ridge regression method

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