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

Kadriye Kurşun; İsmail Gök

Makale detayları

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

Yazarlar:

Kadriye Kurşun | İsmail Gök

Yayıncı:

Karyay Karadeniz Yayımcılık

Ana Başlıklar:

Ziraat Mühendisliği (Diğer)

Dergi:

Black Sea Journal of Agriculture Vol.8 Issue 4, pp.525-532

Belge Tipi:

Makale

Yayın Tarihi:

7/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001354604

pISSN:

2618-6578

Anahtar kelimeler:

Özet:

 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_30.0262 X_40.1921 X_5e . The regression equation was obtained and found to be statistically significant P0.05. The models fit was determined as R20.901, 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.

 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_30.0262 X_40.1921 X_5e . The regression equation was obtained and found to be statistically significant P0.05. The models fit was determined as R20.901, 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.

 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_30.0262 X_40.1921 X_5e . The regression equation was obtained and found to be statistically significant P0.05. The models fit was determined as R20.901, 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.

 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_30.0262 X_40.1921 X_5e . The regression equation was obtained and found to be statistically significant P0.05. The models fit was determined as R20.901, 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.

Makale detayları

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

Yazarlar:

Kadriye Kurşun | İsmail Gök

Yayıncı:

Karyay Karadeniz Yayımcılık

Ana Başlıklar:

Ziraat Mühendisliği (Diğer)

Dergi:

Black Sea Journal of Agriculture Vol.8 Issue 4, pp.525-532

Belge Tipi:

Makale

Yayın Tarihi:

7/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001354604

pISSN:

2618-6578

Duck egg characteristics

Multiple regression

Multicollinearity problem

Ridge regression methodDuck egg characteristics

Multiple regression

Multicollinearity problem

Ridge regression method

Sayı

Makale detayları

Yazarlar: Kadriye Kurşun | İsmail Gök

Yayıncı: Karyay Karadeniz Yayımcılık

Ana Başlıklar: Ziraat Mühendisliği (Diğer)

Dergi: Black Sea Journal of Agriculture Vol.8 Issue 4, pp.525-532

Belge Tipi: Makale

Yayın Tarihi: 7/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001354604

pISSN: 2618-6578

Sayı

Yazarlar:

Kadriye Kurşun | İsmail Gök

Yayıncı:

Karyay Karadeniz Yayımcılık

Ana Başlıklar:

Ziraat Mühendisliği (Diğer)

Dergi:

Black Sea Journal of Agriculture Vol.8 Issue 4, pp.525-532

Belge Tipi:

Makale

Yayın Tarihi:

7/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001354604

pISSN:

2618-6578