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Yıl 2025, Cilt: 9 Sayı: 2, 493 - 501, 26.06.2025

İsmail Gök , Kadriye Kurşun

https://doi.org/10.31015/2025.2.22

Öz

Kaynakça

  • Albayrak, S. A. (2005). Alternative biased estimation techniques of least squares technique in multicollinearity and an application. Zonguldak Kara Elmas University Journal of Social Sciences, (1),105-126, (in Türkiye).
  • Alkan, S., Karabağ, K., Galiç, A., Karslı, T., Balcıoğlu, M.S. (2010). Effects of selection for body weight and egg production on egg quality traits in Japanese quails (Coturnix coturnix japonica) of different lines and relationships between these traits. Kafkas University Journal of Veterinary Faculty, 16(2),239-244, (in Türkiye). http://dx.doi.10.9775/kvfd.2009.633
  • Aktan, S. (2004). Determination of some internal and external quality traits and their relationships in quail eggs by digital image analysis. Animal Production 45(1),7-13 (in Türkiye).
  • Akçay, A., & Sarıözkan, S. (2015). Estimation of income in layer chicken farming by Ridge Regression analysis. Ankara University Veterinary Faculty Journal, (62),69-74, (in Türkiye).
  • Bai, Z. (2017). A new approach to principal component regression for high-dimensional data. Journal of Statistical Theory and Practice, 11(2):184-195.
  • Çetenak, T., Gök, İ., Yavuz, E., Şahin, M. (2024). Statistical models and evaluation criteria used in poultry farming. Black Sea Journal of Agriculture, 7(6),710-719. (in Türkiye). http://dx.doi.10.47115/bsagriculture.1532659
  • Demir, Y., Keskin, S., Çavuşoğlu, Ş. (2021). Introduction and applicability of nonlinear principal component analysis. Kahramanmaraş Sütçü İmam University Journal of Agriculture and Nature, 24(2),442-450 (in Türkiye). http://dx.doi.org/10.18016/ksutarimdoga.vi.770817
  • Dickey, D. A., & Fuller W. A. (1979). distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a),427-431. http://dx.doi.org/10.2307/2286348
  • Gök İ., Yavuz E., Şahin M. (2022). Econometric Analysis of Factors Affecting the Buying or Selling Agricultural Lands. Black Sea Journal of Agriculture, 5(4),455-463 (in Türkiye). https://doi.org/10.47115/bsagriculture.1127834
  • Gök İ., Şahin M., Tolun T. (2023). Determination of Impact Size by Canonical Correlation Analysis of the Factors Affecting the Buying or Selling Agricultural Lands. Cumhuriyet Science Journal, 44(2),411-417, (in Türkiye). https://doi.org/10.17776/csj.1139858
  • Gök İ., and Şahin M. (2023). Investigation of Vegetable Production Amount and the Size of Cultivation Areas in Kahramanmaraş with the Econometric Model. Black Sea Journal of Agriculture, 6(1), 8-15 (in Türkiye). https://doi.org/10.47115/bsagriculture.1138860
  • Gök İ., and Şahin M. (2023). Estimate of Structural Fractures in Wheat Culture and Production in Türkiye by Econometric Analysis. Black Sea Journal of Agriculture, 6(4),411-415 (in Türkiye). https://doi.org/10.47115/bsagriculture.1285159
  • Gök İ., and Şahin M. (2024). Econometric Analysis of Corn Production in Türkiye. Journal of Agricultural Faculty of Gaziosmanpaşa University (JAFAG), 41(2),33-39. (in Türkiye). https://doi.org/10.55507/gopzfd.1288261
  • Gök, İ., & Şahin, M. (2024). Analysis of the relationship lag between beef production amount and average meat price in Türkiye using the Koyck Model. Turkish Journal of Agriculture and Natural Sciences, 11(2),342-346. (in Türkiye). http://dx.doi.org/10.30910/turkjans.1397617
  • Haug, W., et al. (2010). Chemical Composition and Nutritional Value of Quail Eggs. Journal of Agricultural and Food Chemistry, 58(8),4614-4619. ISSN: 2836-2543.
  • Johansen, S. (1995). Likelihood based inference in cointegrated vector autoregressive models. Oxford: Oxford University Press.
  • Jolliffe, I. T. (2002). Principal Component Analysis. Springer-Verlag, New York.
  • Johnson, Richard A. Dean W. Wichern, Applied Multivariate Statistical Analysis, Fifth Edition, New Jersey, Prentice-Hall, Inc., 2002.
  • Jolliffe, I. T. (2004). Principal Component Analysis, Second Edition, New York, Springer Science+Business Media, p.6-9.
  • Kaya, E., Aktan S. (2011). Flock age and hatching egg storage period in Japanese quail: 1. Effects on dark albumen traits. Süleyman Demirel University Journal of Agriculture Faculty, 6(2),30-38, (in Türkiye). ISSN 1304-9984.
  • Kul, S., & Şeker, I. (2004). Phenotypic correlations between some external and internal egg quality traits in the Japanese quail (Coturnix coturnix japonica). International Journal of Poultry Science, 3(6),400-405, (in Türkiye). http://dx.doi.org/10.3923/ijps.2004.400.405
  • Kutlu, H.R., & Erdem, H. (2013). Using multivariate regression analysis to predict egg quality traits in quail eggs. Journal of Animal Science and Technology, 55(5),12-21, (in Türkiye).
  • Maxwell, S. E. (2000). Sample size in multiple regression analysis. Psychological Methods, 5(4),434-458. https://psycnet.apa.org/doi/10.1037/1082-989X.5.4.434
  • Montgomery, D. C., Peck E. A., & Vining, G. G. (2001). Introduction to Linear Regression Analysis, 3rd Edition, John Wiley & Sons, New York.
  • O'Brien, R. M. (2007). A caution regarding rules of thumb for variance factors inflation. Quality & Quantity, 41, 673–690. https://doi.org/10.1007/s11135-006-9018-6
  • Oktay, A., & Yıldız, M. (2017). Impact of multicollinearity on the quality prediction of quail eggs. Journal of Statistical and Computational Methods, 48(4):567-573, (in Türkiye).
  • Olawumi, S., and Chiristiana, B. (2017). Phenotypic correlations between external and internal egg quality traits of Coturnix quails reared under intensive housing system. Journal of Applied Life Sciences International, 12(3),1-6. https://doi.org/10.9734/JALSI/2017/33802
  • Pahm, A. L., et al. (2012). Nutritional Value and Quality Characteristics of Quail Eggs. Poultry Science, 91(10),2525-2531.
  • Rathert, Ç. T., Üçkardeş, F., Narinç, D., Aksoy, T. (2011). Comparision of principal component regression with the least square method in prediction of internal egg quality characteristics in Japanese quails. Kafkas Üniversitesi Veterinerlik Fakültesi Dergisi, 17(5), 687-692, (in Türkiye). https://doi.org/10.9775/kvfd.2010.3974
  • Tolun, T., Yavuz, E., Şahin, M., Gök, İ. (2023). Modeling egg curves ın partridges. Black Sea Journal of Agriculture, 6(1),21-25, (in Türkiye). https://doi.org/10.47115/bsagriculture.1139272
  • Tolun, T., Gök, İ., Şahin, M. (2024). Modeling of some egg characteristics in henna partridges. Black Sea Journal of Agriculture, 7(6),729-742, (in Türkiye). https://doi.org/10.47115/bsagriculture.1555738
  • Üçkardeş, F., Efe, E., Narinç, D., Aksoy, T. (2012). Estimation of egg white index in Japanese quails using Ridge regression method. Academic Journal of Agriculture, (1),11-20, (in Türkiye). ISSN: 2147-6403.
  • Wang, J., et al. (2015). Application of principal component regression to predict egg quality in quails. Poultry Science Journal, 94(6),1292-1298.
  • Yannakopoulos, A. L., Tserveni-Gousi, A. S. (1986). Qualitycharacteristics of quaileggs. British Poultry Science, (27),171-176. https://doi.org/10.4236/ojas.2021.112016
  • Yalçınöz, E., Şahin, M. (2020). Modeling of egg production curves in laying hens. KSÜ Agriculture and Nature Journal, 23(5),1373-1378, (in Türkiye). https://doi.org/10.18016/ksutarimdoga.vi.631937
  • Yavuz, E., Abacı, S. H., Erensoy, K., Şahin, M. (2023). Modeling of ındividual egg weights of Lohmann-Brown layer hens. Turkish Journal of Veterinary & Animal Sciences, 47(3),229-335. (in Türkiye). https://doi.org/10.55730/1300-0128.4290

Prediction model of albumen index and height in Japanese quail eggs via external quality characteristics

Yıl 2025, Cilt: 9 Sayı: 2, 493 - 501, 26.06.2025

İsmail Gök , Kadriye Kurşun

https://doi.org/10.31015/2025.2.22

Öz

This study used multiple regression analysis to estimate the relationships between egg albumen index and height and external quality traits of eggs in Japanese quails. Egg albumen index and height were selected as dependent variables, while egg weight, width, length, shape index and Haugh unit were determined as independent variables. In the multiple regression analysis, although the overall fit of the model was high, it was determined that there were multicollinearity problem among the independent variables. To solve this problem, the Principal Components Regression (PCR) method, which is widely used in the literature, was applied. With this method, the following regression equations were obtained, respectively, by using egg weight (X1, Z1), width (X2, Z2), length (X3, Z3), shape index (X4, Z4) and Haugh unit (X5, Z5) variables in estimating albumen index and height:
Y ̂=(-19.95) ̂-(0.02) ̂X_1-(0.22) ̂X_2-(0.03) ̂X_3+(0.01) ̂X_4+(0.43) ̂X_5+e ̂
T ̂=(-13.21) ̂+(0.09) ̂Z_1+(0.03) ̂Z_2-(0.004) ̂Z_3-(0.005) ̂Z_4+(0.18) ̂Z_5+e ̂
The regression equations obtained were found to be statistically significant (P<0.05) and the goodness of fit of the models were determined as Detaermination coefficient (R²) = 0.86 and 0.99, respectively. Principal Components Regression (PCR) method reduced the errors caused by multicollinearity problem by decreasing the standard errors of the parameters and increased the accuracy of the model. The results show that Principal Components Regression (PCR) method effectively solved the multicollinearity problem and ensured the reliability of the model by increasing the prediction accuracy. These findings reveal that Principal Components Regression (PCR) method can be used effectively in poultry breeding and selection studies.

Anahtar Kelimeler

Multicollinearity problem Least Squares Method (LSM) Quail egg characteristics Principal Components Regression(PCR) method

Kaynakça

  • Albayrak, S. A. (2005). Alternative biased estimation techniques of least squares technique in multicollinearity and an application. Zonguldak Kara Elmas University Journal of Social Sciences, (1),105-126, (in Türkiye).
  • Alkan, S., Karabağ, K., Galiç, A., Karslı, T., Balcıoğlu, M.S. (2010). Effects of selection for body weight and egg production on egg quality traits in Japanese quails (Coturnix coturnix japonica) of different lines and relationships between these traits. Kafkas University Journal of Veterinary Faculty, 16(2),239-244, (in Türkiye). http://dx.doi.10.9775/kvfd.2009.633
  • Aktan, S. (2004). Determination of some internal and external quality traits and their relationships in quail eggs by digital image analysis. Animal Production 45(1),7-13 (in Türkiye).
  • Akçay, A., & Sarıözkan, S. (2015). Estimation of income in layer chicken farming by Ridge Regression analysis. Ankara University Veterinary Faculty Journal, (62),69-74, (in Türkiye).
  • Bai, Z. (2017). A new approach to principal component regression for high-dimensional data. Journal of Statistical Theory and Practice, 11(2):184-195.
  • Çetenak, T., Gök, İ., Yavuz, E., Şahin, M. (2024). Statistical models and evaluation criteria used in poultry farming. Black Sea Journal of Agriculture, 7(6),710-719. (in Türkiye). http://dx.doi.10.47115/bsagriculture.1532659
  • Demir, Y., Keskin, S., Çavuşoğlu, Ş. (2021). Introduction and applicability of nonlinear principal component analysis. Kahramanmaraş Sütçü İmam University Journal of Agriculture and Nature, 24(2),442-450 (in Türkiye). http://dx.doi.org/10.18016/ksutarimdoga.vi.770817
  • Dickey, D. A., & Fuller W. A. (1979). distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a),427-431. http://dx.doi.org/10.2307/2286348
  • Gök İ., Yavuz E., Şahin M. (2022). Econometric Analysis of Factors Affecting the Buying or Selling Agricultural Lands. Black Sea Journal of Agriculture, 5(4),455-463 (in Türkiye). https://doi.org/10.47115/bsagriculture.1127834
  • Gök İ., Şahin M., Tolun T. (2023). Determination of Impact Size by Canonical Correlation Analysis of the Factors Affecting the Buying or Selling Agricultural Lands. Cumhuriyet Science Journal, 44(2),411-417, (in Türkiye). https://doi.org/10.17776/csj.1139858
  • Gök İ., and Şahin M. (2023). Investigation of Vegetable Production Amount and the Size of Cultivation Areas in Kahramanmaraş with the Econometric Model. Black Sea Journal of Agriculture, 6(1), 8-15 (in Türkiye). https://doi.org/10.47115/bsagriculture.1138860
  • Gök İ., and Şahin M. (2023). Estimate of Structural Fractures in Wheat Culture and Production in Türkiye by Econometric Analysis. Black Sea Journal of Agriculture, 6(4),411-415 (in Türkiye). https://doi.org/10.47115/bsagriculture.1285159
  • Gök İ., and Şahin M. (2024). Econometric Analysis of Corn Production in Türkiye. Journal of Agricultural Faculty of Gaziosmanpaşa University (JAFAG), 41(2),33-39. (in Türkiye). https://doi.org/10.55507/gopzfd.1288261
  • Gök, İ., & Şahin, M. (2024). Analysis of the relationship lag between beef production amount and average meat price in Türkiye using the Koyck Model. Turkish Journal of Agriculture and Natural Sciences, 11(2),342-346. (in Türkiye). http://dx.doi.org/10.30910/turkjans.1397617
  • Haug, W., et al. (2010). Chemical Composition and Nutritional Value of Quail Eggs. Journal of Agricultural and Food Chemistry, 58(8),4614-4619. ISSN: 2836-2543.
  • Johansen, S. (1995). Likelihood based inference in cointegrated vector autoregressive models. Oxford: Oxford University Press.
  • Jolliffe, I. T. (2002). Principal Component Analysis. Springer-Verlag, New York.
  • Johnson, Richard A. Dean W. Wichern, Applied Multivariate Statistical Analysis, Fifth Edition, New Jersey, Prentice-Hall, Inc., 2002.
  • Jolliffe, I. T. (2004). Principal Component Analysis, Second Edition, New York, Springer Science+Business Media, p.6-9.
  • Kaya, E., Aktan S. (2011). Flock age and hatching egg storage period in Japanese quail: 1. Effects on dark albumen traits. Süleyman Demirel University Journal of Agriculture Faculty, 6(2),30-38, (in Türkiye). ISSN 1304-9984.
  • Kul, S., & Şeker, I. (2004). Phenotypic correlations between some external and internal egg quality traits in the Japanese quail (Coturnix coturnix japonica). International Journal of Poultry Science, 3(6),400-405, (in Türkiye). http://dx.doi.org/10.3923/ijps.2004.400.405
  • Kutlu, H.R., & Erdem, H. (2013). Using multivariate regression analysis to predict egg quality traits in quail eggs. Journal of Animal Science and Technology, 55(5),12-21, (in Türkiye).
  • Maxwell, S. E. (2000). Sample size in multiple regression analysis. Psychological Methods, 5(4),434-458. https://psycnet.apa.org/doi/10.1037/1082-989X.5.4.434
  • Montgomery, D. C., Peck E. A., & Vining, G. G. (2001). Introduction to Linear Regression Analysis, 3rd Edition, John Wiley & Sons, New York.
  • O'Brien, R. M. (2007). A caution regarding rules of thumb for variance factors inflation. Quality & Quantity, 41, 673–690. https://doi.org/10.1007/s11135-006-9018-6
  • Oktay, A., & Yıldız, M. (2017). Impact of multicollinearity on the quality prediction of quail eggs. Journal of Statistical and Computational Methods, 48(4):567-573, (in Türkiye).
  • Olawumi, S., and Chiristiana, B. (2017). Phenotypic correlations between external and internal egg quality traits of Coturnix quails reared under intensive housing system. Journal of Applied Life Sciences International, 12(3),1-6. https://doi.org/10.9734/JALSI/2017/33802
  • Pahm, A. L., et al. (2012). Nutritional Value and Quality Characteristics of Quail Eggs. Poultry Science, 91(10),2525-2531.
  • Rathert, Ç. T., Üçkardeş, F., Narinç, D., Aksoy, T. (2011). Comparision of principal component regression with the least square method in prediction of internal egg quality characteristics in Japanese quails. Kafkas Üniversitesi Veterinerlik Fakültesi Dergisi, 17(5), 687-692, (in Türkiye). https://doi.org/10.9775/kvfd.2010.3974
  • Tolun, T., Yavuz, E., Şahin, M., Gök, İ. (2023). Modeling egg curves ın partridges. Black Sea Journal of Agriculture, 6(1),21-25, (in Türkiye). https://doi.org/10.47115/bsagriculture.1139272
  • Tolun, T., Gök, İ., Şahin, M. (2024). Modeling of some egg characteristics in henna partridges. Black Sea Journal of Agriculture, 7(6),729-742, (in Türkiye). https://doi.org/10.47115/bsagriculture.1555738
  • Üçkardeş, F., Efe, E., Narinç, D., Aksoy, T. (2012). Estimation of egg white index in Japanese quails using Ridge regression method. Academic Journal of Agriculture, (1),11-20, (in Türkiye). ISSN: 2147-6403.
  • Wang, J., et al. (2015). Application of principal component regression to predict egg quality in quails. Poultry Science Journal, 94(6),1292-1298.
  • Yannakopoulos, A. L., Tserveni-Gousi, A. S. (1986). Qualitycharacteristics of quaileggs. British Poultry Science, (27),171-176. https://doi.org/10.4236/ojas.2021.112016
  • Yalçınöz, E., Şahin, M. (2020). Modeling of egg production curves in laying hens. KSÜ Agriculture and Nature Journal, 23(5),1373-1378, (in Türkiye). https://doi.org/10.18016/ksutarimdoga.vi.631937
  • Yavuz, E., Abacı, S. H., Erensoy, K., Şahin, M. (2023). Modeling of ındividual egg weights of Lohmann-Brown layer hens. Turkish Journal of Veterinary & Animal Sciences, 47(3),229-335. (in Türkiye). https://doi.org/10.55730/1300-0128.4290
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ziraat Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

İsmail Gök 0000-0002-0759-1187

Kadriye Kurşun 0000-0001-9533-7391

Yayımlanma Tarihi 26 Haziran 2025
Gönderilme Tarihi 19 Mart 2025
Kabul Tarihi 5 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 2

Kaynak Göster

APA Gök, İ., & Kurşun, K. (2025). Prediction model of albumen index and height in Japanese quail eggs via external quality characteristics. International Journal of Agriculture Environment and Food Sciences, 9(2), 493-501. https://doi.org/10.31015/2025.2.22
 Kapak Resmi İndir


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