Estimation of Breeding Values with Heterogeneous Residual Variances by Random Regression Models

Bu çalışmada sabit, şansa bağlı genetik ve kalıcı çevre etkilerine sahip üçüncü dereceden şansa bağlı regresyon modelleri (RV1 ve RV10) kullanılmıştır. RV1 modelinde hata varyansı sabit, RV10 modelinde ise denetim günlerinin her biri farklı kabul edilmiştir. Hata varyansı RV1 modelinde 6.83 ve RV10 modelinde 5.30 ile 9.19 arasında tahminlenmiştir. Kalıtım dereceleri RV1 modelinde 0.12-0.53 iken, RV10 modelinde 0.04-0.18 arasında tahminlenmiştir. RV1 ve RV10 modelleri ile tahminlenen denetim günü süt verimi damızlık değerlerine ait Spearman ve Kendall sıra korelasyonları inek (0.79, 0.61) ve boğalarda (0.82, 0.63) birbirine benzer bulunmuştur. Sonuç olarak, her iki modelle elde edilen damızlık değerleri arasındaki ilişkinin yüksek olduğu belirlenmiştir. Sığırların damızlık değerlerinin sıralamasına yönelik korelasyonların yüksek olmasına karşın, sıralama bakımından modeller arasında farklılıklar saptanmıştır. Her iki modele ait damızlık değeri listesinde ilk 100 ineğin sıra değişimleri %22 oranında ortak ve %78 oranında farklı iken, ilk 50 boğanın sıra değişmeleri ise %30 oranında ortak ve %70 oranında farklı bulunmuştur. Genel olarak RV10 modeli damızlık değer tahmininde RV1 modelinden daha iyi bulunmuştur

Şansa Bağlı Regresyon Modelinde Heterojen Hata Varyansları ile Damızlık Değerinin Tahmin Edilmesi

In this study the third order random regression models (RV1 and RV10) including the fixed, random additive genetic and permanent environmental effects were used. In the RV1 model residual variance was constant and in the RV10 model all test day records were taken as different groups. The predicted error variance was found 6.83 in RV1 model and this variance was changed between 5.30 and 9.19 in RV10 model. Heritability values were estimated 0.12-0.53 for RV1 and 0.04-0.18 for RV10 models. Spearman rank and Kendall rank correlations between estimated breeding values of test day milk yields estimated from RV1 and RV10 models within cows (0.79, 0.61) were found almost same with within sires (0.82 and 0.63). Consequently, these correlations indicate that breeding values estimated from RV1 and RV10 models were highly correlated. Although the association between two set of breeding values estimated from RV1 and RV10 models were high, ranking of cows and sires by breeding values were different for two models. The shift in rank of first 100 cows was found 22% same and 78% different, also the shift in rank of first 50 sires was found 30% same and 70% different on RV1 and RV10 models breeding values rank list. Overall, the RV10 model was found better than RV1 model in estimation of breeding value

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