Comparison of fitting performance of ramdom regression models to test day milk yields in Holstein friesians

Bu çalUşmada Ali-Schaeffer fonksiyonu, Wilmink fonksiyonu ve ortagonal Legendre polinomiyal uygulanan şansa bağı regresyon modellerinin denetim günü süt verimlerine uyum performansları karşılaştırılmıştır. Eklemeli ve kalıcı çevre etkileri için Legendre polinomiyal fonksiyonunun ikinci dereceden altıncı dereceye kadar uyumları yapılmış, hata varyansUnUn ise laktasyon boyunca homojen olduğu kabul edilmiştir. Analizler, 1987 ile 1993 yılları arasUnda Dalaman, Tahirova, Sarımsaklı ve Türkgeldi çiftliklerinde buzağılayan, 612 adet Siyah Alaca’nUn toplam 5918 ilk laktasyon kaydına uygulanmıştır. Modellerin karşılaştırılmasUnda, modelin hata varyansı, -2LogL değeri, Akaike ve Bayes bilgi kriterleri ile eklemeli genetik ve kalıcı çevre etkisine ait şansa bağlU regresyon (ko)varyans matrisinin özdeğerleri kullanUlmUştUr. Toplam 27 modelin karşılaştırılması sonucunda, L(6,2), L(6,5) ve L(6,6) modellerinin uyumu daha iyi bulunmuştur.

Anahtar Kelimeler:

sığır, Siyah Alaca(sığır ırkı), kovaryans analizi, çevresel etki, genetik korelasyon, süt verimi, modeller, regresyon analizleri

Siyah alacalarda şansa bağlı regresyon modellerinin denetim günü süt verimlerine uyum performanslarının karşılaştırılması

In this study, random regression models with Ali-Schaeffer functions, Wilmink functions and orthogonal Legendre polynomials were compared for fitting performance to test day milk yields. Legendre polynomials with orders from two to six for additive genetic and permanent environmental effects were fitted under homogeneous error variance assumption throughout lactation. The analyzes were applied to 5918 first lactation test day milk yields of 612 Holstein Friesian cows calving from 1987 to 1993 in Dalaman, Tahirova, SarUmsaklU and Türkgeldi State Farms. To compare the models, residual variances, -2LogL value, Akaike’s information criterion, Bayesian information criterion and eigenvalues for additive genetic and permanent environmental random regression (co)variance matrix were used. Among 27 models, the L(6,2), L(6,5) and L(6,6) were chosen as better models.

Keywords:

cattle, Friesian, analysis of covariance, environmental impact, genetic correlation, milk yield, models, regression analysis,

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