- Turkish Journal of Veterinary Research
- Cilt: 8 Sayı: 2
- Prediction of live weight from body measurements using stepwise regresion models in Karacabey Merino...
Prediction of live weight from body measurements using stepwise regresion models in Karacabey Merino lambs
Authors : Adem Kabasakal
Pages : 103-111
Doi:10.47748/tjvr.1430913
View : 33 | Download : 30
Publication Date : 2024-10-25
Article Type : Research
Abstract :Objective: The aim of this study is to determine regression models that can be used to estimate live weight from body measurements in Karacabey Merino lambs of different ages(6th, 8th, and 12th months).. Material-Method: The animal material for the study consisted of 200 Karacabey merino lambs. Some body measurements were taken from all lambs and live weights were also weighed. For live weight prediction equations with multiple linear regression analysis using some measurements according to age groups, stepwise multiple regression procedure was used in SAS (1999). DUNCAN test, one of the tests for multiple comparisons, was used to show the differences between groups. Result: The least squares means for body length (BL), withers height (HW), back height (BH), rump height (RH), breast depth (CD), breast width (CW), rump width (RW), and live weight (LW) were 71.28 cm, 69.91 cm, 70.50 cm, 71.57 cm, 30.05 cm, 87.25 cm, 21.50 cm, 23.32 cm, and 51.05 kg, respectively. It is noteworthy that the live weight estimation models for three different age groups using stepwise regression analysis(second, third, and fourth models) can be recommended for the 6th (R2:0.82), 8th (R2:0.71), and 12th (R2:0.79) months of life. The variables that can be used in the equations to estimate body weight for this breed, at these ages are HW, CW, RW, CG, CD, and BL. Conclusion: Finally, it has been demonstrated that the live weights of Karacabey merino lambs can be estimated with high accuracy using the stepwise regression method based on body measurements.Keywords : Body measurements, extensive, Karacabey Merino sheep, regression models.