Evaluation of some factors on birth and weaning weights in Awassi sheep by using GLM and CART analysis

• Published in: Tropical animal health and production Vol. 54; no. 6; p. 400
• Main Author: Şahin, Özcan
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2022; Springer Nature B.V
• Subjects: Algorithms; Animals; Awassi; Biomedical and Life Sciences; Birth weight; Birth Weight - genetics; Dairy farms; dairy sheep; Data mining; Environmental factors; farms; Female; Genetic factors; growth and development; Lamb; Life Sciences; Linear Models; Livestock farming; Parturition; Performance prediction; postpartum period; prediction; Pregnancy; Regression Analysis; Regular Articles; Sheep; Veterinary Medicine/Veterinary Science; Weaning; Weight; Zoology; GLM; Birth weight; Awassi; Weaning weight; Environment factors; CART algorithm
• ISSN: 0049-4747; 1573-7438; 1573-7438
• DOI: 10.1007/s11250-022-03405-2

Birth weight (BW), which is the first physiological record of the postnatal period, is an important indicator that affects growth and development, reproduction, and some yields of living things in the future. The present study was carried out using the birth records of 5417 heads of Awassi lambs from 2013 to 2018 in MeMuTa dairy sheep farm in Zengen town of Ereğli district of Konya city in Türkiye. In this study, the effects of some environmental and genetic factors on birth and weaning weight in Awassi lambs were evaluated using both general linear model (GLM) and classification and regression tree (CART) analysis. As a result of the GLM analysis, the least squares’ means of birth and weaning weights (BW and WW) were determined as 4.15 ± 0.05 kg and 16.39 ± 0.13 kg, respectively. Fixed genetic factors such as birth type and sex, and environmental factors such as season and year were found to be significant on birth weight ( P  < 0.01). As for weaning weight, other factors except birth type were found to be similarly important like birth weight ( P  < 0.01). Also, linear regression of birth weight on weaning weight was found to be significant ( P  < 0.01). In GLM and CART analyses, the determination coefficient (R 2 ) was determined to be 23.80% and 11.70% for BW, and 24.11% and 13.18% for WW, respectively. The findings of the analysis results showed that the factors in the model have a similar tendency both in terms of their relative ratios in the total variation in the GLM analysis and in their relative importance in the CART algorithm. It was seen that CART data mining algorithm in the prediction of some genetic and environmental factors on birth and weaning weights using some factors in Awassi lambs produced successful results in predictive performance. Briefly, it was determined that there is a similar tendency to GLM analysis according to CART algorithm analysis in the current study.