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Survival analysis of mortality in pre-weaning kids of Sirohi goat.
- Source :
- Animal; Dec2019, Vol. 13 Issue 12, p2896-2902, 7p
- Publication Year :
- 2019
-
Abstract
- Pre-weaning animals exit a flock through death induced by various reasons, causing significant economic losses to the goat producers. In this study, we investigated the survival from birth to weaning of Sirohi goat kids within framework of the survival analysis. Kid records were accessed from 1997 to 2017, with the information on 4417 pre-weaning animals of farmed Sirohi goat native to the Rajasthan State of India. A multivariable Cox regression was fitted to the data after checking the assumptions of regression. The explanatory variables were sex, type of birth, season of birth, birthweight, doe weight at kidding and year of birth. Model selection eliminated doe weight from the model, and sex, type of birth, season of birth, birthweight and year of birth were retained in the model. With model calibration also, these five covariates were retained in the model. The mortality on the first day after birth was 0.3%, constituting 3.5% of all pre-weaning mortality. The mortality until the end of weaning period was 7.8%. Regression analysis revealed that the higher birthweight at kidding was associated with reduced hazard of death among the kids. Male kids had higher hazards of death compared with female kids. The single-born kids had lower risks of death compared with twin-born kids after accounting for heterogeneity. The winter season had a very high adverse effect on the survival of the kids. With each passing year, risks of death decreased. The results of this study indicate that better survival of kids can be achieved by controlling both environmental and animal-related factors. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17517311
- Volume :
- 13
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Animal
- Publication Type :
- Academic Journal
- Accession number :
- 139709140
- Full Text :
- https://doi.org/10.1017/S1751731119001617