Field-Based Study on One-Month Body Weight Performance of Sangamneri Goat Kids
Dhangada V. R., Lashkare S. V., Bhargande N. B., Gaikwad U. S.
Journal of Advances in Biology & Biotechnology · pp. 1766–1772 · Published 23 Sep 2025
10.9734/jabb/2025/v28i93021Abstract
The present study evaluated the influence of non-genetic factors on the one-month body weight of Sangamneri goat kids under village flock conditions in Maharashtra, India. Data on 14,472 kids were collected under the All India Coordinated Research Project (AICRP) on Goat Improvement, spanning four clusters (Sangamner, Shrirampur, Belha, and Rahuri) over three kidding periods (2005–2010, 2011–2015, and 2016–2020) and three seasons (rainy, winter, and summer). Using least squares analysis of variance under a fixed effects model, the effects of period of kidding, season of kidding, sex of kid, type of birth and effect of cluster were assessed. The overall least squares mean for one-month body weight was 5.58 ± 0.017 kg. All non-genetic factors studied had highly significant effects (P < 0.01) on this trait. Kids born during 2016–2020 recorded the highest weight (6.70 ± 0.019 kg), indicating improvements in management and selection practices over time. Winter-born kids exhibited superior growth (5.70 ± 0.019 kg) compared to those born in summer or rainy seasons, likely due to enhanced maternal nutrition and climatic conditions. Male kids (5.76 ± 0.020 kg) significantly outperformed females (5.40 ± 0.020 kg), reflecting physiological growth advantages. Singleton kids had higher weights (5.72 ± 0.022 kg) compared to twins (5.58 ± 0.016 kg) and triplets (5.44 ± 0.038 kg), likely due to reduced intrauterine and postnatal competition. Among clusters, Rahuri (Cluster 4) recorded the highest average weight (6.02 ± 0.034 kg), suggesting that institutional support and improved veterinary access positively influenced early growth. These findings underscore the critical role of environmental and management factors in shaping early growth performance and provide actionable insights for optimizing Sangamneri goat productivity through targeted, location-specific interventions.
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