Toll Free Helpline (India): 1800 1234 070

Rest of World: +91-9810852116

Free Publication Certificate

Vol. 8, Issue 7 (2019)

Comparative estimation of breeding values in Nellore rams for growth traits using sire and animal models

Author(s):
Vani Sunkara and Dr. Sakunthala Devi
Abstract:
Estimates of breeding values were obtained for birth weight and body weight at 3, 6, 9 and 12 months of age in Nellore sheep maintained at an organized sheep farm at peddakadupuru village in Kurnool district of Andhra pradesh, India. Data on growth traits were recorded for a total of 756 number of lambs belonging to 18 sires and were analyzed by using 3 different sire evaluation methods viz., simple regressed least-squares (SRLS), best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) methods. Error variance estimated by SRLS, BLUP and REML methods for birth weight, body weight 3, 6, 9 and 12 months of age were found to be 0.052, 0.051 and 0.058; 0.206, 0.205 and 0.236; 0.212, 0.211 and 0.231; 0.202, 0.201 and 0.225 and, 0.207, 0.206 and 0.284 respectively. The coefficient of determination (R2) value by SRLS, BLUP and REML methods were found to be 21.6, 27.9 and 1.82; 91.8, 92.5 and 46.1; 95.0, 95.9 and 42.7; 94.9, 96.8, 47.9; 95.3, 97.2 and 18.9 for birth weight and body weights at 3, 6, 9 and 12 months of age respectively. Spearman’s rank correlation and product moment correlations between SRLS and BLUP method was found to be highly significant (P<0.01). The BLUP method seems to be the most efficient, (lower error variance) accurate (higher coefficient of determination) and stable (lower coefficient of variation) method among all. However, significant and higher magnitude of rank correlations between BLUP and SRLS showed that SRLS could be used as next best method.
Pages: 08-11  |  960 Views  76 Downloads


The Pharma Innovation Journal
How to cite this article:
Vani Sunkara, Dr. Sakunthala Devi. Comparative estimation of breeding values in Nellore rams for growth traits using sire and animal models. Pharma Innovation 2019;8(7):08-11.

Call for book chapter