RT Journal T1 ESTIMATING BODY WEIGHT FROM SEVERAL BODY MEASUREMENTS IN HARNAI SHEEP WITHOUT MULTICOLLINEARITY PROBLEM A1 M. A. Khan A1 M. M. Tariq A1 E. Eyduran A1 A. Tatliyer A1 M. Rafeeq A1 F. Abbas A1 N. Rashid A1 M. A. Awan A1 K. Javed JF Journal of Animal and Plant Sciences JO JAPS SN 1018-7081 VO 24 IS 1 SP 120 OP 126 YR 2014 FD 2014/02/01 DO DOI NA AB

The aim of this study was to estimate body weight from several linear body characteristics collected from 730 Harnai sheep, in Pakistan. For this aim, morphological characteristics viz. body length (BL), withers height (WH), chest girth (CG), paunch girth (PG), face length (FL),  length between ears (LBE), length of ears (EARL), width (FTW) and length (FTL) of tail to be useful for breeding purposes were measured. With removing multicollinearity problem, the complex relationship between BW and the measured characteristics was assessed by using scores derived from factor and principal component analyses in multiple regression analysis (MLRA) for male and female sheep. Body weight from morphological characteristics was predicted by Regression tree method. R2 (%), adjusted R2(%), and RMSE values for weight prediction were estimated very high for MLRA (90.6, 90.3, and 4.635 for male sheep, and 92.4, 92.3, and 4.102 for female sheep), whereas use of factor scores in MLRA (87.8, 87.6, 0.352 for male sheep and 92.0, 91.9, and 0.284 for female sheep), and principal component scores (85.9, 85.8, and 0.367 for male sheep and 88.8, 88.7, and 0.335 for female sheep) in MLRA exactly removed multicollinearity problem. Regression tree method explained 84.4 % of total variation in BW.  Consequently, use of factor and principal component scores in MLRA gave breeders a good chance without multicollinearity problem for a more accurate estimation of body weight in Harnai sheep compared to the results of MLRA. The results might present valuable knowledge for genetically improving body weight of Harnai sheep.

K1 Body weight, Factor Analysis, Harnai Sheep, Multicollinearity, Principal Component Analysis, Regression Tree PB Pakistan Agricultural Scientists Forum LK https://thejaps.org.pk/AbstractView.aspx?mid=2014-JAPS-18