Vol. 9, Issue 1 (2020)
Principal component analysis of litter traits in crossbred piglets
Snehasmita Panda, GK Gaur, Dayanidhi Jena, Supriya Chhotaray, Mitek Tarang and Aamir Bashir Wara
This investigation was undertaken to derive fewer independent reproductive traits through principal component analysis. Accordingly, records of 2 litter traits at birth, 4, 6 and 8 week from 42 crossbred (75% Landrace X 25% Bareilly local) pigs, farrowed between September 2017 and April 2018 were used in the present investigation. Principal component analysis was done using PROC PRINCOMP Module of SAS 9.3 software. High correlation coefficients were observed among most of the litter traits. Kaiser-Meyer-Olkin measure of sampling adequacy, Bartlett’s Test of Sphericity and communality were calculated. A single principal component (PC) was extracted for litter traits. It accounted for 82.24% of total variance. PC1 was represented by litter size at 4, 6 and 8 week. This factor seemed to be representing the overall performance of the litter. Accounted PC may be exploited in breeding and selection program for reproductive traits.
How to cite this article:
Snehasmita Panda, GK Gaur, Dayanidhi Jena, Supriya Chhotaray, Mitek Tarang and Aamir Bashir Wara. . The Pharma Innovation Journal. 2020; 9(1): 31-33.