Application of Principal Components Factor Analysis in Quantifying Slaughter Weight and Carcass Characteristics of F1 Crosses between Marshal Parents Stock Broilers and Nigerian Normal Feathered Local Chickens

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Research Paper 01/03/2021
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Application of Principal Components Factor Analysis in Quantifying Slaughter Weight and Carcass Characteristics of F1 Crosses between Marshal Parents Stock Broilers and Nigerian Normal Feathered Local Chickens

Akporhuarho Okpako Philip, I. Udeh
Int. J. Biosci.18( 3), 127-134, March 2021.
Certificate: IJB 2021 [Generate Certificate]

Abstract

Slaughter weight and seven carcass characteristics namely dressed weight, eviscerated weight, wing weight, thigh weight, breast weight, back weight and neck weight of unsexed 200 f1 crossbred chicks were measured. The study aimed at describing objectively the interdependence among carcass characteristics and to predict slaughter weight from their independent factor scores using principal components analysis. Correlations between slaughter weight and carcass characteristics were positive and highly significant except neck weight. From the factor analysis with varimax rotation of the intercorrelated characteristics, two principal components were generated from the reciprocal crossbred chicks and only one principal component from the main crossbred which accounted for 93.96 and 91.64 percent of the total variance respectively. The first principal component reciprocal (Lc × Ex) crossbred PC1, termed general form, had its loadings for thigh weight, dress weight, back weight, wing weight and breast weight, and explained 74.08 percent of the variance. Neck weight primarily determined the second principal component, PC2, which contributed to 19.88% of the generalized variance. The first only principal component for main (Ex × Lc) crossbred chicks, PC1, had its loading for breast weight, dress weight, wing weight, thigh weight and neck weight and explained 91.64 percent of the total variance. Orthogonal carcass characteristics derived from the factor analysis accounted for 97.9 percent, 95.20 percent for main (Ex × Lc) crossbred and reciprocal (Lc × Ex) crossbred chicks respectively, of the variation in slaughter weight of f1 crossbred chickens. The principal component-based prediction model is preferable to original data set-based models for selecting animals for optimal balance.

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