IDENTIFYING PREDICTIVE COMPONENTS OF EGG WEIGHT IN TWO LINES OF DANDARAWI CHICKEN USING PRINCIPAL COMPONENT ANALYSIS

Two Dandarawi chicken lines (selected for high body weight at eight weeks of age and control) in the 7th generation used to unfold the impact of selection for high body weight on egg quality traits, understanding the relationship between these traits and identifying predictive components of egg weight applying principal component analysis. At 40 weeks of age, a total of 120 eggs were collected (60 egg/ line). The measured traits involved egg weight, egg length and breadth, yolk height and diameter, albumin height, weight of yolk, albumin and eggshell and eggshell thickness. Analysis of variance and descriptive statistics for the studied traits were performed using SAS program. Correlation among egg quality traits, principal component analysis, Kaiser-Meyer-Olkin (KMO), and Bartlett’s test of sphericity were computed by SPSS program. The results revealed that the selected line hens laid heavier eggs (56.38 g) than the control line hens (45.51 g), and the selected line outperformed the control line in majority of the traits. In both lines, the correlations between egg weight and most of its components were positive and highly correlated. According to KMO values and Bartlett’s Test, principal component analysis (PCA) was valid for the data sets. Four principal components were identified, that accounted for 74.79 % (selected line) and 73.39 % (control line) of the cumulative variance which were more accurate than the original egg quality traits in predicting egg weight. Consequently, improving the selected Dandarawi line for high body weight in egg quality traits is critical for producing an improved Dandarawi chicken, and the four principal components can be employed effectively as selection strategy to enhance egg quality traits.