Using Principal Component Analysis to Characterize Egg Components in two Waterfowl Species

Amin, Questan Ali; Shaker, Ahmed Sami; Akram, Shilan Aram; Kirkuk, Shahla Mohammed Saeed; Saeed, Rozhgar Baiz; Mohammed, Mohammed Sardar

doi:10.21608/jappmu.2019.58834

Using Principal Component Analysis to Characterize Egg Components in two Waterfowl Species

Document Type : Original Article

Authors

¹ Animal science department, college of agricultural Science and Engineering, Sulaimani University, Sulaimani, Iraq

² Animal production department, agriculture research center, Sulaimani, Iraq.

10.21608/jappmu.2019.58834

Abstract

The present study was done in the laboratories of animal science department that belongs Sulaimani University. During June 2017 to February 2018, a total of (91) duck and (98) geese eggs were collecting from local farms in Sulaimani province to evaluate some external and internal traits. Eggs weighed individually by using electronic balance, and Egg length and breadth of each egg was measured by using digital Vernier caliper. after breaking the eggs, yolk, albumin and shell weight was recorded. Moreover, Yolk diameter was estimated. Mean, standard error, minimum and maximum of the external and internal traits for both species were calculated using the descriptive analysis of SPSS. Person’s coefficients of correlation (r) among egg weight, external and internal egg traits were estimated. From the correlation matrix, data were generated for the principal component analysis. Anti-image correlation, Kaiser-Meyer-Olkin measures of sampling adequacy rotation component matrix, and Bartlett’s test of Spherity were computed to test the validity of the of the factor analysis of the data sets. The result of principle component analysis of egg trait extracted two factors that can objectively be used to describe the interrupted in the original elven egg quality characteristics of duck and geese. Therefore, the use of two orthogonal egg quality factor (PC1 and PC2) extracts from principle component analysis could be more reliable inter predicting egg quality compared to the use of the original inter correlated egg quality. The two principle factor could use in a breeding program for the important of egg quality traits.

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