Principal Variables as an Alternative to Principal Components for Trait Selection in Agricultural Research (Part-II)

Authors: BK Hooda

This article presents an empirical application of Principal Variable Analysis (PVA) methods for trait selection in agricultural research using a dataset of 200 germplasm lines of Indian mustard. It evaluates different subset selection techniques (Jolliffe’s B2, B3, B4 methods, McCabe’s generalized variance, and entropy-based criteria) to identify the most representative variables for breeding programs.

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