Estimating gain by use of a classic selection index under multicollinearity in wheat (Triticum aestivum)

Abstract

It was shown that the classic selection index, under multicollinearity, could not give simultaneous gains for wheat grain production and its primary components. This was due to the instability and, consequently, low precision of the coefficient index estimates. A modification of the prediction process of the index was proposed to avoid the adverse effects of multicollinearity, adopting a procedure based on ridge regression theory. The modified classic selection index, or ridge index, gave more statistically viable index coefficient estimates and gains for all of the characters evaluated. However, lower gains for number of grains per spike and grain yield were obtained, when compared to those obtained with selection for grain yield.