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

It was shown that the classic selection index, under multicollinearity, cou ld not give simultaneous gains for wheat grain production and its primary c omponents. This was due to the instability and, consequently, low precision of the coefficient index estimates. A modification of the prediction proce ss of the index was proposed to avoid the adverse effects of multicollinear ity, adopting a procedure based on ridge regression theory. The modified cl assic selection index, or ridge index, gave more statistically viable index coefficient estimates and gains for all of the characters evaluated. Howev er, lower gains for number of grains per spike and grain yield were obtaine d, when compared to those obtained with selection for grain yield.