تعیین شاخص‌های انتخاب در ارقام ذرت (Zea mays L.) به منظور افزایش عملکرد دانه

Yield is a quantitative trait and improving grain yield through direct selection is time-consuming. Indirect selection consisting of selection indices is more promising. A field experiment was conducted during 1999-2000 growing season in two experimental locations (Kooshkak and Badjgah) of College of Agriculture, Shiraz University, Shiraz. Thirteen corn hybrids were used in a randomized complete block design with three replications in each location. Thirty-five traits were measured in five developmental stages (stem elongation, tasseling, blister, hard dough and physiological maturity) and combined analysis of variance and covariance were conducted. Finally, 12 traits were selected for constructing selection indices via path analysis. Two optimum selection indices were used in this experiment. In both selection indices, different combinations of traits applied as linear function (multivariate linear model) and coefficients of traits in combinations were calculated. The coefficient of indices were obtained from: b=P-1Ga, where b is the vector of index coefficients, P-1 is the inverse of phenotypical variance and covariance matrix, G is the matrix of genotypical variance and covariance and a is the column vector of traits heritability. In the first index, heritability of traits with the same sign was used as economic values. Selection index including grain yield and net assimilation rate in the second stage (NAR2) was the best. In the second index, the sign of genotypic correlation with yield was given to economic values. Finally, selection index including grain yield and NAR2 was the best, too. In both selection indices, correlation of selection indices with genotypic value was equal to 1. This was 14% higher than the first index including yield alone. In both selection indices, physiological indices including net assimilation, crop growth, and relative growth rates were the most important traits comprising the best selection indices.