Showing 2 results for Selection Index
M. Modarresi, M. T. Assad, M. Kheradnam,
Volume 7, Issue 4 (1-2004)
Abstract
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.
A Sh, S J,
Volume 13, Issue 48 (7-2009)
Abstract
In selection index procedure, phenotype and genetic (co)variance matrices of traits are used for calculating different genetic parameters like index coefficients, index variance, genetic gain in selection goal and selection accuracy. Sometimes, it is possible that these matrices become inconsistent or they are not positive, nor definite. In the current study, for investigation of the effect of inconsistency of (co)variance matrices on the results of selection index procedure, 6 kinds of different selection indices: milk production (Milk) , fat percentage of milk (fat%) and herd life (HL) in selection goal were constructed The first to third indices included Milk, fat% and one of the type traits, i.e. rear udder height (Ruh), front teat placement (Ftp) or front udder attachment (Fua) respectively, as correlated traits with herd life. The fourth index included productive traits and the three mentioned type traits altogether, and the fifth and sixth indices as reduced indices, included milk production and fat percentage and just milk production, respectively. Also, the results of using mean of 3 individual records were taken into account. All of calculations were done for both consistent and inconsistent matrices. For making consistency in inconsistent matrices, “bending” method was used. Results showed that the use of inconsistent matrices in selection index calculations will lead to wrong selections and will decrease genetic gain. This conclusion was independent of different economic conditions of production system in different years. When using consistent matrices, index 4, that had the most information from selection goal, was the best index.
