Experimental comparison of methods for simultaneous selection of two correlated traits in Tribolium : 1. Empirical and theoretical selection indexes

Relative efficiency of selection methods to improve a ratio of two traits in Tribolium

Three generations of upward selection for the egg mass/adult weight ratio were carried out in Tribolium castaneum. The experiment involved five lines: E - selected for increased egg mass; W - selected for decreased adult weight; R - selected for egg mass/adult weight directly; L - linear index selected with economic weights of m 2: -m 1 egg mass to adult weight (m 1 and m 2 are the means for adult weight and egg mass, respectively); NL - nonlinear index selected. Adult weight (7 days after adult emergence) and egg mass (between 7 and 11 days) were measured. The NL, E, and L lines had the greatest observed responses for the ratio; the R and W lines were not effective in improving the egg mass/adult weight ratio. It was expected that the NL line would be superior to the E, L, and R lines, and that the W line would respond the least. Observed response was significant for egg mass in the NL line, and for adult weight in the E, W, and R lines. Strong selection to increase egg mass seems to represent the optimal criterion for the ratio to be improved. The usefulness of nonlinear indices as selection criteria to improve a nonlinear trait, previously found to be optimal for a trait defined as the product of two component traits, appears to hold also for the selective improvement of the ratio of two traits. Serious limitations expected for direct selection of the ratio have been confirmed in this experiment.

Factor and principal component analyses as alternatives to index selection

Selections from factor and principal component analyses were compared with those from the Smith-Hazel index when selecting for several switchgrass (Panicum virgatum L.) traits. The objective of this study was to examine several alternatives to index selection. Such procedures would potentially eliminate problems of selection associated with Smith-Hazel indices, including errors in genetic parameter estimates and difficulty in assigning relative economic weights to traits. Selection was performed on 1,280 plants that were evaluated over 2 years at 1 location, in a randomized complete block design with 4 replicates. The plants were evaluated for forage yield and several forage quality traits. The comparisons of index selection with principal factor analysis, maximum-likelihood factor analysis and principal component analysis were made for three sets of traits (five traits per set) to estimate repeatability for the comparisons. Multivariate analyses were performed on both simple and genotypic correlation matrices. Comparisons were made by computing Spearman's rank correlations between selection index plant scores and scores computed from multivariate analysis and by determining the number of plants selected in common for the selection methods. Among the three multivariate analysis methods evaluated in this study, principal component analysis had the highest correlation with index selection. The high correlation for principal component analysis of simple correlation matrices indicates the potential for using this statistical method for selection purposes. This would permit the breeder to reduce field costs (e.g., time, labor, equipment) required to obtain the genetic parameter estimates necessary to construct selection indices.