The Use of Selection Indices in Maize (Zea mays L.)
Estimates of genetic variances for yield and its components—ear number, kernel rows, kernels per row, and kernel weight—and genetic covariances among them were computed for a synthetic population of maize, using 100 S5 lines randomly chosen out of a lot developed from the population with a minimum of selection. Selection indices for various combinations of yield and its components were then constructed using these estimates of phenotypic and genotypic variances and covariances, and the corresponding estimates of expected genetic advance for yield were compared with that for yield alone. An expected advance of 7% in yield was calculated by considering selection for yield itself. Selection for yield based on the index using all five characters was expected to be 13% more efficient than selection for yield alone. Selection based on the index using kernel rows and kernel weight was almost as efficient as selection for yield itself. However, when the expected genetic advance was computed for one location, this index was 8.3% more efficient. Selection based on any of the components considered alone was much less efficient than that based on yield itself. The actual gain realized for some of the indices involving yield and the various components considered alone was much less efficient than that based on yield itself. The actual gain realized for some of the indices involving yield and the various components compared favorably with the predicted genetic advance.
KeywordsKernel Weight Selection Index Genetic Advance Maize Population Actual Gain
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- Comstock, R. E. and Robinson, H. F. (1952). Estimation of average dominance of genes. Heterosis, pp. 494–516. Iowa State College Press, Ames, Ia.Google Scholar
- Gardner, C. O., Harvey, P. H., Comstock, R. E., and Robinson, H. F. (1953). Dominance of genes controlling quantitative characters in maize. Agron. J. 45: 186–191.Google Scholar
- Homer, T. W. (1952). Non-allelic gene interactions and the interpretation of quantitative genetic data. Ph.D. dissertation. North Carolina State College Library.Google Scholar
- Homer, T. W., Comstock, R. E., and Robinson, H. F. (1955). Non-allelic gene interactions in the interpretation of quantitative genetic data. NC Agr. Exp. Sta. Tech. Bull. 118, 117 pp.Google Scholar
- Kempthorne, O. (1957). An Introduction to Genetic Statistics, 545 pp. Wiley, New York.Google Scholar
- Kuhn, W. E. and Stucker, R. E. (1973). Selection indices to improve yield and ears per plant in corn. In Agronomy Abstracts,American Society of Agronomy, Madison, Wisconsin.Google Scholar
- Robinson, H. F., Comstock, R. E., and Harvey, P. H. (1951). Genotypic and phenotypic correlations in corn and their implications in selection. Agron J. 43: 283–287.Google Scholar
- Robinson, H. F., Comstock, R. E. and Harvey, P. H. (1955). Genetic variances in open pollinated varieties of corn. Genetics 40: 46–60.Google Scholar
- Subandi, Compton, W. A., and Empig, L. T. (1973). Comparison of the efficiencies of selection indices for three traits in two variety crosses of corn. Crop Sci. 13: 184–186.Google Scholar