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Associations among certain morphological traits of diallel cross progenies in Bromus inermis Leyss

Published online by Cambridge University Press:  27 March 2009

S. N. Mishra  and
P. N. Drolsom
S. N. Mishra
Affiliation:
Department of Agronomy, University of Wisconsin, Madison, U. S. A.
P. N. Drolsom
Affiliation:
Department of Agronomy, University of Wisconsin, Madison, U. S. A.
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Summary

A study of correlations among certain morphological traits of progenies from a 6 x 6 diallel cross was made. In general, genotypic correlations were similar in sign to the phenotypic correlations in all but two of the 21 cases, but there were differences in magnitude (nine differed by 0·40 and four of these by more than 0·70). Some estimates of the environmental correlations were large (1·57, 1·52, 0·78, 0·75, 0·73 and 0·54). Positive and significant correlations indicated that improvement in some characters related to forage and seed yield should be possible by selection among the diallel progenies.

Path analysis was used as a means of analysing phenotypic correlation coefficients among seven contemporary variables. The method was employed to analyse the system of all possible correlations among certain plant measurements. By this technique one may find the maximum effect, compatible with the data, which can be assigned to a general size factor (common to all variables) and determine the nature and degree of influence of residual, group, and special factors. In most of these the influence of the general size factor predominated (minor in the case of leaf width, pCX = –0·31; and florets per spikelet, pGX = –0·09). Only two of the 21 correlations required factors in addition to the general size (florets per spikelet and spikelets per panicle, excess correlation –0·46; and leaf width and culm diameter, excess correlation +0·53). Special factors acting on each part separately from the other were present in all cases. The study indicated that the genetic differences in this study were largely in general size and to a small extent in group and special factors.

Type
Research Article
Information
The Journal of Agricultural Science , Volume 81 , Issue 1 , August 1973 , pp. 69 - 76
Copyright
Copyright © Cambridge University Press 1973

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References

Bean, F. W. (1970). Genotypic variation in inflorescence length in Phleum pratense. J. agric. Sri., Camb. 75, 169–74.CrossRefGoogle Scholar
Carlson, I. T. & Moll, R. H. (1962). Phenotypic and genotypic variation and covariation in quantitative characters in strains of orchardgrass. Crop Sci. 2, 281–86.CrossRefGoogle Scholar
Falconer, D. S. (1960). Introduction to Quantitative Genetics. New York: Ronald Press.Google Scholar
Hotelling, H. (1936). Simplified calculation of principal components. Psychometrica 1, 27–35.CrossRefGoogle Scholar
Johnson, H. W., Robinson, H. F. & Comstock, R. E. (1955). Genotypic and phenotypic correlations and their implications in selection. Agron. J. 47, 477–83.CrossRefGoogle Scholar
Spearman, C. (1905). ‘General intelligence’, objectively determined and measured. Am. J. Psych. 15, 201–92.CrossRefGoogle Scholar
Wright, S. (1954). The interpretation of multivariate system. In Statistics and Mathematics in Biology (ed. Kempthorne, O., Bancroft, T. A., Gowen, J. W. and Lush, J. L.), pp. 11–33. Ames, Iowa State University Press.Google Scholar
Wright, S. (1968). Evolution and Genetics of Populations. Vol. I. Genetic and Biometric Foundations. Chicago and London: University of Chicago Press.Google Scholar