A Study on Genetic Distances Among Germplasm Accessions of French Bean

In a usual hierarchical cluster analysis, the identification of genetic distances among germplasm accessions through morphological data on qualitative as well as quantitative characters recorded using the International Plant Genetic Resources Institute (IPGRI)/ National Bureau of Plant Genetic Resources (NBPGR) descriptors, the high numerical nature of the quantitative data leads to the masking of smaller numerical but very important qualitative characters, leading to a lesser precision. This is true with D² statistics and also the principal component based vector analysis leading to genetic divergence, restricting the use of highly significant qualitative parameters in germplasm characterization, often resulting in misclassifications even at the species level. Hence, the molecular markers are relied upon for final conclusions. Efficient data transformation systems to arrive at the exact genetic distances by accounting for both the qualitative as well as quantitative characters with equal weightage are being detailed hereunder. Among the models proposed, (value - mean)/SD was proved to be the best and the results are further supported by the factor analysis of principal components derived from the correlation matrix.