Diversity pattern in Sesamum mutants selected for a semi-arid cropping system

Abstract

Due to the complex requirements of moisture stress, substantial genetic diversity with a wide array of character combinations and effective simultaneous selection for several variables is necessary for improving the productivity and adaptation of a component crop in order for it to fit into a cropping system under semi-arid tropical conditions. Sesamum indicum L. is grown in Venezuela after rice/sorghum/or maize under such conditions. A mutation breeding program was undertaken using six locally adapted varieties to develop genotypes suitable for the above system. The diversity pattern for nine variables was assessed by multivariate analysis in 301 M₄ progenies. Analysis of the characteristic roots and principal components in three methods of selection, i.e., M₂ bulks (A), individual plant selection throughout (B), and selection in M₃ for single variable (C), revealed differences in the pattern of variation between varieties, selection methods, and varieties × methods interactions. Method B was superior to the others and gave 17 of the 21 best M₅ progenies. 'Piritu' and 'CF' varieties yielded the most productive progenies in M₅ and M₆. Diversity was large and selection was effective for such developmental traits as earliness and synchrony, combined with multiple disease resistance, which could be related to their importance by multivariate analyses. Considerable differences in the variety of character combinations among the high yielding. M₅ progenies of 'CF' and 'Piritu' suggested possible further yield improvement. The superior response of 'Piritu' and 'CF' over other varieties in yield and adaptation was due to major changes in plant type and character associations. Multilocation testing of M₅ generations revealed that the mutant progenies had a 40%–100% yield superiority over the parents; this was combined with earliness, synchrony, and multiple disease resistance, and was confirmed in the M₆ generation grown on a commercial scale. This study showed that multivariate analysis is an effective tool for assessing diversity patterns, choice of appropriate variety, and selection methodology in order to make rapid progress in meeting the complex requirements of semi-arid cropping systems.