Combining ability of standardized indices for multi-trait selection in tobacco

Abstract

Several traits must be simultaneously considered in selection of tobacco cultivars for meeting the requirements of farmers, manufacturers and consumers. Breeders should have an understanding of associations between economically-important traits in order to devise the best strategy to have response to selection for all them. Utilization of selection indices has been shown to be one of the most efficient strategy for selecting for correlated characters. In tobacco, no reports can be found within the academic literature for multiple trait selection. In this study we demonstrate the efficiency of the Sum of the Standardized Variables Index (SSV) for multi-trait selection in tobacco. The method was evaluated using a collection of thirteen inbred lines and hybrids derived using a diallel scheme. The hybrids, parental lines, and checks were evaluated in two field locations. The traits assessed were yield (YLD), general quality index (GQI), leaf stem to lamina ratio, percent total alkaloids, and percent total sugars. We considered weights according to the economic importance of each trait: 0.4 for YLD, 0.3 for GQI and 0.1 for the remaining characters. The SSV index proved to be efficient and easy to interpret, and could be used to generate genetic gain for almost all characters in the desired direction. General combining ability (GCA) explained the larger part of the variation of the index in the diallel analysis. The mean heterosis estimate was 2.02%. Some hybrid combinations exhibited heterosis levels greater than 10%, indicating that increased attention might need to be given to commercialization of F1 hybrids.

Selection parameters for improvement of yield and quality in tomatillo

“…In tomatillo, few studies on correlation without investigating the effect of indirect selection, such as path coefficient analysis as a tool for enhancement selection gain, have been reported to estimate the associations between yield and other traits (Peña- Lomelí et al, 2008;Santos et al, 2021). In this respect, multiple traits should be taken into consideration simultaneously in selection to meet farmers, manufacturers and consumer requirements (Carvalho et al, 2021).…”