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Multivariate analyses and genetic correlations of traits related to fruit yield of tomato in a derived savannah ecology

Year: 2025
Type: article
Abstract: Field-planted tomato cultivation is generally more hindered by deficient moisture and diseases than pests in most locations in Nigeria. Development of location-specific cultivars requires an understanding of available resources and trait relationships. An open-field pot experiment was conducted to evaluate twenty-one tomato genotypes for genotypic and environmental effects on trait performance and fruit production. Data were collected on morpho-physiological and agronomic characters at different stages of growth and subjected to multivariate and genetic correlation analyses. Factor analysis explained 80.7 percent of the total variation within seven axes and identified girth, height, leaf and reproductive traits as the important characteristics for describing the variation. The dendrogram from cluster analysis grouped the tomato genotypes into six clusters with five of the groups having one genotype with each being described by different traits. Heritability estimate was high for days to 50% flowering (99.5%), moderate for fruit weight per fruit (55.9%) but generally low for other traits. Highly significant genetic correlations (p<0.01) were observed among many of the traits that mostly describe the variation. Total fruit weight had a significant and positive genetic correlation with fruit weight per fruit (0.39). The two traits however recorded counteracting but significant relationships with plant height (0.81, -0.44), basal girth (0.39, -0.36), and middle girth (0.44, -0.32). The findings narrowed down the traits of interest in breeding for enhanced yield under moisture-limited conditions and indicated careful but ample cycles of hybridization and selection for reasonable progress.
Authors: Hamzat, A. A., Nassir, A. L., Adewusi, K. M., Olagunju, S. O., Oguntade, O. A., Odusanya, O. A., Sosanya, O. S.
Language: English
Subfield: Plant Science
Open Access status: green
OpenAlex ID: W6920930372
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