ArticleFood science & nutrition2022
Genetic characterization and quantitative trait relationship using multivariate techniques reveal diversity among tomato germplasms.
Article in Food science & nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Genetic Variability, Trait Association, and Multi-Trait Selection of New Indeterminate Tomato Genotypes Under Protected Cultivation.Plants (Basel, Switzerland) · 2026Article
- Morphological diversity of Chinese chinquapin (Castanea henryi (Skan) Rehder & E.H. Wilson) germplasm.BMC plant biology · 2026Article
- Delineating genotype × environment interaction for horticultural traits in tomato using GGE and AMMI biplot analysis.Scientific reports · 2025Article
- Effects of exogenous 2,4-epibrassinolide on photosynthetic traits of 53 cowpea varieties under NaCl stress.Open life sciences · 2024Article
- Phenotyping new rapeseed lines based on multiple traits: Application of GT and GYT biplot analyses.Food science & nutrition · 2023Article
- Genetic characterization and quantitative trait relationship using multivariate techniques reveal diversity among tomato germplasms.Food science & nutrition · 2022Article
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Abstract
Tomato accessions collected from different sources were evaluated to study their diversity, genotype-traits association, as well as pinpoint most selective trait(s) in a controlled environment in Jimma, Ethiopia. The two terms pot experiments were carried out in randomized complete block design with three replications. The genotype-trait (GT) biplot revealed high percentage variability above 70% in related growth traits for the first and second principal components (PC) summed up, in the two trials, whereas related floral and fruit traits association indicated medium to high (55%-65%) total explained variations in both seasons. It further showed that 'wild parent', 'CLN2498D', 'CLN2498F', 'UC Dan India', 'Ruma', 'PT4722A', 'CLN2679F', 'CLN2585C' and 'CLN2585D' were the best performers in most of the related growth, floral, and fruit traits in those seasons. Principal component analysis showed that traits, such as plant height, number of branches, leaves, nodes, internodes, stem girth, style length, stigma length and diameter, flower length and width, number of flowers per truss, number of fruits per truss, and fruit weight per plant, in the first dimension were positively related to yield and consistent with high loading factors in both seasons and could be underpinned highly important in breeding for increased fruit yield. Clustering and its comparison of means showed that 'CLN2498D', 'PT4722A', 'Ruma', 'Tropimech', and 'UC Dan India' of cluster I in both trials expressed the best traits including related growth, floral, and fruit traits. Therefore, selection for any trait would favor accessions in this cluster.
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