ArticleData in brief2024
A dataset on multi-trait selection approach for the evaluation of F1 tomato hybrids along with their parents under hot and humid conditions in Bangladesh.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Comparative nutritional analysis of newly developed interspecific citrus hybrids: multivariate insights for crop improvement.Scientific reports · 2026Article
- Genetic Variability, Trait Association, and Multi-Trait Selection of New Indeterminate Tomato Genotypes Under Protected Cultivation.Plants (Basel, Switzerland) · 2026Article
- Integrating combining ability and multivariate analysis for the selection of superior tomato hybrids.Frontiers in plant science · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This dataset aims to evaluate the use of multiple trait-based selection methods with multi-trait genotype-ideotype distance index (MGIDI) models to identify superior summer F1 tomato hybrids suitable for the climatic conditions of countries like Bangladesh. The dataset was generated using 14 cross combinations from a Line × Tester mating design, along with seven parental lines and two tester parents of tomatoes with diverse genetic bases and heat tolerance qualities in a randomized complete block (RCB) design. The likelihood ratio (LR) test indicated highly significant genotype effects for most of the analyzed traits. A heatmap of correlation analyses between 16 traits identified a highly significant positive correlation (
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