ArticleScientific reports2025
Association and reliability analysis of multi-trait selection methods and selection of superior genotypes across the traits in Indian mustard.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Multi-trait model-based assessment of selection efficiency and stability in soybean germplasm.Journal of applied genetics · 2026Article
- QTL mapping for root traits during post-tillering stage under moisture-deficit stress in wheat.Plant molecular biology · 2026Article
- Dataset of multi-trait selection approach of superior purple-fleshed Sweet Potato (PFSP) genotypes.Data in brief · 2026Article
- Multi-traits and stability-based selection of high-yielding mungbean (Vigna radiata L.) genotypes in Benin.Scientific reports · 2026Article
- Multi-trait selection for drought-tolerant soybean accessions under contrasting water regimes.PloS one · 2026Article
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7 authors.
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Abstract
Selection of desirable genotypes across the traits is the most challenging task for plant breeders. This experiment aims to study the association and reliability of the Smith-Hazel Selection Index (SH), Factor Analytic Best Linear Unbiased Prediction (FAI-BLUP), Multi-Trait Selection Index (MTSI) and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) selection index with Weighted Rank Aggregation (WRA) and Genotype by Yield×Trait (GYT) Biplot analysis for the selection of superior genotypes. The evaluation of 55 genotypes, including parents and hybrids, was done at CRC of SVPUAT Meerut, UP, India, during 2023-2024 following Randomized Complete Block Design within three replications. The FAI BLUP and MGIDI both revealed the highest percentage increase in selection differential for SY, followed by SL, HI, SMR and TW. The highest rank correlation was observed between SHI and MTSI, followed by MGIDI and FAI BLUP. The Venn diagram revealed the best genotypes in all four indexes are C3, C4, C7, C32 and C36. The WRA analysis also suggested similar best genotypes such as C4 followed by C3, C27, C7 and C32 by assigning different weights to four indexes. PCA of the GT biplot revealed the PC1 and PC2 accounting for a total cumulative variance of 72.29%, whereas in GYT biplot PC1 and PC2 accounted for a cumulative variance of 96.96%, which is greater than GT biplot. Amongst all the selection indexes FAI-BLUP, MTSI and MGIDI are found more reliable whereas genotypes namely C3, C4, C7 and C32 can further be used in crop improvement programs.
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