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Abstract Background Globally, the cultivation of cotton is constrained by its tendency for extended periods of growth. Early maturity plays a potential role in rainfed-based multiple cropping system especially in the current era of climate change. In the current study, a set of 20 diverse Gossypium hirsutum genotypes were evaluated in two crop seasons with three planting densities and assessed for 11 morphological traits related to early maturity. The study aimed to identify genotype(s) that mature rapidly and accomplish well under diverse environmental conditions based on the two robust multivariate techniques called multi-trait stability index (MTSI) and multi-trait genotype-ideotype distance index (MGIDI). Results MTSI analysis revealed that out of the 20 genotypes, three genotypes, viz., NNDC-30, A-2, and S-32 accomplished well in terms of early maturity traits in two seasons. Furthermore, three genotypes were selected using MGIDI method for each planting densities with a selection intensity of 15%. The strengths and weaknesses of the genotypes selected based on MGIDI method highlighted that the breeders could focus on developing early-maturing genotypes with specific traits such as days to first flower and boll opening. The selected genotypes exhibited positive genetic gains for traits related to earliness and a successful harvest during the first and second pickings. However, there were negative gains for traits related to flowering and boll opening. Conclusion The study identified three genotypes exhibiting early maturity and accomplished well under different planting densities. The multivariate methods (MTSI and MGIDI) serve as novel approaches for selecting desired genotypes in plant breeding programs, especially across various growing environments. These methods offer exclusive benefits and can easily construe and minimize multicollinearity issues.

Background: Globally, the cultivation of cotton is constrained by its tendency for extended periods of growth. Early maturity plays a potential role in rainfed-based multiple cropping system especially in the current era of climate change. In the current study, a set of 20 diverse Gossypium hirsutum genotypes were evaluated in two crop seasons with three planting densities and assessed for 11 morphological traits related to early maturity. The study aimed to identify genotype(s) that mature rapidly and accomplish well under diverse environmental conditions based on the two robust multivariate techniques called multi-trait stability index (MTSI) and multi-trait genotype-ideotype distance index (MGIDI). Results: MTSI analysis revealed that out of the 20 genotypes, three genotypes, viz., NNDC-30, A-2, and S-32 accomplished well in terms of early maturity traits in two seasons. Furthermore, three genotypes were selected using MGIDI method for each planting densities with a selection intensity of 15%. The strengths and weaknesses of the genotypes selected based on MGIDI method highlighted that the breeders could focus on developing early-maturing genotypes with specific traits such as days to first flower and boll opening. The selected genotypes exhibited positive genetic gains for traits related to earliness and a successful harvest during the first and second pickings. However, there were negative gains for traits related to flowering and boll opening. Conclusion: The study identified three genotypes exhibiting early maturity and accomplished well under different planting densities. The multivariate methods (MTSI and MGIDI) serve as novel approaches for selecting desired genotypes in plant breeding programs, especially across various growing environments. These methods offer exclusive benefits and can easily construe and minimize multicollinearity issues. [ABSTRACT FROM AUTHOR]

Multi-environment trials (MET) are crucial for selecting genotypes that are well-suited to different environmental conditions. Incorporating multiple traits in the analysis can provide more reliable recommendations for selecting genotypes with desirable traits, including resistance to the Mungbean Yellow Mosaic Virus (MYMV) and high yield potential. The use of a Multi-Trait Stability Index (MTSI) is a good approach for analyzing the stability of genotypes across multiple traits under MYMV stress. In the present investigation, the performance of thirteen green gram genotypes were evaluated for traits such as yield, plant height, number of branches per plant, and resistance to MYMV. The main objective of the study is to identify highly productive and stable mung bean genotypes resistant to MYMV. MTSI can be calculated by combining information on the performance of genotypes across multiple traits and environmental conditions to provide a single index that indicates the overall stability of genotypes across traits and environments. The results helped to identify two green gram genotypes (Yadadri and JNG-18) that were high-yielding with stable resistance to MYMV stress across multiple environmental conditions. This can provide useful information to breeders for the development of suitable genotypes against MYMV in the affected areas.

In Bangladesh, sweet potato holds the fourth position as a crucial carbohydrate source, trailing rice, wheat, and potato. However, locally grown sweet potato varieties often display limited stability and yield. To tackle this challenge, diverse selection methods and statistical models were utilized to pinpoint sweet potato genotypes showcasing both stability and superior yield and quality traits. In the initial two years, multiple selection methods were employed to narrow down the collections based on preferences for yield and its contributing traits. Subsequently, a multi-environment trial (MET) was conducted in the following year to pinpoint superior and stable genotypes with desirable yield and quality characteristics. An integrated approach involving the Multi-Trait Genotype Ideotype Distance Index (MGIDI), Factor Analysis and Ideotype-Design (FAI-BLUP), and Smith-Hazel Index (SH) led to the identification of 71 superior sweet potato genotypes out of a total of 351 in the initial growing season. In the subsequent season, the MGIDI selection index was applied to the 71 genotypes, resulting in the selection of 11 top-performing genotypes. This selection process was complemented by a detailed analysis of the strengths and weaknesses of the selected genotypes. In the MET, the mixed effect model, specifically the linear mixed model (LMM), identified significant genotypic and genotype-environment interaction (GEI) variances. This points to elevated heritability and selection accuracy, ultimately boosting the model's reliability. By combining the strengths of LMM and additive main effects and multiplicative interaction (AMMI), the best linear unbiased prediction (BLUP) index identified H20 as the top-performing genotype for marketable root yield (MRY), H37 for dry weight of root (DW), H8 for beta carotene (BC) and H41 for vitamin c (VC). These genotypes surpassed the overall average in the WAAS index. For simultaneous stability and high performance, the WAASBY index selected H37 for MRY, H6 for DW, H61 for BC, and H3 for VC. Finally, genotypes H3 and H20 were selected using multi-trait stability index (MTSI), as they possessed high performance and stability. Based on the selection sense, the objective has been achieved with regards to the trait MRW, which serves as a major criterion for a superior variety of sweet potato.

Guar, the most popular vegetable, is tolerant of drought and is a valuable industrial crop enormously grown across India, Pakistan, USA, and South Africa for pharmaceutically and cosmetically usable galactomannan (gum) content present in seed endosperm. Guar genotypes with productive traits which could perform better in differential environmental conditions are of utmost priority for genotype selection. This could be achieved by employing multivariate trait analysis. In this context, Multi-Trait Stability Index (MTSI) and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) were employed for identifying high-performing genotypes exhibiting multiple traits. In the current investigation, 85 guar accessions growing in different seasons were assessed for 15 morphological traits. The results obtained by MTSI and MGIDI indexes revealed that, out of 85, only 13 genotypes performed better across and within the seasons, and, based on the coincidence index, only three genotypes (IC-415106, IC-420320, and IC-402301) were found stable with high seed production in multi-environmental conditions. View on strengths and weakness as described by the MGIDI reveals that breeders concentrated on developing genotype with desired traits, such as quality of the gum and seed yield. The strength of the ideal genotypes in the present work is mainly focused on high gum content, short crop cycle, and high seed yield possessing good biochemical traits. Thus, MTSI and MGIDI serve as a novel tool for desired genotype selection process simultaneously in plant breeding programs across multi-environments due to uniqueness and ease in interpreting data with minimal multicollinearity issues.

Guar, the most popular vegetable, is tolerant of drought and is a valuable industrial crop enormously grown across India, Pakistan, USA, and South Africa for pharmaceutically and cosmetically usable galactomannan (gum) content present in seed endosperm. Guar genotypes with productive traits which could perform better in differential environmental conditions are of utmost priority for genotype selection. This could be achieved by employing multivariate trait analysis. In this context, Multi-Trait Stability Index (MTSI) and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) were employed for identifying high-performing genotypes exhibiting multiple traits. In the current investigation, 85 guar accessions growing in different seasons were assessed for 15 morphological traits. The results obtained by MTSI and MGIDI indexes revealed that, out of 85, only 13 genotypes performed better across and within the seasons, and, based on the coincidence index, only three genotypes (IC-415106, IC-420320, and IC-402301) were found stable with high seed production in multi-environmental conditions. View on strengths and weakness as described by the MGIDI reveals that breeders concentrated on developing genotype with desired traits, such as quality of the gum and seed yield. The strength of the ideal genotypes in the present work is mainly focused on high gum content, short crop cycle, and high seed yield possessing good biochemical traits. Thus, MTSI and MGIDI serve as a novel tool for desired genotype selection process simultaneously in plant breeding programs across multi-environments due to uniqueness and ease in interpreting data with minimal multicollinearity issues. [ABSTRACT FROM AUTHOR]