Deployment of AMMI, GGE-biplot and MTSI to select elite genotypes of castor (Ricinus communis L.)

Delineation of genotype × environment interaction and identifying superior red sorghum [Sorghum bicolor L. Moench] genotypes via multi-trait-based stability selection methods

Red sorghum, a versatile crop with high nutritional and biochemical value, was evaluated for agronomic and grain quality traits using 27 genotypes across diverse environmental zones of Tamil Nadu. The data collected were subjected to Additive Main Effects and Multiplicative Interaction (AMMI) and Genotype-by-Environment Interaction (GGE) biplot models to recommend a specific genotype for the particular locality. The analysis of variation of the pooled data revealed a significant interaction effect between genotype and environment for the majority of the examined traits. Correlation analysis revealed a significant positive association of panicle weight and a negative association of micronutrient content with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (50.2%). GGE biplot showed E2 as a highly discriminating environment for grain yield and also identified environment-specific genotypes viz., G11 for E1, E3 and G6 for E2 environments. The GGE biplots recommended G9 and G14 as high-yielding stable genotypes, outperforming the check variety PAIYUR 2 (G15) by 15.83% and 36.16% respectively, across all environments, particularly in E1 and E3. The genotypes G14, G18, G21 and G26 shown wide adaptation and excelled as biofortified genotypes with significant Fe and Zn contents. Multi-trait stability evaluation approaches such as multi trait stability index (MTSI), multitrait genotype‒ideotype distance index (MGIDI), multi-trait index based on factor analysis and genotype-ideotype distance (FAI-BLUP), multitrait mean performance and stability index (MTMPS) and Smith-Hazel index assuming 15% selection intensity were adopted. G14 consistently ranked as the top and steady performer in all evaluation methods. The identified genotype demonstrated exceptional reliability, high yield potential, and early maturity, making them suitable candidates for variety and hybrid development, as well as ideotype breeding programs aimed at ensuring food and nutritional security.

Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses

Bread wheat is a vital staple crop worldwide; including in Ethiopia, but its production is prone to various environmental constraints and yield reduction associated with adaptation. To identify adaptable genotypes, a total of 12 bread wheat genotypes (G1 to G12) were evaluated for their genotype-environment interaction (GEI) and stability across three different environments for two years using Additive Main Effect and Multiplicative Interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplots analysis. GEI is a common phenomenon in crop improvement and is of significant importance in genotype assessment and recommendation. According to combined analysis of variance, grain yield was considerably impacted by environments, genotypes, and GEI. AMMI and GGE biplots analysis also provided insights into the performance and stability of the genotypes across diverse environmental conditions. Among the 12 genotypes, G6 was selected by AMMI biplot analysis as adaptive and high-yielding genotype; G5 and G7 demonstrated high stability and minimal interaction with the environment, as evidenced by their IPCA1 values. G7 was identified as the most stable and high-yielding genotype. The GGE biplot's polygon view revealed that the highest grain yield was obtained from G6 in environment three (E3). E3 was selected as the ideal environment by the GGE biplot. The top three stable genotypes identified by AMMI stability value (ASV) were G5, G7, and G10, while the most stable genotype determined by Genotype Selection Index (GSI) was G7. Even though G6 was a high yielder, it was found to be unstable according to ASV and ranked third in stability according to GSI. Based on the study's findings, the GGE biplot genotype view for grain yield identified Tay genotype (G6) to be the most ideal genotype due to its high grain yield and stability in diverse environments. G7 showed similar characteristics and was also stable. These findings provide valuable insights to breeders and researchers for selecting high-yielding and stable, as well as high-yielding specifically adapted genotypes.

Sweet potato (Ipomoea batatas L.) genotype selection using advanced indices and statistical models: A multi-year approach

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.

Stability Analysis and Identification of Superior Hybrids in Pearl Millet [Pennisetum glaucum (L.) R. Br.] Using the Multi Trait Stability Index

Pearl millet stands as an important staple food and feed for arid and semi-arid regions of India and South Africa. It is also a quick supplier of important micronutrients like Fe and Zn via grain to combat micronutrient deficiencies among people in developing countries. India has notably spearheaded advancements in pearl millet production and productivity through the All India Coordinated Pearl Millet Improvement Project. There were 21 hybrids evaluated over arid and semi-arid ecologies of the western and southern regions of India. AMMI and GGE biplot models were adopted to recommend a specific hybrid for the particular locality. A joint analysis of variation indicated a significant genotype-environment interaction for most of the agronomical and grain micronutrient parameters. Pearson's correlation values dissected the significant and positive correlation among agronomic traits and the negative correlation with grain micronutrient traits. GGE biplot analysis recommended the SHT 106 as a dual-purpose hybrid and SHT 115 as a biofortified hybrid for the grain's Fe and Zn content. SHT 110 and SHT 108 were selected as stable and high grain yield-producing hybrids across all environments and specifically for E1, E2, and E4 as per the Which-Won-Where and What biplot. SHT 109 and SHT 103 hybrids were stable and high dry fodder yield-producing hybrids across all environments. In this study, the Multi-Trait Stability Index (MTSI) was employed to select the most stable and high-performing hybrids for all traits. It selected SHT 120, SHT 106, and SHT 104 for stability and great performance across all environments. These findings underscored the significance of tailored hybrid recommendations and the potential of pearl millet in addressing both food security and malnutrition challenges in various agro-ecological regions.

Agronomic performance and yield stability of extra-early maturing maize hybrids in multiple environments in the Sahel

Frequent occurrence of drought, heat, low soil fertility and Striga infestation are the main stress factors reducing maize yield in the Sahel. Adoption of stable multiple stress tolerant maize cultivars in the region is crucial for achieving food security. However, selection of a stable high yielding cultivar is complicated by genotype × environment interaction (GEI) due to differential responses to growing conditions. Eleven extra-early maturing multiple-stress tolerant maize hybrids and two checks arranged in a randomized complete block design was evaluated across nine locations for two years in Mali and Niger. The objectives of this study were to identify (i) stable and high-yielding maize hybrids, and (ii) suitable test locations for selecting promising extra-early maize hybrids. GGE biplot was used for graphical analysis. Significant genotype, location and GEI effects were detected for grain yield and number of ears per plant. EEWQH-13 produced the highest grain yield (3860 kg ha-1) while EEYQH-1 had the poorest yield (2663 kg ha-1) with trial mean of 3395 kg ha-1 for all hybrids. GGE biplot explained 69.6 % of the total variation in grain yield among the hybrids. The polygon view identified EEWQH-13 as the best hybrid across six of the nine test locations. EEPVAH-58 was identified as the most stable high yielding hybrid across the nine test locations followed by EEWQH-16 and EEWQH-13. The nine locations were clustered under two mega-environments (ME1, ME2). Among the nine test locations, Tara and Aderaoua clustered in ME1 were the most suitable ones for selecting promising extra-early maize hybrids for wider adaptation. The three hybrids, EEPVAH-58, EEWQH-16, and EEWQH-13, identified in this study could be recommended for on-farm evaluation to confirm the consistency of their yield performance for possible release and commercialization in Mali and Niger.

Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection

Unpredictable weather vagaries in the Asian tropics often increase the risk of a series of abiotic stresses in maize-growing areas, hindering the efforts to reach the projected demands. Breeding climate-resilient maize hybrids with a cross-tolerance to drought and waterlogging is necessary yet challenging because of the presence of genotype-by-environment interaction (GEI) and the lack of an efficient multi-trait-based selection technique. The present study aimed at estimating the variance components, genetic parameters, inter-trait relations, and expected selection gains (SGs) across the soil moisture regimes through genotype selection obtained based on the novel multi-trait genotype-ideotype distance index (MGIDI) for a set of 75 tropical pre-released maize hybrids. Twelve traits including grain yield and other secondary characteristics for experimental maize hybrids were studied at two locations. Positive and negative SGs were estimated across moisture regimes, including drought, waterlogging, and optimal moisture conditions. Hybrid, moisture condition, and hybrid-by-moisture condition interaction effects were significant (p ≤ 0.001) for most of the traits studied. Eleven genotypes were selected in each moisture condition through MGIDI by assuming 15% selection intensity where two hybrids, viz., ZH161289 and ZH161303, were found to be common across all the moisture regimes, indicating their moisture stress resilience, a unique potential for broader adaptation in rainfed stress-vulnerable ecologies. The selected hybrids showed desired genetic gains such as positive gains for grain yield (almost 11% in optimal and drought; 22% in waterlogging) and negative gains in flowering traits. The view on strengths and weaknesses as depicted by the MGIDI assists the breeders to develop maize hybrids with desired traits, such as grain yield and other yield contributors under specific stress conditions. The MGIDI would be a robust and easy-to-handle multi-trait selection process under various test environments with minimal multicollinearity issues. It was found to be a powerful tool in developing better selection strategies and optimizing the breeding scheme, thus contributing to the development of climate-resilient maize hybrids.

Screening of castor germplasm for wilt reaction and morpho-molecular characterization of resistant genotypes

Castor (Ricinus communis L.) is an important industrial versatile non-edible oilseed C₃ crop belongs to spurge family. Its oil has exceptional properties which provides an industrial importance to this crop. The present investigation was aimed to evaluate the genotypes of castor for Fusarium wilt reaction in pot followed by characterization of resistant genotypes for yield related traits in field and inter-genotype genetic diversity at DNA level. The percent disease incidence (PDI) among 50 genotypes ranged from 0 to 100%. A total of 36 genotypes were found wilt resistant (28 highly resistant and 8 resistant). ANOVA revealed that the genotypes MSS was significant for each trait studied, indicating the existence of plentiful variability in the experimental material. The morphological characterization showed that DCS-109 (73.30 cm) had a dwarf stature The genotype RG-1954 was superior for oil content (50.29%) with moderate for shelling out (67.63). RG-1673 was outstanding for seed boldness as 100 seed weight for this genotype was maximum (38.98 gm). JI-403 had maximum seed yield per plant (SYPP; 354.88 gm). SYPP positively associated with all traits except oil and seed length:breadth ratio. The path analysis revealed that the direct effects of NPR (0.549), TLFP (0.916), and CPP on SYPP are quite significant. A total of 38 alleles from 18 SSR markers were amplified in 36 genotypes. The NJ tree could divide 36 genotypes into three main clusters. AMOVA revealed 15% and 85% variance among and within subpopulations, respectively. Both morphological and SSR data demonstrated to be effective tools for discerning inter-genotypes diversity and categorizing high-yielding and disesae-tolerant castor genotypes lines.