AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trails (METs).

The stability and high yielding of Vigna subterranea L. Verdc. genotype is an important factor for long-term development and food security. The effects of G × E interaction on yield stability in 30 Bambara groundnut genotypes in four different Malaysian environments were investigated in this research. The experiment used a randomized complete block design with three replications in each environment. Over multiple harvests, yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare were evaluated in the main and off-season in 2020 and 2021. Stability tests for multivariate stability parameters were performed based on analyses of variance. For all the traits, the pooled analysis of variance revealed highly significant (p < 0.01) variations between genotypes, locations, seasons, and genotypes by environment (G × E interaction). A two-dimensional GGE biplot was generated using the first two principal components (axis 1 and axis 2), which accounted for 94.97% and 3.11% difference in GEI for yield per hectare, respectively. Season and location were found to be the most significant causes of yield heterogeneity, accounting for 31.13% and 14.02% of overall G + E + G × E variation, respectively, according to the combined study of variance. The GGE biplot revealed that the three winning genotypes G1, G3, and G5 appear across environments whereas AMMI model exposed genotypes viz G18, G14, G7, G3, G1, and G5 as best performer. Based on ideal genotype ranking genotype G1 was the best performer, with a high mean yield and high stability in the tested environment. According to the AEC line, genotypes G1 and G3 were extremely stable, while genotypes G2 and G4 were low stable, with a high average yielding per hectare. A GGE and AMMI biplot graphically showed the interrelationships between the tested environment and genotypes, classified genotypes into three categories as well as simplifying visual evaluations, according to this investigation. According to our results, breeding could improve yield production, and the genotypes discovered could be recommended for commercial cultivation.

Khan MMH ，Rafii MY ，Ramlee SI ，Jusoh M ，Al Mamun M ... -  《Scientific Reports》

AMMI and GGE biplot analyses of Bambara groundnut [Vigna subterranea (L.) Verdc.] for agronomic performances under three environmental conditions.

The two most common styles to analyze genotype-by-environment interaction (GEI) and estimate genotypes are additive main effects and multiplicative interaction (AMMI) and genotype + genotype × environment (GGE) biplot. Therefore, the aim of this study was to find the winning genotype(s) under three locations, as well as to investigate the nature and extent of GEI effects on Bambara groundnut production. The experiment was carried out in the fields of three environments with 15 Bambara groundnut accessions using the randomized complete block design (RCBD) with three replications each in Ibadan, Osun, and Odeda. Yield per plant, fresh seed weight, total number of pods per plant, hundred seed weight, length of seeds, and width of seeds were estimated. According to the combined analysis of variance over environments, genotypes and GEI both had a significant (p < 0.001) impact on Bambara groundnut (BGN) yield. This result revealed that BGN accessions performed differently in the three locations. A two-dimensional GGE biplot was generated using the first two principal component analyses for the pattern of the interaction components with the genotype and GEI. The first two principal component analyses (PCAs) for yield per plant accounted for 59.9% in PCA1 and 40.1% in PCA2. The genotypes that performed best in each environment based on the "which-won-where" polygon were G8, G3, G2, G11, G6, and G4. They were also the vertex genotypes for each environment. Based on the ranking of genotypes, the ideal genotypes were G2 and G6 for YPP, G1 and G5 for FPW, G15 and G13 for TNPP, G3 and GG7 for HSW, G7 and G12 for LOS, and G10 and G7 for WOS. G8 was recorded as the top most-yielding genotype. G8, G4, G7, and G13 were high yielding and the most stable across the environments; G11, G14, and G9 were unstable, but they yielded above-average performance; G14, G12, G15, and G1 were unstable and yielded poorly, as their performances were below average. Bowen was the most discriminating and representative environment and is classified as the superior environment. Based on the performance of accessions in each region, we recommend TVSU 455 (G8) and TVSU 458 (G3) in Bowen, TVSU 455 (G8) and TVSU 939 (G6) and TVSU 454 (G1) in Ibadan, and TVSU 158 (G2) and TVSU 2096 (G10) in Odeda. The variety that performed best in the three environments was TVSU 455 (G8). They could also be used as parental lines in breeding programs.

Esan VI ，Oke GO ，Ogunbode TO ，Obisesan IA ... -  《Frontiers in Plant Science》

Hereditary analysis and genotype × environment interaction effects on growth and yield components of Bambara groundnut (Vigna subterranea (L.) Verdc.) over multi-environments.

This investigation was carried out to explore G × E interaction for yield and its associated attributes in 30 Bambara groundnut genotypes across four environments in tropical Malaysia. Such evaluations are essential when the breeding program's objective is to choose genotypes with broad adaption and yield potential. Studies of trait relationships, variance components, mean performance, and genetic linkage are needed by breeders when designing, evaluating, and developing selection criteria for improving desired characteristics in breeding programs. The evaluation of breeding lines of Bambara groundnut for high yield across a wide range of environments is important for long-term production and food security. Each site's experiment employed a randomized complete block design with three replicates. Data on vegetative and yield component attributes were recorded. The analysis of variance revealed that there were highly significant (p ≤ 0.01) differences among the 30 genotypes for all variables evaluated. A highly significant and positive correlation was identified between yield per hectare and dry seed weight (0.940), hundred seed weight (0.844), fresh pod weight (0.832), and total pod weight (0.750); the estimated correlation between dry weight of pods and seed yield was 1.0. The environment was more important than genotype and G × E in determining yield and yield components.A total of 49% variation is covered by PC1 (33.9%) and PC2 (15.1%) and the genotypes formed five distinct clusters based on Ward hierarchical clustering (WHC) method. The genotypes S5G1, S5G3, S5G5, S5G6, S5G8, S5G7, S5G2, S5G4, S5G10, S5G13, S5G11, and S5G14 of clusters I, II, and III were closest to the ideal genotype with superior yield across the environments. The PCA variable loadings revealed that an index based on dry pod weight, hundred seed weight, number of total pods and fresh pod weight could be used as a selection criteria to improve seed yield of Bambara groundnut.

Khan MMH ，Rafii MY ，Ramlee SI ，Jusoh M ，Al Mamun M ... -  《Scientific Reports》

Path-coefficient and correlation analysis in Bambara groundnut (Vigna subterranea [L.] Verdc.) accessions over environments.

In a breeding program, studies of genotypic and phenotypic relationships among agricultural crop traits are useful to design, evaluate, and develop selection criteria for desirable traits. Using path coefficient analysis, the present study was executed to estimate the phenotypic, genotypic, and environmental correlation coefficients between yield and yield-related traits and to determine the direct and indirect effects of yield-related traits on yield per plant. A total of 30 genotypes of Vigna subterranea were studied under tropical conditions at two sites over two planting seasons (considered as four environments). The experiment at each site used a randomized complete block design with three replicates. Data were collected on vegetative and yield component attributes. Based on analysis of variance, pooled results showed that there were positive and highly significant differences (p ≤ 0.01) among the 30 genotypes for all attributes studied. Highly significant and positive strong correlation at phenotypic level was observed for dry seed weight (0.856), hundred seed weight (0.754), fresh pod weight (0.789), and total pod weight (0.626) with yield in kg per hectare, while moderate positive correlations were observed for harvest cut (0.360) and days to maturity (0.356). However, a perfect positive correlation was observed for the dry weight of pods with seed yield. In contrast, days to 50% flowering (- 0.350) showed a negative significant relationship with yield per hectare. The dried pod weight attribute (1.00) had a high positive direct effect on yield. Fresh pod weight had the greatest indirect effect on yield per hectare, followed by the number of total pods by dry pod weight. As a result, dry pod weight, hundred seed weight, number of total pods, and fresh pod weight could be used as selection criteria to improve the seed yield of Bambara groundnut (Vigna subterranea).

Khan MMH ，Rafii MY ，Ramlee SI ，Jusoh M ，Al Mamun M ... -  《Scientific Reports》

Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters.

Rice (Oryza sativa L.) is an important member of the family Poaceae and more than half of world population depend for their dietary nutrition on rice. Rice cultivars with higher yield, resilience to stress and wider adaptability are essential to ensure production stability and food security. The fundamental objective of this study was to identify higher-yielding rice genotypes with stable performance and wider adaptability in a rice growing areas of Pakistan. A triplicate RCBD design experiment with 20 Green Super Rice (GSR) advanced lines was conducted at 12 rice growing ecologies in four Provinces of Pakistan. Grain yield stability performance was assessed by using different univariate and multivariate statistics. Analysis of variance revealed significant differences among genotypes, locations, and G x E interaction for mean squares (p < 0.05) of major yield contributing traits. All the studied traits except for number of tillers per plant revealed higher genotypic variance than environmental variance. Broad sense heritability was estimated in the range of 44.36% to 98.60%. Based on ASV, ASI, bi, Wi2, σ2i and WAAS statistics, the genotypes G1, G4, G5, G8, G11 and G12 revealed lowest values for parametric statistics and considered more stable genotypes based on  paddy yield. The additive main effects and multiplicative interaction (AMMI) model revealed significant variation (p < 0.05) for genotypes, non-signification for environment and highly significant for G × E interaction. The variation proportion of PC1 and PC2 from interaction revealed 67.2% variability for paddy yield. Based on 'mean verses stability analysis of GGE biplot', 'Which-won-where' GGE Biplot, 'discriminativeness vs. representativeness' pattern of stability, 'IPCA and WAASB/GY' ratio-based stability Heat-map, and ranking of genotypes, the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 were observed ideal genotypes with yield potential more than 8 tons ha-1. Discriminativeness vs. representativeness' pattern of stability identifies two environments, E5 (D.I Khan, KPK) and E6 (Usta Muhammad, Baluchistan) were best suited for evaluating genotypic yield performance. Based on these findings we have concluded that the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 could be included in the commercial varietal development process and future breeding program.

Ahmed MS ，Majeed A ，Attia KA ，Javaid RA ，Siddique F ，Farooq MS ，Uzair M ，Yang SH ，Abushady AM ... -  《Scientific Reports》