Yam (Dioscorea spp.) is a main staple tuber crop in Nigeria and the West African region. Its performance is determined by genotypes and also the environment of growth. This study assessed the agronomic performance and yield stability of elite white yam (Dioscorea rotundata) genotypes across diverse Nigerian environments. A total of 25 genotypes were evaluated at three locations in two consecutive growing seasons, 2022 and 2023, for fresh tuber yield, disease resistance, and tuber quality traits. The genotype’s performance and stability for the measured traits were assessed using various analytical tools such as additive main effects and multiplicative interaction (AMMI) and multi-trait stability index (MTSI). The AMMI analysis revealed significant differences among the genotypes and across the environments for all traits (p < 0.001, p < 0.01). The PCA revealed that the first two principal components (PC1 and PC2) explained a substantial portion of the total variation (49.84%). The MTSI identified four clones: G18, G19, G24, and G16 as promising candidates for improved yam production in Nigeria with high and stable performance for the multiple traits.

This study evaluated the yield stability and environmental responsiveness of 42 pro-vitamin A cassava genotypes across multi-season trials using Finlay-Wilkinson (FW) regression and trait-based clustering approaches. Regression parameters-intercept and slope were used to quantify baseline yield potential and sensitivity to environmental variation, respectively. Hierarchical and k-means clustering grouped genotypes into three biologically distinct clusters with clear agronomic relevance. Cluster 2 genotypes exhibited moderate responsiveness and positive yield baselines, indicating broad adaptability and suitability for regional deployment. Cluster 3 showed high environmental sensitivity but low yield potential, suggesting limited resilience under marginal conditions. Cluster 1 comprised highly responsive genotypes with poor baseline productivity, reflecting unstable performance and strong genotype × environment interaction. One-way ANOVA confirmed significant differences among clusters for both slope (F(2,39) = 40.89, p < 0.001) and intercept (F(2,39) = 102.10, p < 0.001), validating the clustering structure. The dendrogram confirmed the cluster structure and provided a basis for selecting key genotypes. The results inform environment-specific breeding strategies and emphasize the importance of integrating multiple traits into future clustering approaches to improve cultivar selection accuracy.

There is need to improve soybean yield potentials per unit area in the tropics, at least to the world average productivity level. To achieve this, attention has to be paid to the selection of high yielding and stable genotypes through plant breeding improvement programmers. Twenty four soybean lines were investigated across three agro ecological zones in Nigeria to determine their productivity. In each of the sites, the experiments were laid out in randomized complete block design with three replications. Data were collected on growth and yield parameters.

Yield instability and pod shattering are the major problems associated with soybean production in Nigeria. To study Genotype × Environment interaction effects on seed yield and pod shattering behaviour of some soybean genotypes in Nigeria, an experiment was conducted in three (3) environments within the country. In each environment, the experiment was laid out in a randomized complete block design (RCBD) with three replications. During the harvest, pod shattering evaluation was conducted using the sun-dry method. Data were collected on seed yield and pod shattering percentage and analyzed using Additive Main Effect and Multiplicative Interaction (AMMI) and Genotype plus Genotype × Environment Interaction (GGE) bi-plot analyses. Genotypes NCRI SOYAC18, NCRI SOYAC78, NCRI SOYAC9, NCRI SOYAC20, NCRI SOYAC61, NCRI SOYAC22, NCRI SOYAC28 and NCRI SOYAC76, with yields above 1.23 ton/ha recorded high and stable yield across environments. For pod shattering resistance, nine genotypes (NCRI SOYAC3, NCRI SOYAC69, NCRI SOYAC77, NCRI SOYAC29, NCRI SOYAC9, NCRI SOYAC7, NCRI SOYAC67, NCRI SOYAC76 and NCRI SOYAC22) had stable pod shattering resistance across environments. Therefore, only three genotypes (NCRI SOYAC9, NCRI SOYAC22, and NCRI SOYAC76) were stable in both high yield and resistance to pod shattering. Consequently, any soybean breeding programme that involves high yield and pod shattering resistance could consider these three genotypes.

This study evaluated the yield stability and environmental responsiveness of 42 pro-vitamin A cassava genotypes across multi-season trials using Finlay-Wilkinson regression and trait-based clustering approaches. Regression parameters-intercept and slope were used to quantify baseline yield potential and sensitivity to environmental variation, respectively. Hierarchical and k-means clustering grouped genotypes into three biologically distinct clusters with clear agronomic relevance. Cluster 2 genotypes exhibited moderate responsiveness and positive yield baselines, indicating broad adaptability and suitability for regional deployment. Cluster 3 showed high environmental sensitivity but low yield potential, suggesting limited resilience under marginal conditions. Cluster 1 comprised highly responsive genotypes with poor baseline productivity, reflecting unstable performance and strong genotype × environment interaction. One-way ANOVA confirmed significant differences among clusters for both slope (F(2,39) = 40.89, P < 0.001) and intercept (F(2,39) = 102.10, P < 0.001), validating the clustering structure. Dendrogram profiling reinforced these classifications, offering a quantitative framework for genotype prioritization. The findings support strategic breeding decisions tailored to agroecological contexts and highlight the need for multi-trait integration in future clustering models to enhance cultivar deployment precision.