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Genotype-by-environment (GEI) analysis guides the recommendation of best-performing crop genotypes and production environments. The objective of this study was to determine the extent of GEI on seed yield in tepary bean for genotype recommendation and cultivation in drought-prone environments. Forty-five genetically diverse tepary bean genotypes were evaluated under non-stressed and drought-stressed conditions for two seasons using a 9 × 5 alpha lattice design with three replications in four testing environments. Data were collected on seed yield (SY) and days to physiological maturity (DTM) and computed using a combined analysis of variance, the additive main effect and multiplicative interaction (AMMI), the best linear unbiased predictors (BLUPs), the yield stability index (YSI), the weighted average of absolute scores (WAASB) index, the multi-trait stability index (MTSI), and a superiority measure. AMMI analysis revealed a significant (p < 0.001) GEI, accounting for 13.82% of the total variation. Genotype performance was variable across the test environments, allowing the selection of best-suited candidates for the target production environment. The environment accounted for a substantial yield variation of 52.62%. The first and second interaction principal component axes accounted for 94.8 and 4.7% of the total variation in the AMMI-2 model, respectively, of surmountable variation due to GEI. The AMMI 2 model family was sufficient to guide the selection of high-yielding and stable genotypes. Based on best linear unbiased predictors (BLUPs), yield stability index (YSI), superiority measure (Pi), and broad adaptation, the following tepary bean genotypes were identified as high-yielding and suited for drought-prone environments: G40138, G40148, G40140, G40135, and G40158. The selected tepary bean genotypes are recommended for cultivation and breeding in Malawi or other related agroecologies. [ABSTRACT FROM AUTHOR]

Selecting genetically diverse and complementary parental lines and superior crosses are pre-requisites in developing improved cultivars. The objectives of this study were to determine the combining ability effects and gene action conditioning rice yellow mottle virus disease (RYMVD) resistance and agronomic traits in rice (Oryza sativa L.). Ten parental lines and their 45 F2 progenies were field evaluated in three locations using a 5 × 11 alpha lattice design with two replications. The genotype × site interaction effects were significant (p < 0.05) for the number of tillers (NT), number of panicles per plant (NPP), number of grains per panicle (NGP), percentage of filled grains (PFG), thousand grain weight (TGW), RYMVD resistance and grain yield (GY). The analysis of general and specific combining ability (GCA and SCA) indicated involvement of both additive and non-additive gene action governing inheritance of traits. High GCA/SCA ratio estimate revealed additive genetic effect was predominant. Parental lines Mwangaza, Lunyuki, Salama M-57, Salama M-19, IRAT 256 and Salama M-55, which had negative GCA effects for RYMVD, and families such as SARO 5 × Salama M-55, IRAT 245 × Rangimbili, Rangimbili × Gigante and Rangimbili × Mwangaza, which had negative SCA effects for RYMVD, were selected for RYMV resistance breeding. The crosses Rangimbili × Gigante, Gigante × Salama M-19 and Rangimbili × Salama M-55 were selected due to their desirable SCA effects for GY. The predominance of additive gene effects for agronomic traits and RYMVD resistance in the present breeding populations suggested that rice improvement could be achieved through gene introgression using recurrent selection. [ABSTRACT FROM AUTHOR]