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ABSTRACT Tepary bean (Phaseolus acutifolius A. Gray) is an under‐utilized genetic resource with significant potential for food security and stress tolerance breeding. Expanding its cultivation in southern Africa requires high‐yielding, locally adapted and drought‐tolerant varieties. This study determined the combining ability and genetic components for seed yield and related traits in tepary bean genotypes under non‐stress (NS) and drought‐stress (DS) conditions. Seven parents were selected through rigorous phenotyping and crossed using a half‐diallel design. The 7 parents and 21 F2 progenies were evaluated in 2021/2022 season at Kasinthula and Bunda sites in Malawi under NS and DS conditions using a 4 × 7 lattice design with three replications. The specific combining ability (SCA) × location interaction effect was significant (p 0.50 for NPP and NSP under DS conditions suggested a preponderance of additive gene effects. G40145, G40148 and G40150 parental lines were good combiners for NPP and SY. The F2 families from crosses such as Zimbabwe landrace/G40138, Zimbabwe landrace/G40150, G40059/G40145, G40059/G40148, G40138/G40150 and G40145/G40150 were identified as best specific combiners, with enhanced SY of 1.67 t/ha under DS conditions. The study recommends advancing high‐performing early‐generation families for selection across representative environments to facilitate variety release and commercialization.

Vaccination is one of the essential measures in reducing transmission, morbidity, and mortality rates of a disease. However, the COVID-19 vaccination is facing hesitancy across the globe, Malawi included. A population-based cross-sectional study was conducted in Malawi to document knowledge, attitudes, and practices on COVID-19 vaccination. The study targeted the general adult population and employed a multi-stage sampling technique. The Census Enumeration Areas within the 16 selected districts served as a primary sampling unit. Among the total 3068 participants, 1947 (63.6%) were female. About 1039 (34.1%) participants had primary education, while only 169 (5.5%) had college education. A total of 2936 (95.7%) participants knew about the COVID-19 vaccine, and 2063 (68.4%) felt that the COVID-19 vaccine was effective. A total of 1180 (38.7%) got vaccinated. Knowledge of the COVID-19 vaccination was significantly associated with participants’ education levels, location, occupation, marital status, household family income, and whether they were suffering from chronic illness or not. Overall, the level of knowledge and attitudes about the COVID-19 vaccination was good. This study has also established that different population groups have statistically different levels of knowledge and attitudes regarding COVID-19 vaccination. This study has also indicated a significant relationship between the rate of vaccination and several factors. Therefore, this calls for stakeholders to continue awareness and group-targeted tailored campaigns so as to increase COVID-19 vaccination.

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.