Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield
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...
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| Format: | Article |
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MDPI AG
2022-12-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/13/1/12 |
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| author | Saul Eric Mwale Hussein Shimelis Wilson Nkhata Abel Sefasi Isaac Fandika Jacob Mashilo |
| author_facet | Saul Eric Mwale Hussein Shimelis Wilson Nkhata Abel Sefasi Isaac Fandika Jacob Mashilo |
| author_sort | Saul Eric Mwale |
| collection | DOAJ |
| description | 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 (<i>p</i> < 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. |
| first_indexed | 2024-03-09T13:53:10Z |
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| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-09T13:53:10Z |
| publishDate | 2022-12-01 |
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| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-935eb2cb3c0d4bb68fd8fb718a0ae5a82023-11-30T20:47:42ZengMDPI AGAgronomy2073-43952022-12-011311210.3390/agronomy13010012Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed YieldSaul Eric Mwale0Hussein Shimelis1Wilson Nkhata2Abel Sefasi3Isaac Fandika4Jacob Mashilo5Crop Science Discipline, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg 3201, South AfricaCrop Science Discipline, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg 3201, South AfricaAfrican Centre for Crop Improvement (ACCI), University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg 3201, South AfricaHorticulture Department, Lilongwe University of Agriculture and Natural Resources, Lilongwe 201303, MalawiKasinthula Agricultural Research Station, Chikwawa 315105, MalawiCrop Science Discipline, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg 3201, South AfricaGenotype-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 (<i>p</i> < 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.https://www.mdpi.com/2073-4395/13/1/12additive main effect and multiplicative interactionbest linear unbiased predictorsdroughttepary beanyield stabilitygenotype-by-environment interaction |
| spellingShingle | Saul Eric Mwale Hussein Shimelis Wilson Nkhata Abel Sefasi Isaac Fandika Jacob Mashilo Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield Agronomy additive main effect and multiplicative interaction best linear unbiased predictors drought tepary bean yield stability genotype-by-environment interaction |
| title | Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield |
| title_full | Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield |
| title_fullStr | Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield |
| title_full_unstemmed | Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield |
| title_short | Genotype-by-Environment Interaction in Tepary Bean (<i>Phaseolus acutifolius</i> A. Gray) for Seed Yield |
| title_sort | genotype by environment interaction in tepary bean i phaseolus acutifolius i a gray for seed yield |
| topic | additive main effect and multiplicative interaction best linear unbiased predictors drought tepary bean yield stability genotype-by-environment interaction |
| url | https://www.mdpi.com/2073-4395/13/1/12 |
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