Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling
The growing global demand for soybean protein is driving the expansion of cultivation into new agricultural frontiers. Kenya has been progressing in the development of soybean genotypes to identify those best adapted to its diverse agroecological conditions. However, the selection of genotypes with...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/177508 |
| _version_ | 1855540580772216832 |
|---|---|
| author | Stella, A.A. Pavan, J.P.S. Araujo, M.S. Fregonezi, B.F. Unzimai, I.V. Leles, E.P. Santos, M.F. Goldsmith, P. Chigeza, G. Diers, B.W. Gathungu, T. Njoroge, J. Pinheiro, J.B. |
| author_browse | Araujo, M.S. Chigeza, G. Diers, B.W. Fregonezi, B.F. Gathungu, T. Goldsmith, P. Leles, E.P. Njoroge, J. Pavan, J.P.S. Pinheiro, J.B. Santos, M.F. Stella, A.A. Unzimai, I.V. |
| author_facet | Stella, A.A. Pavan, J.P.S. Araujo, M.S. Fregonezi, B.F. Unzimai, I.V. Leles, E.P. Santos, M.F. Goldsmith, P. Chigeza, G. Diers, B.W. Gathungu, T. Njoroge, J. Pinheiro, J.B. |
| author_sort | Stella, A.A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The growing global demand for soybean protein is driving the expansion of cultivation into new agricultural frontiers. Kenya has been progressing in the development of soybean genotypes to identify those best adapted to its diverse agroecological conditions. However, the selection of genotypes with superior agronomic traits and high stability remains limited. This study quantified the magnitude of genotype-by-environment (G
E) interaction and selected genotypes with the best performance and stability based on a multi-trait approach. A total of 65 genotypes were evaluated across 19 environments from 2019 to 2023/24 growing seasons using a randomized complete block design. Stability was assessed using the Weighted Average of Absolute Scores index, considering plant height (PH), number of days to maturity (NDM), and grain yield (GY). Multi-trait selection was performed using the Desired Gain Index, applying a 20% selection intensity, followed by the genetic gain estimation. Using the likelihood ratio test, we identified significant effects of genotype, environment, and G
E interaction. The overall mean values observed in the experiments were 62.30 cm for PH, 120 days for NDM, and 1783.70 kg ha−1 for GY. In the multi-trait analysis, we selected the ideotypes G42, G26, G46, G35, G53, G41, G12, G54, G39, G52, G02, and G37. This selection resulted in a genetic gain of 6.5% for PH, 1.3% for NDM, and 15.6% for GY. These genotypes exhibited high genetic potential and adaptation to Kenyan conditions. |
| format | Journal Article |
| id | CGSpace177508 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1775082025-12-08T09:54:28Z Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling Stella, A.A. Pavan, J.P.S. Araujo, M.S. Fregonezi, B.F. Unzimai, I.V. Leles, E.P. Santos, M.F. Goldsmith, P. Chigeza, G. Diers, B.W. Gathungu, T. Njoroge, J. Pinheiro, J.B. glycine max soybeans adaptation genetic gain selection index The growing global demand for soybean protein is driving the expansion of cultivation into new agricultural frontiers. Kenya has been progressing in the development of soybean genotypes to identify those best adapted to its diverse agroecological conditions. However, the selection of genotypes with superior agronomic traits and high stability remains limited. This study quantified the magnitude of genotype-by-environment (G E) interaction and selected genotypes with the best performance and stability based on a multi-trait approach. A total of 65 genotypes were evaluated across 19 environments from 2019 to 2023/24 growing seasons using a randomized complete block design. Stability was assessed using the Weighted Average of Absolute Scores index, considering plant height (PH), number of days to maturity (NDM), and grain yield (GY). Multi-trait selection was performed using the Desired Gain Index, applying a 20% selection intensity, followed by the genetic gain estimation. Using the likelihood ratio test, we identified significant effects of genotype, environment, and G E interaction. The overall mean values observed in the experiments were 62.30 cm for PH, 120 days for NDM, and 1783.70 kg ha−1 for GY. In the multi-trait analysis, we selected the ideotypes G42, G26, G46, G35, G53, G41, G12, G54, G39, G52, G02, and G37. This selection resulted in a genetic gain of 6.5% for PH, 1.3% for NDM, and 15.6% for GY. These genotypes exhibited high genetic potential and adaptation to Kenyan conditions. 2025 2025-11-03T13:48:00Z 2025-11-03T13:48:00Z Journal Article https://hdl.handle.net/10568/177508 en Open Access application/pdf Stella, A.A., Pavan, J.P., Araujo, M.S., Fregonezi, B.F., Unzimai, I.V., Leles, E.P., ... & Pinheiro, J.B. (2025). Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling. Scientific reports, 15(1): 27575, 1-14. |
| spellingShingle | glycine max soybeans adaptation genetic gain selection index Stella, A.A. Pavan, J.P.S. Araujo, M.S. Fregonezi, B.F. Unzimai, I.V. Leles, E.P. Santos, M.F. Goldsmith, P. Chigeza, G. Diers, B.W. Gathungu, T. Njoroge, J. Pinheiro, J.B. Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling |
| title | Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling |
| title_full | Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling |
| title_fullStr | Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling |
| title_full_unstemmed | Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling |
| title_short | Soybean selection in Kenya enhanced by multi-trait and genotype-by-environment interaction modeling |
| title_sort | soybean selection in kenya enhanced by multi trait and genotype by environment interaction modeling |
| topic | glycine max soybeans adaptation genetic gain selection index |
| url | https://hdl.handle.net/10568/177508 |
| work_keys_str_mv | AT stellaaa soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT pavanjps soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT araujoms soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT fregonezibf soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT unzimaiiv soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT lelesep soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT santosmf soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT goldsmithp soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT chigezag soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT diersbw soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT gathungut soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT njorogej soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling AT pinheirojb soybeanselectioninkenyaenhancedbymultitraitandgenotypebyenvironmentinteractionmodeling |