Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains
Regular measurement of realized genetic gain allows plant breeders to assess and review the effectiveness of their strategies, allocate resources efficiently, and make informed decisions throughout the breeding process. Realized genetic gain estimation requires separating genetic trends from nongene...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Wiley
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/152128 |
| _version_ | 1855541952210010112 |
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| author | Dieng, Ibnou Gardunia, Brian Covarrubias‐Pazaran, Giovanny Gemenet, Dorcus C. Trognitz, Bodo Ofodile, Sam Fowobaje, Kayode Ntukidem, Solomon Shah, Trushar Imoro, Simon Tripathi, L. Mushoriwa, Hapson Mbabazi, Ruth Salvo, Stella Derera, John |
| author_browse | Covarrubias‐Pazaran, Giovanny Derera, John Dieng, Ibnou Fowobaje, Kayode Gardunia, Brian Gemenet, Dorcus C. Imoro, Simon Mbabazi, Ruth Mushoriwa, Hapson Ntukidem, Solomon Ofodile, Sam Salvo, Stella Shah, Trushar Tripathi, L. Trognitz, Bodo |
| author_facet | Dieng, Ibnou Gardunia, Brian Covarrubias‐Pazaran, Giovanny Gemenet, Dorcus C. Trognitz, Bodo Ofodile, Sam Fowobaje, Kayode Ntukidem, Solomon Shah, Trushar Imoro, Simon Tripathi, L. Mushoriwa, Hapson Mbabazi, Ruth Salvo, Stella Derera, John |
| author_sort | Dieng, Ibnou |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Regular measurement of realized genetic gain allows plant breeders to assess and review the effectiveness of their strategies, allocate resources efficiently, and make informed decisions throughout the breeding process. Realized genetic gain estimation requires separating genetic trends from nongenetic trends using the linear mixed model (LMM) on historical multi‐environment trial data. The LMM, accounting for the year effect, experimental designs, and heterogeneous residual variances, estimates best linear unbiased estimators of genotypes and regresses them on their years of origin. An illustrative example of estimating realized genetic gain was provided by analyzing historical data on fresh cassava (Manihot esculenta Crantz) yield in West Africa (https://github.com/Biometrics‐IITA/Estimating‐Realized‐Genetic‐Gain). This approach can serve as a model applicable to other crops and regions. Modernization of breeding programs is necessary to maximize the rate of genetic gain. This can be achieved by adopting genomics to enable faster breeding, accurate selection, and improved traits through genomic selection and gene editing. Tracking operational costs, establishing robust, digitalized data management and analytics systems, and developing effective varietal selection processes based on customer insights are also crucial for success. Capacity building and collaboration of breeding programs and institutions also play a significant role in accelerating genetic gains. |
| format | Journal Article |
| id | CGSpace152128 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace1521282025-05-20T07:33:49Z Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains Dieng, Ibnou Gardunia, Brian Covarrubias‐Pazaran, Giovanny Gemenet, Dorcus C. Trognitz, Bodo Ofodile, Sam Fowobaje, Kayode Ntukidem, Solomon Shah, Trushar Imoro, Simon Tripathi, L. Mushoriwa, Hapson Mbabazi, Ruth Salvo, Stella Derera, John systems manihot esculenta crops cassava data breeding environment genotypes capacity building institutions costs selection strategies measurement resources genomics collaboration yield trends model estimation genetic gain data management modernization processes plant accounting manihot esculenta crantz gene gene editing genetic tracking genomic selection capacity plant breeders traits Regular measurement of realized genetic gain allows plant breeders to assess and review the effectiveness of their strategies, allocate resources efficiently, and make informed decisions throughout the breeding process. Realized genetic gain estimation requires separating genetic trends from nongenetic trends using the linear mixed model (LMM) on historical multi‐environment trial data. The LMM, accounting for the year effect, experimental designs, and heterogeneous residual variances, estimates best linear unbiased estimators of genotypes and regresses them on their years of origin. An illustrative example of estimating realized genetic gain was provided by analyzing historical data on fresh cassava (Manihot esculenta Crantz) yield in West Africa (https://github.com/Biometrics‐IITA/Estimating‐Realized‐Genetic‐Gain). This approach can serve as a model applicable to other crops and regions. Modernization of breeding programs is necessary to maximize the rate of genetic gain. This can be achieved by adopting genomics to enable faster breeding, accurate selection, and improved traits through genomic selection and gene editing. Tracking operational costs, establishing robust, digitalized data management and analytics systems, and developing effective varietal selection processes based on customer insights are also crucial for success. Capacity building and collaboration of breeding programs and institutions also play a significant role in accelerating genetic gains. 2024-06 2024-09-11T09:26:01Z 2024-09-11T09:26:01Z Journal Article https://hdl.handle.net/10568/152128 en Open Access Wiley Dieng, I., Gardunia, B., Covarrubias–Pazaran, G., Gemenet, D. C., Trognitz, B., Ofodile, S., Fowobaje, K., Ntukidem, S., Shah, T., Imoro, S., Tripathi, L., Mushoriwa, H., Mbabazi, R., Salvo, S., & Derera, J. (2024). Q&A: Methods for estimating genetic gain in sub–Saharan Africa and achieving improved gains. The Plant Genome, 17(2). Portico. https://doi.org/10.1002/tpg2.20471 |
| spellingShingle | systems manihot esculenta crops cassava data breeding environment genotypes capacity building institutions costs selection strategies measurement resources genomics collaboration yield trends model estimation genetic gain data management modernization processes plant accounting manihot esculenta crantz gene gene editing genetic tracking genomic selection capacity plant breeders traits Dieng, Ibnou Gardunia, Brian Covarrubias‐Pazaran, Giovanny Gemenet, Dorcus C. Trognitz, Bodo Ofodile, Sam Fowobaje, Kayode Ntukidem, Solomon Shah, Trushar Imoro, Simon Tripathi, L. Mushoriwa, Hapson Mbabazi, Ruth Salvo, Stella Derera, John Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains |
| title | Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains |
| title_full | Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains |
| title_fullStr | Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains |
| title_full_unstemmed | Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains |
| title_short | Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains |
| title_sort | q a methods for estimating genetic gain in sub saharan africa and achieving improved gains |
| topic | systems manihot esculenta crops cassava data breeding environment genotypes capacity building institutions costs selection strategies measurement resources genomics collaboration yield trends model estimation genetic gain data management modernization processes plant accounting manihot esculenta crantz gene gene editing genetic tracking genomic selection capacity plant breeders traits |
| url | https://hdl.handle.net/10568/152128 |
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