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

Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains

2024

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.

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Mots clés AGROVOC

accounting breeding capacity building cassava collaboration costs crops data data management environment estimation gene gene editing genetic gain genomic selection genomics genotypes institutions manihot esculenta measurement model modernization plant plant breeders processes resources selection strategies systems tracking trends

Informations bibliographiques

Publié dans

The Plant Genome

Volume 17 Numéro 2 ISSN 1940-3372

Editeur

Wiley

D'autres materias

Manihot esculenta crantz; Genetic; Yield; Traits; Capacity

Langue

anglais

Licence

Open Access, CC-BY-4.0

Type

Journal Article; Journal Part

Source

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

Auteur institutionnelle

CGIAR Trust Fund

Sur AGRIS depuis: 2024-11-28

Date de modification: 2025-06-18

Format: MODS

Fournisseur de données

Cette notice bibliographique a été fournie par International Livestock Research Institute

Découvrez la collection de ce fournisseur de données dans AGRIS

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