Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection‐based breeding programs (2024)
- Authors:
- USP affiliated authors: FRITSCHE NETO, ROBERTO - ESALQ ; SILVA, ALLISON VIEIRA DA - ESALQ ; PRADO, MELINA - ESALQ
- Unidade: ESALQ
- DOI: 10.1002/csc2.21384
- Subjects: ALGORITMOS GENÉTICOS; GENOMAS; GENÔMICA; GERMOPLASMA VEGETAL; MELHORAMENTO GENÉTICO VEGETAL; SELEÇÃO GENÉTICA
- Language: Inglês
- Imprenta:
- Source:
- Título: Crop Science
- ISSN: 0011-183X
- Volume/Número/Paginação/Ano: v. 64, p. 3323–3338, 2024
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
FRITSCHE‐NETO, Roberto et al. Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection‐based breeding programs. Crop Science, v. 64, p. 3323–3338, 2024Tradução . . Disponível em: https://doi.org/10.1002/csc2.21384. Acesso em: 09 fev. 2026. -
APA
Fritsche‐Neto, R., Yassue, R. M., Silva, A. V. da, Prado, M., & DoVale, J. C. (2024). Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection‐based breeding programs. Crop Science, 64, 3323–3338. doi:10.1002/csc2.21384 -
NLM
Fritsche‐Neto R, Yassue RM, Silva AV da, Prado M, DoVale JC. Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection‐based breeding programs [Internet]. Crop Science. 2024 ; 64 3323–3338.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1002/csc2.21384 -
Vancouver
Fritsche‐Neto R, Yassue RM, Silva AV da, Prado M, DoVale JC. Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection‐based breeding programs [Internet]. Crop Science. 2024 ; 64 3323–3338.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1002/csc2.21384 - Optimizing multi-environment trials in the Southern US Rice belt via smart-climate-soil prediction-based models and economic importance
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Informações sobre o DOI: 10.1002/csc2.21384 (Fonte: oaDOI API)
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