Genomic prediction enables early but low-intensity selection in soybean segregating progenies (2020)
- Authors:
- USP affiliated authors: FRITSCHE NETO, ROBERTO - ESALQ ; MENDONÇA, LEANDRO DE FREITAS - ESALQ ; GALLI, GIOVANNI - ESALQ
- Unidade: ESALQ
- DOI: 10.1002/csc2.20072
- Subjects: GENÉTICA QUANTITATIVA; GENÔMICA; MELHORAMENTO GENÉTICO VEGETAL; SELEÇÃO GENÉTICA; SOJA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Crop Science
- ISSN: 0011183X
- Volume/Número/Paginação/Ano: online, p. 1-16, 2020
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MENDONÇA, Leandro de Freitas et al. Genomic prediction enables early but low-intensity selection in soybean segregating progenies. Crop Science, p. 1-16, 2020Tradução . . Disponível em: https://doi.org/10.1002/csc2.20072. Acesso em: 28 dez. 2025. -
APA
Mendonça, L. de F., Galli, G., Malone, G., & Fritsche-Neto, R. (2020). Genomic prediction enables early but low-intensity selection in soybean segregating progenies. Crop Science, 1-16. doi:10.1002/csc2.20072 -
NLM
Mendonça L de F, Galli G, Malone G, Fritsche-Neto R. Genomic prediction enables early but low-intensity selection in soybean segregating progenies [Internet]. Crop Science. 2020 ; 1-16.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1002/csc2.20072 -
Vancouver
Mendonça L de F, Galli G, Malone G, Fritsche-Neto R. Genomic prediction enables early but low-intensity selection in soybean segregating progenies [Internet]. Crop Science. 2020 ; 1-16.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1002/csc2.20072 - The accuracy of different strategies for building training sets for genomic predictions in soybean segregating populations
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Informações sobre o DOI: 10.1002/csc2.20072 (Fonte: oaDOI API)
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