CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction (2021)
- Authors:
- USP affiliated authors: FRITSCHE NETO, ROBERTO - ESALQ ; YASSUE, RAFAEL MASSAHIRO - ESALQ ; GALLI, GIOVANNI - ESALQ
- Unidade: ESALQ
- DOI: 10.1007/s10681-021-02831-x
- Subjects: AMOSTRAGEM; GENÔMICA; MODELOS PARA PROCESSOS ESTOCÁSTICOS; SELEÇÃO GENÉTICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Heidelberg
- Date published: 2021
- Source:
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: cc-by-nc-nd
-
ABNT
YASSUE, Rafael Massahiro et al. CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction. Euphytica, v. 217, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1007/s10681-021-02831-x. Acesso em: 23 abr. 2024. -
APA
Yassue, R. M., Sabadin, F., Galli, G., Alves, F. C., & Fritsche-Neto, R. (2021). CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction. Euphytica, 217, 1-13. doi:10.1007/s10681-021-02831-x -
NLM
Yassue RM, Sabadin F, Galli G, Alves FC, Fritsche-Neto R. CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction [Internet]. Euphytica. 2021 ; 217 1-13.[citado 2024 abr. 23 ] Available from: https://doi.org/10.1007/s10681-021-02831-x -
Vancouver
Yassue RM, Sabadin F, Galli G, Alves FC, Fritsche-Neto R. CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction [Internet]. Euphytica. 2021 ; 217 1-13.[citado 2024 abr. 23 ] Available from: https://doi.org/10.1007/s10681-021-02831-x - Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids
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Informações sobre o DOI: 10.1007/s10681-021-02831-x (Fonte: oaDOI API)
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