The effect of bienniality on genomic prediction of yield in arabica coffee (2020)
- Authors:
- USP affiliated authors: FRITSCHE NETO, ROBERTO - ESALQ ; GALLI, GIOVANNI - ESALQ
- Unidade: ESALQ
- DOI: 10.1007/s10681-020-02641-7
- Subjects: CAFÉ; GENÔMICA; SELEÇÃO GENÉTICA; SEQUENCIAMENTO GENÉTICO
- Keywords: Previsão de ano
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Heidelberg
- Date published: 2020
- Source:
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
CARVALHO, Humberto Fanelli et al. The effect of bienniality on genomic prediction of yield in arabica coffee. Euphytica, v. 216, n. 101, p. 1-16, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10681-020-02641-7. Acesso em: 27 dez. 2025. -
APA
Carvalho, H. F., Galli, G., Ferrão, L. F. V., Nonato, J. V. A., Padilha, L., Maluf, M. P., et al. (2020). The effect of bienniality on genomic prediction of yield in arabica coffee. Euphytica, 216( 101), 1-16. doi:10.1007/s10681-020-02641-7 -
NLM
Carvalho HF, Galli G, Ferrão LFV, Nonato JVA, Padilha L, Maluf MP, Resende Júnior MFR de, Guerreiro Filho O, Fritsche-Neto R. The effect of bienniality on genomic prediction of yield in arabica coffee [Internet]. Euphytica. 2020 ; 216( 101): 1-16.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1007/s10681-020-02641-7 -
Vancouver
Carvalho HF, Galli G, Ferrão LFV, Nonato JVA, Padilha L, Maluf MP, Resende Júnior MFR de, Guerreiro Filho O, Fritsche-Neto R. The effect of bienniality on genomic prediction of yield in arabica coffee [Internet]. Euphytica. 2020 ; 216( 101): 1-16.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1007/s10681-020-02641-7 - Population-tailored mock genome enables genomic studies in species without a reference genome
- Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum
- Genomic prediction enables early but low-intensity selection in soybean segregating progenies
- CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction
- Classification of plant growth‐promoting bacteria inoculation status and prediction of growth‐related traits in tropical maize using hyperspectral image and genomic data
- EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture
- Deep purple - an open-pollinated variety to induce haploids in tropical maize
- Impact of the complexity of genotype by environment and dominance modeling on the predictive accuracy of maize hybrids in multi-environment prediction models
- On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids
- Automated machine learning: a case study of genomic “image-based” prediction in maize hybrids
Informações sobre o DOI: 10.1007/s10681-020-02641-7 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 2999064-The_effect_of_bie... |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
