Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum (2020)
- Authors:
- USP affiliated authors: FRITSCHE NETO, ROBERTO - ESALQ ; GALLI, GIOVANNI - ESALQ
- Unidade: ESALQ
- DOI: 10.1002/ppj2.20010
- Subjects: AERONAVES NÃO TRIPULADAS; ANÁLISE ESPECTRAL; ANTRACNOSE; FENOLOGIA; FENÓTIPOS; FUNGOS FITOPATOGÊNICOS; IMAGEM DIGITAL; SORGO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: The Plant Phenome Journal
- ISSN: 2578-2703
- Volume/Número/Paginação/Ano: v. 3, art. e20010, p. 1-14, 2020
- Status:
- Artigo publicado em periódico de acesso aberto (Gold Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
GALLI, Giovanni et al. Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum. The Plant Phenome Journal, v. 3, p. 1-14, 2020Tradução . . Disponível em: https://doi.org/10.1002/ppj2.20010. Acesso em: 30 mar. 2026. -
APA
Galli, G., Horne, D. W., Collins, S. D., Jung, J., Chang, A., Fritsche‐Neto, R., & Rooney, W. L. (2020). Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum. The Plant Phenome Journal, 3, 1-14. doi:10.1002/ppj2.20010 -
NLM
Galli G, Horne DW, Collins SD, Jung J, Chang A, Fritsche‐Neto R, Rooney WL. Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum [Internet]. The Plant Phenome Journal. 2020 ; 3 1-14.[citado 2026 mar. 30 ] Available from: https://doi.org/10.1002/ppj2.20010 -
Vancouver
Galli G, Horne DW, Collins SD, Jung J, Chang A, Fritsche‐Neto R, Rooney WL. Optimization of UAS‐based high‐throughput phenotyping to estimate plant health and grain yield in sorghum [Internet]. The Plant Phenome Journal. 2020 ; 3 1-14.[citado 2026 mar. 30 ] Available from: https://doi.org/10.1002/ppj2.20010 - Population-tailored mock genome enables genomic studies in species without a reference genome
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