Source: The Plant Phenome Journal. Unidade: ESALQ
Subjects: AERONAVES NÃO TRIPULADAS, ANÁLISE ESPECTRAL, ANTRACNOSE, FENOLOGIA, FENÓTIPOS, FUNGOS FITOPATOGÊNICOS, IMAGEM DIGITAL, SORGO
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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: 08 out. 2024.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/ppj2.20010NLM
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 2024 out. 08 ] Available from: https://doi.org/10.1002/ppj2.20010Vancouver
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 2024 out. 08 ] Available from: https://doi.org/10.1002/ppj2.20010