Cargando…
Prediction of plant-level tomato biomass and yield using machine learning with unmanned aerial vehicle imagery
BACKGROUND: The objective of this study is twofold. First, ascertain the important variables that predict tomato yields from plant height (PH) and vegetation index (VI) maps. The maps were derived from images taken by unmanned aerial vehicles (UAVs). Second, examine the accuracy of predictions of to...
Autores principales: | Tatsumi, Kenichi, Igarashi, Noa, Mengxue, Xiao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8281694/ https://www.ncbi.nlm.nih.gov/pubmed/34266447 http://dx.doi.org/10.1186/s13007-021-00761-2 |
Ejemplares similares
-
Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
por: Bellis, Emily S., et al.
Publicado: (2022) -
Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture
por: Ogawa, Daisuke, et al.
Publicado: (2020) -
Application of Deep-Learning Methods to Bird Detection Using Unmanned Aerial Vehicle Imagery
por: Hong, Suk-Ju, et al.
Publicado: (2019) -
Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Extract Rice Lodging
por: Zhao, Xin, et al.
Publicado: (2019) -
Applications of Unmanned Aerial Vehicle Based Imagery in Turfgrass Field Trials
por: Zhang, Jing, et al.
Publicado: (2019)