Biomass estimation of World rice (Oryza sativa L.) core collection based on the convolutional neural network and digital images of canopy
ABSTRACTAbove-ground biomass (AGB) is an important indicator of crop productivity. Destructive measurements of AGB incur huge costs, and most non-destructive estimations cannot be applied to diverse cultivars having different canopy architectures. This insufficient access to AGB data has potentially...
Main Authors: | Kota Nakajima, Yu Tanaka, Keisuke Katsura, Tomoaki Yamaguchi, Tomoya Watanabe, Tatsuhiko Shiraiwa |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2023-04-01
|
Series: | Plant Production Science |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/1343943X.2023.2210767 |
Similar Items
-
Spatio-Temporal Estimation of Biomass Growth in Rice Using Canopy Surface Model from Unmanned Aerial Vehicle Images
by: Clement Oppong Peprah, et al.
Published: (2021-06-01) -
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region
by: S. Kraatz, et al.
Published: (2022-12-01) -
Improving efficiency of ground-truth data collection for UAV-based rice growth estimation models: investigating the effect of sampling size on model accuracy
by: Tomoaki Yamaguchi, et al.
Published: (2024-01-01) -
Integrating the Textural and Spectral Information of UAV Hyperspectral Images for the Improved Estimation of Rice Aboveground Biomass
by: Tianyue Xu, et al.
Published: (2022-05-01) -
Quantitative Trait Locus Mapping of High Photosynthetic Efficiency and Biomass in Oryza longistaminata
by: Si Fengfeng, et al.
Published: (2022-11-01)