Quantifying Effects of Excess Water Stress at Early Soybean Growth Stages Using Unmanned Aerial Systems
Low-gradient agricultural areas prone to in-field flooding impact crop development and yield potential, resulting in financial losses. Early identification of the potential reduction in yield from excess water stress at the plot scale provides stakeholders with the high-throughput information needed...
Main Authors: | Stuart D. Smith, Laura C. Bowling, Katy M. Rainey, Keith A. Cherkauer |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/13/15/2911 |
Similar Items
-
Improving the efficiency of soybean breeding with high-throughput canopy phenotyping
by: Fabiana Freitas Moreira, et al.
Published: (2019-11-01) -
High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data
by: Predrag Ranđelović, et al.
Published: (2023-08-01) -
Phenotypic Variation and Genetic Architecture for Photosynthesis and Water Use Efficiency in Soybean (Glycine max L. Merr)
by: Miguel Angel Lopez, et al.
Published: (2019-05-01) -
Yield prediction by machine learning from UAS-based mulit-sensor data fusion in soybean
by: Monica Herrero-Huerta, et al.
Published: (2020-06-01) -
Diversity Characterization of Soybean Germplasm Seeds Using Image Analysis
by: Seong-Hoon Kim, et al.
Published: (2022-04-01)