Review of Crop Phenotyping in Field Plot Experiments Using UAV-Mounted Sensors and Algorithms

The phenotyping of field crops quantifies a plant’s structural and physiological characteristics to facilitate crop breeding. High-throughput unmanned aerial vehicle (UAV)-based remote sensing platforms have been extensively researched as replacements for more laborious and time-consuming manual fie...

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Bibliographic Details
Published in:Drones (Basel) 2024-06, Vol.8 (6), p.212
Main Authors: Tanaka, Takashi Sonam Tashi, Wang, Sheng, Jørgensen, Johannes Ravn, Gentili, Marco, Vidal, Armelle Zaragüeta, Mortensen, Anders Krogh, Acharya, Bharat Sharma, Beck, Brittany Deanna, Gislum, René
Format: Article
Language:English
Subjects:
Abiotic stress
Agricultural production
agriculture
Algorithms
Big Data
Biomass
breeding
Cameras
Crop diseases
crop phenotyping
Crop production
Cropping systems
Crops
Data processing
Deep learning
Drone aircraft
Ensemble learning
Helicopters
Machine learning
Physiology
Platforms
Remote sensing
Senescence
Sensors
Unmanned aerial vehicles
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Summary:The phenotyping of field crops quantifies a plant’s structural and physiological characteristics to facilitate crop breeding. High-throughput unmanned aerial vehicle (UAV)-based remote sensing platforms have been extensively researched as replacements for more laborious and time-consuming manual field phenotyping. This review aims to elucidate the advantages and challenges of UAV-based phenotyping techniques. This is a comprehensive overview summarizing the UAV platforms, sensors, and data processing while also introducing recent technological developments. Recently developed software and sensors greatly enhance the accessibility of UAV-based phenotyping, and a summary of recent research (publications 2019–2024) provides implications for future research. Researchers have focused on integrating multiple sensing data or utilizing machine learning algorithms, such as ensemble learning and deep learning, to enhance the prediction accuracies of crop physiological traits. However, this approach will require big data alongside laborious destructive measurements in the fields. Future research directions will involve standardizing the process of merging data from multiple field experiments and data repositories. Previous studies have focused mainly on UAV technology in major crops, but there is a high potential in minor crops or cropping systems for future sustainable crop production. This review can guide new practitioners who aim to implement and utilize UAV-based phenotyping.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones8060212