High-Throughput Crop Phenotyping Using Unmanned Aerial Vehicle Imagery

Dear Colleagues,

The global population is expected to reach 9.6 billion by 2050, which will introduce enormous challenges to the agricultural sector, with the context of the limited availability of arable lands, scarcity of irrigation water, and severe negative impact of climate change. These challenges have encouraged the efforts in breeding programs, which investigate the genetic diversity in germplasm collection to identify the crop traits relating to the resistance of abiotic/biotic stress and crop production. Genetic tools always lead to huge amounts of data, but the extraction of phenotypic traits from large-scale and time series crop imaging data remains unsatisfactory. Consequently, bridging the gap between phenotypes and genotypes is a significant research field in modern agriculture. Unmanned Aerial Vehicles (UAVs), which can carry a range of imaging sensors, typically in the visible and infrared domain but also in both 2D and 3D formats, have been employed in high-throughput and non-destructive crop phenotyping over time. Recent developments in sensor technology, image analysis, and machine learning need to be integrated with UAV imagery to gain more quantitative knowledge of key plant traits in crop breeding and production.

This Special Issue aims to collect the results of the latest innovative research in the application of UAV imagery and machine learning for the high-throughput phenotyping. Original research articles and reviews are welcome in both agricultural and horticultural areas. The list below provides a general (but not exhaustive) overview of the topics that are solicited for this Special Issue:

• Novel UAV imaging sensors for plant phenotyping;
• 2D or 3D image analysis algorithms including object detection, segmentation, and classification for key crop trait estimation;
• UAV imaging sensor calibration;
• Sensor fusion and corresponding image analysis.

Dr. Bo Li
Dr. Jiangang Liu
Dr. Wei Guo
Dr. Talukder Zaki Jubery
Guest Editors

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