Maize, or corn, grows tall, with thin stalks that boast ears of the cereal grain used in food production, trade and security globally. However, due to rain, wind and other increasingly extreme weather events, the maize falls down, risking the entire crop. Called lodging, the physical fall results in shorter plants and overlapping leaves—both of which negatively impact the plant's ability to grow.
Conventional lodging prevention and mitigation requires many agricultural technicians significant time to investigate the crop fields, according to a team of researchers based in China. They said that a potential solution could be a rapid, non-destructive method of remote monitoring, called Unmanned Aerial Vehicle (UAV)-based hyperspectral imaging. The team recently found that the method can accurately evaluate maize recovery without the time or expense of individuals physically inspecting the crops.
The team published their approach on Aug. 28 in the Journal of Remote Sensing.
"UAV-based hyperspectral imaging technology revolutionizes the way we monitor and assess the recovery of lodging crops," said first author Qian Sun, a doctor at Yangzhou University.
"This advanced method allows for rapid, non-destructive evaluation of plant health and growth. This not only aids in better understanding the state of plants but also enhances overall crop management practices, potentially leading to more effective interventions and improved agricultural production."
UAV-based hyperspectral imaging involves using drone-like vehicles that can fly with limited human input and examine the field. For every pixel in an image, the method determines the multiple spectral bands—a much more detailed understanding than human eyesight, which only sees across three bands of visible light.
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