Researchers at Iowa State University and North Carolina State University have created a robotic system that can precisely gauge the angle of leaves on maize plants in the field. Plant breeders can rapidly and effectively gather relevant data using this new technology, AngleNet, to spot desirable and unfavorable features in genetic lines.
Using a protractor to measure leaves manually is a time-consuming and labor-intensive way of determining leaf angles. Therefore, hardware and software comprise the two main parts of AngleNet, which the National Science Foundation of the United States funds.
The hardware consists of four levels, each with two cameras, which enable 3D modeling of plants by capturing a stereoscopic picture of the leaves. The tool takes numerous stereoscopic photographs, from various heights, of each plant it passes as it is guided along a row of plants. This visual information is entered into software that determines the leaf angle for each plant’s leaves at various heights.
Dr. Guo-Xun Xiang, an assistant professor of electrical and computer engineering at NC State and a co-author of the study, explains that plant breeders must understand both the leaf angle and the height of the leaves. “This provides students with the knowledge they need to evaluate the distribution of leaf angles for each row of plants.”
To evaluate the accuracy of AngleNet, the researchers compared leaf angle measurements taken by hand using traditional methods and measurements made by the robot in a cornfield. They discovered that the AngleNet angles were accurate to within five degrees of the angles measured manually, which is well within the allowable margin of error for plant breeding.
To employ this technology, “we’re already collaborating with several agricultural experts, and we’re confident that additional researchers will be interested in using the technology to guide their work,” adds Xiang. Our ultimate objective is to hasten agricultural yield-improving plant breeding research.
AngleNet’s automated technology provides an efficient way for plant breeders to collect data on leaf angles, which is a critical component in identifying desirable traits in genetic lines. As a result, this technology can potentially revolutionize plant breeding research and improve crop yield.
Photo by Joran Quinten on Unsplash
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