Thursday, March 9, 2023
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Robotic system checks on corn crops by measuring leaf angles

With a purpose to see how properly a corn plant is performing photosynthesis, it’s essential test the angle of its leaves relative to its stem. And whereas scientists ordinarily have to take action manually with a protractor, a brand new robotic system can now do the job rather more rapidly and simply.

Developed by a workforce from North Carolina State College and Iowa State College, the AngleNet system combines an current PhenoBot 3.0 wheeled agricultural robotic with particular machine-learning-based software program. Mounted on the robotic are 4 PhenoStereo digicam modules, each consisting of two cameras and a set of strobe lights. The modules are organized one above the opposite, with areas in between.

Because the remotely managed robotic strikes alongside rows of corn crops, the cameras routinely seize stereoscopic side-view pictures of the leaves on every plant at totally different heights. The software program combines these pictures to type three-dimensional fashions of these leaves, from which the angles of the leaves relative to the stem may be calculated.

Moreover, as a result of the digicam modules are mounted at recognized heights, it is potential to find out how excessive the leaves are positioned above the bottom – which is one other necessary piece of data.

“In corn, you need leaves on the high which can be comparatively vertical, however leaves additional down the stalk which can be extra horizontal,” stated NC State’s Asst. Prof. Lirong Xiang, first writer of the examine. “This permits the plant to reap extra daylight. Researchers who give attention to plant breeding monitor this form of plant structure, as a result of it informs their work.”

In a check of the know-how, leaf angles measured by the AngleNet system have been discovered to fall inside 5 levels of these measured by hand. Based on the scientists, this quantity is properly throughout the accepted margin of error for functions of plant breeding.

“We’re already working with some crop scientists to utilize this know-how, and we’re optimistic that extra researchers will likely be taken with adopting the know-how to tell their work,” stated Xiang. “In the end, our objective is to assist expedite plant breeding analysis that may enhance crop yield.”

A paper on the analysis was lately revealed within the Journal of Area Robotics. And for one more instance of a leaf-inspecting bot, try the College of Illinois’ Crop Phenotyping Robotic.

Supply: North Carolina State College



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