Robotic System Controls Corn Crops By Measuring Leaf Angles

To see how properly a corn plant performs photosynthesis, examine the angle of the leaves relative to the stem. And whereas scientists usually have to do that manually with a protractor, a brand new robotic system can now do that job a lot quicker and extra simply.

Developed by a group from North Carolina State University and Iowa State University, the AngleNet system combines an current PhenoBot 3.0 wheeled agricultural robotic with devoted machine learning-based software program. Four PhenoStereo digital camera modules are mounted on the robotic, every consisting of two cameras and a set of strobe lights. The modules are positioned one above the opposite, with areas in between.

As the remote-controlled robotic strikes previous rows of corn crops, the cameras mechanically take stereoscopic side-view pictures of every plant’s leaves at totally different heights. The software program combines these pictures into three-dimensional fashions of these leaves, from which the angles of the leaves relative to the stem could be calculated.

In addition, as a result of the digital camera modules are mounted at identified heights, it’s doable to find out how excessive the leaves are above the bottom – which is one other vital piece of knowledge.

“With corn, you want leaves on the top that are relatively vertical, but leaves further down the stem that are more horizontal,” mentioned NC State’s Asst. prof. Lirong Xiang, first creator of the research. “This allows the plant to harvest more sunlight. Plant breeding researchers keep an eye on this type of plant architecture as it informs their work.”

In a take a look at of the expertise, blade angles measured by the AngleNet system have been discovered to fall inside 5 levels of angles measured by hand. According to the scientists, this quantity is properly throughout the accepted margin of error for plant breeding.

“We’re already working with some crop scientists to leverage this technology, and we’re optimistic that more researchers will be interested in applying the technology to inform their work,” mentioned Xiang. “Ultimately, our goal is to accelerate plant breeding research that will improve crop yields.”

A paper on the analysis was just lately printed within the Journal of discipline robotics. And for an additional instance of a leaf-inspecting bot, take a look at the University of Illinois Crop Phenotyping Robot.

Source: North Carolina State University


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