Photo credit: Lawrence Berkeley National Laboratory
A new artificial intelligence technology promises to ensure food security and sustainability in our warming world.
The device analyzes roots to help track plant growth and biomass, which could lead to applications related to crop quality and yield, according to the Interesting Engineering report. It was developed by scientists from Lawrence Berkeley National Laboratory's Applied Mathematics and Computational Research and Environmental Genomics and Systems Biology Divisions.
Called RhizoNet, the deep learning backbone and convolutional neural network work by examining small patches of images, according to a news release about the research, which was published in Scientific Reports.
“It revolutionizes root image analysis, offering accurate insights into root behavior under different environmental conditions,” IE reported.
It's an essential tool, as scientists around the world work to engineer plants that can survive extreme weather events and increasingly use human-made, dirty energy sources. Worse and more frequent due to rising temperatures.
Bayer, for example, is awaiting full approval of “short corn,” which can withstand the high winds that wreak havoc on crops in the Midwest and can be planted more densely than conventional corn. Which increases productivity.
Abroad, researchers in England and Vietnam worked to make rice more saline in an effort to combat seawater intrusion.
New plant technology may result in similar advances, although it is also a step toward the development of automated laboratories, per IE, who reported that RhizoNet outperformed manual methods.
“Using smaller image patches, the model better captured the fine details of the root and improved its accuracy,” the news outlet said.
According to the release, the researchers hope the study will lead to sustainable energy solutions in addition to plant- and microbe-based technologies to control carbon pollution.
“We have made great strides in reducing the manual work involved in plant cultivation experiments. [image acquisition system] EcoBOT, and now RhizoNet, is reducing the manual work involved in analyzing the generated data,” said EGSB research scientist Peter Ander, per IE. “This increases our throughput and allows us to target self-driving labs. leads to.”
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