Artificial Intelligence Tasked To Help Protect Bees From Certain Pesticides

Researchers in the Oregon State University College of Engineering have harnessed the power of artificial intelligence to help protect bees from pesticides.

Cory Simon, Assistant Professor of chemical engineering, and Xiaoli Fern, Associate Professor of computer science, led the project, which involved training a machine learning model to predict whether any proposed new herbicide, fungicide, or insecticide would be toxic to honey bees based on the compound’s molecular structure.

The findings, featured on the cover of The Journal of Chemical Physics in a special issue, “Chemical Design by Artificial Intelligence,” are important because many fruit, nut, vegetable, and seed crops rely on bee pollination.

Without bees to transfer the pollen needed for reproduction, almost 100 commercial crops in the US would vanish. Bees’ global economic impact is annually estimated to exceed $100 billion.

“Pesticides are widely used in agriculture, which increase crop yield and provide food security, but pesticides can harm off-target species like bees,” Simon says. “And since insects, weeds, etc. eventually evolve resistance, new pesticides must continually be developed, ones that don’t harm bees.”

Graduate students Ping Yang and Adrian Henle used honey bee toxicity data from pesticide exposure experiments, involving nearly 400 different pesticide molecules, to train an algorithm to predict if a new pesticide molecule would be toxic to honey bees.

“The model represents pesticide molecules by the set of random walks on their molecular graphs,” Yang says.

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