Artificial intelligence (AI) is the buzz phrase of 2024. Though far from that cultural spotlight, scientists from agricultural, biological and technological backgrounds are also turning to AI as they collaborate to find ways for these algorithms and models to analyze datasets to better understand and predict a world impacted by climate change.
Artificial intelligence is the buzz phrase of 2024. Though far from that cultural spotlight, scientists from agricultural, biological and technological backgrounds are also turning to AI as they collaborate to find ways for these algorithms and models to analyze datasets to better understand and predict a world impacted by climate change.
Tuinstra, the Wickersham Chair of Excellence in Agricultural Research, professor of plant breeding and genetics in the department of agronomy and the science director for Purdue's Institute for Plant Sciences, said,"This study highlights how advances in UAV-based data acquisition and processing coupled with deep-learning networks can contribute to prediction of complex traits in food crops like maize.
"Plants tell a story for themselves," Crawford said."They react if they are stressed. If they react, you can potentially relate that to traits, environmental inputs, management practices such as fertilizer applications, irrigation or pests." "This is one of the first AI models to add plant genetics to the story of yield in multiyear large plot-scale experiments," Tuinstra said."Now, plant breeders can see how different traits react to varying conditions, which will help them select traits for future more resilient varieties. Growers can also use this to see which varieties might do best in their region."
Neural networks have the appearance of chicken wire, with linkages connecting points that ultimately communicate with every other point. Aviles Toledo adapted this model with long short-term memory, which allows past data to be kept constantly in the forefront of the computer's"mind" alongside present data as it predicts future outcomes.
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