By Scout Nelson
Dr. Ruti Das Choudhury, a research associate professor at the School of Natural Resources, is leading new projects that aim to make artificial intelligence (AI) more understandable and reliable for agricultural use. Her goal is to help farmers see not only the results AI provides but also the reasoning behind those results.
Currently, farmers can input data and receive AI-based recommendations, but they often do not know how the system reaches its conclusions. To address this challenge, Choudhury is leading two major projects: “Explainable AI for Precision Agriculture: A Data-Driven Approach to Crop Recommendation” and “Explainable Artificial Intelligence for Phenotype-Genotype Mapping Using Time-Series Data Analytics.”
“We will have an answer, an explanation of the output of the model, and we can verify that explanation with the existing knowledge of the farmers,” said Choudhury.
The first project focuses on developing AI systems that can justify their crop recommendations by identifying which factors—such as soil pH, rainfall, or temperature—most influenced by the outcome. The second explores how AI can map genetic and physical plant traits using explainable algorithms.
“That's the idea, like deeper insight into the predictions that AI model is doing, and if we can do that, that will make the model more transparent, interpretable and trustworthy and will adhere to the ethical aspects of AI,” Choudhury said.
Choudhury’s research team includes Sanjan Baitalik and Rajashik Datta, undergraduate students from the Institute of Engineering and Management in Kolkata, India. The trio began their work in January 2025 and quickly achieved early results.
Choudhury is also proposing a university course titled “Artificial Intelligence, Computer Vision and Data Analytics for Agriculture and Natural Resources”, designed to teach future professionals about ethical and explainable AI.
She believes that success in this research will be a major step toward making AI in agriculture more transparent and trustworthy. “It would help farmers understand why an AI system makes certain predictions or decisions rather than having to just accept the decisions blindly,” Choudhury said.
Photo Credit:istock-primeimages
Categories: Nebraska, General