By Andi Anderson
Purdue Agriculture experts are using artificial intelligence (AI) and machine learning (ML) to solve challenges in farming, animal care, and environmental research. These technologies help analyze large data sets, detect patterns, and support informed decisions.
In urban studies, Dr. Brady Hardiman uses AI and LiDAR to map tree species and track invasive plants. This helps improve city green spaces and manage urban forests better. His team uses high-resolution images to spot issues like buckthorn spread in Chicago’s forests.
In animal science, Dr. Upinder Kaur’s team built a small robot that collects data from inside a cow’s stomach. It tracks temperature, pH, and methane, helping farmers reduce emissions and monitor animal health more accurately.
Dr. Sajad Jamshidi uses ML to predict how climate change affects rice yields. His team found that past breeding programs helped rice adapt to warming climates, even without that goal. This model helps test rice responses to weather without years of field trials.
Dr. Ankita Raturi designs decision tools like a “Netflix for crops” to help farmers choose cover crops based on soil, climate, and goals. Her lab also builds models to simulate food systems, helping farmers and policymakers plan more effectively.
Dr. Somali Chaterji focuses on building ML tools for detecting crop diseases using both labeled and unlabeled images. These models can run on small devices like drones, making it easier to monitor large fields in real time. Her work improves data accuracy and reduces the need for powerful computers.
From precision livestock tracking to climate-smart farming and urban forest mapping, Purdue’s use of AI is creating practical solutions for today’s agricultural and environmental challenges.
Photo Credit: purdue-university
Categories: Indiana, Equipment & Machinery