Sulaymon Eshkabilov, NDSU assistant professor of agricultural and biosystems engineering, and a team of researchers were awarded a $1 million research grant from the USDA’s Specialty Crop Multistate Program.
The research team is made up of Eshkabilov, who serves as the principal investigator, along with co-principal investigator Ivan Simko, a research geneticist with the USDA, and co-principal investigators Senay Simsek, head a professor of food science at Purdue University, and Amanda Deering, associate professor of produce food safety at Purdue University.
The project aims to apply machine learning algorithms to develop classification, estimation and prediction models for lettuce crops with the goal of enhancing production efficiency and food safety while minimizing the environmental impact.
Over 2,000 lettuce samples will be collected from plants grown using nine combinations of fertilizers (nitrogen and phosphorus) and three watering regimes. Egg-washing wastewater will then be applied in controlled environmental agriculture units. The research team will study the challenges and opportunities associated with using egg-washing wastewater for lettuce cultivation. Using wastewater conserves water resources and provides valuable nutrients to the crops, reducing freshwater usage and fertilizer costs.
The study's outcomes may contribute to a wider adoption of wastewater treatment and reuse practices, ensuring compliance with regulatory standards and enhancing food safety. The dissemination of findings through research articles, conferences and seminars aims to broaden the understanding of sustainable agricultural practices and wastewater management in the scientific community and among stakeholders.
The team will collect over 2,500 hyperspectral and 5,000 true color (red, green, blue) imagery data along with the in-situ laboratory measured data and analyze them using machine learning models. The acquired data from this research will serve as baseline data for the development of smart fertilizer and water management systems for mass lettuce production.
