Sponsored by the U.S. Department of Agriculture’s (USDA) National Institute of Food and Agriculture (NIFA)

Shaping Tomorrow’s Greenhouse Innovators

Funded by the Core Agriculture Research and Extension (CARE) program in 2026, CROP-SIM brings together partners from higher education and the manufacturing sector to create a transformational labor training tool, with $300,000 in funding provided towards the initiative.

Commercial greenhouse operations have identified that training new and existing employees on computerized climate control systems is a bottleneck for a well-trained workforce. There is a critical need to practice climate control virtually, where effects on greenhouse environment and crop performance can be observed. This project will develop an advanced virtual training tool for controlled environment agriculture, specifically targeting teen-leaf lettuce, a sector increasing in U.S. sales value by 36% annually. The tool will feature a climate control user interface connected to both a greenhouse energy model and a crop growth model. By enabling training in a virtual environment, CROP-SIM will help prevent crop losses from management errors, a risk in real-world settings. The project has four key objectives aimed at enhancing greenhouse management/profitability, improving resource efficiency, and supporting sustainable industry growth.

Aiming for Long-Term Impact:

Our long-term goal is that the Greenhouse CROP-SIM project can develop a framework that can be expanded for future training opportunities. Based on our greenhouse stakeholder collaborators we believe a conservative estimate is that this training tool could lead to at least a 5% reduction in crop losses annually and if applied to the current $400 million U.S. greenhouse lettuce value we expect an annual economic return of at least $20 million. This project could scale to the development of more robust models and expanded crops. For example, future research can expand the number of crops incorporated into the model by calibrating/validating crop specific models for other common CEA crops such as tomatoes, cucumbers, herbs, and strawberries. We would also like to implement additional languages (such as Spanish) into future training tools. Finally, the overall framework is meant to be agnostic to the climate control system. By developing a standardized API (i.e., communication interface) the greenhouse energy model and crop models will be able to connect to other climate control interfaces that implement the API. 

Neil Mattson

GLASE Principal Investigator and Associate Professor at Cornell University

Gretchen Schimelpfenig

Executive Director at GLASE

Tyler Pakulski

Extension Specialist at GLASE

Manuela Zamora

Executive Director at NY Sun Works

Director of CEA Operations at NY Sun Works

Crystal Huff

Director at Commonwealth Charter Academy Cyber Charter School