Advancing Meter Resolution Crop Simulation Model as a Testbed for Precision Agricultural Applications
Year: 2025
Type: conference-paper
Abstract: Crop simulation models (CSMs) offer significant potential beyond traditional agronomic analysis, particularly for advancing digital technologies in precision agriculture. This work presents a framework for creating meter-scale field digital twins by integrating CSMs. The framework leverages public highresolution geographical data with the WOrld FOod STudies (WOFOST) crop simulation model to create a digital twin. The twin is calibrated using local field measurements and simulates key agronomic and environmental variables with high spatial precision. In its initial simulation of a soybean crop in a 110-acre field at 5m×5m resolution, a variation of 10 bu/ac was observed. Qualifying it as a high-fidelity virtual testbed for designing and evaluating sensor networks, stress scenarios, and field trials. Supporting the deployment and optimization of emerging digital systems in precision agriculture.
Authors: Sneha Jha, James V. Krogmeier
Institution: Purdue University West Lafayette
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Funder: National Science Foundation
OpenAlex ID: W4413503141