Mark Smith

USDA-ARS Adaptive Cropping Systems Laboratory (ACSL), in association with Nebraska Water Center, will conduct a half-day workshop/demo on ‘Crop Simulation Models for Agricultural Systems Applications - Introducing the CLASSIM Interface’. This workshop will be conducted as part of the Water for Food Global conference that will be held April 28-May 2, 2025, hosted by the Daugherty Water for Food Global Institute at the University of Nebraska Lincoln.  

USDA-ARS ACSL Crop Models and CLASSIM 

ACSL is at the forefront of developing and improving mechanistic, process-based crop and soil models. These models simulate crop growth and development, yield, root growth, soil water, nutrient, heat and gas dynamics, soil carbon and nitrogen transformations, and greenhouse gas emissions, and account for environmental, cultivar, and management interactions. The crop models were recently updated with more accurate components for predicting photosynthesis and transpiration, including improved functions for high-temperature responses, and are integrated with a two-dimensional finite element-based soil process simulator. 

USDA-ARS ACSL developed the Crop Land And Soil SIMulation (CLASSIM) graphical user interface to provide standardized access to these crop models. CLASSIM is designed to function as a standalone Windows-based application. This Python-based interface simplifies the use of USDA crop models for corn, cotton, potato, soybean and cereal rye.  

Workshop Goal and Objectives:  

The goal of the workshop is to familiarize participants with the USDA-ARS ACSL crop models and CLASSIM. Workshop will consist of a mix of lectures and hands-on training using preset examples. Lectures will address the (a) science behind the models, (b) the different modules used to represent soil-plant-atmospheric components, (c) crop input data requirements, (d) model outputs and other model capabilities. Training will provide participants with the opportunity to simulate different agricultural scenarios and interpret the variability in plant growth, development and yield responses to different management and environmental conditions.