James McKinion (Mississippi State University)
|Scale||Organs, Whole_plant, Field|
|Format of model inputs and outputs||NA|
Crop management and input optimization with GLYCIM: differing cultivarsVR. Reddy,B. Acock,ED. WhislerComputers and Electronics in Agriculture, 1995 View paper
GLYCIM is a dynamic soybean simulation model with hourly time steps. It predicts growth and yield of a soybean crop in response to climate, soil, and management practices by deterministic simulation of organ-level processes such as photosynthesis, transpiration, carbon partitioning, and organ growth and development.
Some case studies
Farmers use GLYCIM for pre-plant planning decisions like the selection of cultivar/soil type combination, planting date, and row spacing, and post-plant decisions like irrigation scheduling, harvest timing, and yield prediction. The use of the model for crop management, decision making, and input optimization shows promise in increasing profits to growers and improvements to environment and groundwater quality. Amendable to the testing of management adjustments to climate variation. Currently GLYCIM is used by farmers and several extension services in nine states in the U.S.