Evaluation of the STICS crop growth model with maize cultivar parameters calibrated for Eastern Canada

Crop growth models are great tools for studying and anticipating the future impacts of rising demands for agricultural production while satisfying constraints with respect to product safety, the landscape, and the environment. Before crop growth models can be applied, however, they need to be calibrated and evaluated for cultivars representative of a given ecozone. This study presents an evaluation of the STICS crop growth model using maize cultivar parameters calibrated for the Mixedwood Plains ecozone in Eastern Canada. In the study area, which extends from southwestern Quebec to southern Ontario, the available crop heat units (CHU, in CHU index) for plant growth vary between 2,500 and 3,500 CHU. One cultivar was first calibrated in the STICS model using leaf area index (LAI) and yield data from Ottawa, Ontario. The model gave good predictions of LAI, biomass, and yield for the cultivar CanMaisNE in the range of 2,500-2,900 CHU. The root mean square error of the predictions was 28.1% for LAI, 17.5% for biomass, and 10.1% for yield. A second cultivar, CanMaisSE, was defined for the higher CHU range (2,900-3,300 CHU). CanMaisSE had the same crop and cultivar parameters as CanMaisNE except for the duration of grain filling, which was increased by 6-7 days to account for the longer growing season in the area with 3,300 CHU. Good predictions of LAI, biomass, and yield were obtained for CanMaisSE, with root mean square error values of 30.6%, 25.2%, and 16.1%, respectively. Defining these two generic maize cultivars was sufficient to estimate biomass, yield, and LAI over the entire study area. This work is the first calibration and performance evaluation of the STICS crop model for maize in North America. Moreover, these new grain maize cultivars, adapted to a shorter growing season, open new opportunities for using STICS in northern countries.