Yield response functions often provide little assistance to farmers in making decision about farm management strategies. Yield rates vary spatially and maps produced by the yield monitor systems are evidence of the degree of within-field variability. Process-based crop models can play a significant role in the development of alternatives for obtaining sustainable crop production systems Crop simulation models have the potential to integrate the effects of temporal and multiple stress interaction on crop growth under different environmental and management conditions. The strength of these models is their ability to account for stress by simulating the temporal interaction of stress on plant growth each day during the season.
The objective of paper is to present a procedure that allows for the selection of optimal nitrogen fertilizer rates to be applied spatially on previously identified management zones through crop simulation modelling. An analysis was carried out to assess the effects of climate variability in selecting variable rates nitrogen. The integration of yield maps, remote sensing imagery, ground truth measurements, electrical resistivity imaging allowed for the identifications of three distinct management zones based on their ability to produce yield and their stability over time. After validating the SALUS model, we simulated 7 N rates from 0 to 180 kg N/ha with a 30 kg N/ha increment. The model results illustrate the different N responses for each of the zone. The analysis allowed us to identify the optimal N rate for each of the zone based on agronomic, economic and environmental sustainability of N management. The model provided excellent results when compared to the measured data; it also showed to be a valuable tool that would help farmer reduce their economic risk and environmental impact related to N fertilization.
