Using the CERES-Maize Model to Simulate Crop Yield in a Long-Term Field Experiment in Hungary

Precision crop production requires accurate yield prediction and nitrogen management. Crop simulation models may assist in exploring alternative management systems for optimizing water, nutrient microelements use efficiencies, increasing maize yields. Our objectives were: (i) to access the ability of CERES-Maize model predicting yields long-term experiments Hungary; (ii) assess effects different (different rates—0, 30, 60, 90, 120, 150 kg ha?1). A experiment conducted Látókép (Hungary) with various N-fertilizer applications allowed us predict under conditions. The aim research is explore quantify ecological, biological, agronomic factors affecting plant production, as well conduct basic science studies on stress populations, which are made possible by 30-year database high level instrumentation. was calibrated data from a field trial. purpose this evaluation investigate how simulated N treatments experiments. Sushi hybrid’s increased elevated concentrations. observed ranged 5016 14,920 ha?1 during 2016–2020 growing season. range between 6671 13,136 ha?1. highest obtained at dose each year studied. In several cases, DSSAT-CERES Maize accurately predicted yields, but it sensitive seasonal estimated inaccurately. Based results, variance analysis significantly affected (2016–2020) doses. fertilizer significant difference yield, combination both actual did not show any significance.