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

The global precision farming area is constantly increasing, and precision sweet maize production developed the most. Sweet maize yield is above average in precision farming. Additionally, its role in healthy nutrition is becoming increasingly important due to new hybrids with high carotenoid content. Precision farming techniques are needed to produce healthy food. In particular, nutrient supply and irrigation, sowing, crop management and harvesting need to be carried out with precision techniques. These factors are all prerequisites for effective and healthy growing and processing. The aim was to use the yields of the four sweet maize hybrids grown on the largest area to examine their nutritional values and concentrations (mg kg⁻¹ dry matter) and to analyse their yield per hectare. Concentration is important for the consumer because K, P, Mg, Ca, Fe, Zn, and Na play an important role in metabolism, skin protection, and bone and tooth health. The new results obtained show that the amount of lutein and zeaxanthin per hectare is important for the processing industry, especially for use in food supplements. Their anti-inflammatory effects and their role in disease prevention (cardiovascular diseases, Age-Related Macular Degeneration (AMD)) have been demonstrated. Consumers choose sweet maize mainly on the basis of its palatability, which is why the sugar content of the hybrids was also studied. We assumed that the element concentration in the yield of new hybrids with higher yield per hectare does not decrease with increasing yield. The concentrations of zeaxanthin, β-cryptoxanthin and β-carotene appear in one principal component and they are in close positive correlation with each other. The lutein concentration was independent of the former three compounds. The independence of the lutein concentration means that it is not possible to estimate its amount based on the other three components. For yield per unit area, the correlation is one-dimensional. Yield determines the lutein, zeaxanthin, β-cryptoxanthin and β-carotene concentrations per hectare.