Field trials were carried out in the Sudan Savannah of Nigeria to assess the usefulness of CERES–maize crop model as a decision support tool for optimizing maize production through manipulation of plant dates. The calibration experiments comprised of 20 maize varieties planted during the dry and rainy seasons of 2014 and 2015 at Bayero University Kano and Audu Bako College of Agriculture Dambatta. The trials for model evaluation were conducted in 16 different farmer fields across the Sudan (Bunkure and Garun—Mallam) and Northern Guinea (Tudun-Wada and Lere) Savannas using two of the calibrated varieties under four different sowing dates. The model accurately predicted grain yield, harvest index, and biomass of both varieties with low RMSE-values (below 5% of mean), high d-index (above 0.8), and high r-square (above 0.9) for the calibration trials. The time series data (tops weight, stem and leaf dry weights) were also predicted with high accuracy (% RMSEn above 70%, d-index above 0.88). Similar results were also observed for the evaluation trials, where all variables were simulated with high accuracies. Estimation efficiencies (EF)-values above 0.8 were observed for all the evaluation parameters. Seasonal and sensitivity analyses on Typic Plinthiustalfs and Plinthic Kanhaplustults in the Sudan and Northern Guinea Savannas were conducted. Results showed that planting extra early maize varieties in late July and early maize in mid-June leads to production of highest grain yields in the Sudan Savanna. In the Northern Guinea Savanna planting extra-early maize in mid-July and early maize in late July produced the highest grain yields. Delaying planting in both Agro-ecologies until mid-August leads to lower yields. Delaying planting to mid-August led to grain yield reduction of 39.2% for extra early maize and 74.4% for early maize in the Sudan Savanna. In the Northern Guinea Savanna however, delaying planting to mid-August resulted in yield reduction of 66.9 and 94.3% for extra-early and early maize, respectively.

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Soil fertility decline coupled with the failure to conduct soil analysis by the farmers while generating fertilizer recommendations is among the factors that led to low yield especially in the Dry Savanna of Nigeria which is characterized by a dramatic increase in population. In this study, the performance of the soils at Bunkure Local Government Area of Kano State that was under irrigation farming was estimated using the NUTMON model. This was part of the strategies for boosting agricultural production and to have adequate and sustainable rural development. The experimental findings of this study showed obviously that most of the farms in the research area received a sufficient amount of fertilizer during the growing season despite the lower fertility status of the soils. Even with the continuous productivity within crop-based cropping unit, highly positive balance was obtained for N and slightly for P and K. The result as obtained from the data processing module of the NUTMON model revealed positive partial balances in kg/ha as 220.7, 26.3 and 47.8 for farms 1, 2, and 3 respectively, with the highest balance at farm 2 and the lowest at farm 3, despite the higher quantity of fertilizer (IN 1) that was applied to farm 1 of about 342 kg of Nitrogen. However, the N, P, and K were exported to the farm through the harvested grains and crop residues (OUT 1) and crop residues (OUT 2) considering partial balance. On the other hand, Phosphorus partial balance was also positive as a result revealed 55.0, 13.6 and 16.9kg/ha of Phosphorus for farms 1, 2 and 3 respectively. The K balances for farms 1, 2 and 3 in kg/ha as 68.8, 13.6 and 23.7 respectively which means farm 1 has the highest balance and farm 3 has the lowest. The result showed that the NUTMON model was a valuable tool for estimating nutrient balance and maintaining soil fertility in the study area. Reviewing fertilizer recommendation and its adherence by the farmers was recommended to have an appreciable yield in the study area.