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 twenty maize varieties planted during the dry and rainy seasons of 2014 and 2015 at Bayero University Kano and Audu Bako College of Agriculture Danbatta. 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 4 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.

Diagnostic on-farm nutrient omission trials were conducted over two cropping seasons (2015 and 2016) to assess soil nutrients related constraints to maize yield in the northern Nigerian savanna agro-ecological zone and to quantify their variability. Two sets of trials were conducted side by side, one with an open pollinated maize variety (OPV) and the other one with a hybrid maize variety and each set had six equal treatments laid out in 198 farmers’ fields. The treatments comprised (i) a control, (ii) a PK (‘−N,’ without N), (iii) an NK (‘−P,’ without P), (iv) an NP (‘−K,’ without K), (v) an NPK and (vi) an NPK + S + Ca + Mg + Zn + B (‘+SMM,’ NPK plus secondary macro- and micro-nutrients). Moderate to a large variability in most soil characteristics was observed in the studied fields. Consequently, cluster analysis revealed three distinct yield-nutrient response classes common for the two types of maize varieties. These define classes were fields that have (i) no-response to any nutrient, (ii) a large response to N and P and (iii) a large response to N alone. Although overall yield performance of OPV and hybrid varieties was similar, a distinct fourth class was identified for the hybrid variety, (iv) fields with a large response to N and secondary macro- and micro-nutrients. The results indicate that the large variability in soil nutrients related constraints need to be accounted for to optimize maize yield in the northern Nigerian savanna. The development of field- and area-specific fertilizer recommendations is highly needed, using simple decision support tools that consider variable soil fertility conditions and yield responses as obtained from this study.

• New and better fitting QUEFTS’ prediction equations for indigenous soil N, P, and K supply were developed for the Northern Nigerian Savanna. • A good correlation was observed between the observed and parameterized QUFETS predicted maize grain yield. • The QUEFTS model predicted a balanced N, P, K uptake to linearly increase with grain yield until 50-60% of the potential yield. • The QUEFTS model is a suitable tool for site-specific nutrient recommendations in maize in the Northern Nigerian Savanna.