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.

Sustainable crop production in the Nigerian Sudan Savanna biome requires a good understanding of the fertility status of the soil in order to impose appropriate nutrient management strategies. Field surveys were conducted to assess the fertility status of selected soils from Shanono and Bunkure Local Government Areas (LGAs) of Kano State in the Northern Nigerian Sudan Savanna. All the surveyed fields had soil organic C, total N and ECEC within very low and low fertility classes. Very low and low available P was also found in the majority of fields with only 25.0 and 8.7% of the fields falling in the moderate P fertility range in Shanono and Bunkure LGA respectively. About 75.0% of fields in Shanono LGA and 39.1% in Bunkure LGA fell within the low exchangeable K class, with the rest of the fields having moderate level. Despite moderate to high content of exchangeable Ca and Mg in most of the fields, 4.3-8.7% of the fields had depleted status of the two basic cations. Micronutrients (Zn, Cu, Mn and Fe) levels in all the fields were in the moderate and high classes, except the subsurface soil of Shanono LGA where 4.2% of the fields had low Cu contents. Correlation analysis between northerly latitude and soil properties showed a northward increase in sand, pH and Zn levels and a decrease in silt and available Fe levels. The low status of Ca, Mg and Cu in some of the fields indicates the insufficiency of the current fertilizer recommendations which focus mainly on primary macronutrients (N, P and K). Therefore, apart from recommending all strategies that will enhance and stabilize organic matter, current fertilizer recommendations need to be reviewed and should contain other nutrients in addition to primary macronutrients.

Site-specific nutrient management can reduce soil degradation and crop production risks related to undesirable timing, amount, and type of fertilizer application. This study was conducted to understand the spatial variability of soil properties and delineate spatially homogenous nutrient management zones (MZs) in the maize belt region of Nigeria. Soil samples (n = 3387) were collected across the area using multistage and random sampling techniques, and samples were analyzed for pH, soil organic carbon (SOC), macronutrients (N, P, K, S, Ca and Mg), micronutrients (S, B, Zn, Mn and Fe) content, and effective cation exchange capacity (ECEC). Spatial distribution and variability of these parameters were assessed using geostatistics and ordinary kriging, while principal component analysis (PCA) and multivariate K-means cluster analysis were used to delineate nutrient management zones. Results show that spatial variation of macronutrients (total N, available P, and K) was largely influenced by intrinsic factors, while that of S, Ca, ECEC, and most micronutrients was influenced by both intrinsic and extrinsic factors with moderate to high spatial variability. Four distinct management zones, namely, MZ1, MZ2, MZ3, and MZ4, were identified and delineated in the area. MZ1 and MZ4 have the highest contents of most soil fertility indicators. MZ4 has a higher content of available P, Zn, and pH than MZ1. MZ2 and MZ3, which constitute the larger part of the area, have smaller contents of the soil fertility indicators. The delineated MZs offer a more feasible option for developing and implementing site-specific nutrient management in the maize belt region of Nigeria.

19Establishing balanced nutrient requirements for maize (Zea mays L.) in the Northern Nigerian 20 Savanna is paramount to develop site-specific fertilizer recommendations to increase maize 21 yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model 22 QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced 23 nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the 24 Northern Nigerian Savanna. Data from on-farm nutrient omission trials conducted in 2015 and 25 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. 26 Northern Guinea Savanna "NGS" and Sudan Savanna "SS") were used to parameterize and 27 validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and 28 soil properties were not well described with the QUEFTS default equations and consequently 29 new and better fitting equations were derived. The average fertilizer recovery fractions of N, P 30 and K in the NGS were generally comparable with the QUEFTS default values, but lower 31 recovery fractions of these nutrients were observed in the SS. The parameters of maximum 32 accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained 33 were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone 34 and 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone. The model 35 predicted a linear relationship between grain yield and above-ground nutrient uptake until yield 36reached about 50 to 60% of the yield potential. When the yield target reached 60% of the 37 potential yield (i.e. 6.0 tonnes per hectare), the model showed above-ground nutrient uptake of 38 2 19.4, 3.3 and 23.0 kg N, P, and K, respectively, per one tonne of maize grain in the NGS, and 39 17.3, 5.3 and 26.2 kg N, P and K, respectively, per one tonne of maize grain in the SS. These 40 results suggest an average NPK ratio in the plant dry matter of about 5.9:1:7.0 for maize in the 41 NGS and 3.3:1:4.9 for maize in the SS. There was a close agreement between observed and 42 parameterized QUEFTS predicted yields across the two agro-ecological zones (R 2 = 0.70 for 43 the NGS and 0.86 for the SS). We concluded that the QUEFTS model can be used for balanced 44 nutrient requirement estimations and development of site-specific fertilizer recommendations 45 for maize intensification in the Northern Nigerian Savanna.46