Soybean production is limited by poor soil fertility and unstable rainfall due to climate variability in the Nigeria savannas. There is a decline in the amount and duration of rainfall as one moves from the south to north of the savanna zones. The use of adapted soybean varieties and optimum sowing windows are avenues to increase productivity in the face of climate variability. Crop simulation models can be used as tools for the evaluation of alternative management options for a particular location, including fertilizer application rates, plant density, sowing dates and land use. In this study, we evaluated the performance of the Cropping System Model (CSM)-CROPGRO-Soybean to determine optimum sowing windows for three contrasting soybean varieties (TGX1835-10E, TGX1904-6F and TGX1951-3F) cultivated in the Nigeria savannas. The model was calibrated using data from ten field experiments conducted under optimal conditions at two sites (BUK and Dambatta) in Kano in the Sudan savanna (SS) agro-ecology over four growing seasons. Data for model evaluation were obtained from independent experiment for phosphorus (P) response trials conducted under rainfed conditions in two locations (Zaria and Doguwa) in the northern Guinea savanna (NGS) zone. The model calibration and evaluation results indicated good agreement between the simulated and observed values for the measured parameters. This suggests that the CROPGRO-Soybean model was able to accurately predict the performance of soybean in the Nigeria savannas. Results from long-term seasonal analysis showed significant differences among the agro-ecologies, sowing windows and the soybean varieties for grain yield. Higher yields are simulated among the soybean varieties in Zaria in the NGS than in Kano the SS and Jagiri in the southern Guinea savanna (SGS) agro-ecological zones. Sowing from June 1 to July 5 produced optimal yield of TGX1951-3F and TGX1835-10E beyond which yield declined in Kano. In Zaria and Jagiri the simulated results show that, sowing from June 1 to July 12 are appropriate for all the varieties. The variety TGX1951-3F performed better than TGX1904-6F and TGX1835-10E in all the agro-ecologies. The TGX1951-3F is, therefore, recommended for optimum grain yield in the savannas of northern Nigeria. However, the late maturing variety TGX1904-6F is not recommended for the SS due to the short growing season in this zone.

The soils of the Nigeria savannas are particularly low in nitrogen (N) and phosphorus (P) and negatively affects maize productivity. The main objective of the study was to evaluate the interactive effect of N and P fertilizers on maize growth, grain yield, nitrogen uptake and N use efficiency. Field experiments were conducted during the 2015 and 2016 cropping seasons at Iburu in southern Guinea and Zaria in northern Guinea savanna zones of Nigeria. The treatments consisted of three levels of nitrogen (0, 60, and 120 kg N ha^-1) and three levels of phosphorus (0, 13, and 26 kg P ha^-1). The experimental design consisted of three replications in a split-plot design, with N as the main plot and P as the subplot. Our results show that the response of maize to N depends on the application of P. Higher yields were obtained with the combined application of 120 kg N ha^-1 and 26 kg P ha^-1 in both locations. With no P applied, plant N uptake (PNU) was greater at N rate of 120 kg ha^-1 at Iburu while in Zaria, it increases with increase in N from 0 to 60 kg ha^-1. When P was applied at 13 kg ha^-1, the PNU increased by 52 and 66% at Iburu while in Zaria the increases were 51 and 57% each with N application of 60 and 120 kg ha^-1, respectively, compared with zero N rate. The values for N recovery efficiency (NRE) and agronomic efficiency (AE) were lower for N rate of 120 than for 60 kg ha^-1 irrespective of P application rate at both locations. The N utilization efficiency (NUTE) however was higher at 120 N kg ha^-1 under 26 kg P ha^-1across locations. It can be concluded from these results that in low fertile soils environments such as the Nigeria savannas, N fertilizer should be applied along with P fertilizer for optimum growth, grain yield and nitrogen use efficiency of maize.

Increasing delays in the onset of the rainy season and extended dry spells in the Nigerian savannas are complicating the determination of optimal planting dates for rain-fed crops, which increases risks for farmers. This study evaluated the impact of planting dates on soybean [Glycine max (L.) Merr.] performance to identify optimal planting dates for different soybean varieties in two agroecological zones (AEZs) of Nigeria. The study involved six planting dates (15 June, 22 June, 29 June, 6 July, 13 July, and 20 July) and three soybean varieties (TGX-1835-10E, TGX-1951-3F, TGX-1904-6F). Results showed significant differences in growth and yield parameters based on location, variety, and planting date. In the Sudan savanna (SS), AEZ at BUK-Kano, optimal yields (>1500 kg ha⁻¹) were achieved when planting TGX-1835-10E and TGX-1951-3F from 15 to 29 June and TGX-1904-6F on 15 June. Planting beyond 29 June reduces yields by 12–55% for TGX-1835-10E and 27–63% for TGX-1951-3F. For TGX-1904-6F, planting after 15 June reduces yields by 27–90%. In the Northern Guinea savanna (NGS) AEZ at Zaria, optimal yields (>1500 kg ha⁻¹) were obtained when planting TGX-1835-10E and TGX-1951-3F from 15 June to 6 July, and TGX-1904-6F between 15 to 29 June. Delaying planting beyond these dates significantly reduced yields by 18–31% for TGX-1835-10E and 12–20% for TGX-1951-3F and 10–41% for TGX-1904-6F.

Declining soil fertility particularly phosphorus deficiency, low organic carbon, moisture stress and high cost of input are factors limiting soybean yield in the Nigeria savanna. Supplementary irrigation, nutrient application and inoculation with Bradyrhizobium could increase the grain yield of soybean. We evaluated the effects of Rhizobia inoculant, phosphorus fertilization, manure, and supplementary irrigation on the nodulation and productivity of a tropical soybean variety in two locations in northern Nigeria in the 2017 and 2018 cropping seasons. The treatments consisted of five input bundles: Supplementary irrigation +17.5 kg P ha⁻¹ + 4 t ha⁻¹ poultry manure + nodumax inoculant (S + P + M + I); 17.5 kg P ha⁻¹ + 4 t ha⁻¹ poultry manure + nodumax inoculant (P + M + I); 17.5 kg P ha⁻¹ + nodumax inoculant (P + I); 17.5 kg PP ha⁻¹ (P); and nodumax inoculant (I). Economic analysis was done to determine the benefit-cost ratio (BCR) for each input bundle. In Kano, the input bundle S + P + M + I produced mean number of nodules that were 38, 102, 200 and 352% higher than that of input bundles P + M + I, P + I, P and I, respectively. At Lere, the application of input bundle S + P + M + I increased mean number of nodules by 33, 81, 93 and 182% over that of input bundles P + M + I, P + I, P and I, respectively. Mean grain yield in Kano was greater for input bundle S + P + M + I over P + M + I, P + I, P and I bundles by 31, 50, 64 and 223%, respectively. In Lere, grain yield for input bundle S + P + M + I was higher than that of input bundles P + M + I, P + I, P and I only, by 27, 47, 41 and 184% respectively. The input bundle P + M + I produced the highest BCR (1.4) in Kano and application only of P produced the highest BCR (1.3) in Lere. Supplementary irrigation was not found to be profitable due to the high cost of supplementary irrigation.The application of P with or without manure/inoculant is recommeded for profitable soybean production in the savannas of Nigeria.

A well-calibrated and evaluated GROPGRO module of the Decision Support System for Agro-technological Transfer (DSSAT) was used to simulate productivity of soybean in northern Nigeria under climate change. Both historical (1990–2019) and projected climate scenarios from 5 general circulation models (GCMs) under two representative concentration pathways (RCP 4.5 and RCP 8.5) in the mid-century (2040–2069) and end of the century (2070–2099) periods were used. Depending on climate scenario, the minimum temperature is expected to rise by 1.7–4.4^oC at Kano in the Sudan savanna (SS) agroecological zone (AEZ) and 1.4–4.0^oC at Zaria in the northern Guinea savanna (NGS) AEZ, while maximum temperatures are projected to increase by 1.7–4.1^oC in the SS and 1.3–3.6^oC in the NGS. Seasonal average rainfall will increase by 4.8–14.5% in the SS and decrease by 2.6–3.8% in the NGS, relative to the baseline climate. The model predicted delaying trends for days to flowering and maturity for both varieties in all climate scenarios in the two AEZs. Despite the delay in flowering and increase in crop cycle length, climate change will result in grain yield reduction in most of the future scenarios. Across location, variety and time slice, the grain yield will decline by between 8.4 and 23.6% under RCP4.5 scenario, with much higher decline by between 28.7 and 51.4% under RCP 8.5 scenario. However, using the early maturing variety can reduce the adverse effects of climate change on grain yield. On average, the yield of the early-maturing TGX1835-10E is predicted to be 15.2% higher under RCP4.5 scenario and up to 21.7% under RCP8.5 than that of the medium-maturing TGX1951-3F for both centuries in the SS AEZ. In the NGS, the average yield of TGX1835-10E is predicted to be 9.0% and 7.5% higher than that of TGX1951-3F under RCP4.5 and RCP8.5 scenarios, respectively. Using early-maturing soybean varieties is a key management strategy to boost the resilience of soybean production in Nigeria’s savannas under climate change conditions.