Simulating the Response of Drought–Tolerant Maize Varieties to Nitrogen Application in Contrasting Environments in the Nigeria Savannas Using the APSIM Model

Abstract

This paper assessed the application of the Agricultural Production Systems sIMulator (APSIM)–maize module as a decision support tool for optimizing nitrogen application to determine yield and net return of maize production under current agricultural practices in the Nigeria savannas. The model was calibrated for two maize varieties using data from field experiments conducted under optimum conditions in three locations during the 2017 and 2018 cropping seasons. The model was evaluated using an independent dataset from an experiment conducted under different nitrogen (N) levels in two locations within Southern and Northern Guinea savannas. The results show that model accurately predicted days to 50% anthesis and physiological maturity, leaf area index (LAI), grain yield and total dry matter (TDM) of both varieties with low RMSE and RMSEn (%) values within the range of acceptable statistics indices. Based on 31-year seasonal simulation, optimum mean grain yield of 3941 kg ha−1 for Abuja, and 4549 for Kano was simulated at N rate of 120 kg ha–1 for the early maturing variety 2009EVDT. Meanwhile in Zaria, optimum mean yield of 4173 kg ha–1 was simulated at N rate of 90 kg ha−1. For the intermediate maturing variety, IWDC2SYNF2 mean optimum yields of 5152, 5462, and 4849 kg ha−1, were simulated at N application of 120 kg ha−1 for all the locations. The probability of exceeding attainable mean grain yield of 3000 and 4000 kg ha−1 for 2009EVDT and IWDC2SYNF2, respectively would be expected in 95% of the years with application of 90 kg N ha−1 across the three sites. Following the profitability scenarios analysis, the realistic net incomes of US$ 536 ha–1 for Abuja, and US$ 657 ha−1 for Zaria were estimated at N rate of 90 kg ha−1 and at Kano site, realistic net income of US$ 720 ha–1was estimated at N rate of 120 kg ha−1 for 2009EVDT.For IWDC2SYNF2, realistic net incomes of US$ 870, 974, and 818 ha−1 were estimated at N application of 120 kg ha−1 for Abuja, Zaria, and Kano respectively. The result of this study suggests that 90 kg N ha−1 can be recommended for 2009EVDT and 120 kg N ha–1 for IWDC2SYNF2 in Abuja and Zaria while in Kano, 120 kg N ha−1 should be applied to both varieties to attain optimum yield and profit.

Simulating potential yield of rainfed soybean in northeast Nigeria

“…Contrary to earlier findings elsewhere in the Nigeria savannas, ( Bebeley et al, 2022 for soybean, Tofa et al, 2020 and Beah et al, 2020 for maize), higher yields were simulated for most of the locations in the Sudan savannas than for the Guinea savannas across the two States This is unexpected because higher crop yields are usually obtained in the Guinea savannas than in the Sudan savannas because of higher rainfall and longer growing season in the Guinea savannas than elsewhere in the savannas. Average rainfall in both zones was however, more than 1000 mm per year, suggesting that rainfall limitation may not be the most important determinant of soybean yield in the two zones.…”

Evaluation and application of the CROPGRO-soybean model for determining optimum sowing windows of soybean in the Nigeria savannas

“…Determination of optimum sowing dates for crops involves several experiments covering large areas and repeated over long period of time to capture the seasonal variability in the onset, amount of rainfall and distribution 15 . Also, data for one location is not useful for another location because of variation in rainfall, temperature and soil conditions 16 . Several related factors such as location, year-to-year climate conditions, and maturity group selection make the determining of the optimum sowing date for soybeans a complex decision 17 , 18 .…”

In silico evidence for the utility of parsimonious root phenotypes for improved vegetative growth and carbon sequestration under drought

“…The soils in these sites have been identified as Mollisol – Udoll (Iowa), Alfisol – Ustalf (Zaria), and Andosol – Vitrand (Jalisco). Soil profile data, including soil texture, soil bulk density, and relative water content at –33 and –1500kPa, from the ISRIC soil hub database ( ) is used for Iowa and Jalisco, and for Zaria a published dataset is used ( Beah et al., 2020 ). These soil profile datasets are implemented to estimate the corresponding van Genuchten parameters using the online freeware Rosetta3 ( ).…”