Maximising net returns to fertiliser use by financially constrained smallholder farmers in uganda

Abstract

Financial constraints usually limit fertiliser use by smallholder farmers and it is important that they maximise net returns on their investment. Fifteen crop-nutrient response functions, including six crops, were derived from results of 84 trials conducted in Uganda. The benefit:cost ratio (BC) for typical fertiliser use costs and grain prices in Uganda was greatest for a small amount of N applied to dry bean (Phaseolus vulgaris L.) followed by N applied to rice (Oryza spp.). Next most profitable was P applied to groundnut (Arachis hypogaea L.) and soybean (Glycine max L.), followed by N applied to maize (Zea mays L.)and grain sorghum (Sorghum bicolor L.), with lower or no BC for the remaining nine response functions. The Fertiliser Optimisation Tool was developed for Uganda to maximise net returns to fertiliser use for finance-limited crop management in consideration of the area of each crop to be planted, fertiliser costs, expected grain value, and money available for investment. The tool optimises across the 15 response functions to provide the crop-nutrient-rate combinations expected to maximise net returns. The tool does not account for soil test information, expected yield, and previous crop as these did not account for significant variation in yield. In an example with 1 ha each of the above six crops and US$135 available for fertiliser use, the optimised BC was 17.4 compared 4.5 and 6.2 for N applied to maize and rice at rates to maximise net returns ha-1. The solution commonly determines low or zero rates for nutrients applied to some crop but the greatly improved returns on investment create the potential for gradually increasing future investments in fertiliser. This approach to fertiliser use of maximising net returns on investment has potential to gradually enable much increased fertiliser use because of the relatively high returns on investment compared to traditional fertiliser use recommendations.