Farmers in Africa have not been fully convinced to invest in fertilizer owing to the uncertainty of returns to investment. This is despite the fact that, more than two-thirds of people in Sub-Saharan Africa rely on agriculture for employment and many of them live on small farms and earn less than $1 per day and as such, the usage of fertilizer remains low and stagnant hence the yields in have  been  persistently  lower  than  other  parts   of   the world. Moreover, there has been a mixture of trend from high soil nutrient deficits and very low fertilizer use (3% of global fertilizer consumption; 7 kg/ha versus > 150 kg/ha in Asia) World Bank (2007). It is as a result of this the average yield of cereals and average intensity of modern inputs has stagnated in contrast to what has been observed in most developing regions, World Bank (2007). Most  often  when  they  apply  fertilizer,  the   smallholder farmers in Africa, do it to only a small part of their farm, since they have to make choices that maximize the benefit-to-cost ratio; where fertilizer applications is based on the crop-nutrient rate combinations that gives the greatest net returns for their investment (Kaizzi et al., 2012a). However, existing fertilizer recommendations do not allow farmers to maximize net returns on their investment. In addition to these issues a lack of information about correct application rates, timings, and the use of the correct products for different crops compounds the problems associated with blanket fertilizer recommendations (Rware et al., 2014).

Responding to these myriad of problems facing the farming community in Africa, several governments in SSA in partnership with international and regional bodies introduced inputs subsidy programs as immediate solutions with a view to fostering the use of contemporary inputs and increase agricultural productivity (Druilhe and Barreiro-Hurlé, 2012; Jayne and Rashid, 2013). However, Tavneet Suri (2007), found that on the realization that the fertilizer requires many other complementary inputs, or be risky, many countries have either withdrawn or scaled back fertilizer subsidies, in part because of fiscal constraints and other related barriers such as corruption and inefficiency in the administration of fertilizer subsidies.

The objective fertilizer recommendations in Africa are maximizing yield or profit per hectare. This only satisfies the need for farmers with good financial abilities to apply fertilizer across their entire crop land to maximize net returns per hectare (Kaizzi et al., 2015).  Most initiatives have focussed advocating for use of fertilizer to increase crop yields for the food security in Africa. However, with the recent clarion call for farmers to practice farming as a business, there is a paradigm shift on the real focus by farmers is maximising returns to fertilizer investment. The small holder farmers are more focused in using fertilizer for increased yields and get increased returns to investment given their little income for farming inputs (Rware et al., 2014). This paper therefore, addresses the process of developing a fertilizer use optimization approach with the extension workers using the optimization approach to advice farmers to optimize returns from fertilizer use.

To further come up with tailor made solutions to the plight of the small holder farmers’ inability to optimize productivity, a collaborative research project optimization of fertilizer recommendations in African (OFRA) 2013 to 2016 was designed jointly funded by AGRA, implemented by CABI and science support by the University of Nebraska Lincoln was designed. The project collaborated with the Africa Soil Health Consortium (ASHC) and Africa Soil Information Services (AfSIS) and National Research Organizations in Burkina Faso, Ethiopia, Ghana, Kenya, Malawi, Mali, Niger, Nigeria, Mozambique, Rwanda, Tanzania, Uganda and Zambia. The broad objective was to develop agro ecological zones (AEZs) specific and crop specific crop response functions  for  the  13  African countries and development of the fertilizer use optimization approach to address the plight of the smallholder farmers who have little to invest in fertilizer purchases and help them maximize returns to investment on fertilizer and be able to make better choices on which crops would give most returns if fertilizer is applied. This paper discusses the use of the optimization approach to maximize net returns for the farmer’s in the economic and agronomic context. The real problem why the approach is needed, and the relevant basic principles and describes how the approach was developed, the tools that support the approach, the requirements in the roll out of the approach and the sustainability considerations of the approach.

Development of the fertilizer use optimization approach in OFRA involved reviewing of past literature on crop nutrient, soil fertility, fertilizer recommendation and general crop response research. This was to identify gaps in relation to crop nutrient response functions and fertilizer recommendations and given an indication to where OFRA trials could be located. The gaps were filled through establishment of trials across 13 different countries in the SSA. The countries were picked because they fell in the list of the chore countries focused into by the AGRA (financing organization). UNL provided quality control of the data and the science aspects of the project. Further, the choice of crops in countries was informed by the position of this crops in the policy whether an important food crop or source of income for the country as well as for the small holder farmers. A standard protocol for establishing the trials and soil and foliar sampling was developed by the science leader in consultation with the country PIs from the 13 countries to guide the PIs in conducting their trials. Selection of trial sites was guided by use of the GIS tool and AEZs, areas considered as country food basket, areas where past research was done and the knowledge of the country teams in relation to the AEZs. AfSIS ensured that the comprehensive database is linked to geo-referenced soil, climate and remote sensing data. Spatial information from AfSIS enhanced accurate and efficient use of the agronomy field research data in the OFRA/SHC database.

Optimization approach

There is generally low use of fertilizer by the smallholder in Africa which largely affects their productivity levels. This is exacerbated by the fact that many of these farmers do not have the financial capacity to use enough fertilizer to maximize net returns per hectare. This is addition to the high fertilizer costs and low commodity prices, associated with costly input supply and inefficient marketing channels; the farmers profit potential is highly reduced. These smallholder farmers have more than one competing needs for the little cash they have  and the most pressing need often take priority especially when profitability of fertilizer use is not convincing. These farmers therefore need high net returns on their investments in fertilizer use if they have to embrace the fertilizer use technology in their farms (Kaizzi et al., 2013). Optimization approach is achieved by allocating fertilizer to an optimized choice of crop-nutrient-rate combinations where the farmer gets good returns to investment.

The profitability of different crop-nutrient combinations varies with the relative value of crops, the costs of fertilizer nutrients, the magnitude of each crop’s response to an applied nutrient, and the shape of the  response curve.  Nutrient  application  continues  in  a curvilinear trend until yield reaches a plateau. However, yields sometimes does decrease from a peak with high application rates  may be due to localized fertilizer salt effects, severe soil water depletion at a critical growth stage following a period of vigorous growth, increased disease, or more lodging (Kaizzi et al., 2015). A method of optimizing across these response functions was developed to determine the allocation of fertilizer investment to the crop-nutrient-rate combinations that maximize net returns on investment. Whereas large scale farmers have adequate finance may strive to maximize net returns per hectare resulting from fertilizer use, majority of the smallholder farmers have meagre opportunities for improvement and are largely vulnerable to agricultural shocks.

Reliable crop–nutrient response functions for an agro-ecological zone are essential for estimating likely profitability of crop–nutrient rate decisions. These functions can be determined using results from locally conducted research and extrapolation of results from other locations with similar growing conditions. Smallholder farms often produce four or more substantial crops and optimization of fertilizer use may involve 12 or more crop–nutrient combinations to determine the optimal rate for a farmer’s situation. A computer-based fertilizer optimization tool and its paper version are described (Charles and Kaizzi, 2015). In Figure 1, the crop–nutrient response is represented by an asymptotic function such as Y = a − bc^N, where Y is yield, a is yield at the plateau, b is the possible yield increase resulting from nutrient application, c is a curvature coefficient giving an abrupt response at low c values and having a value of 1 with a linear response, and N is the nutrient application rate (Kaizzi et al., 2012c). If cash is not a constraint, the amount of fertilizer that maximizes returns per area of land Economically Optimum Rates (EOR) can be applied. But if financially constrained, the amount of fertilizer that maximizes returns per shilling invested, which is less than the EOR, should be applied. If farm gate prices of produce decline or fertilizer prices increase, farmers have to apply less fertilizer to maintain the EORs. For example, in trials carried out in Uganda (Figure 1), the EOR for maize decreased from 44 to 33 kg N/ ha as C: P increased from 10 to 20. For cash constrained farmers, maximum benefits, that is, highest benefit-to-cost ratio (region indicated with oval) could be obtained by applying less than 30 kg N/ha (Jansen et al., 2013). 

The fertilizer optimization tool (FOT)

Fertilizer Optimization tool is the main tool in the optimization approach that was developed. It is available in three versions (computer excel, the paper and the mobile app version). In OFRA project the mobile app was developed and tested in Uganda in partnership with Grameen Foundation. Despite the fact that it was the most preferred and going by the mobile role in extension in the current world, the mobile app did not continue due to funding challenges. A total of 65 AEZs and crop specific FOTs were developed across 13 countries as shown in Table 1, in consideration of the pats research and field trials data. Important to note is that the crops covered by the project represent about 54% of important crops in Africa.

The optimization approach and supporting tools were developed for different AEZs in 13 countries in SSA. It is an innovation approach with the potential to change smallholder and resource poor farmers to be able to maximize their returns to investment in fertilizer. The approach will go a long way in creating a case of farmers’ ability to make profits through farming as well as the policy formulators in planning for fertilizer subsidy programmes. However, it is recommended that researchers to work closely with farmers to validate the approach comparing the predicted versus actual. There is also need to further explore options of integrating the optimization approach with the input supply chain and also bringing in agricultural loan institutions as the approach provides the evidence that investment in fertilizer is profitable and would help in building a case to advance farmers loans. In other words the approach acts as a mini business plan to convince the bank to advance the loan.

The authors have not declared any conflict of interests.