Optimizing fertilizer use by providing soil quality information: experimental evidence from Madagascar

Abstract Background Improving food security in sub-Saharan Africa (SSA) requires increasing agricultural productivity. The increased and effective use of chemical fertilizers is widely recognized as one of the key strategies for achieving this goal. However, many smallholder farmers in SSA still grow crops without using fertilizer, and even when they do use fertilizer, the amount applied is often less than the recommended level. In addition to various constraints related to input markets and farmers’ socioeconomic characteristics, uncertainty about crop yield response is known to discourage fertilizer use. The purpose of this study was to investigate how site-specific information on soil characteristics can help farmers optimize their fertilizer application decisions by reducing uncertainty in yield response. Our unique approach uses simple binary information about the expected effectiveness of nitrogen fertilizer based on a single soil parameter. Methodology The simple binary information was generated for a focal rice plot of each 70 household. Based on the evaluation of oxalate-extractable phosphorus content in the soil composites collected from each of these plots, each plot was categorized into either high or low in terms of the expected effectiveness of nitrogen application. A randomized controlled trial was conducted to estimate the impact of providing this simple binary information primarily on nitrogen application rate and, consequently, on rice yield and income at plot-level and household-level. Results The results showed that first, compared to those in the target plots of the control households, the nitrogen application rate was greater in the target plots of the treatment households who were informed of the high expected effectiveness. Second, information that the expected effectiveness was high increased the amount of nitrogen fertilizer in the target plot compared to that in other plots with no information about expected effectiveness within a household. Third, this change in fertilizer allocation led to higher rice yields and higher rice incomes at the household level. Conclusions These results highlight how the binary information about the expected effectiveness with a single soil parameter can improve fertilizer allocation among rice plots and its use efficiency to increase rice productivity and income.