Abstract
Fertilizer microdosing is being widely promoted across sub-Saharan Africa, yet all recommendations regarding this technology are derived from short-term studies. Such studies are insufficient to properly assess the production risk caused by climatic variability. To address this issue while avoiding costly long-term experiments, a common and well accepted strategy is to combine results from short-term experiments with validated dynamic crop models. However, there have been few documented attempts so far to model fertilizer microdosing under sub-humid tropical conditions. The objective was therefore to evaluate the potential of the DSSAT model for simulating maize response to fertilizer microdosing, and to use the validated model to assess the effects of inter-annual rainfall variability on maize productivity and economic risk. The model was calibrated and validated against data from a 2-year on-station experiment (2014 and 2015) with 2 levels of hill-placed manure and five mineral fertilization options including broadcast and fertilizer microdosing. Model simulations were in good agreement with the observed grain and biomass yields for conventional broadcast fertilization, with relative RMSE and d-values of 12% and 0.96 for grain and 8% and 0.97 for biomass, respectively. For fertilizer microdosing, the N stress coefficient needed to be adjusted to avoid occurrence of large N stresses during simulation. After optimization, the model adequately reproduced grain yields for fertilizer microdosing, with relative RMSE of 10%. Considering the long-term scenario analysis, the use of the validated model showed that the application of 2 g of NPK15-15-15 fertilizer + 1 g urea per hill (equivalent to 23.8 kg N ha-1, 4.1 kg P ha-1 and 7.8 kg K ha-1) improved both the minimum guaranteed yield and the long-term average without increasing inter-annual variability and the economic risk compared to unfertilized plots. Even though combining microdosing with manure (1-3 t ha-1) was economically slightly riskier than microdosing alone, this risk remained low since a value-cost ratio of 2 could be achieved in almost 100% of the years. Furthermore, combined application consistently reduced the inter-annual yield variability.
Highlights
In Sub-Saharan Africa (SSA), low crop yields are a persistent concern because of their impact on food security, chronic poverty, and hunger (Morris et al, 2007; Vanlauwe et al, 2015)
We examined the ability of the DSSAT CERESMaize model to accurately simulate maize response to fertilizer microdosing, and whether the validated model can be used to assess the effects of seasonal climate variability on maize productivity and economic risk
The model could adequately reproduce grain yields for fertilizer microdosing, indicating that it could be used as decision support tools through long-term scenario analysis
Summary
In Sub-Saharan Africa (SSA), low crop yields are a persistent concern because of their impact on food security, chronic poverty, and hunger (Morris et al, 2007; Vanlauwe et al, 2015). One critical risk component is related to the as yet unpredictable temporal distribution of rainfall over the course of a season This uncertainty regarding the temporal rainfall distribution drives much of the behavior of smallholder farmers (Akponikpè et al, 2011; Marteau et al, 2011; Comoé and Siegrist, 2015; Guan et al, 2017), since partial or total crop failure due to drought stress can strongly affect the profitability of crop intensification technologies. It is crucial to consider this long-term variability when evaluating new technologies This is especially true for fertilizer management practices given that rainfed crop response to fertilizer inputs is strongly dependent on the amount and distribution of rainfall (Akponikpè et al, 2010; MacCarthy et al, 2010; Folberth et al, 2013). Microdosing is generally considered as a stopgap option for subsistence farmers for whom achieving some minimal yield every year to cover household food requirements is more important than maximizing yields in favorable years
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