# **1. Introduction**

Agriculture is central to rural livelihoods in Sub-Saharan Africa, where smallholder family farming contributes up to 69 percent of rural household incomes (Davis et al., 2017), with direct effects on household consumption and nutrition outcomes (Azzarri et al. 2015; Dillon et al., 2017; Kirk et al., 2018; Slavchevska et al., 2015). In view of the importance of agriculture for farming households and the evidence regarding the disproportionate reduction in poverty associated with growth in the agricultural sector vis-à-vis other sectors, increasing agricultural productivity has been a long-standing goal of African governments. Nevertheless, the observed yields for staple crops, such as cereals, remain significantly lower than potential yields, especially in rain-fed areas (Lobell et al., 2009). Research has also asserted that (i) the large dispersion in agricultural productivity among African smallholders is driven in part by unobserved heterogeneity in land quality (Gollin and Udry, 2021), and (ii) poor crop yields in the region are driven in part by depletion of soil nutrients, which, besides its direct impact on crop yields, also adversely affects the effectiveness of non-land inputs (Berazneva et al., 2018).

The micro-level relationships between crop yields and a range of both climatic and non-climatic factors have been studied extensively in African smallholder farming systems, utilizing socioeconomic and agricultural survey data which, if georeferenced, have also been integrated with third-party geospatial data sources.<sup>2</sup> Despite the rich evidence base on the drivers of/constraints to crop yields, the research on the impact of soil fertility on farm- and plot-level agricultural productivity outcomes, including crop yields, has, however, been relatively limited.

The knowledge gaps have been mainly due to (i) systematic measurement errors in farmers’ subjective soil quality assessments (Berazneva et al., 2018; Carletto et al., 2017); (ii) lack of integration of objective sampling and testing of soils as part of household and farm surveys that are critical for understanding the drivers of agricultural production and productivity at the microlevel (Gourlay et al., 2017); and (iii) the mismatch between the scale of African smallholder farming and the spatial resolution of publicly-available, continent-wide geospatial data on soil properties - most notably generated with 250-meter spatial resolution as part of the Africa Soil Information Service (AFSIS) initiative (Hengl et al., 2015).

A related strand of research includes the geospatial assessments of the suitability of growing conditions for specific crops and these assessments have been made available also at the level of relatively aggregated geographic areas, leveraging primarily geospatial data that may or may not be complemented with ground data on soil properties (Abd-Elmabod et al., 2019; Ahamed et al.,

> 2 See for instance the research on low levels of agricultural input use (Sheahan and Barrett, 2017), intra- and interhousehold gender differences in levels of and returns to agricultural inputs (Udry, 1996; Kilic et al., 2015; Aguilar et al. 2015; Oseni et al. 2015; Slavchevska, 2015), imperfections in land and labor markets (Palacios-Lopez and Lopez, 2015; Deininger et al., 2017; Dillon and Barrett, 2017), and impacts of extreme weather events on agriculture (McCarthy et al., 2021; Michler et al., 2019; Wineman et al., 2017).

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