While the importance of soils in agriculture cannot be overlooked, plot level soil data remain scarce in the current data landscape. Large-scale household surveys efforts are increasing in low-income countries and assessing the accuracy, scalability and cost-effectiveness of available methods is crucial. Here, we firstly explore soil data requirements for a set of objectives that include identifying a soil constraint, improving recommendation domain studies and capturing soil metrics as

more »

... es, or as outcomes. We then expose the lessons learned from a methodological experiment in rural Ethiopia, where different approaches - farmer's self-elicitation and miniaturized spectrometers - are compared against laboratory benchmarks for a set of soil parameters: soil texture, soil pH and soil organic C. With the exception of soil particle sizes, we find that soil parameters captured through farmer's elicitation do not converge with objective metrics. Miniaturized spectrometers can provide reasonably accurate data for the identification of soil constraints - soil acidity, low organic C or sandy soils. Approximate quantitative predictions can also be delivered for soil pH (R2 = 0.72) and organic C (R2 = 0.60). The additional costs of plot sampling and analysis are in the range of $19-$23 per sample, with the additional percentage of plots with correct data equivalent to 10% for the identification of sandy soils, 75% for low organic C and 89% of acidic soils.