A conceptual model is developed to measure the value of information from in-field soil sensing technologies as compared with grid and other soil sampling methods. Soil sensing offers greater spatial accuracy and the potential to apply inputs such as nitrogen fertilizer immediately, avoiding changes in nutrient status that occur with delays between soil sampling and fertilizer application. By contrast, soil sampling offers greater measurement accuracy, because it does not rely on proxy variables such as electrical conductivity to infer nutrient status. The average profitability and relative riskiness of soil sensing versus sampling depend upon 1) the trade-off between, on the one hand, the spatial and temporal accuracy of sensing and, on the other hand, the measurement accuracy of sampling, 2) the cost of data collection, and 3) input and product prices. Similar trade-offs govern the relative riskiness of sensing versus sampling.