Successful variable-rate applications of agricultural inputs, such as lime, rely on quality of input data. Systematic soil sampling is the most common method used for creating variable rate prescription maps. Low density of economically feasible such sampling has been the main cause of poor accuracy of lime prescription maps. To increase sampling density, on-the-go sensing technology was developed to map soil pH and other relevant attributes. In this study, several fields in eastern Nebraska were mapped using both automated on-the-go mapping and systematic grid sampling approaches. Ten random validation locations in each field were used to compare prescribed liming rate with the lime requirement that is based on the traditional buffer pH test. The data collected was used to compare four of the most popular soil acidity management scenarios: 1) no liming, 2) uniform rate liming, 3) variable rate liming based on a systematic grid sampling, and 4) variable rate liming based on sensor-based mapping.