The uncertainties in agricultural production necessitate detailed knowledge of the effi- ciency of production within each farm to maintain sustainability. To accomplish a more ecologically based agriculture with the goal of intensification by maximizing production and profit as well as minimizing environmental impact, we hypothesize that a site-spe- cific knowledge base can be efficiently achieved through modern precision agriculture (PA) technologies at the field scale. The two goals of this study were to quantify the spa- tiotemporal variation of crop responses and the variables driving crop production, crop quality, and field-scale farmer net-return. We conducted on-farm experiments (OFE) on several fields for three years where we varied nitrogen fertilizer rate as a management input causing changes in crop response. Using a Monte Carlo approach, we assessed the probability that crop responses varied across fields and between years. To deter- mine the drivers of crop production, quality, and net-return we performed sensitivity analyses on each field to assess spatial variation in variables with the most influence on crop responses and farmer profits. Our analysis provided evidence that winter wheat yield and protein content in response to variable nitrogen fertilizer rates are variable across time and space. Elevation as a covariate to nitrogen fertilizer rate was the pri- mary driver of yields and protein across most fields yet varied between fields and across years in fields. The drivers of net-return varied between fields and across years prima- rily between yield and protein. However, in some cases the most influential factor was the base price received, controlled by the grain elevators that growers sell to, indicating that in some fields and years, farmer’s net-returns are dictated by variables outside of a farmers control or ability to manage. These results provide basic evidence justifying the use of OFE for farm management and that management needs to be specific to each field and point in time, with management prescriptions being made specifically for a field based on information gathered specifically from that field. OFE will enable farmers to identify these drivers and understand how their inputs influence yield and protein within fields. Using information provided by OFE with decision support systems can en- able farmers to make informed management decisions that maximize their profits and increase the efficiency of chemical inputs, such as nitrogen fertilizer. 363 DOI : 10.17180/NP12-JB28