The Strawberry Advisory System (SAS) was developed to improve temporal precision of fungicide application. Based on Net Present Value (NPV), it outperforms the traditional fungicide application method given weather and market conditions typical for Florida (Vorotnikova et al., 2014). This study uses stochastic dominance and efficiency with respect to a function (SDRF and SERF) criterion to rank ten-year NPV for SAS-based and traditional fungicide application methods, given a range of farmers’ risk preferences. SERF is a valuable tool because it incorporates a utility function and a range of decision-maker risk preferences. Data from two production experiments were used: 1) research trials at the University of Florida’s farm, and 2) field experiments at seven commercial strawberry farms, located in different Florida counties. Each experiment included two diseases, anthracnose and Botrytis, and two cultivars, more- and less-disease resistant. The results based on research trials show that for both diseases and cultivars, the SAS-based method is the most preferred given any farmers’ risk aversion levels. However, the results based on results from commercial farms show that while the SAS-based method ranks higher for the more-resistant cultivar, the traditional fungicide application method is preferred for the less-resistant cultivar, for any farmers’ risk preference.