A Comprehensive Fungicide Application Decision Support System for Control of White Mold

Sclerotinia sclerotiorum, or white mold, is a resilient and devastating disease that has emerged as a significant threat to many of the broadleaf crops of the United States. Sclerotinia is known to infect about 408 species of plants. It has been estimated to cause hundreds of millions of dollars in losses annually to the United States' dry edible bean, sunflower, canola, and soybean crops. The disease has been especially problematic in the Upper Midwest, where the proliferation of susceptible crops has led to fewer economically viable resistant crop rotation options. The development and spread of white mold is highly dependent upon the weather. The prevailing weather conditions largely determine the reproductive nature of the fungus as well as its ability to infect plants. Available fungicides offer many susceptible crops protection from the disease. However, dwindling agricultural profit margins and the related growth in farm size make it increasingly impractical for producers to routinely scout and monitor all of their fields for impending disease problems. This is especially true in the regions hardest hit by the disease, where it is no longer uncommon for the various fields of a given farm to spread across areas of well over 100 square miles. Further, the considerable expense associated with applying these fungicides often prohibits preemptive action against the disease since there are currently no reliable decision support systems available to aid producers in determining the probability of disease development in their fields. The proposed program is directed at utilizing advanced site-specific meteorological analysis techniques and the ever-growing stream of weather observations (both in-situ and remotely-sensed) to support a fungicide application decision support system (FADSS). Specifically, funds from this Phase II award will be used to develop a FADSS for control of white mold in dry edible beans, although it will be easily extensible to other susceptible crops upon collection of datasets for those crops. This system will be designed to aid producers in evaluating the risk of white mold development and the potential for receiving a return on a fungicide investment in each field. The FADSS will integrate crop disease, leaf wetness, and soil models, a wide range of in-situ and remotely-sensed weather observations, sophisticated weather analysis and forecast systems, an economical tool for assessment of white mold spore concentrations, and internet and computer telephony technology into a comprehensive FADSS. The system will require only very infrequent interaction with the producer, and will use both the internet and computer telephony to notify producers of impending problems. The automated nature of the FADSS and its application of `push' technology will help it to succeed where others have failed by avoiding the pitfall of being a drain on the producer's time. This approach to minimizing disease losses stands to have a significant positive impact in a much shorter time than efforts to breed disease resistance to the disease.