Field Scale Spatial Distribution And Genotypic Diversity Of Sclerotinia Sclerotiorum In Soybeans

Download or read book Field-Scale Spatial Distribution and Genotypic Diversity of Sclerotinia Sclerotiorum in Soybeans written by Tyler Mcfeaters and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: White mold (WM) in soybeans, caused by Sclerotinia sclerotium (S.s.), is the second most devastating disease of soybeans in the world. The disease causes an average of 2.5% yield loss in soybean production annually in Pennsylvania (PA), which equates to approximately $6,000,000. However, many growers still do not scout for white mold or have not been able to manage it well. My thesis aims to increase our understanding of the biology of S.s. at the field-scale, which will improve sampling strategies, crop loss estimations, and field experimental designs. Studying the genotypic diversity of S.s. populations at a field scale will help to improve management strategies like fungicide applications. The first objective of my thesis was to determine the spatial distribution of WM disease incidence and of S.s. sclerotia in the soil. My second objective was to determine if there was evidence of clonality in field-scale populations of S.s. Third, we determined if the state-scale Pennsylvania population of S.s. was clonal and compared that population to New York and Minas Gerais, Brazilian populations. Fourth, we validated the Sporecaster mobile application for use by soybean growers to forecast WM risk in the Northeast United States. Eight fields were selected for soil sampling of thirty-five quadrats. S.s. sclerotia were manually removed and isolated in the lab. DNA was extracted for 286 isolates and genotyped by fragment analysis. Microsatellite regions of the DNA were amplified at 10 loci and PCR products were analyzed by capillary electrophoresis. The same fields were also scouted to quantify the disease incidence in each quadrat. Lastly, soybean fields in PA and New York were monitored and scouted to conduct a validation of the Sporecaster mobile application for forecasting white mold risk. Across both years, the maximum number of sclerotia in a field was 3.3 sclerotia/kg soil and the maximum disease incidence for a field was 14% due to warmer and drier weather conditions at most locations. The spatial distribution of the pathogen at a field-scale was randomly distributed and only one field showed aggregation. Genotypic results indicated 83 multilocus genotypes were present across PA. Despite a high genotypic diversity, populations at a field scale were clonal and showed little evidence of outcrossing. The Sporecaster mobile application had a two-year average accuracy of 57-74% at predicting white mold disease incidence. Our increased knowledge of the pathogen and the use of the Sporecaster app will help to improve management recommendations and guide future research of white mold management tactics.