Soil health is fundamentally influenced by soil organic matter (SOM). It is traditionally measured through lab analysis of soil samples, which can be time intensive and costly. Previous work has shown that SOM is a suitable proxy for soil health and can be measured in real-time by permittivity sensors. This experiment is to determine the correlation between soil permittivity and SOM in annual tilled soy/corn fields and perennial zero-tilled turfgrass fields to aid in soil health evaluation. Composite soil samples were taken at five randomized locations within each field and then sent to the UMN Soil Testing Laboratory for SOM analysis. To measure permittivity, an Acclima TDR 315H soil sensor was inserted into three sub locations within a square meter of the randomized locations. Correlation analysis showed that SOM was positively correlated (r = 0.88) with permittivity in all three fields. An ANOVA showed that SOM and permittivity similarly differentiated between different crop types and tillage (p<0.001). The relationship between SOM and permittivity is significant; therefore, these results suggest that soil health can be estimated by soil permittivity sensing in medium textured soils. Further work should evaluate the on-farm usefulness of this approach for soil health management.

White mold (Sclerotinia sclerotiorium) is a devastating plant pathogen causing substantial yield losses across hundreds of plant species. Despite initial success of fungicides, S. sclerotiorium has been shown to develop resistance when the chemicals are applied in small doses for prolonged periods of time. This study investigates the efficacy of biocontrol agents in managing S. sclerotiorum Stem Rot (SSR) in canola, an under-researched crop in this context. Various biocontrol agents including Coniothyrium Minitans (Contans), Bacillus amyloliquefaciens (Double Nickle LC), Bacillus subtilis (Serenade OPTI), and Endura (Boscalid) were applied at different bloom stages in randomized plots of a canola SSR-infected field. Treatments involved both individual and combined applications of these agents. Additionally, the field contained buried bags of sclerotia, the resting structures of the mold. Evaluation protocols included disease ratings, calculating disease severity index (DSI), yield assessment at harvest, and analysis of mycelial growth in cultures alongside microbial work and DNA extractions for the sclerotia. Plots containing Bacillus subtilis proved to be the most promising in managing disease based off the DSI calculations. Interestingly, the DSI in the Contans plots was higher than the untreated plot. Sclerotia viability assays from the Contans and untreated plots were also consistent with these results.

Alfalfa has been bred to have reduced lignin in stems to improve cattle digestibility and increase milk production, but it remains unclear how forage lignin content impacts root architecture and chemistry. Variation in these root traits among lines differing in stem lignin content could have implications for global carbon and nitrogen cycling. We evaluated tap and fine roots of three alfalfa lines varying in stem lignin content for biomass, surface area, length, lignin content, and the carbon-to-nitrogen ratio (C:N). Roots were excavated at the early flower stage in St. Paul and Rosemount, MN, from three-year-old alfalfa stands. The increased lignin line had the highest mean C:N, suggesting reduced root decomposition compared to the other lines. The reduced lignin line had the largest fine root biomass, so although it had a lower C:N than the others, it had the largest carbon and nitrogen inputs to the soil. We predict that stem lignin content is positively associated with root lignin content. These data show that variation in stem lignin influences root architecture and chemistry, and that reduced lignin lines can contribute labile C and N to the soil via high root biomass with stoichiometry conducive to nutrient cycling.

Blackspot bruise is an internal defect in potatoes that causes major economic losses as many varieties remain susceptible. There are no standardized methodologies to screen for blackspot bruise vulnerability. This study was conducted to develop a standard protocol to screen for bruise resistance and enable the efficient selections of potatoes to breed more resistant varieties. The effect of different storage times, storage temperatures, and tumbling times were evaluated to determine the procedure that induced bruise development. Susceptibility was measured by bruise incidence, color, and severity. A lower pulp temperature at the time of impact, moderate tumbling duration, and warm post-impact storage conditions led to the most significant bruising. Severity was found to be a more reliable metric than incidence to assess bruise susceptibility. An index was calculated to accurately assess blackspot bruise resistance.

Corn and soybeans are the most economically valuable crops in Minnesota and represent significant land usage in the state with farmers reporting 14.5 million acres of corn and 7 million acres of soybeans planted in 2024. Continued warming and fluctuations between extreme weather events driven by climate change are expected to increase pest pressure, flood damage, and risk of heat stress for crops and farmworkers. Six climate-conscious commercial corn and soybean farmers located predominantly in southern Minnesota were interviewed to understand their perceived extreme weather and climate impacts, farm management responses to these conditions, and risk management concerns for their farm’s future. These semi structured interviews were recorded, transcribed, and underwent a preliminary analysis of key concerns to ground the development of an interactive decision-making tool. The goal of this research is to help farmers and their agricultural advisors assess their agricultural risks due to climate change and the actions they can take to prepare for Minnesota’s extreme weather and climate impacts. We expect that findings from our research will inform our ability to advise on best climate preparedness practices for short term (in season), mid term (1-3 years), and long term (10-15 year) time horizons.