Fungicide efficacy on tar spot and yield of corn in the Midwestern United States

Tar spot of corn caused by Phyllachora maydis has recently led to significant yield losses in the eastern corn belt of the Midwestern United States. Foliar fungicides containing quinone outside inhibitors(QoI), demethylation inhibitors(DMI), and succinate dehydrogenase inhibitors(SDHI) are commonly used to manage foliar diseases in corn. To mitigate the losses from tar spot thirteen foliar fungicides containing single or multiple modes of action (MOA/FRAC groups) were applied at their recommended rates in a single application at the standard tassel/silk growth stage timing to evaluate their efficacy against tar spot in a total of eight field trials in Illinois, Indiana, Michigan, and Wisconsin during 2019 and 2020. The single MOA fungicides included either a QoI or DMI. The dual MOA fungicides included a DMI with either a QoI or SDHI, and fungicides containing three MOAs included a QoI, DMI, and SDHI. Tar spot severity estimated as the percentage of leaf area covered by P. maydis stroma of the non-treated control at dent growth stage ranged from 1.6 to 23.3% on the ear leaf. Averaged across eight field trials all foliar fungicide treatments reduced tar spot severity, but only prothioconazole+trifloxystrobin, mefentrifluconazole+pyraclostrobin+fluxapyroxad, and mefentrifluconazole+pyraclostrobin significantly increased yield over the non-treated control. When comparing fungicide treatments by the number of MOAs foliar fungicide products that had two or three MOAs decreased tar spot severity over not treating and products with one MOA. The fungicide group that contained all three MOAs significantly increased yield over not treating with a fungicide or using a single MOA.

Spatiotemporal variability in the oxidative potential of ambient fine particulate matter in the Midwestern United States

We assessed the oxidative potential (OP) of both water-soluble and methanol-soluble fractions of ambient fine particulate matter (PM2.5) in the Midwestern United States. A large set of PM2.5 samples (N=241) was collected from five sites set up in different environments, i.e., urban, rural, and roadside, in Illinois, Indiana, and Missouri during May 2018–May 2019. Five acellular OP endpoints, including the consumption rate of ascorbic acid and glutathione in a surrogate lung fluid (SLF) (OPAA and OPGSH, respectively), dithiothreitol (DTT) depletion rate (OPDTT), and ⚫OH generation rate in SLF and DTT (OPOH−SLF and OPOH−DTT, respectively), were measured for all PM2.5 samples. PM2.5 mass concentrations in the Midwestern US as obtained from these samples were spatially homogeneously distributed, while most OP endpoints showed significant spatiotemporal heterogeneity. Seasonally, higher activities occurred in summer for most OP endpoints for both water- and methanol-soluble extracts. Spatially, the roadside site showed the highest activities for most OP endpoints in the water-soluble extracts, while only occasional peaks were observed at urban sites in the methanol-soluble OP. Most OP endpoints showed similar spatiotemporal trends between mass- and volume-normalized activities across different sites and seasons. Comparisons between two solvents (i.e., water and methanol) showed that methanol-soluble OP generally had higher activity levels than corresponding water-soluble OP. Site-to-site comparisons of OP showed stronger correlations for methanol-soluble OP compared to water-soluble OP, indicating a better extraction of water-insoluble redox-active compounds from various emission sources into methanol. We found a weak correlation and inconsistent slope values between PM2.5 mass and most OP endpoints. Moreover, the poor to moderate intercorrelations among different OP endpoints indicate different mechanisms of OP represented by these endpoints and thus demonstrate the rationale for analyzing multiple acellular endpoints for a better and more comprehensive assessment of OP.

Characteristics and Predictability of Midwestern United States Drought

Characteristics and predictability of drought in the Midwestern United States, spanning the Great Plains to the Ohio Valley, at local and regional scales are examined during 1916-2015. Given vast differences in hydroclimatic variability across the Midwest, drought is evaluated in four regions identified using a hierarchical clustering algorithm applied to an integrated drought index based on soil moisture, snow water equivalent, and three-month runoff from land surface models forced by observed analyses. Highlighting the regions containing the Ohio Valley (OV) and Northern Great Plains (NGP), the OV demonstrates a preference for sub-annual droughts, the timing of which can lead to prevalent dry epochs, while the NGP demonstrates a preference for annual-to-multi-annual droughts. Regional drought variations are closely related to precipitation, resulting in a higher likelihood of drought onset or demise during wet seasons: March-November in the NGP and all year in the OV, with a preference for March-May and September-November. Due to the distinct dry season in the NGP, there is a higher likelihood of longer drought persistence, as the NGP is four times more likely to experience drought lasting at least one year compared to the OV. While drought variability in all regions and seasons are related to atmospheric wave trains spanning the Pacific-North American sector, longer-lead predictability is limited to the OV in December-February because it is the only region/season related to slow-varying sea surface temperatures consistent with El Niño-Southern Oscillation. The wave trains in all other regions appear to be generated in the atmosphere, highlighting the importance of internal atmospheric variability in shaping Midwestern drought.

Exploring information seeking of rural older adults during the COVID-19 pandemic

PurposeThis study investigates the impact of the COVID-19 pandemic on the types and sources of information sought by older adults along with their motivations in the Midwestern United States.Design/methodology/approachInterviews were conducted with 30 older adults residing in rural communities around the Midwestern United States during late-summer (July/August) 2020, using a protocol based on Dervin's Sense-Making Methodology. The resulting data was analyzed using standard content analysis procedures, guided by the theoretical frameworks based on Dervin's Sense-Making and Williamson's Ecological Model of Information Behavior. Implications of COVID-19 for the normative behaviors described in these models are discussed.FindingsFindings show that older adults were concerned primarily with health and political information during this period, but that this information was not necessarily sought only to address an informational need, but also to satisfy the need to maintain social and emotional connections in coping with isolation and loneliness. Sources of information that allowed for social interaction with people were favored. Wider personal networks (community members) were strained by the social distancing measures and closures. These findings have theoretical and practical implications for considering the impact of social restrictions on information seeking behaviors of older adults in a time of crisis.Originality/valueThis study is the first, known to the authors, that applied the two adopted theoretical frameworks to explore information seeking behaviors of older adults during the COVID-19 pandemic.