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University of Minnesota Crookston 8765
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University of Minnesota Twin Cities 106994

Recent Submissions

Adsorption of Microcystins onto Synthetic and Natural Clay Minerals
Li, Yuan; Hondzo, Miki; Yang, Judy; LI002413@umn.edu; Li, Yuan; Yang Research Group
The proliferation of cyanobacterial harmful algal blooms and their toxins, especially microcystins, represents a significant threat to water quality worldwide. Clay-based adsorption offers a promising method to mitigate this threat. This study compares the adsorption of microcystins onto a synthetic clay (laponite) and two natural clays (bentonite and kaolinite) under various chemical conditions. We specifically examined the effects of solution pH, salinity, and cation type on the adsorption process. The difference between the initial and equilibrium concentrations of microcystins, divided by the clay concentration, determines the toxin’s removal efficiency. Our laboratory experiments demonstrate that at neutral pH, laponite exhibits greater toxin-removal efficiency than bentonite, followed by kaolinite. Consequently, laponite is more effective at removing microcystins compared to natural clays. All three clays exhibit reduced adsorption efficiency as pH increases from 7 to 9, with kaolinite showing the most significant decrease. Additionally, higher salinity levels and the presence of divalent cations such as Ca²⁺ boost the adsorption ability of all three clays. Across all tested chemical scenarios, laponite consistently outperforms bentonite and kaolinite in capturing microcystins, demonstrating its greater efficiency across diverse water chemistries. Our results highlight the potential of laponite for removing microcystins and demonstrate that both the clay type and the water’s chemical characteristics play a critical role in toxin removal efficiency. These findings pave the way for future applications of clays to lower microcystin pollution across various aquatic environments, from freshwater sources to brackish estuaries.
"Photon Interaction Frequency Is Essential to Maximize Plasmon-Driven Charge Transfer" - Raman spectra data files and figure data. Collected at the University of Minnesota-Twin Cities Campus between Dec 2024- Jan 2025
Koble, MaKenna; Sarkar, Arghya; Frontiera, Renee; rrf@umn.edu; Frontiera, Renee; University of Minnesota Frontiera Lab
The data includes Raman spectra collected under different excitation conditions (continuous wave and pulsed illumination) for an experimental research study. The data is presented in the paper "Photon Interaction Frequency Is Essential to Maximize Plasmon-Driven Charge Transfer". The upload also includes the data used for the main text figures in the paper. This data was used to draw conclusions about how photon interaction frequency impacts plasmon-driven charge transfer to methyl viologen.
Complete data and code to generate datasets in: Occurrence and environmental data for aquatic plants of Minnesota from 1999-2018
(2024-07-15) Verhoeven, Michael; Larkin, Daniel J.; michael.verhoeven.mrv@gmail.com; Verhoeven, Michael; Minnesota Aquatic Invasive Species Research Center (MAISRC); Fisheries Systems Ecology Lab
A dataset (and multi-scale aggregations thereof) of point-level occurrences, relative abundances, and associated environmental data for macrophytes (freshwater plants) across Minnesota. The data encompass 3,194 surveys of 1,520 lakes and ponds performed over a 19-year timespan. A total of 372,091 points were sampled, across which 231 taxa were recorded. Macrophyte occurrence data and depth, as well as point-level relative-plant-abundance measures for a subset of surveys, were collated, cleaned, and joined to geospatial data and Secchi-depth measurements of water clarity, enabling light availability, a primary control on aquatic plant growth, to be estimated.
Support and Guide: Observational Coding Scale Manual for Primary Care Clinician Conversations with Parents
(2025) Mehus, Chris; Ballard, Jaime; Driscoll, Janette; Sargeant, Laura; Exsted, Marci
Geometry-based mass grading of mango fruits using image processing
(2017-05-13) Rahman, Towfiq; Momin, Abdul; Sultana, M.S.; Igathinathane, C.; Ziauddin, A.T.M.; Grift, T.E.
Mango (Mangifera indica) is an important, and popular fruit in Bangladesh. However, the post-harvest processing of it is still mostly performed manually, a situation far from satisfactory, in terms of accuracy and throughput. To automate the grading of mangos (geometry and shape), we developed an image acquisition and processing system to extract projected area, perimeter, and roundness features. In this system, images were acquired using a XGA format color camera of 8-bit gray levels using fluorescent lighting. An image processing algorithm based on region based global thresholding color binarization, combined with median filter and morphological analysis was developed to classify mangos into one of three mass grades such as large, medium, and small. This system achieved an accuracy of 97% for projected area and Feret diameter, 79% for perimeter, and 36% for roundness. To achieve a finer grading, two different grading features could be used in sequence. The image grading system is simple and efficient and can be considered a suitable first stage to mechanizing the commercial grading of mangos in Bangladesh. Moreover, the method has the potential to be applied to other crops with suitable adjustments.