Rapid Sample Preparation and Fast GC–MS-MS for the Analysis of Pesticides and Environmental Contaminants in Fish
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A rapid, high-throughput analytical method was developed and evaluated for the simultaneous determination of pesticides and environmental contaminants in fish. The compounds included polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and flame retardants. The method was based on a QuEChERS (quick, easy, cheap, effective, rugged, and safe) technique with acetonitrile extraction, and a dispersive solid-phase extraction (dSPE) cleanup. Three sorbent combinations were compared for cleanup efficiency and recoveries of the contaminants: C18+PSA, traditionally used for lipid removal in dSPE, and two novel sorbents, based on silica coated with zirconium dioxide (ZrO2 ) and ZrO2 /C18, designed for phospholipid removal. The dSPE cleanup with ZrO2 sorbent provided the highest efficiency with the lowest baseline, as well as satisfactory recoveries (70–120% calculated based on isotope-labeled internal standards) for the most analytes. The method allows for quick sample preparation of fish samples for the analysis of almost 200 targeted contaminants using fast, lowpressure gas chromatography with tandem mass spectrometry (GC–MS-MS), thus providing a wide scope of analysis.
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Spectroscopy and GPC to Evaluate Dissolved Organic Matter
February 4th 2025In a new study, a team of scientists used gel permeation chromatography, three-dimensional excitation-emission matrix fluorescence spectroscopy, and UV-visible spectroscopy to assess road runoff from drinking water treatment plants to evaluate the method' capacity for removing dissolved organic matter (DOM).
Blood-Glucose Testing: AI and FT-IR Claim Improved Accuracy to 98.8%
February 3rd 2025A research team is claiming significantly enhanced accuracy of non-invasive blood-glucose testing by upgrading Fourier transform infrared spectroscopy (FT-IR) with multiple-reflections, quantum cascade lasers, two-dimensional correlation spectroscopy, and machine learning. The study, published in Spectrochimica Acta Part A, reports achieving a record-breaking 98.8% accuracy, surpassing previous benchmarks for non-invasive glucose detection.
Distinguishing Horsetails Using NIR and Predictive Modeling
February 3rd 2025Spectroscopy sat down with Knut Baumann of the University of Technology Braunschweig to discuss his latest research examining the classification of two closely related horsetail species, Equisetum arvense (field horsetail) and Equisetum palustre (marsh horsetail), using near-infrared spectroscopy (NIR).
