Improving Sensitivity and Selectivity in Pesticide Analysis with GC–MS and GC–MS-MS
Spectroscopy E-Books
The selection of analytical methods for gas chromatography (GC)-amenable pesticides is often based on requirements for sensitivity and selectivity for regulatory needs or other monitoring requirements. Methods with both electron ionization (EI) and negative chemical ionization (NCI) are often required to cover the full range of GC–amenable pesticides at trace levels. Pesticides fragment easily in EI and CI sources such that the molecular ion is often low in abundance. NCI can provide added selectivity and sensitivity over EI methods. NCI is most commonly used in selected-ion monitoring mode. The lack of availability of parent ions for collision-induced dissociation for tandem mass spectrometry (MS) can limit the feasibility of GC–MS-MS for pesticides that significantly fragment in the ion source. Options for improving sensitivity by using of large-volume cold on column or programmable temperature vaporizer injections are presented. Read more
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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).
