Spectroscopy and GPC to Evaluate Dissolved Organic Matter
In 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
Spectroscopy 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).
Best of the Week: Microplastics in U.S. Seafood, Tea Classification, Artificial Intelligence
Top articles published this week include a video interview that explores quantifying microplastics and anthropogenic particles in seafood, an interview discussing how spectroscopy can assess salmon freshness, and a news article about using near-infrared (NIR) spectroscopy in classifying tea.
Quantifying Microplastics and Anthropogenic Particles in Marine and Aquatic Environments
Spectroscopy recently sat down with Elise Granek, Susanne Brander, and Summer Traylor to discuss their recent study quantifying microplastics (MPs) and anthropogenic particles (APs) in the edible tissues of black rockfish, lingcod, Chinook salmon, Pacific herring, Pacific lamprey, and pink shrimp.
NIR Spectroscopy with AI Proves to be a Powerful Combination for Tea Classification
January 29th 2025A team of researchers from Nankai University has developed an advanced method to classify tea types using near-infrared spectroscopy (NIRS) and artificial intelligence (AI). Their approach, involves a fine-tuned 1DResNet model, outperforms traditional methods, and offers an accurate, non-destructive, and efficient classification solution for the tea industry.
Raman Spectroscopy Takes a Leap Forward in Forensic Drug Detection
Researchers have demonstrated the potential of deep ultraviolet Raman spectroscopy (DUVRS) as a rapid, nondestructive, and sensitive tool for detecting antihistamines like cetirizine in oral fluid samples, paving the way for broader forensic applications.