Mid-Infrared Emission Study Proposes New Principle for Noninvasive Blood Sugar Measurement
September 12th 2025A research team in Japan has proposed a new principle, called the emission integral effect, to explain how mid-infrared passive spectroscopic imaging can detect blood glucose levels without invasive methods. Their findings suggest that dilute components like glucose may be more identifiable than concentrated ones when using this technique.
New Infrared Device Measures Blood Sugar Without a Prick
September 11th 2025Researchers have developed a miniature non-invasive blood glucose monitoring system using near-infrared (NIR) technology. The compact, low-cost device uses infrared light to measure sugar levels through the fingertip, offering a painless alternative to traditional finger-prick tests.
Molar Absorptivity Model Powers Near-Infrared Glucose Testing
September 10th 2025Researchers from Sharif University of Technology, Tehran, present an approach using near-infrared absorbance and molar absorptivity to estimate blood glucose with a drawn blood sample—showing comparable performance to methods that apply principal components regression (PCR).
Mini-Tutorial on NIR Aquaphotomics for Rapid, Non-Destructive Biofluid and Food Analysis
September 9th 2025Near-infrared (NIR) spectroscopy combined with aquaphotomics shows potential for a rapid, non-invasive approach to detect subtle biochemical changes in biofluids and agricultural products. By monitoring water molecular structures through water matrix coordinates (WAMACs) and visualizing water absorption spectrum patterns (WASPs) via aquagrams, researchers can identify disease biomarkers, food contaminants, and other analytes with high accuracy. This tutorial introduces the principles, practical workflow, and applications of NIR aquaphotomics for everyday laboratory use.
Demystifying the Black Box: Making Machine Learning Models Explainable in Spectroscopy
September 8th 2025This tutorial provides an in-depth discussion of methods to make machine learning (ML) models interpretable in the context of spectroscopic data analysis. As atomic and molecular spectroscopy increasingly incorporates advanced ML techniques, the black-box nature of these models can limit their utility in scientific research and practical applications. We present explainable artificial intelligence (XAI) approaches such as SHAP, LIME, and saliency maps, demonstrating how they can help identify chemically meaningful spectral features. This tutorial also explores the trade-off between model complexity and interpretability.
NIR Aquaphotomics Milk Analysis Method Detects Johne’s Disease in Dairy Cows
September 4th 2025Researchers have demonstrated a non-invasive method using milk and near-infrared spectroscopy combined with Aquaphotomics to accurately detect Paratuberculosis in dairy cattle. The technique offers faster, more sensitive diagnosis than traditional methods.
Spectroscopy Guides Long-Term Conservation of Renaissance Murals in Valencia
Researchers at the University of the Basque Country, along with Català Restauradors S.L. analyzed the emergence of soluble salts on mural paintings in the vault of the Valencia Cathedral, using Raman and micro-energy-dispersive X-ray fluorescence spectroscopy combined with ion chromatography.
Aquaphotomic NIR Spectroscopy Technique Could Rapidly Detect Toxic Aflatoxin in Maize
September 3rd 2025Researchers have demonstrated that visible and near-infrared spectroscopy, combined with chemometric and aquaphotomic analysis, can accurately classify and quantify aflatoxin contamination in white and yellow maize, offering a faster, non-destructive alternative to traditional methods.