Established to develop a community-sourced glossary covering key functional near-infrared spectroscopy (fNIRS) terms, including those related to the continuous-wave (CW), frequency-domain (FD), and time-domain (TD) NIRS techniques, the fNIRS Glossary Project features over 300 terms categorized into six key domains: analysis, experimental design, hardware, neuroscience, mathematics, and physics. It also includes abbreviations, symbols, synonyms, references, alternative definitions, and figures where relevant.

This article shows the benefits and ease with which mid-infrared testing can reveal supply change mismanagement events and help to quickly identify and correct mishaps.

A new tutorial provides a step-by-step, hands-on guide to using multivariate data analysis tools like PCA and PLS to extract meaningful insights from complex pharmaceutical data sets.

Top articles published this week include a preview of our upcoming content series for National Space Day, a news story about air quality monitoring, and an announcement from Metrohm about their new Midwest office.

Researchers from Tsinghua University and Qinghai University have uncovered how specific ambient gas properties affect the stability and accuracy of laser-induced breakdown spectroscopy (LIBS) signals.

A new dual-spectroscopy approach reveals real-time pollution threats in indoor workspaces. Chinese researchers have pioneered the use of laser-induced breakdown spectroscopy (LIBS) and aerosol mass spectrometry to uncover and monitor harmful heavy metal and dust emissions from soldering and welding in real-time. These complementary tools offer a fast, accurate means to evaluate air quality threats in industrial and indoor environments—where people spend most of their time.

Researchers from SGF International and Geisenheim University combine 1H NMR and HPLC-DAD to elevate juice quality assurance.

A new study published in Applied Food Research demonstrates that near-infrared spectroscopy (NIRS) can effectively detect subclinical bovine mastitis in milk, offering a fast, non-invasive method to guide targeted antibiotic treatment and support sustainable dairy practices.

A global research team has detailed how smart sensors, artificial intelligence (AI), machine learning, and Internet of Things (IoT) technologies are transforming the detection and management of environmental pollutants. Their comprehensive review highlights how spectroscopy and sensor networks are now key tools in real-time pollution tracking.

Here is a collection of recent studies that used spectroscopic techniques in environmental analysis.

Jiangxi Agricultural University researchers use AI and vis-NIRS to predict meat quality and freezing duration with high accuracy.

Scientists at Oak Ridge National Laboratory have demonstrated that a fast, laser-based mass spectrometry method—LA-ICP-TOF-MS—can accurately detect and identify airborne environmental particles, including toxic metal particles like ruthenium, without the need for complex sample preparation. The work offers a breakthrough in rapid, high-resolution analysis of environmental pollutants.