Near Infrared (NIR) Spectroscopy

A study from Chinese researchers demonstrates how combining satellite imagery, land use data, and machine learning can improve pollution monitoring in fast-changing urban rivers. The study focuses on non-optically active pollutants in the Weihe River Basin and showcases promising results for remote, data-driven water quality assessments.

New research highlights how remote satellite sensing technologies are changing the way scientists monitor inland water quality, offering powerful tools for tracking pollutants, analyzing ecological health, and supporting environmental policies across the globe.

Modern remote sensing technologies have evolved from coarse-resolution multispectral sensors like MODIS and MERIS to high-resolution, multi-band systems such as Sentinel-2 MSI, Landsat OLI, and UAV-mounted spectrometers. These advancements provide greater spectral and spatial detail, enabling precise monitoring of environmental, agricultural, and land-use dynamics.

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.

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

Researchers from Jiangsu University and Zhejiang University of Water Resources and Electric Power have developed a transfer learning approach that significantly enhances the accuracy and adaptability of NIR spectroscopy models for detecting mycotoxins in cereals.

In this two-part "Icons of Spectroscopy" column, executive editor Jerome Workman Jr. details how Karl H. Norris has impacted the analysis of food, agricultural products, and pharmaceuticals over six decades. His pioneering work in optical analysis methods including his development and refinement of near-infrared spectroscopy, has transformed analysis technology. In this Part II article of a two-part series, we summarize Norris’ foundational publications in NIR, his patents, achievements, and legacy.

Researchers from Gifu Pharmaceutical University and Gifu University Hospital unveil a novel polaprezinc (PLZ) mucoadhesive film designed to replace painful lozenges for cancer patients.

In this "Icons of Spectroscopy" column, executive editor Jerome Workman Jr. details how Karl H. Norris has impacted the analysis of food, agricultural products, and pharmaceuticals over six decades. His pioneering work in optical analysis methods including his development and refinement of near-infrared (NIR) spectroscopy has transformed analysis technology. This Part I article of a two-part series introduces Norris’ contributions to NIR.

A new study by researchers from Palo Alto Research Center (PARC, a Xerox Company) and LG Chem Power presents a novel method for real-time battery monitoring using embedded fiber-optic sensors. This approach enhances state-of-charge (SOC) and state-of-health (SOH) estimations, potentially improving the efficiency and lifespan of lithium-ion batteries in electric vehicles (xEVs).

A recent study from Chinese researchers sheds light on protein unfolding and hydration structure dynamics in hydrogels, with implications for drug delivery and biomedical applications.

Researchers in China have developed a lightweight deep learning system for rapid, non-destructive analysis of wheat flour composition.

A study published in Sustainability by Giuseppe Bonifazi and his team at Sapienza University of Rome demonstrates how short-wave infrared (SWIR) spectroscopy combined with machine learning offers a noninvasive, accurate, and sustainable method for detecting asbestos in various materials.

This study compares the sensitivity of CIE Lab values, peak area, and yellowness index for the determination of color attributes among a set of white and stained seashells exposed to tea tannins.

A recent study demonstrates that near-infrared (NIR) spectroscopy can be used as a rapid, nondestructive method for accurately assessing sugar cane quality.

A new study published in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy demonstrates that near infrared (NIR) spectroscopy is a highly accurate and reliable method for authenticating hazelnut cultivars and geographical origins.

Recent advancements in exoplanet detection, including high-resolution spectroscopy, adaptive optics, and artificial intelligence (AI)-driven data analysis, are significantly improving our ability to identify and study distant planets. These developments mark a turning point in the search for habitable worlds beyond our solar system.

Scientists are using advanced spectroscopic techniques to probe the universe, uncovering vital insights about celestial objects. A new study by Diriba Gonfa Tolasa of Assosa University, Ethiopia, highlights how atomic and molecular physics contribute to astrophysical discoveries, shaping our understanding of stars, galaxies, and even the possibility of extraterrestrial life.

Astronomers have made a significant leap in the study of exoplanet atmospheres with a new ground-based spectroscopic technique that rivals space-based observations in precision. Using the Exoplanet Transmission Spectroscopy Imager (ETSI) at McDonald Observatory in Texas, researchers have analyzed 21 exoplanet atmospheres, demonstrating that ground-based telescopes can now provide cost-effective reconnaissance for future high-precision studies with facilities like the James Webb Space Telescope (JWST) (1-3).

In this "Icons of Spectroscopy" column, executive editor Jerome Workman Jr. details how Tomas B. Hirschfeld has made many significant contributions to vibrational spectroscopy and has inspired and mentored many leading scientists of the past several decades.

Researchers at Oregon State University explore how machine learning, optical sensors, and robotics are transforming food quality assessment and processing, improving efficiency and reducing waste.

Given the importance of this nomenclature in guiding authors and reviewers, we invite members of the spectroscopy community to provide feedback, suggest updates, or participate in future revisions.

Near-infrared spectroscopy was recently used to estimate sweetness and total soluble solids content in cherry tomatoes.

Hyperspectral imaging was recently used to characterize chicken breast affected by myopathies, which can affect their texture and quality.

A study by researchers at Universidad de Talca in Chile explores the integration of artificial intelligence (AI), the Internet of Things (IoT), and remote sensing to modernize modern farming. The research highlights how these technologies optimize resource use, improve crop yields, and promote sustainable agricultural practices.

A recent review by researchers at Nagpur University and Seth Kesarimal Porwal College explores the ever advancing landscape of the Internet of Things (IoT) and its essential components—sensors and actuators. The review paper classifies various IoT sensors and examines their role in integrating the physical and digital worlds to enable smarter devices and enhanced automation.

A team of researchers from the International Iberian Nanotechnology Laboratory (INL) in Braga, Portugal, has developed an autonomous Internet of Things (IoT) spectral sensing system designed to monitor grape ripening in real-time. The study, led by Hugo M. Oliveira, Alessio Tugnolo, Natacha Fontes, Carlos Marques, and Álvaro Geraldes, was published in Computers and Electronics in Agriculture and introduces a novel approach to non-destructive, in-situ optical monitoring of grape maturity.