Near Infrared (NIR) Spectroscopy

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.

A new study examines the role of Internet of Things (IoT) technology in fostering sustainable urban development. Through a systematic review of 73 publications, researchers highlight how IoT-enabled sensors improve air quality, transportation, disaster management, and resource efficiency in smart cities.

Researchers highlight the growing role of Internet of Things (IoT) and sensor technologies in enhancing food security and agricultural sustainability. The study, published in Ain Shams Engineering Journal, explores the applications, benefits, and challenges of smart agriculture, emphasizing the potential of optical sensors in monitoring and optimizing farming practices.

A recent study provides an in-depth overview of the latest advancements in infrared (IR) semiconductor sensor technology, highlighting new materials, enhanced detection capabilities, and expanding applications across industrial, medical, security, and environmental fields. The research explores how quantum dots, graphene, and novel nanomaterials are revolutionizing IR detection, paving the way for more efficient and versatile sensor systems.

Scientists explore the potential of dilute III-V NIR semiconductors for Tuberculosis diagnostics, offering improved sensitivity and efficiency.

Researchers have developed a novel approach to improve the accuracy of near-infrared spectroscopy (NIRS or NIR) in quantifying highly porous, patient-specific drug formulations. By combining machine learning with advanced Raman imaging, the study enhances the precision of non-destructive pharmaceutical analysis, paving the way for better personalized medicine.

Top articles published this week include a video interview that explores using label-free spectroscopic techniques for tumor classification, an interview discussing how near-infrared (NIR) spectroscopy can classify different types of horsetails, and a news article about detecting colorless microplastics (MPs) using NIR spectroscopy and machine learning (ML).

This new study highlights the potential of visible-near-infrared (Vis-NIR) spectroscopy for predicting phosphorus sorption parameters.

A recent study conducted by Shanghai researchers developed a high-accuracy model for identifying plastic pollution.

Researchers have developed a small near-infrared (NIR) spectrometer dedicated to achieve painless, accurate glucose measurements.

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).

A recent paper published in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy argued that near-infrared (NIR) spectroscopy technology is the most sustainable choice for food production.

A 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.

Researchers have explored the potential of combining near-infrared spectroscopy (NIRS) with machine learning (ML) to create a non-invasive, rapid diagnostic tool for liver fibrosis detection, a key factor in transplant surgery planning. These approaches could offer a more accurate and accessible alternative to traditional methods like biopsy.