Near Infrared (NIR) Spectroscopy

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.

Scientists demonstrate a self-supervised learning framework that dramatically improves near-infrared spectroscopy classification results, even with minimal labeled data.

This excerpt from The Concise Handbook of Analytical Spectroscopy, which spans five volumes, serves as a comprehensive reference, detailing the theory, instrumentation, sampling methods, experimental design, and data analysis techniques for each spectroscopic region.

A recent study published in Meat Science highlighted how visible and near-infrared (vis-NIR) spectroscopy, when combined with chemometrics, can differentiate lamb meat based on pasture-finishing durations.

Spectroscopy sat down with Daniel Cozzolino of the University of Queensland to discuss his latest research using near-infrared (NIR) spectroscopy to determine the fatty acid content in black soldier fly.

Researchers from the Universidade de São Paulo have demonstrated the effectiveness of near-infrared spectroscopy combined with chemometric models for real-time, precise monitoring of Zika virus-like particle vaccine production.

A new study published in Food Control introduces an approach for assessing antioxidant levels in edible oils using artificial intelligence and spectroscopy, offering significant potential for improving food quality control.

A recent study combines hyperspectral imaging (HSI) technology with chemometrics to deliver improved quality control of black garlic.

A recent study developed an accurate, non-destructive geo-traceability method using NIR spectroscopy and machine learning to authenticate the geographic origins of Gastrodia elata Bl.

Top articles published this week include two peer-reviewed articles that explore optical detection technology for seed vigor and classifying flowers, as well as a profile on Benjamin Manard, who was recognized as the winner of the 2025 Emerging Leader in Atomic Spectroscopy.

In this article, the basic principles, advantages, and limitations of different optical techniques for obtaining seed vigor estimates are introduced and reviewed, and the key technology of non-destructive optical detection of single seeds will be discussed.

Researchers have developed a novel three-step hybrid variable selection strategy, SiPLS-RF(VIM)-IMIV, to enhance the accuracy and efficiency of soil potassium measurement using near-infrared spectroscopy, offering significant advancements for precision agriculture and real-time soil monitoring.

Miniaturized NIR spectrometers are transforming forensic science by enabling rapid, cost-effective, and portable field analysis.

A recent study published in Food Research International demonstrates how visible and near-infrared spectroscopy (Vis-NIRS) combined with machine-learning algorithms can accurately authenticate meat and fat based on livestock feeding systems, offering a sustainable and reliable solution for traceability in the meat industry.

HSI is widely applied in fields such as remote sensing, environmental analysis, medicine, pharmaceuticals, forensics, material science, agriculture, and food science, driving advancements in research, development, and quality control.

The following is a summary of selected articles published recently in Spectroscopy on the subject of handheld, portable, and wearable spectrometers representing a variety of analytical techniques and applications. Here we take a closer look at the ever shrinking world of spectroscopy devices and how they are used. As spectrometers progress from bulky lab instruments to compact, portable, and even wearable devices, the future of spectroscopy is transforming dramatically. These advancements enable real-time, on-site analysis across diverse industries, from healthcare to environmental monitoring. This summary article explores cutting-edge developments in miniaturized spectrometers and their expanding range of practical applications.

This study aimed to assess and detect adulteration of Kelulut honey with different percentages of rice syrup using near-infrared (NIR) spectroscopy.

Over the past two years Spectroscopy Magazine has increased our coverage of artificial intelligence (AI), deep learning (DL), and machine learning (ML) and the mathematical approaches relevant to the AI topic. In this article we summarize AI coverage and provide the reference links for a series of selected articles specifically examining these subjects. The resources highlighted in this overview article include those from the Analytically Speaking podcasts, the Chemometrics in Spectroscopy column, and various feature articles and news stories published in Spectroscopy. Here, we provide active links to each of the full articles or podcasts resident on the Spectroscopy website.

Researchers have developed a novel method combining near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy with advanced data fusion techniques to improve the accuracy of non-structural carbohydrate estimation in diverse tree tissues, advancing carbon cycle research.

Despite its widespread adoption in food quality analysis, near-infrared (NIR) spectroscopy lags behind in regulatory recognition. A study led by researchers from Italy and Spain highlights the disparity between its scientific applications and official methods, urging standardized regulations to fully leverage NIR's sustainability benefits.

Researchers in China have developed a novel workflow for near-infrared reflectance spectroscopy (NIRS or NIR) that enhances the detection of low-level petroleum hydrocarbon pollution in soils, revealing new diagnostic features and significantly improving sensitivity for environmental monitoring.