Will Wetzel

Researchers from the Institute of Agrifood Research and Technology (IRTA) in Catalunya, Spain used fluorescence and Raman spectroscopy to explore complex tissue changes behind wooden breast myopathy in chickens.

Because the United Arab Emirates is seeing an increase in pet ownership, the quality of both dry and wet pet food is undergoing greater scrutiny to ensure its safety and efficacy. Lucy Semerjian, who works as a Chair and Associate Professor in the Department of Environmental Health Science at the University of Sharjah in Sharjah, United Arab Emirates, recently explored this topic in a recent paper

A recent study conducted in the Journal of Food Composition and Analysis examined the concentrations of ten metals in 52 commercially available wet and dry cat food samples, assessing their compliance with U.S. and European pet food safety standards. The lead author of this study, Lucy Semerjian, recently sat down with Spectroscopy to discuss the findings of her study.

In an announcement on June 12, Rigaku Analytical Devices, which is a division of Rigaku Holdings Corporation headquartered in Akishima, Tokyo, announced the launch of its Icon series of 1064-nm Raman analyzers, its fourth-generation of the instrument.

Researchers from Ca’ Foscari University of Venice and the University of Padua have uncovered the earliest direct evidence of Upper Palaeolithic humans deliberately processing the non-edible plant Isatis tinctoria, revealing complex behaviors involving medicinal or dye-related plant use over 32,000 years ago.

A Texas A&M AgriLife Research study published in Rangelands found that region-specific calibration significantly improves the accuracy of FNIRS-based nutritional monitoring for beef cattle grazing the Edwards Plateau.

Top articles published this week include an interview about aromatic–metal interactions, a tutorial article about the recent advancements in tip-enhanced Raman spectroscopy (TERS), and a news article about using shortwave and near-infrared (SWIR/NIR) spectral imaging in cultural heritage applications.

A new study demonstrates how handheld near-infrared spectroscopy can be a powerful, accurate tool to distinguish real cashmere from wool.

Researchers from Hebei University and Hebei University of Engineering have developed a hyperspectral imaging method combined with data fusion and machine learning to accurately and non-destructively assess walnut quality and classify storage periods.

A new study demonstrates that paper bagging significantly enhances Fuji apple quality and appearance. Hyperspectral imaging combined with machine learning offers a powerful, non-destructive method for evaluating fruit grown under different cultivation conditions.

In a recent study published in the journal Beverages, a team of researchers from the National Institute for Research and Development of Isotopic and Molecular Technologies and Babeș-Bolyai University explored a new way to improve wine authentication

A recent study published in the journal Food Chemistry explored Brazil’s cachaça industry, focusing on a new analytical method that can confirm the geographic origin of cachaças from the Brejo Paraibano region in Brazil.

A new study highlights how chemometrics-powered spectroscopic techniques offer a fast, non-destructive, and cost-effective method for detecting phenolics and vitamins in foods.

Researchers in China propose novel postharvest processing mode using vis-NIR spectroscopy and deep learning to accurately measure pomelo sweetness.

Researchers from Jinan University and Guangzhou Customs Technology Center have developed a cost-effective UV-vis spectroscopy and machine learning method to accurately identify recycled PET content as low as 10%, advancing sustainable packaging and circular economy efforts.

Top articles published this week include an interview with 2025 Clara Craver Award recipient Prashant Jain, an Icons of Spectroscopy column on Bruce R. Kowalski, and an interview with Pooja Sheevam about quantifying mineral basalts in the Hawaiian PTA-2 drill core.

In the final part of this video interview with Pooja Sheevam, she discusses the importance of her study in understanding the mineralogical and geochemical processes in Hawaii.

Researchers from Tianjin Agricultural University, Nankai University, and Zhejiang A&F University have developed a highly accurate method using near-infrared spectroscopy and machine learning to rapidly detect and classify microplastics in chicken feed.

Explore advancements in infrared spectroscopy and insights from Brian Smith, a key columnist, on the future of this evolving field.

In Part IV of our conversation with Pooja Sheevam, she discusses how scanning electron microscopy with an energy-dispersive X-ray spectroscopy (SEM-EDS) and bulk X-ray fluorescence (XRF) were used to better understand fluid-rock interactions.

Researchers use EC-SERS to reveal the first detailed structural study of hU-II peptide in aqueous solution, paving the way for new drug development.

A recent review in the Journal of Pharmaceutical Analysis highlights how AI, particularly deep learning, is revolutionizing Raman spectroscopy by enhancing its accuracy, efficiency, and applications in drug development, quality control, and clinical diagnostics.

In Part III, our discussion with Pooja Sheevam focused on the use of long-wave IR (LWIR) spectroscopy in analyzing basaltic rocks.

A recent study examined the inner structure of calcium silicate hydrate, a principal binding agent in concrete.

Shanghai researchers develop high-accuracy machine learning system to identify colorless microplastics across varied environments.

A recent study explored new rapid screening alternatives to traditional methods for detecting pork adulteration in meatballs, aiding halal food authentication efforts.

In this interview segment, Pooja Sheevam elaborates on what LWIR and SWIR are and what advantages they both offer when analyzing Hawaiian geology.

Top articles published this week include an interview with Pooja Sheevam about her study analyzing Hawaii’s PTA-2 drill core, several news stories on recent meteorite studies, and a news article on using Raman spectroscopy and artificial intelligence (AI) to detect adulteration in maple syrup.

In Part I of our video interview with Pooja Sheevam, she discusses why she and her team used both LWIR and SWIR spectroscopy in analyzing Hawaii's PTA-2 drill core, and how the two techniques complemented each other in the study.