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This tutorial explores the challenges posed by nonlinearities in spectroscopic calibration models, including physical origins, detection strategies, and correction approaches. Linear regression methods such as partial least squares (PLS) dominate chemometrics, but real-world data often violate linear assumptions due to Beer–Lambert law deviations, scattering, and instrumental artifacts. We examine extensions beyond linearity, including polynomial regression, kernel partial least squares (K-PLS), Gaussian process regression (GPR), and artificial neural networks (ANNs). Equations are provided in full matrix notation for clarity. Practical applications across near-infrared (NIR), mid-infrared (MIR), Raman, and atomic spectroscopies are discussed, and future research directions are outlined with emphasis on hybrid models that integrate physical and statistical knowledge.

A recent study examined how portable instrumentation could be applied in the detection of diabetes.

Recently, a team of researchers from Portugal examined a new method that could improve accessibility to kidney disease diagnostics.

Despite decades of major monetary investment for applied research in multiple spectroscopic sensing technologies, achieving an accurate, portable, and painless noninvasive glucose monitor remains a major unmet goal in diabetes care. This goal is extremely difficult due to persistent challenges with sensitivity, analyte specificity, accuracy, calibration stability, and biological interference.

Besides the technical program, which encompasses plenary talks, poster sessions, short courses, and many contributed oral presentations, SciX also has several social events for attendees to enjoy in the evenings during the conference week. We highlight these social events here.

This Chemometrics in Spectroscopy column traces the historical and technical development of these methods, emphasizing their application in calibrating spectrophotometers for prediction of measured sample chemical or physical properties and explores how AI and deep learning are reshaping the spectroscopic landscape.

In the final part of our conversation with Leonardos “Leo” Gkouvelis, we discussed what happens when opposition effects are ignored when studying exoplanets and how it impacts our understanding of their surface composition.

Click here to access the Spectroscopy September/October North America PDF in an interactive format.

Click here to access the Spectroscopy September/October Europe PDF in an interactive format.

A new review article published in Applied Spectroscopy Reviews highlights how visible–near infrared (Vis-NIR) spectroscopy could improve the way scientists detect and monitor potentially toxic trace elements (PTEs) in soil and sediments.

A recent study proposed and tested a new approach for monitoring the nutritional quality of orange juice.

Top articles published this week include a video interview discussing the opposition surge effect in astronomy, a peer-reviewed article about charge transfer complexes in antibiotics, and a news article about using reflectance spectroscopy to analyze soil in the Amazon.

In this study, the ground state structure and CT transition of the complex formed by the reaction of hydrogen peroxide (H2O2) with the five antibiotics (TMP, NOR, OFL, CIP, and SMR) were theoretically investigated by density functional theory (DFT).

In a continuation of our conversation with Leonardos “Leo” Gkouvelis, who is in the Faculty of Physics at Ludwig Maximilian University (Munich, Germany), we discussed the phenomenon of shadow hiding and coherent back scattering in astronomy, particularly in the context of observing celestial bodies like the moon and exoplanets.

Recently, a team of researchers examined how to improve camouflage technology for defense applications by integrating spatial and spectral dimensions across optical, thermal infrared, terahertz, and microwave bands.

A new study demonstrates that combining multi-pass FT-IR with a quantum cascade laser, two-dimensional correlation spectroscopy, and machine learning reportedly boosts the accuracy of non-invasive blood-glucose testing. The approach reports a 98.8% classification accuracy, suggesting potential for clinically viable, needle-free diabetes monitoring.

In this interview segment, Leo Gkouvelis of Ludwig Maximilian University discusses the opposition surge effect and how his study explored a new method for modeling the opposition surge effect in studying exoplanets.

As part of the SciX Conference program, a keynote presentation is set to take place on Monday October 6, 2025, from 8:30–9:30 am EST in Ballroom B. This year’s keynote speaker is Michael Gold of Redwire, and he will deliver a talk titled, “Unveiling the Unknown: The Pursuit to Understand UAP’s."

This year, the SciX Conference will take place at the Northern Kentucky Convention Center in Covington, Kentucky, from October 5–10, 2025

This tutorial explores the motivation, mathematical underpinnings, and practical approaches to fusing spectral data, with emphasis on early, intermediate, and late fusion strategies.

A recent study provided new information on how berberine mid-chain fatty acid salts interact with lysozyme.

This Icons of Spectroscopy Series article features William George “Bill” Fateley, who shaped modern vibrational spectroscopy through landmark reference books and research papers, pioneering instrumentation, decades of editorial leadership, and deep commitments to students and colleagues. This article reviews his career arc, scientific contributions, and enduring legacy.

A recent study conducted by researchers from the Taiyuan University of Technology (China) explored a new way to detect pesticide residues at very low levels.

A research team in Japan has proposed a new principle, called the emission integral effect, to explain how mid-infrared passive spectroscopic imaging can detect blood glucose levels without invasive methods. Their findings suggest that dilute components like glucose may be more identifiable than concentrated ones when using this technique.

Researchers have developed a miniature non-invasive blood glucose monitoring system using near-infrared (NIR) technology. The compact, low-cost device uses infrared light to measure sugar levels through the fingertip, offering a painless alternative to traditional finger-prick tests.