Best of the Week: Estimating Prediction Uncertainty, Icons of Spectroscopy

This week, Spectroscopy published a variety of articles highlighting recent studies in several application areas, including environmental monitoring, data science, and plasma spectrochemistry. Key techniques highlighted in these articles include infrared (IR) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy. Happy reading!

Smarter Spectroscopy With a New Machine Learning Approach to Estimate Prediction Uncertainty

In a recent study conducted by A.M.C. Wadoux (University of Sydney) and L. Ramirez-Lopez (University of Minnesota), they investigated using quantile regression forest (QRF), a machine learning (ML) method, to improve prediction accuracy and quantify uncertainty in spectroscopic analyses. When tested on soil and mango datasets using IR spectra, QRF delivered reliable predictions while generating sample-specific uncertainty intervals, addressing a major gap in current chemometric models (1). Though some intervals were overestimated, the 90% prediction interval proved accurate (1). The authors recommend QRF for practical spectroscopy applications, emphasizing its value in agriculture, food science, and pharmaceuticals, where both prediction accuracy and reliability are critical (1).

Earle K. Plyler: Setting the Standard in Infrared Spectroscopy

Earle K. Plyler (1897–1976) was an IR spectroscopist whose five-decade career shaped modern molecular spectroscopy. After early work at UNC and Michigan, he led the Infrared Spectroscopy Section at the National Bureau of Standards (1945–1962), producing high-precision line lists, band centers, and calibration methods that became global standards (2). Later, at Florida State University (FSU), he built programs, mentored students, and advanced spectroscopy in the Southeast. Plyler authored over 100 papers, innovated instrumentation, and trained future leaders like Walter Gordy (2). His legacy endures through the APS Earle K. Plyler Prize, honoring major contributions to molecular spectroscopy and dynamics (2).

From Raman to Chemometrics: Discover the Pioneers Who Revolutionized Modern Spectroscopy

The “Icons of Spectroscopy” series celebrates the work of scientists and researchers whose discoveries shaped modern analytical science. Figures like C.V. Raman, who revealed the Raman effect and validated quantum theory, and Albert Michelson, whose interferometer laid the groundwork for FT-IR spectroscopy, changed how we study light (3). Clara Craver’s IR spectral libraries remain vital references, while Bruce Kowalski pioneered chemometrics to interpret complex data. Their collective contributions, which span measurement precision, quantum discovery, reference tools, and data analysis, form the backbone of today’s spectroscopy (3). The series underscores that progress in science is a continuum of innovation, built on the persistence and brilliance of multiple generations (3).

Horiba Launches Spectrometer Designed for Water Research and Environmental Monitoring

In a recent announcement, Horiba Scientific announced the launch of the Aqualog-Next, which is a fifth-generation spectrometer made by them. According to the company, it combines speed, precision, and advanced data processing to tackle water-related challenges, integrating with EzSpec software for streamlined workflows and data integrity (4). Analysts can perform data acquisition, processing, and reporting, with features like inner-filter effect correction and three-dimensional (3D)-to-two-dimensional (2D) profiling, enhancing result accuracy and data sharing (4). Horiba’s A-TEEM technology captures absorbance and fluorescence data simultaneously, addressing inner filter effect distortions for reliable measurements (4). The spectrometer supports NIST traceability and multivariate analysis methods, making it adaptable for diverse applications in water science and environmental monitoring.

Returning to Tucson: The 2026 Winter Conference on Plasma Spectrochemistry

The 2026 Winter Conference on Plasma Spectrochemistry will be held in Tucson, Arizona, from January 11–17, 2026, with short courses starting January 9. This event is organized by the International Atomic Spectrometry Association (IASA). According to the conference organizers, the Winter Conference on Plasma Spectrochemistry is expected to attract approximately 500 participants from 30 countries (5). The program will feature symposia on plasma instrumentation, nanomaterial analysis, elemental speciation, metallomics, and automation, alongside specialized sessions on MS, glow discharge, laser-assisted techniques, and isotope analysis (5).

References

1. Workman, Jr., J. Smarter Spectroscopy With a New Machine Learning Approach to Estimate Prediction Uncertainty. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/smarter-spectroscopy-with-a-new-machine-learning-approach-to-estimate-prediction-uncertainty (accessed 2025-08-27).
2. Workman, Jr., J. Earle K. Plyler: Setting the Standard in Infrared Spectroscopy. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/earle-k-plyler-setting-the-standard-in-infrared-spectroscopy (accessed 2025-08-27).
3. Workman, Jr., J.; Hroncich, C. From Raman to Chemometrics: Discover the Pioneers Who Revolutionized Modern Spectroscopy. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/from-raman-to-chemometrics-pioneers-modern-spectroscopy (accessed 2025-08-27).
4. Wetzel, W. Horiba Launches Spectrometer Designed for Water Research and Environmental Monitoring. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/horiba-launches-spectrometer-designed-for-water-research-and-environmental-monitoring (accessed 2025-08-27).
5. Wetzel, W. Returning to Tucson: The 2026 Winter Conference on Plasma Spectrochemistry. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/returning-to-tucson-the-2026-winter-conference-on-plasma-spectrochemistry (accessed 2025-08-27).