Dmitry Kurouski of Texas A&M University speaks to Spectroscopy Editor Patrick Lavery about Raman spectroscopy's role in determining crop yield of key food items as the world population continues to increase.
(1) Farber, C.; Kurouski, D. Raman Spectroscopy and Machine Learning for Agricultural Applications: Chemometric Assessment of Spectroscopic Signatures of Plants as the Essential Step Toward Digital Farming. Front. Plant. Sci. 2022, 13, 887511. DOI: 10.3389/fpls.2022.887511
Raman Spectroscopy to Detect Lung Cancer and Monitor Vaccine Effects
January 20th 2025A new study highlights the use of Raman spectroscopy to detect lung cancer and evaluate the effects of the PCV13 vaccine. Researchers found distinct biochemical changes in lung cancer patients and healthy individuals, revealing the vaccine's significant impact on immune response.
An Inside Look at the Fundamentals and Principles of Two-Dimensional Correlation Spectroscopy
January 17th 2025Spectroscopy recently sat down with Isao Noda of the University of Delaware and Young Mee Jung of Kangwon National University to talk about the principles of two-dimensional correlation spectroscopy (2D-COS) and its key applications.
Nanometer-Scale Studies Using Tip Enhanced Raman Spectroscopy
February 8th 2013Volker Deckert, the winner of the 2013 Charles Mann Award, is advancing the use of tip enhanced Raman spectroscopy (TERS) to push the lateral resolution of vibrational spectroscopy well below the Abbe limit, to achieve single-molecule sensitivity. Because the tip can be moved with sub-nanometer precision, structural information with unmatched spatial resolution can be achieved without the need of specific labels.
New SERS-Microfluidic Platform Classifies Leukemia Using Machine Learning
January 14th 2025A combination of surface-enhanced Raman spectroscopy (SERS) and machine learning on microfluidic chips has achieved an impressive 98.6% accuracy in classifying leukemia cell subtypes, offering a fast, highly sensitive tool for clinical diagnosis.
New Study on Edible Oil Analysis Integrates FT-NIR and Machine Learning
January 14th 2025A 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.