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
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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.
Integrating Spectroscopy with Machine Learning to Differentiate Seed Varieties
July 15th 2025Researchers at the University of Belgrade have demonstrated that combining Raman and FT-IR spectroscopy with machine learning algorithms offers a highly accurate, non-destructive method for identifying seed varieties in lettuce, paprika, and tomato.