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
Best of the Week: SciX Award Interviews, Tip-Enhanced Raman Scattering
June 13th 2025Top 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.
Researchers Use Machine Learning and Hyperspectral Imaging to Pinpoint Best Apple Bagging Techniques
June 12th 2025A 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.
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.
MIR Spectroscopy Validates Origin of Premium Brazilian Cachaças
June 11th 2025A 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.
New NIR/Raman Remote Imaging Reveals Hidden Salt Damage in Historic Fort
June 10th 2025Researchers have developed an analytical method combining remote near-infrared and Raman spectroscopy with machine learning to noninvasively map moisture and salt damage in historic buildings, offering critical insight into ongoing structural deterioration.