Raman spectroscopy for agricultural applications

Over the last decade, we observe a significant interest in Raman spectroscopy expressed by plant biologists and other agriculturalists. However, many of these people have limited experience in Raman analyses. To this end, we wrote an extensive method-focused manuscript in which we critically discuss key steps in analyses for spectroscopic data. We also conveyed the major differences between analysis of certain peaks vs the full spectra, as well as discussed how both types of spectral analyses could complement each other. We also focused on chemometric analysis of data, including supervised methods, such as PLS-DA. Using our own data, we demonstrated a contribution of spectral preprocessing, model parameters and validation in the performance of supervised methods in data classification. We also critically discussed practical applications of peak fitting and 2-D correlation spectroscopy and demonstrated how these approaches can be useful to extract valuable information about biological processes that take place in plants.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-09-01
DOI
https://doi.org/10.3389/fpls.2025.1607036
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
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article

Raman spectroscopy for agricultural applications

Isaac D. Juárez, Dmitry Kurouski
3 links
Frontiers in Plant Science
Spectroscopy and Chemometric Analyses
article

Raman spectroscopy for agricultural applications

Isaac D. Juárez, Dmitry Kurouski
article en

Abstract

Over the last decade, we observe a significant interest in Raman spectroscopy expressed by plant biologists and other agriculturalists. However, many of these people have limited experience in Raman analyses. To this end, we wrote an extensive method-focused manuscript in which we critically discuss key steps in analyses for spectroscopic data. We also conveyed the major differences between analysis of certain peaks vs the full spectra, as well as discussed how both types of spectral analyses could complement each other. We also focused on chemometric analysis of data, including supervised methods, such as PLS-DA. Using our own data, we demonstrated a contribution of spectral preprocessing, model parameters and validation in the performance of supervised methods in data classification. We also critically discussed practical applications of peak fitting and 2-D correlation spectroscopy and demonstrated how these approaches can be useful to extract valuable information about biological processes that take place in plants.

Frontiers in Plant ScienceVol. 16
Texas A&M University (US)
Openalex Percentile: Top 74%
Spectroscopy and Chemometric Analyses
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