Identification of earliest point for detection of plant virus infection through Raman spectroscopy and principal component analysis

Kaustav Das; Fawzia Novianti; Ken Komatsu; Terumasa Ito; Kazuhiko Misawa

doi:10.1117/12.3002321

13 March 2024 Identification of earliest point for detection of plant virus infection through Raman spectroscopy and principal component analysis

Kaustav Das, Fawzia Novianti, Ken Komatsu, Terumasa Ito, Kazuhiko Misawa

Author Affiliations +

Proceedings Volume PC12879, Photonic Technologies in Plant and Agricultural Science; PC1287904 (2024) https://doi.org/10.1117/12.3002321
Event: SPIE LASE, 2024, San Francisco, California, United States

Abstract

Plant disease outbreaks pose serious threats to global food security. A rigid methodology that accounts for rapid identification of the earliest point of infection caused by plant viruses is necessary. Raman spectroscopy that generates spectral signatures of cellular-level dynamics resonates the virus induced alteration in plants through moderations in spectral features. Here, we present a model study to identify the earliest point of infection. Measured spectra from healthy and virus infected Arabidopsis thaliana plants are applied to principal component analysis. We found a separation as early as 8 days post inoculation between healthy and virus infected plants.

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Kaustav Das, Fawzia Novianti, Ken Komatsu, Terumasa Ito, and Kazuhiko Misawa "Identification of earliest point for detection of plant virus infection through Raman spectroscopy and principal component analysis", Proc. SPIE PC12879, Photonic Technologies in Plant and Agricultural Science, PC1287904 (13 March 2024); https://doi.org/10.1117/12.3002321

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