Paper
17 May 2016 Classification of cucumber green mottle mosaic virus (CGMMV) infected watermelon seeds using Raman spectroscopy
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Abstract
The Cucumber Green Mottle Mosaic Virus (CGMMV) is a globally distributed plant virus. CGMMV-infected plants exhibit severe mosaic symptoms, discoloration, and deformation. Therefore, rapid and early detection of CGMMV infected seeds is very important for preventing disease damage and yield losses. Raman spectroscopy was investigated in this study as a potential tool for rapid, accurate, and nondestructive detection of infected seeds. Raman spectra of healthy and infected seeds were acquired in the 400 cm-1 to 1800 cm-1 wavenumber range and an algorithm based on partial least-squares discriminant analysis was developed to classify infected and healthy seeds. The classification model’s accuracies for calibration and prediction data sets were 100% and 86%, respectively. Results showed that the Raman spectroscopic technique has good potential for nondestructive detection of virus-infected seeds.
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Hoonsoo Lee, Hyoun-Sub Lim, and Byoung-Kwan Cho "Classification of cucumber green mottle mosaic virus (CGMMV) infected watermelon seeds using Raman spectroscopy", Proc. SPIE 9864, Sensing for Agriculture and Food Quality and Safety VIII, 98640D (17 May 2016); https://doi.org/10.1117/12.2228264
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Cited by 1 scholarly publication and 2 patents.
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KEYWORDS
Raman spectroscopy

Calibration

Data modeling

Nondestructive evaluation

Agriculture

Luminescence

Spectroscopy

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