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Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)

Root rot of Panax ginseng caused by Cylindrocarpon destructans, a soil-borne fungus is typically diagnosed by frequently checking the ginseng plants or by evaluating soil pathogens in a farm, which is a time- and cost-intensive process. Because this disease causes huge economic losses to ginseng far...

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Autores principales: Park, Eunsoo, Kim, Yun-Soo, Faqeerzada, Mohammad Akbar, Kim, Moon S., Baek, Insuck, Cho, Byoung-Kwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930644/
https://www.ncbi.nlm.nih.gov/pubmed/36818876
http://dx.doi.org/10.3389/fpls.2023.1109060
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author Park, Eunsoo
Kim, Yun-Soo
Faqeerzada, Mohammad Akbar
Kim, Moon S.
Baek, Insuck
Cho, Byoung-Kwan
author_facet Park, Eunsoo
Kim, Yun-Soo
Faqeerzada, Mohammad Akbar
Kim, Moon S.
Baek, Insuck
Cho, Byoung-Kwan
author_sort Park, Eunsoo
collection PubMed
description Root rot of Panax ginseng caused by Cylindrocarpon destructans, a soil-borne fungus is typically diagnosed by frequently checking the ginseng plants or by evaluating soil pathogens in a farm, which is a time- and cost-intensive process. Because this disease causes huge economic losses to ginseng farmers, it is important to develop reliable and non-destructive techniques for early disease detection. In this study, we developed a non-destructive method for the early detection of root rot. For this, we used crop phenotyping and analyzed biochemical information collected using the HSI technique. Soil infected with root rot was divided into sterilized and infected groups and seeded with 1-year-old ginseng plants. HSI data were collected four times during weeks 7–10 after sowing. The spectral data were analyzed and the main wavelengths were extracted using partial least squares discriminant analysis. The average model accuracy was 84% in the visible/near-infrared region (29 main wavelengths) and 95% in the short-wave infrared (19 main wavelengths). These results indicated that root rot caused a decrease in nutrient absorption, leading to a decline in photosynthetic activity and the levels of carotenoids, starch, and sucrose. Wavelengths related to phenolic compounds can also be utilized for the early prediction of root rot. The technique presented in this study can be used for the early and timely detection of root rot in ginseng in a non-destructive manner.
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spelling pubmed-99306442023-02-16 Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer) Park, Eunsoo Kim, Yun-Soo Faqeerzada, Mohammad Akbar Kim, Moon S. Baek, Insuck Cho, Byoung-Kwan Front Plant Sci Plant Science Root rot of Panax ginseng caused by Cylindrocarpon destructans, a soil-borne fungus is typically diagnosed by frequently checking the ginseng plants or by evaluating soil pathogens in a farm, which is a time- and cost-intensive process. Because this disease causes huge economic losses to ginseng farmers, it is important to develop reliable and non-destructive techniques for early disease detection. In this study, we developed a non-destructive method for the early detection of root rot. For this, we used crop phenotyping and analyzed biochemical information collected using the HSI technique. Soil infected with root rot was divided into sterilized and infected groups and seeded with 1-year-old ginseng plants. HSI data were collected four times during weeks 7–10 after sowing. The spectral data were analyzed and the main wavelengths were extracted using partial least squares discriminant analysis. The average model accuracy was 84% in the visible/near-infrared region (29 main wavelengths) and 95% in the short-wave infrared (19 main wavelengths). These results indicated that root rot caused a decrease in nutrient absorption, leading to a decline in photosynthetic activity and the levels of carotenoids, starch, and sucrose. Wavelengths related to phenolic compounds can also be utilized for the early prediction of root rot. The technique presented in this study can be used for the early and timely detection of root rot in ginseng in a non-destructive manner. Frontiers Media S.A. 2023-02-01 /pmc/articles/PMC9930644/ /pubmed/36818876 http://dx.doi.org/10.3389/fpls.2023.1109060 Text en Copyright © 2023 Park, Kim, Faqeerzada, Kim, Baek and Cho https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Park, Eunsoo
Kim, Yun-Soo
Faqeerzada, Mohammad Akbar
Kim, Moon S.
Baek, Insuck
Cho, Byoung-Kwan
Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)
title Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)
title_full Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)
title_fullStr Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)
title_full_unstemmed Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)
title_short Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)
title_sort hyperspectral reflectance imaging for nondestructive evaluation of root rot in korean ginseng (panax ginseng meyer)
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930644/
https://www.ncbi.nlm.nih.gov/pubmed/36818876
http://dx.doi.org/10.3389/fpls.2023.1109060
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