Direct Detection of<i>Cylindrocarpon destructans</i>, Root Rot Pathogen of Ginseng by Nested PCR from Soil Samples

Jang, Chang Soon; Lim, Jeong-Hyeon; Seo, Mun Won; Song, Jeong Young; Kim, Hong Gi

doi:10.4489/myco.2010.38.1.033

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…C . destructans may survive in soil for over 10 years, thereby complicating the control of root rot [ 4 ]. The accumulation of soilborne pathogens and allelochemicals in P .…”

Section: Introductionmentioning

confidence: 99%

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Time-Course Transcriptome Analysis Reveals Resistance Genes of Panax ginseng Induced by Cylindrocarpon destructans Infection Using RNA-Seq

Gao

et al. 2016

PLoS ONE

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Panax ginseng C. A. Meyer is a highly valued medicinal plant. Cylindrocarpon destructans is a destructive pathogen that causes root rot and significantly reduces the quality and yield of P. ginseng. However, an efficient method to control root rot remains unavailable because of insufficient understanding of the molecular mechanism underlying C. destructans-P. ginseng interaction. In this study, C. destructans-induced transcriptomes at different time points were investigated using RNA sequencing (RNA-Seq). De novo assembly produced 73,335 unigenes for the P. ginseng transcriptome after C. destructans infection, in which 3,839 unigenes were up-regulated. Notably, the abundance of the up-regulated unigenes sharply increased at 0.5 d postinoculation to provide effector-triggered immunity. In total, 24 of 26 randomly selected unigenes can be validated using quantitative reverse transcription (qRT)-PCR. Gene ontology enrichment analysis of these unigenes showed that “defense response to fungus”, “defense response” and “response to stress” were enriched. In addition, differentially expressed transcription factors involved in the hormone signaling pathways after C. destructans infection were identified. Finally, differentially expressed unigenes involved in reactive oxygen species and ginsenoside biosynthetic pathway during C. destructans infection were indentified. To our knowledge, this study is the first to report on the dynamic transcriptome triggered by C. destructans. These results improve our understanding of disease resistance in P. ginseng and provide a useful resource for quick detection of induced markers in P. ginseng before the comprehensive outbreak of this disease caused by C. destructans.

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“…C . destructans may survive in soil for over 10 years, thereby complicating the control of root rot [ 4 ]. The accumulation of soilborne pathogens and allelochemicals in P .…”

Section: Introductionmentioning

confidence: 99%

“…Researchers studied the genetic diversity and pathogenicity of C . destructans [ 4 , 9 ]. However, the P .…”

Section: Introductionmentioning

confidence: 99%

Time-Course Transcriptome Analysis Reveals Resistance Genes of Panax ginseng Induced by Cylindrocarpon destructans Infection Using RNA-Seq

Gao

et al. 2016

PLoS ONE

View full text Add to dashboard Cite

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“…However, the quality and quantity of ginseng have decreased by 30–60% owing to various soil-mediated root diseases ( Young Sook et al., 2012 ; Farh et al., 2018 ). Root rot caused by Cylindrocarpon destructans is the main soil-mediated disease affecting ginseng crops in Korea, and repeated cultivation of ginseng leads to a very high possibility of infection ( Jang et al., 2010 ).…”

Section: Introductionmentioning

confidence: 99%

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

Park

Kim²,

Faqeerzada

et al. 2023

Front. Plant Sci.

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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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“…There are many existing methods [27,28] to identify the presence of Cylindrocarpon destructans, but these methods are destructive in nature. The root rot disease has been identified from the plant leaves using hyperspectral leaf images and machine learning techniques [25].…”

Section: Introductionmentioning

confidence: 99%

Analysis of RGB Plant Images to Identify Root Rot Disease in Korean Ginseng Plants Using Deep Learning

et al. 2022

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Ginseng is an important medicinal plant in Korea. The roots of the ginseng plant have medicinal properties; thus, it is very important to maintain the quality of ginseng roots. Root rot disease is a major disease that affects the quality of ginseng roots. It is important to predict this disease before it causes severe damage to the plants. Hence, there is a need for a non-destructive method to identify root rot disease in ginseng plants. In this paper, a method to identify the root rot disease by analyzing the RGB plant images using image processing and deep learning is proposed. Initially, plant segmentation is performed, and then the noise regions are removed in the plant images. These images are given as input to the proposed linear deep learning model to identify root rot disease in ginseng plants. Transfer learning models are also applied to these images. The performance of the proposed method is promising in identifying root rot disease.

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Direct Detection ofCylindrocarpon destructans, Root Rot Pathogen of Ginseng by Nested PCR from Soil Samples

Cited by 10 publications

References 20 publications

Time-Course Transcriptome Analysis Reveals Resistance Genes of Panax ginseng Induced by Cylindrocarpon destructans Infection Using RNA-Seq

Time-Course Transcriptome Analysis Reveals Resistance Genes of Panax ginseng Induced by Cylindrocarpon destructans Infection Using RNA-Seq

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

Analysis of RGB Plant Images to Identify Root Rot Disease in Korean Ginseng Plants Using Deep Learning

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