• Mycobiology
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• v.35 no.1
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• pp.39-43
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• 2007

The antifungal effect of pine needle extract prepared by a distinguishable extraction method and the dry distillation method, was examined. The effect of this extract itself was insignificant. The chemical components of pine needle extract were then investigated by gas chromatographic analysis, and four, chemical components, acetol, furfural, 5-methyl furfural, and terpine4-ol, were identified. The antifungal effects of those four chemical components against Alternaria mali (A. mali), an agent of Alternaria blotch of apple, were then examined. It was observed that the minimum inhibitory concentrations (MICs) were 6.25, 0.78, 0.78, and 12.5 (mg/ml) of acetol, furfural, 5-methyl furfural, and terpine-4-ol, respectively. MICs of furfural and 5-methyl furfural had the same order of magnitude as that of an antifungal agrochemical, chlorothalonil. Although furfural itself can not be completely substituted for an antifungal agrochemical, a partial mixture of furfural and antifungal agrochemical may be used as a substitute. The use of agrochemicals for the prevention of plant disease caused by pathogenic fungus such as A. mali could be partially reduced by the application of this mixture.

• Biomedical Science Letters
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• v.25 no.3
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• pp.211-217
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• 2019

Research has established a strong connection between a diet rich in antioxidants and a decreased incidence of cardiovascular disease and cancer. These diets prominently feature fruits and vegetables containing high amounts of vitamins A, B, C and E, carotenoids, and minerals. Different processing conditions for these foods can alter their nutrient complement and potency. This study compared the antioxidant properties of a range of processed fruits and vegetables to see which yielded the highest level of antioxidant activity. We used an acetaminophen-induced oxidative stress mouse model to evaluate the antioxidant effects of extracts of processed apple, pear, carrot, cabbage, broccoli, and radish. Our results showed that the administration of these fruits decreased the expression of oxidative stress indicators such as ALT, AST, catalase, superoxide dismutase, GPx, and 8-OHdG. They also significantly protected mice livers from APAP-induced damage, as shown by histological evaluation. Our results have demonstrated the positive effects of processed fruits and vegetables in a mouse model of oxidative stress.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.410-416
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• 2022

Erwinia amylovora, the causal agent of fire-blight disease in apple and pear trees, was first isolated in South Korea in 2015. Although numerous studies, including omics analyses, have been conducted on other strains of E. amylovora, studies on South Korean isolates remain limited. In this study, we conducted a comparative proteomic analysis of the strain TS3128, cultured in three media representing different growth conditions. Proteins related to virulence, type III secretion system, and amylovoran production, were more abundant under minimal conditions than in rich conditions. Additionally, various proteins associated with energy production, carbohydrate metabolism, cell wall/membrane/envelope biogenesis, and ion uptake were identified under minimal conditions. The strain TS3128 expresses these proteins to survive in harsh environments. These findings contribute to understanding the cellular mechanisms driving its adaptations to different environmental conditions and provide proteome profiles as reference for future studies on the virulence and adaptation mechanisms of South Korean strains.

• The Plant Pathology Journal
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• v.17 no.2
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• pp.77-82
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• 2001

Erwinia amylovora causes a devastating disease called fire blight in rosaceous trees and shrubs such as apple, pear, and raspberry. To successfully infect its hosts, the pathogen requires a set of clustered genes termed hrp. Studies on the hrp system of E. amylovora indicated that it consists of three functional classes of genes. Regulation genes including hrpS, hrpS, hrpXY, and hrpL produce proteins that control the expression of other genes in the cluster. Secretion genes, many of which named hrc, encode proteins that may form a transmembrane complex, which is devoted to type III protein secretion. Finally, several genes encode the proteins that are delivered by the protein secretion apparatus. They include harpins, DspE, and other potential effector proteins that may contribute to proliferation of E. amylovora inside the hosts. Harpins are glycine-rich heat-stable elicitors of the hypersensitive response, and induce systemic acquired resistance. The pathogenicity protein DseE is homologous and functionally similar to an avirulence protein of Pseudomonas syringae. The region encompassing the hrpldsp gene cluster of E. amylovora shows features characteristic of a genomic island : a cryptic recombinase/integrase gene and a tRNA gene are present at one end and genes corresponding to those of the Escherichia coli K-12 chromosome are found beyond the region. This island, designated the Hrp pathogenicity island, is more than 60 kilobases in size and carries as many as 60 genes.

• The Korean Journal of Mycology
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• v.51 no.4
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• pp.447-460
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• 2023

Fire blight, a plant disease caused by Erwinia amylovora, continues to cause considerable damage to fruit-bearing trees belonging to the Rosaceae family, such as apples and pears. In Korea, to hinder its rapid spread diseased apple and pear trees have been buried since its first occurrence. To determine the safety of this control method, the buried plant materials and adjacent soil have been investigated. In the process of investigating the microbiota of the buried soil, Bisifusarium allantoides, Botryotrichum domesticum, Microascus verrucosus, Paraphoma pye, Phaeosphaeria culmorum, Ramophialophora globispora, Sordaria tomentoalba, and Striaticonidium brachysporum were identified as unrecorded species in Korea. To report the above eight species as Korean unrecorded species, we report their morphological and molecular features in this study.

• Research in Plant Disease
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• v.29 no.1
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• pp.23-38
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• 2023

The fire blight caused by Erwinia amylovora (Ea) is a devastating disease of Rosaceae plants, including commercially important apple and pear trees. Since the first report in Korea in May 2015, it has been spreading to neighboring regions gradually. Host plants can be infected by pollinators like bees, rainfall accompanied by wind, and cultural practices such as pruning. Many studies have revealed that wild Rosaceae plants such as Cotoneaster spp., Crataegus spp., Pyracantha spp., Prunus spp., and Sorbus spp. can be reservoirs of Ea in nature. However, wild Rosaceae plants in Korea have not been examined yet whether they are susceptible to fire blight. Therefore, the susceptibility to fire blight was examined with 25 species in 10 genera of wild Rosaceae plants, which were collected during 2020-2022, by artificial inoculation. Bacterial suspension (10⁸ cfu/ml) of Ea type strain TS3128 was inoculated artificially in flowers, leaves, stems, and fruits of each plant species, and development of disease symptoms were monitored. Moreover, the presence of Ea bacteria from inoculated samples were checked by conventional polymerase chain reaction. Total 14 species of wild Rosaceae plants showed disease symptoms of fire blight, and Ea bacteria were detected inside of inoculated plant parts. These results suggest that wild Rosaceae plants growing nearby commercial apple and pear orchards in Korea can be Ea reservoirs, and thus they should be monitored regularly to minimize the damage by Ea infection and spreading.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.923-935
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• 2022

This paper deals with detection and classification of leaf diseases for phenomics systems. As the smart farm systems of plants are increased, It is important to determine quickly the abnormal growth of plants without supervisors. This paper considers the color distribution and shape information of leaf diseases, and designs two deep leaning networks in training the leaf diseases. In the first step, color distribution of input image is analyzed for possible diseases. In the second step, the image is first partitioned into small segments using mean shift clustering, and the color information of each segment is inspected by the proposed Color Network. When a segment is determined as disease, the shape parameters of the segment are extracted and inspected by proposed Shape Network to classify the leaf disease types in the third step. According to the experiments with two types of diseases (frogeye/rust and tipburn) for apple leaves and iceberg, the leaf diseases are detected with 92.3% recall for a segment and with 99.3% recall for an input image where there are usually more than two disease segments. The proposed method is useful for detecting leaf diseases quickly in the smart farm environment, and is extendible to various types of new plants and leaf diseases without additional learning.

• Korean journal of applied entomology
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• v.25 no.4 s.69
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• pp.221-228
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• 1986

An empirical model to predict initial disease occurrence and subsequent progress of Alternaria leaf spot was constructed based on the modified degree day temperature and frequency of rainfall in three years field experiments. Climatic factors were analized 10-day bases, beginning April 20 to the end of August, and were used as variables for model construction. Cumulative degree portion (CDP) that is over $10^{\circ}C$ in the daily average temperature was used as a parameter to determine the relationship between temperature and initial disease occurrence. Around one hundred and sixty of CDP was needed to initiate disease incidence. This value was considered as temperature threshhold. After reaching 160 CDP, time of initial occurrence was determined by frequency of rainfall. At least four times of rainfall were necessary to be accumulated for initial occurrence of the disease after passing temperature threshhold. Disease progress after initial incidence generally followed the pattern of frequency of rainfall accumulated in those periods. Apparent infection rate (r) in the general differential equation dx/dt=xr(1-x) for individual epidemics when x is disease proportion and t is time, was a linear function of accumulation rate of rainfall frequency (Rc) and was able to be directly estimated based on the equation r=1.06Rc-0.11($R^2=0.993$). Disease severity (x) after t time could be predicted using exponential equation $[x/(1-x)]=[x_0/(1-x)]e^{(b_0+b_1R_c)t}$ derived from the differential equation, when $x_0$ is initial disease, $b_0\;and\;b_1$ are constants. There was a significant linear relationship between disease progress and cumulative number of air-borne conidia of Alternaria mali. When the cumulative number of air-borne conidia was used as an independent variable to predict disease severity, accuracy of prediction was poor with $R^2=0.3328$.

• Research in Plant Disease
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• v.18 no.4
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• pp.391-395
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• 2012

To investigate the occurrence of viruses in peach, leaf samples were collected from peach trees in commercial orchard of six areas in Korea. Reverse transcription polymerase chain reaction (RT-PCR) was used to identify the presence of the following stone fruit viruses: Apple chlorotic leaf spot virus (ACLSV), Apple mosaic virus (ApMV), Prune dwarf virus (PDV), Prunus necrotic ringspot virus (PNRSV) and Plum pox virus (PPV). About 65.0% of the 515 samples were infected with ACLSV and PNRSV. Virus-like symptoms showing mosaic on leaves was observed in ACLSV infected peach trees. However, PNRSV infected peach trees showed no symptoms. These viral DNAs by sequence analysis were confirmed 4 ACLSV isolates and 3 PNRSV isolates. The Korean peach isolates of ACLSV and PNRSV showed 70-99% and 88-99% amino acid sequence identities, respectively, with those reported previously and their amino acid sequence identities with each other were approximately 95% and 88%, respectively. Phylogenetic analysis indicated that the Korean ACLSV isolates belong to the A group of ACLSV. The Korean PNRSV isolates reported in this study were grouped into I (PV32), II (PV96) and III (PE5) groups.

• Research in Plant Disease
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• v.22 no.2
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• pp.100-106
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• 2016

We have studied the mycelia growth of four soil-borne fungal pathogens under light qualities and two lighting types (continuous and intermittent) provided by light-emitting diodes (LEDs). As a result, each mycelia growth on Phytophthora cactorum KACC40166, Athelia rolfsii KACC40170, and Helicobasidium mompa KACC40836 strain showed the similar growth rates within 10% or less difference among treatments compared to dark control, regardless of lighting types. However, the mycelia growth on Rosellinia necatrix KACC40168 strain was significantly suppressed by blue, blue+green and blue+red LED as well as fluorescent lamp compared to a dark control, in common with lighting types. The melanin pigment on R. necatrix KACC40168 strain showed relatively to induce more strongly under green LED and fluorescent lamp, whereas no induction under red LED and a control, regardless of lighting types. Thus, the hypha width on R. necatrix KACC40168 was significantly thinned by blue and blue+green LED compared to a control, in common with lighting types.