• The Plant Pathology Journal
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• v.38 no.5
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• pp.432-448
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• 2022

Planthopper infestation in rice causes direct and indirect damage through feeding and viral transmission. Host microbes and small RNAs (sRNAs) play essential roles in regulating biological processes, such as metabolism, development, immunity, and stress responses in eukaryotic organisms, including plants and insects. Recently, advanced metagenomic approaches have facilitated investigations on microbial diversity and its function in insects and plants, highlighting the significance of microbiota in sustaining host life and regulating their interactions with the environment. Recent research has also suggested significant roles for sRNA-regulated genes during rice-planthopper interactions. The response and behavior of the rice plant to planthopper feeding are determined by changes in the host transcriptome, which might be regulated by sRNAs. In addition, the roles of microbial symbionts and sRNAs in the host response to viral infection are complex and involve defense-related changes in the host transcriptomic profile. This review reviews the structure and potential functions of microbes and sRNAs in rice and the associated planthopper species. In addition, the involvement of the microbiota and sRNAs in the rice-planthopper-virus interactions during planthopper infestation and viral infection are discussed.

• The Plant Pathology Journal
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• v.39 no.5
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• pp.417-429
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• 2023

Ralstonia solanacearum species complex (RSSC) is a soil borne plant pathogen causing bacterial wilt on various important crops, including Solanaceae plants. The bacterial pathogens within the RSSC produce exopolysaccharide (EPS), a highly complicated nitrogencontaining heteropolymeric polysaccharide, as a major virulence factor. However, the biosynthetic pathway of the EPS in the RSSC has not been fully characterized. To identify genes in EPS production beyond the EPS biosynthetic gene operon, we selected the EPS-defective mutants of R. pseudosolanacearum strain SL341 from Tn5-inserted mutant pool. Among several EPSdefective mutants, we identified a mutant, SL341P4, with a Tn5-insertion in a gene encoding a putative NDP-sugar epimerase, a putative membrane protein with sugar-modifying moiety, in a reverse orientation to EPS biosynthesis gene cluster. This protein showed similar to other NDP-sugar epimerases involved in EPS biosynthesis in many phytopathogens. Mutation of the NDP-sugar epimerase gene reduced EPS production and biofilm formation in R. pseudosolanacearum. Additionally, the SL341P4 mutant exhibited reduced disease severity and incidence of bacterial wilt in tomato plants compared to the wild-type SL341 without alteration of bacterial multiplication. These results indicate that the NDP-sugar epimerase gene is required for EPS production and bacterial virulence in R. pseudosolanacearum.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.115-120
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• 2023

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.204-204
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• 2022

Transformant construction using protoplasts requires less sample preparation time than particle bombardment and Agrobacterium-mediated transfection. There are two protoplast transfection methods: the PEG-mediated transfection method and the Lipofectamine transfection method. When Lipofectamine is mixed with DNA, Lipofectamine surrounds DNA like a cell membrane because of the positive charge of Lipofectamine. The Lipofectamine-DNA complex makes DNA insertion into cells easier. Fectin has similar functions to lipofectamine and is less expensive than lipofectamine. The 3D-fectin technology has been highlighted in animal cell transfection. Therefore, we performed PEG-mediated transfection, Lipofectamine transfection, and 3D-pectin transfection with a GFP construct. Protoplasts were isolated using the first leaf of "Bobwhite" after 4 hours of incubation in an isolation Buffer (cellulase + macerozyme). Protoplasts transformed by each method were cultured for 48 hours, and then GFP fluorescence expression was confirmed under confocal microscopy. GFP signals were detected in PEG-mediated transfection and Lipofectamine transfection. And the GFP signals were also detected in protoplasts to which 3D-fectin technology was applied, suggesting that 3D-fectin technology can be used for plant protoplast transfection.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.107-112
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• 2024

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.

• Korean Journal of Plant Taxonomy
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• v.42 no.1
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• pp.40-49
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• 2012

The NE Asiatic Solidago virgaurea complex in Korea has been reported on 5 taxa (S. virgaurea subsp. asiatica, S. virgaurea var. taquetii, S. virgaurea var. coreana, S. virgaurea subsp. leiocarpa, and S. virgaurea subsp. gigantea). However, the broad morphological variations and a lack of diagnostic characteristics have made it difficult to distinguish these taxa and have thus resulted in a complicated taxonomy in the complex. Therefore, to clarify the classification and delimitation of each taxon, the morphological characteristics of the S. virgaurea complex were investigated by examining the original descriptions and type specimens. Field work was also conducted to investigate the morphological and geographic features. In conclusion, S. japonica Kitam., as a legitimate name, was distributed all over the country except for the Is. Ulleung-do in Korea, as distinguished from S. virgaurea L. Both S. virgaurea var. taquetii and S. virgaurea var. coreana were considered as synonyms of S. japonica, as their morphological characteristics were within the variation range of those of S. japonica. Furthermore, S. virgaurea subsp. leiocarpa does not occur in Korea. Additional investigations are required to clarify the classification of S. virgaurea subsp. gigantea, whose populations were not found during the investigation in this study. S. dahurica, meanwhile, was distributed in the northern part of North Korea.

• Research in Plant Disease
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• v.24 no.4
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• pp.313-320
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• 2018

Fusarium infection rate of the paddy rice grain after harvest seemed to be influenced by the average temperature from late July (before heading) to the end of September (during ripening). In case of 2010 and 2013 in which average temperature of the same period was similar, Fusarium infection was related to cumulative precipitation, cumulative precipitation days, and precipitation durations over two days. The distribution ratio of Fusarium species complex isolated from paddy rice grains after harvest was 57% in 2010 and 45% in 2013 for Fusarium graminearum species complex (FGSC), 35% and 50% for Fusarium incarnatum-equiseti species complex, and 8% and 5% for Fusarium fujikuroi species complex (FFSC). The distribution ratios of FGSC and FFSC were higher in 2010 than 2013. Among the total 26 promoted rice varieties, the 'Mihyang' showed resistant response against the natural infection with Fusarium species belonging to FGSC and the varieties of 'Nampyeong', 'Hi-ami'and 'Younghojinmi' showed resistant response against the natural infection with overall Fusarium pathogens. Majority of the promoted rice varieties could not be classified for resistance or susceptibility. These results are valuable as basic data to determine the resistance and susceptibility of rice variety against Fusarium spp. infection in the field.

• Journal of Environmental Science International
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• v.22 no.12
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• pp.1643-1650
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• 2013

This study investigated water quality of effluents and stream from the sewage treatment plants located at Gumi Complex 4, Gumi, and Wonpyeong in Gumi. Downstream region was found to increase the concentration of nutrients for sewage treatment plant effluent. Both phosphorus and nitrogen were accounted most as soluble form. In particular, the high ratio of dissolved effluent of sewage treatment plants were investigated. In the streams, Phosphorus concentration was high during rainy season and nitrogen concentration was high in the dry season. Sewage treatment plant effluent was relatively less microbial activity and nutrient concentrations were higher in the winter. TN/TP ratio was the highest in the upstream region and the lowest in the sewage treatment plant effluent. The effect of the nutrient matter from a discharge of a sewage treatment plant on rivers varied depending on the size of the river and the treatment plant. However, the influence of the concentration was greater than that of flowrate. Sewage treatment plant effluent loads phosphorus, nitrogen accounted for 8% and 6% respectively at the point N3 of the Nakdong river.

• Korean Journal Plant Pathology
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• v.14 no.3
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• pp.191-202
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• 1998

About 300 actinomycetes were isolated from two forest and one sea-shore soil and tested for inhibitory effects on mycelial growth of six plant pathogenic fungi Magnaporthe grisea, Alternaria mali, Colletotrichum gloeosporioides, Phytophthora capsici, Fusarium oxysporum f. sp. cucumerinum, and Rhizoctonia solani. Among 300 actinomycetes tested, only 16 actinomycetes showed the antifungal activity against the test fungi. Isolate NH 50 was selected for production and purification of antifungal antibiotic substances. Actinomycete isolate NH 50 displayed the broad antifungal spectra against 11 plant pathogenic fungi. To identify actinomycete isolate NH 50, cultural characteristics on various agar media, diaminopimelic acid type, and morphological characteristics by scanning electron microscopy were examined. As a result, actinomycete isolate NH 50 was classified as a rare actinomycete that had LL-DAP type and did not produce spores. After incubation of isolate NH 50 in yeast extract-malt extract-dextrose broth, antifungal compound NH-B1 that inhibited mycelial growth of some plant pathogenic fungi was purified from the methanol eluates of XAD-16 resins by a series of purification procedures, i.e., silica gel flash chromatography, C18 flash chromatography, Sephadex LH-20 column chromatography, silica gel medium pressure liquid chromatography (MPLC), C18 MPLC, and high pressure liquid chromatography (HPLC). UV spectrum and 1HNMR spectrum of antifungal compound NH-B1 dissolved in methanol were examined. The antibiotic NH-B1 showed the major peaks at 230 and 271.2nm. Based on the data of 1H-NMR spectrum, NH-B1 was confirmed to be an extremely complex polymer of sugars called polysaccharides. The antibiotic NH-B1 showed strong antifungal activity against Alternaria solani and Cercospora kikuchi, but weak activity against M. grisea.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.213-220
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• 2006

Plant construction industry is a high value-adding industry because it is complex industry comprising engineering, procurements of equipments and construction. So, Revenue increase in overseas plant projects would boost up not only domestic construction industry but also growth of national economy. Recently, overseas plant-construction market is expanding dramatically. For instant, Middle-east countries are constantly increasing their orders for the construction of petro-chemical plants stimulated by sky-rocketing oil prices. The purpose of this research is to develop management techniques for plant projects such as work break-down structure, knowledge management system, logistics & procurement system, and risk assessment tools. We believe our research would contribute to the competion of Korean engineeing companies and contractors in overseas plant-construction market.