• The Plant Pathology Journal
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• v.20 no.4
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• pp.302-307
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• 2004

Three pairs of specific primers were developed for rapid and precise RT-PCR detection of three seed-transmissible viruses, namely Peanut clump virus (PCV, Pecluvirus), White clover mosaic virus (WCIMV, Potexvirus) and Carrot red leaf virus (CaRLV, Luteovirus). Each primer set was found in conserved region through multiple sequence alignment in the DNAMAN. Total nucleic acids extracted from PCV-, WCMV-, and CaRLV-infected seeds and healthy plants were used for RT-PCR detection using each virus-specific primer, Sizes of PCV, WCIMV, and CaRLV PCR products were 617bp (PCV-uni5 and PCV-uni3 primers), 561bp (WCMV-CP5 and WCMV-CP3 primers), and 626bp (CL1-UP and CL2-DN primers); which corresponded to the target sizes. Nucleotides sequences of each amplified cDNA were confirmed which belonged to the original virus. This study suggests that these virus-specific primer sets can specifically amplify viral sequences in infected seeds. Thus, they can be used for specific detection of three viruses (PCV, WCMV and CaRLV) from imported seed samples for plant quarantine service.

• Korean Journal Plant Pathology
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• v.2 no.2
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• pp.96-101
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• 1986

Total 29 commercial crucifer seed lots were tested for seed transmission of Xanthomonas campestris pv. campestris by seed washing liquid plating assay. One imported cabbage seed lot was found to carry Xanthomonas campestris pv. campestris. Several methods and chemicals for eradication of Xanthomonas campestris pv. campestris in and on the cabbage seed were tested for effectiveness. Soaking cabbage seed in $3\3%$ hydrogen peroxide solution for 30 minutes effectively eradicated Xanthomonas campestris pv. campestris in a naturally infested seed lot. In a field survey, black rot turned out to be an important disease in cabbage in Korea.

• Journal of KIISE
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• v.44 no.10
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• pp.1105-1111
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• 2017

Influence maximization (IM) is the problem of finding a seed set composed of k nodes that maximizes the influence spread in social networks. However, one of the biggest problems of existing solutions for IM is that it takes too much time to select a k-seed set. This performance issue occurs at the micro and macro levels. In this paper, we propose a fast hybrid method that addresses two issues at micro and macro levels. Furthermore, we propose a path-based community detection method that helps to select a good seed set. The results of our experiment with four real-world datasets show that the proposed method resolves the two issues at the micro and macro levels and selects a good k-seed set.

• Korean Journal Plant Pathology
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• v.14 no.6
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• pp.630-635
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• 1998

Tobacco mosaic tobamovirus (TMV), cucumber mosaic cucumovirus (CMV), cucumber green mottle mosaic tobamovirus (CGMMV) and zucchini yellow mosaic potyvirus (ZYMV) from individual fruits and seeds of hot pepper and cucumber were detected by the reverse transcription-polymerase chain reaction (RT-PCR). The dilution end-points for RT-PCR in curde sap from TMV. and CMV - infected hot pepper leaves and CMV - and CGMMV-infected cucumber leaves were 10-5. However, the amount of PCR product obtained from preparation of ZYMV-infected cucumber leaf was 10-fold lower than those of CMV or CGMMV-infected cucumber leaves. In hot pepper, both TMV and CMV were detected in all parts of the fruit wall tissue, but the yields of PCR products in the fruit stalk and its surrounding tissues were higher than those of the end parts of the fruit. On the other hand, in cucumber fruit infected with CMV, CGMMV or ZYMV, the fruit wall tissue and seed located in both stalk and end parts showed higher yields of PCR products than those of intermediate parts. Of five viruses that were analysed, only TMV in hot pepper seed, and CGMMV and CMV in cucumber seed were detected in testa parts.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.23-29
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• 2020

The National Institute of Agricultural Sciences of the Rural Developement Administration (NAS, RDA) is conducting various studies on various crops, such as monitoring the cultivation environment and analyzing harvested seeds for high-throughput phenotyping. In this paper, we propose a deep learning-based rice seed segmentation method to analyze the seeds of various crops owned by the NAS. Using Mask-RCNN deep learning model, we perform the rice seed segmentation from manually taken images under specific environment (constant lighting, white background) for analyzing the seed characteristics. For this purpose, we perform the parameter tuning process of the Mask-RCNN model. By the proposed method, the results of the test on seed object detection showed that the accuracy was 82% for rice stem image and 97% for rice grain image, respectively. As a future study, we are planning to researches of more reliable seeds extraction from cluttered seed images by a deep learning-based approach and selection of high-throughput phenotype through precise data analysis such as length, width, and thickness from the detected seed objects.

• Proceedings of the Korean Nutrition Society Conference
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• 2001.05a
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• pp.200.2-200
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• 2001

• Mycobiology
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• v.51 no.4
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• pp.195-209
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• 2023

The seed borne disease such as bakanae is difficult to control. Crop yield loss caused by bakanae depending on the regions and varieties grown, ranging from 3.0% to 95.4%. Bakanae is an important disease of rice worldwide and the pathogen was identified as Fusarium fujikuroi Nirenberg (teleomorph: Gibberella fujikuroi Sawada). Currently, four Fusaria (F. fujikuroi, F. proliferatum, F. verticillioides and F. andiyazi) belonging to F. fujikuroi species complex are generally known as the pathogens of bakanae. The infection occurs through both seed and soil-borne transmission. When infection occurs during the heading stage, rice seeds become contaminated. Molecular detection of pathogens of bakanae is important because identification based on morphological and biological characters could lead to incorrect species designation and time-consuming. Seed disinfection has been studied for a long time in Korea for the management of the bakanae disease of rice. As seed disinfectants have been studied to control bakanae, resistance studies to chemicals have been also conducted. Presently biological control and resistant varieties are not widely used. The detection of this pathogen is critical for seed certification and for preventing field infections. In South Korea, bakanae is designated as a regulated pathogen. To provide highly qualified rice seeds to farms, Korea Seed & Variety Service (KSVS) has been producing and distributing certified rice seeds for producing healthy rice in fields. Therefore, the objective of the study is to summarize the recent progress in molecular identification, fungicide resistance, and the management strategy of bakanae.

• Journal of Biomedical Engineering Research
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• v.31 no.6
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• pp.427-433
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• 2010

Although tracking methods are efficient and popular for vessel segmentation, they require a seed to initiate an instance of tracking. In this paper, a new method to detect new seeds for tracking of arterial segments from CT angiography (CTA) and to construct a vascular structure is proposed. The proposed algorithm is based on shape analysis of connected components in a volume of interest around a vessel segment which was already extracted by tracking. The eigenvalues of the covariance matrix are used as the shape features for detection. The experimental results on actual clinical data showed that the results totally revealed the arterial tree not hindered by bone or veins. In visual comparison to a method which combines registration and subtraction of both pre-contrast and post-contrast CT volumes, the proposed method produced comparable results to the reference method and were confirmed of its feasibility for clinical use of reducing the cost and burden of patients.

• Research in Plant Disease
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• v.17 no.1
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• pp.52-58
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• 2011

The aim of this research was to develop specific and sensitive PCR-based procedures for simultaneous detection of economically important plant pathogenic bacteria and seed borne virus in commercial Brassicaceae crop seeds, Xanthomonns campestris pv. campestris (Xcc) and Lettuce Mosaic Virus (LMV). Bacterial and virus diseases of Brassicaceae leaves are responsible for heavy losses. PCR with arbitral primers: selection of specific primers, performance of PCR with specific primers and determination of the threshold level for pathogens detection. To detect simultaneously the Xcc and LMV in commercial Brassicaceae crop seeds (lettuce, kohlrabi, radish, chinese cabbage and cabbage), two pairs of specific primer (LMV-F/R, Xcc-F/R) were synthesized by using primer-blast program (http://www.ncbi.nlm.nih.gov/tools/primer-blast/). The multiplex PCR for the two pathogens in Brassicaceae crop seeds could detect specifically without interference among primers and/or cDNA of other plant pathogens. The pathogen detection limit was determined at 1 ng of RNA extracted from pathogens. In the total PCR results for pathogen detection using commercial kohlrabi (10 varieties), lettuce (50 varieties), radish (20 varieties), chinese cabbage (20 varieties) and cabbage (20 varieties), LMV and Xcc were detected from 39 and 2 varieties, respectively. In the PCR result of lettuce, LMV and Xcc were simultaneously detected in 8 varieties.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.