• Research in Plant Disease
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• v.24 no.3
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• pp.233-236
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• 2018

A multiplex RT-PCR (mRT-PCR) assay was developed for the detection of the recently reported viruses, Cherry virus A (CVA), Little cherry virus 1 (LChV-1), and Little cherry virus 2 (LChV-2), in cherry plants in Korea. Eight sets of primers were designed for each virus and their specificity was tested by using various combinations of mixed primer sets. From the designed primer sets, one combination was selected and further evaluated to estimate the optimum temperature and detection limits of the mRT-PCR. A newly developed mRT-PCR assay was also tested using 20 cherry samples collected in the field. This mRT-PCR assay may be a useful tool for field surveys of diseases and the rapid detection of these three viruses in cherry plants.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.1-14
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• 2009

The Capacitated Vehicle Routing Problem (CVRP) is the problem that the vehicles stationed at central depot are to be optimally routed to supply customers with demands, satisfying vehicle capacity constraints. The CVRP is the NP-hard as it is a natural generalization of the Traveling Salesman Problem (TSP). In this article, we propose the heuristic algorithm, called the bisection seed detection method, to solve the CVRP. The algorithm is composed of 3-phases. In the first phase, we work out the initial cluster using the improved sweep algorithm. In the next phase, we choose a seed node in each initial cluster by using the bisection seed detection method, and we compose the rout with the nearest node from each seed. At this phase, we compute the regret value to decide the list of priorities for the node assignment. In the final phase, we improve the route result by using the tabu search and exchange algorithm. We compared our heuristic with different heuristics such as the Clark-Wright heuristic and the genetic algorithm. The result of proposed heuristic show that our algorithm can get the nearest optimal value within the shortest execution time comparatively.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1171-1181
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• 2014

In this paper, we propose improved methods which are image conversion and extraction method of watershed seed using morphological characteristic of teeth on complement image. Conventional tooth segmentation methods are occurred low detection ratio at molar region and over, overlap segmentation owing to specular reflection and morphological feature of molars. Therefore, in order to solve the problems of the conventional methods, we propose the image conversion method and improved extraction method of watershed seed. First, the image conversion method is performed using RGB, HSI space of tooth image for to extract boundary and seed of watershed efficiently. Second, watershed seed is reconstructed using morphological characteristic of teeth. Last, individual tooth segmentation is performed using proposed seed of watershed by watershed algorithm. Therefore, as a result of comparison with marker controlled watershed algorithm and the proposed method, we confirmed higher detection ratio and accuracy than marker controlled watershed algorithm.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.490-498
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• 2018

Panicle blight and seed rot disease caused mainly by Burkholderia glumae and Burkholderia gladioli is threatening rice cultivation worldwide. The bacteria have been reported as seed-borne pathogens from rice. Accurate detection of both pathogens on the seeds is very important for limiting the disease dissemination. Novel primer pairs targeting specific molecular markers were developed for the robust detection of B. glumae and B. gladioli. The designed primers were specific in detecting the target species with no apparent cross-reactions with other related Burkholderia species at the expected product size. Both primer pairs displayed a high degree of sensitivity for detection of B. glumae and B. gladioli separately in monoplex PCR or simultaneously in duplex PCR from both extracted gDNA and directly preheated bacterial cell suspensions. Limit of detection was as low as 0.1 ng of gDNA of both species and $3.86{\times}10^2cells$ for B. glumae and $5.85{\times}10^2cells$ for B. gladioli. On inoculated rice seeds, the designed primers could separately or simultaneously detect B. glumae and B. gladioli with a detection limit as low as $1.86{\times}10^3cells$ per rice seed for B. glumae and $1.04{\times}10^4cells$ per rice seed of B. gladioli. The novel primers maybe valuable as a more sensitive, specific, and robust tool for the efficient simultaneous detection of B. glumae and B. gladioli on rice seeds, which is important in combating rice panicle blight and seed rot by early detection and confirmation of the dissemination of pathogen-free rice seeds.

• The Plant Pathology Journal
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• v.22 no.1
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• pp.11-15
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• 2006

Five seed samples of carrot were tested to detect Alternaria spp. by blotter method. A. alternata and A. radicina were detected from all the seed samples as high as $25.8-70.5\%$ and $37.5-63.5\%$, respectively. A. dauci was detected from four seed samples as low as $0.5-7.5\%$. The three Alternaria spp. were detected from the pericarp and the seed coat and endosperm of the carrot seeds but not from the embryo by component plating test. A. alternata and A. radicina were much more detected from the pericarp than the seed coat and endosperm. A. dauci was detected from the pericarp and the seed coat and endosperm at similar rate. The seed sample which was most severely infected with A. radicina showed the lowest rate of germination in the test on top of paper (TP). In the TP test, differences in total infection rate of A. radicina and A. dauci of the seed samples were very closely correlated with those in incidence of seedling rot on the seed samples. However, there was no correlation between infection rate of A. alternata and rate of germination or seedling rot of the seed samples. Soil test for seedling growth revealed that there was no correlation between differences in total infection rate of A. radicina and A. dauci and those in rate of normal seedlings of the seed samples.

• Journal of Bio-Environment Control
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• v.13 no.2
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• pp.90-95
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• 2004

This study was conducted to develop an algorithm for the embryo location in seed by using machine vision. The topic of this research is to detect the embryo location in seed regardless of seed supply direction. In order to detect the embryo location in Cham Bak, Tuktojwa and Hukjong, the effect of seed posture in the supply line was investigated. When the seed posture angle of Chambak from horizontal direction was $30^{\circ}$, the detection accuracy for embryo location was 77.8%, while detection accuracy was 100% for the $0^{\circ}$ or $15^{\circ}$. When seed posture angle of Tuktojwa was $30^{\circ}$ from the horizontal direction, the detection accuracy was 89.5% and it was 100% for the $0^{\circ}$ and $15^{\circ}$. Embryo location detection accuracy for the Hukjong was 94.4% when the seed posture angle from the horizontal direction is $30^{\circ}$, and it was 100% for the $0^{\circ}$ and $15^{\circ}$. When seeds are fed into the posturing and seeding line, the seed postures within $30^{\circ}$ with mechanical means, and at most $15^{\circ}$ seed stand posture. the developed algorithm can detect the embryo position in the seed. So, this embryo detection system is very useful tool in the posturing and seeding line.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.209-220
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• 2012

In this paper, we propose an adaptive pavement region detection method that is robust to changes of structural patterns in a natural scene. In order to segment out a pavement reliably, we propose two step approaches. We first detect the borderline of a pavement and separate out the candidate region of a pavement using VRays. The VRays are straight lines starting from a vanishing point. They split out the candidate region that includes the pavement in a radial shape. Once the candidate region is found, we next employ the adaptive multi-seed region growing(A-MSRG) method within the candidate region. The A-MSRG method segments out the pavement region very accurately by growing seed regions. The number of seed regions are to be determined adaptively depending on the encountered situation. We prove the effectiveness of our approach by comparing its performance against the performances of seed region growing(SRG) approach and multi-seed region growing(MSRG) approach in terms of the false detection rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.687-690
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• 2015

Forward collision warning systems(FCWS) and lane change assist systems(LCAS) need regions of interest for detecting lanes and objects as road regions. Watershed segmentation is effective algorithm that classify the road. That algorithm is split results appear differently depending on Watershed line with local minimum in the early part of the seed. If not road regions or vehicles combined the road's seed, It segment road with the others. For compensate the that defect, It has to adaptive change by road environment. The method is that image segmentate the several of regions of interest. Then It is set in a straight line that is detected in regions of interest. If It was detected cars on seed, seed is adjusted the location. And If It wasn't include the line, seed is adjusted the length for final decision the seed. We can detect the road region using the final seed that selected according to the road environment.

• Research in Plant Disease
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• v.21 no.2
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• pp.74-81
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• 2015

The specific and sensitive nested-PCR method to detect Acidovorax citrulli, a causal agent of bacterial fruit blotch on cucurbitaceae, was developed. PCR primers were designed from the draft genome sequence which was obtained with the Next Generation Sequencing of A. citrulli KACC10651, and the nested-PCR primer set (Ac-ORF 21F/Ac-ORF 21R) were selected by checking of specificity to A. citrulli with PCR assays. The selected nested-PCR primer amplified the 140 bp DNA only from A. citrulli strains, and detection sensitivity of the nested PCR increased 10,000 times of $1^{st}$ PCR detection limit (10 ng genomic DNA/PCR). The nested PCR detected A. citrulli from the all samples of seed surface wash (external seed detection) of the artificially inoculated watermelon seeds with $10^1cfu/ml$ and above population of A. citrulli while the nested PCR could not detected A. citrulli from the mashed seed suspension (internal seed detection) of the all artificially inoculated watermelon seeds. When the naturally infested watermelon seeds (10% seed infested rate with grow-out test) used, the nested PCR detected A. citrulli from 2 seed samples out of 10 replication samples externally and 5 seed samples out of 10 replication samples internally. We believe that the nested-PCR developed in this study will be useful method to detect A. citrulli from the Cucurbitaceae seeds.

• Research in Plant Disease
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• v.17 no.1
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• pp.44-51
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• 2011

The aim of this study was to develop specific and sensitive PCR-based procedures for simultaneous detection of economically important plant seed infection pathogenic bacteria and virus, Xanthomonns campestris pv. vesicatoria (Xcv), Clavibacter michiganensis subsp. michiganensis (Cmm), Erwinia carotovora subsp. carotovora (Ecc), Pepper mild mottle virus (PMMoV) and Tobacco mild green mosaic virus (TMGMV) in pepper and tomato seeds. Most of pepper and tomato bacterial and virus diseases are responsible for germination and growth obstruction. 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 Xcv, Cmm, Ecc, PMMoV and TMGMV in pepper and tomato seeds, five pairs (Cmm-F/R, Ecc-F/R, Xcv-F/R, PMMoV-F/R, TMGMV-F/R) of specific primer were synthesized by primer-blast program. The multiplex PCR for the five pathogens in pepper and tomato seeds could detect specially without interference among primers and/or cDNA of plant seeds and other plant pathogens. The PCR result for pathogen detection using 20 commercial pepper and 10 tomato seed samples, Ecc was detected from 4 pepper and 2 tomato seed samples, PMMoV was detected from 1 pepper seed sample, and PMMoV and TMGMV were simultaneously detected from 1 pepper seed sample.