• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.343-350
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• 2022

It is worth verifying the effectiveness of data integration between data with different features. This study investigated whether the data integration affects the accuracy of deep neural network (DNN), and which integration method shows the best improvement. This study used two different public datasets. One public dataset was taken in an actual farm in India. And another was taken in a laboratory environment in Korea. Leaf images were selected from two different public datasets to have five classes which includes normal and four different types of plant diseases. DNN used pre-trained VGG16 as a feature extractor and multi-layer perceptron as a classifier. Data were integrated into three different ways to be used for the training process. DNN was trained in a supervised manner via the integrated data. The trained DNN was evaluated by using a test dataset taken in an actual farm. DNN shows the best accuracy for the test dataset when DNN was first trained by images taken in the laboratory environment and then trained by images taken in the actual farm. The results show that data integration between plant images taken in a different environment helps improve the performance of deep neural networks. And the results also confirmed that independent use of plant images taken in different environments during the training process is more effective in improving the performance of DNN.

• Journal of Korean Society of Forest Science
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• v.59 no.1
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• pp.121-142
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• 1983

Recently mycorrhizal research has been one of the most fast-growing research areas in modern plant science and microbiology. The application potential of mycorrhizal techniques to agriculture and forestry is enormous in view of the ubiquitous nature of mycorrhizae and known benefits of mycorrhizae to host plants. Unfortunately, very few scientists in Korea are currently involved in mycorrhizal research. When a team of American plant pathologists visited Korea in September 1982 to participate in the Korea-U.S.A. Joint Seminar on Forest Diseases and Insect Pests, they were surprised by the principal author's statement that there was no single research project on mycorrhizae sponsored by Korean government or any scientific institutions. The author initiated a few years ago a research project on the ecology of tree mycorrhizae with a foreign financial support. Major areas of interest were survey of ectomycorrhizae in relation to soil fertility, taxonomic distribution of mycorrhizae among woody plants, identification of ectomycorrhizal fungi, and growth response of woody plants to artificial inoculation. In spite of the enormous application potential of mycorrhizae to agronomic plants, the subject of mycorrhizae has not been recognized by Korean agronomists, foresters or pathologists. The purpose of this review rather written in Korean is to introduce the techniques of mycorrhizal research to Korean scientists and to urge them to participate in challenging new scientific field which might bring us a remarkable increase in crop productivity and tree growth through manipulation of this unique symbiosis. In this review, following topics were discussed in the same order: introduction; brief history of mycorrhizal research; morphology and classification of mycorrhizae; distribution of mycorrhizae in plant kingdom and in soil profile; physiology of mycorrhizae (functions, mineral nutrition, mycorrhizal formation); interaction of mycorrhizae with soil-born plant pathogens. mycorrhizae in nitrogen-fixing plants; application of mycorrhizal techniques to nursery practices (isolation, culture, inoculation, and response); prospect in the future.

• Journal of Veterinary Science
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• v.21 no.3
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• pp.43.1-43.13
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• 2020

Background: Canine parvovirus (CPV) and feline panleukopenia (FPV) cause severe intestinal disease and leukopenia. Objectives: In Korea, there have been a few studies on Korean FPV and CPV-2 strains. We attempted to investigate several genetic properties of FPV and CPV-2. Methods: Several FPV and CPV sequences from around world were analyzed by Bayesian phylo-geographical analysis. Results: The parvoviruses strains were newly classified into FPV, CPV 2-I, CPV 2-II, and CPV 2-III genotypes. In the strains isolated in this study, Gigucheon, Rara and Jun belong to the FPV, while Rachi strain belong to CPV 2-III. With respect to CPV type 2, the new genotypes are inconsistent with the previous genotype classifications (CPV-2a, -2b, and -2c). The root of CPV-I strains were inferred to be originated from a USA strain, while the CPV-II and III were derived from Italy strains that originated in the USA. Based on VP2 protein analysis, CPV 2-I included CPV-2a-like isolates only, as differentiated by the change in residue S297A/N. Almost CPV-2a isolates were classified into CPV 2-III, and a large portion of CPV-2c isolates was classified into CPV 2-II. Two residue substitutions F267Y and Y324I of the VP2 protein were characterized in the isolates of CPV 2-III only. Conclusions: We provided an updated insight on FPV and CPV-2 genotypes by molecular-based and our findings demonstrate the genetic characterization according to the new genotypes.

• Mycobiology
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• v.34 no.2
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• pp.45-55
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• 2006

Although Fursarium oxysporum causes diseases in economically important plant hosts, identification of F. oxysporum formae speciales has been difficult due to confusing phenotypic classification systems. To resolve these complexity, we evaluated genetic relationship of nine formae speciales of F. oxysporum with random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), and translation elongation factor-l alpha ($EF-1{\alpha}$) gene. In addition, the correlation between mycotoxin content of fusaric acid and isolates based on molecular marker data was evaluated using the modified Mantel's test. According to these result, these fusaric acid-producing strains could not identify clearly, and independent of geographic locations and host specificities. However, in the identification of F. oxysporum formae speciales, especially, AFLP analysis showed a higher discriminatory power than that of a the RAPD and $EF-1{\alpha}$ analyses, all three techniques were able to detect genetic variability among F. oxysporum formae speciales in this study.

• Research in Plant Disease
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• v.14 no.1
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• pp.10-14
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• 2008

Batcterial wilt caused by Ralstonia solanacearum is one of important and widespread diseases worldwide as well as in Korea. Bacterial wilt disease caused by R. solanacearum has been reported mainly in solanaceous crops including eggplant (Solanum melongena), tomato (Solanum lycopersicum), potato (S. tuberosum), and pepper (Capsicum annuum). A total of 48 strains of R. solanacearum from eggplant were collected during 2005 and 2006. They were confirmed as R. solanacearum by PCR amplification with primer pair flipcF/flipcR resulting in production of 470-bp DNA fragment. The 15 isolates exhibited pathogenicity on eggplant and tomato, but less virulent on pepper than other species. The biovar of collected isolates, which have been reported of five types worldwide, were classified as biovars 3 and 4 by physiological test. Biovar 4 was the dormant type without pathogenicity on eggplant rootstock, whereas biovar 3 had pathogenicity on eggplant rootstocks that is resistant to R. solanacearum, indicating necessity of breeding new rootstock with resistance to R. solanacearum biovar 3

• The Plant Pathology Journal
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• v.32 no.5
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• pp.423-430
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• 2016

Clubroot disease caused by Plasmodiophora brassicae is one of the most serious diseases in Brassica crops worldwide. In this study, the pathotypes of 12 Korean P. brassicae field isolates were determined using various Chinese cabbage including 22 commercial cultivars from Korea, China, and Japan, and 15 inbred lines. All P. brassicae isolates exhibited the typical clubroot disease on non-clubroot resistant cultivar, indicating that the isolates were highly pathogenic. According to the reactions on the Williams' hosts, the 12 field isolates were initially classified into five races. However, when these isolates were inoculated onto clubroot-resistant (CR) cultivars of Chinese cabbage, several isolates led to different disease responses even though the isolates have been assigned to the same race by the Williams' host responses. Based on the pathogenicity results, the 12 field isolates were reclassified into four different groups: pathotype 1 (GN1, GN2, GS, JS, and HS), 2 (DJ and KS), 3 (HN1, PC, and YC), and 4 (HN2 and SS). In addition, the CR cultivars from Korea, China, and Japan exhibited distinguishable disease responses to the P. brassicae isolates, suggesting that the 22 cultivars used in this study, including the non-CR cultivars, are classified into four different host groups based on their disease resistance. Combining these findings, the four differential hosts of Chinese cabbage and four pathotype groups of P. brassicae might provide an efficient screening system for resistant cultivars and a new foundation of breeding strategies for CR Chinese cabbage.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.73-73
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• 2019

Angelica gigas Nakai (Korean danggui), a member of the Umbelliferae family, is a Korean traditional medicinal plant whose roots have been used for treating gynecological diseases. Transcriptomics is the study of the transcriptome, which is the complete set of RNA transcripts that are produced by the genome, using high-throughput methods, such as microarray analysis. In this study, transcriptome analysis of A.gigas Nakai was carried out. Transcriptome sequencing and assembly was carried out by using Illumina Hiseq 2500, Velvet and Oases. A total of 109,591,555 clean reads of A. gigas Nakai was obtained after trimming adaptors. The obtained reads were assembled with an average length of 1,154 bp, a maximum length of 13,166 bp, a minimum length of 200 pb, and N50 of 1,635 bp. Functional annotation and classification was performed using NCBI NR, InterprotScan, KOG, KEGG and GO. Candidate genes for phenylpropanoid biosynthesis were obtanied from A.gigas transcriptome and the genes and its proteins were confirmed through the NCBI homology BLAST searches, revealing high identity with other othologous genes and proteins from various plants pecies. In RNA sequencing analysis using an Illumina Next-Seq2500 sequencer, we identified a total 94,930 transcripts and annotated 71,281 transcripts, which provide basic information for further research in A.gigas Nakai. Our transcriptome data reveal that several differentially expressed genes related to flower color in A.gigas Nakai. The results of this research provide comprehensive information on the A.gigas Nakai genome and enhance our understanding of the flower color related gene pathways in this plant.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.86-96
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• 2020

Based on the use cases of image recognition technology, this study looked at how artificial intelligence plays a role in image recognition technology. Through image recognition technology, satellite images can be analyzed with artificial intelligence to reveal the calculation of oil storage tanks in certain countries. And image recognition technology makes it possible for searching images or products similar to images taken or downloaded by users, as well as arranging fruit yields, or detecting plant diseases. Based on deep learning and neural network algorithms, we can recognize people's age, gender, and mood, confirming that image recognition technology is being applied in various industries. In this study, we can look at the use cases of domestic and overseas image recognition technology, as well as see which methods are being applied to the industry. In addition, through this study, the direction of future research was presented, focusing on various successful cases in which image recognition technology was implemented and applied in various industries. At the conclusion, it can be considered that the direction in which domestic image recognition technology should move forward in the future.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.30-43
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• 2018

Many studies have been carried out to retrieve images using colors, shapes, and textures which are characteristic of images. In addition, there is also progress in research related to the disease images of the crop. In this paper, to be a help to identify the disease occurred in crops grown in the agricultural field, we propose a similarity-based crop disease search system using the diseases image of horticulture crops. The proposed system improves the similarity retrieval performance compared to existing ones through the combination descriptor without using a single descriptor and applied the weight based calculation method to provide users with highly readable similarity search results. In this paper, a total of 13 Descriptors were used in combination. We used to retrieval of disease of six crops using a combination Descriptor, and a combination Descriptor with the highest average accuracy for each crop was selected as a combination Descriptor for the crop. The retrieved result were expressed as a percentage using the calculation method based on the ratio of disease names, and calculation method based on the weight. The calculation method based on the ratio of disease name has a problem in that number of images used in the query image and similarity search was output in a first order. To solve this problem, we used a calculation method based on weight. We applied the test image of each disease name to each of the two calculation methods to measure the classification performance of the retrieval results. We compared averages of retrieval performance for two calculation method for each crop. In cases of red pepper and apple, the performance of the calculation method based on the ratio of disease names was about 11.89% on average higher than that of the calculation method based on weight, respectively. In cases of chrysanthemum, strawberry, pear, and grape, the performance of the calculation method based on the weight was about 20.34% on average higher than that of the calculation method based on the ratio of disease names, respectively. In addition, the system proposed in this paper, UI/UX was configured conveniently via the feedback of actual users. Each system screen has a title and a description of the screen at the top, and was configured to display a user to conveniently view the information on the disease. The information of the disease searched based on the calculation method proposed above displays images and disease names of similar diseases. The system's environment is implemented for use with a web browser based on a pc environment and a web browser based on a mobile device environment.