• Animal Systematics, Evolution and Diversity
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• 제31권4호
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• pp.257-265
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• 2015

In Korean Peninsula, a total of 175 syrphid species are currently known. As a result of ongoing systematic study of the family Syrphidae, we have discovered the following five species for the first time in the Korean Peninsula: Mallota rossica Portschinsky, 1877, M. shatalkini Mutin, 1999, Sphiximorpha rachmaninovi (Violovitsh, 1981), Volucella bivitta Huo et al., 2007, and V. inanoides Hervé-Bazin, 1923. Among these taxa, Sphiximorpha Rondani, 1850, is the genus recorded for the first time in Korea. In total, three subfamilies, 16 tribes, 70 genera, and 180 species are now officially recognized for the Korean syrphid fauna. In order to facilitate their identification, we here provide specific diagnoses and color photographs for the species listed.

• Mycobiology
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• 제46권4호
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• pp.341-348
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• 2018

A new species of arbuscular mycorrhizal fungi (Glomeromycota), Acaulospora koreana, was isolated from forest soils in South Korea. This novel fungus was collected from the rhizosphere of Lindera obtusiloba and Styrax obassia in forest and propagated with Sorghum bicolor in pot. Morphological characteristics of spores of A. koreana are rarely distinguished from Acaulospora mellea, which is reported as one of the most abundant mycorrhizal species in Korea. However, molecular evidence of rDNA sequence using improved primers for glomeromycotan fungal identification strongly supported that A. koreana is different from A. mellea but also any other species belonging to the genus Acaulospora. This is the first novel glomeromycatan fungus introduced in South Korea, but it suggests that there is a high possibility for discovering new arbuscular mycorrhizal fungi considering the abundance of plant species and advanced phylogenetic analysis technique.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제4권1호
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• pp.16-27
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• 2023

Primary succession on bare rocks is a challenge for invaders, including one of which was plants. The invasion of bare rock by exotic species raises the question of whether their presence hinders or facilitates succession. This study aimed to determine the role of exotic species in primary succession in six overburden (OB) coal mines using a chronosequence approach. Vegetation analysis was undertaken using line transects. Measurements were carried out on the absolute and relative coverage of each species. Native and exotic species were identified and grouped using information from local communities, identification books, and websites. The relationship between time and number of species, time, and relative dominance of exotic and native species was analyzed using Pearson's correlation. Species number and dominance data were analyzed descriptively. The number of native species from the six OB heaps was higher (57) than that from exotic heaps (50). Neither the number of species nor the coverage showed a significant relationship with time. Exotic species predominated throughout the age of the embankment but tended to decrease over time. Temporary dominance by exotic species plays a role in assisting primary succession in the OB. This process might be prolonged without the temporary dominance of exotic species during early primary succession.

• 한국산림과학회지
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• 제110권2호
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• pp.155-164
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• 2021

자연환경에 대한 국민들의 관심 증가로 스마트폰과 같은 휴대용 기기를 이용한 수목 동정의 자동화에 대한 요구가 증가하고 있다. 최근 딥러닝 기술의 발전에 힘입어, 외국에서는 수목 인식 분야에의 적용이 활발하게 이루어지고 있다. 수목의 분류를 위해 꽃, 잎 등 다양한 형질들을 대상으로 연구가 진행되고 있지만, 접근성을 비롯한 여러 장점을 가진 수피의 경우 복잡도가 높고 자료가 부족하여 연구가 제한적이었다. 본 연구에서는 국내에서 흔히 관찰 가능한 수목 54종의 사진자료를 약 7,000 여장 수집 및 공개하였고, 이를 해외의 20 수종에 대한 BarkNet 1.0의 자료와 결합하여 학습에 충분한 수의 사진 수를 가지는 53종을 선정하고, 사진들을 7:3의 비율로 나누어 훈련과 평가에 활용하였다. 분류 모델의 경우, 딥러닝 기법의 일종인 합성곱 신경망을 활용하였는데, 가장 널리 쓰이는 VGGNet (Visual Geometry Group Network) 16층, 19층 모델 두 가지를 학습시키고 성능을 비교하였다. 또한 본 모형의 활용성 및 한계점을 확인하기 위하여 학습에 사용하지 않은 수종과 덩굴식물과 같은 방해 요소가 있는 사진들에 대한 모델의 정확도를 확인하였다. 학습 결과 VGG16과 VGG19는 각각 90.41%와 92.62%의 높은 정확도를 보였으며, 더 복잡도가 높은 모델인 VGG19가 조금 더 나은 성능을 보임을 확인하였다. 학습에 활용되지 않은 수목을 동정한 결과 80% 이상의 경우에서 같은 속 또는 같은 과에 속한 수종으로 예측하는 것으로 드러났다. 반면, 이끼, 만경식물, 옹이 등의 방해 요소가 존재할 경우 방해요소가 자치하는 비중에 따라 정확도가 떨어지는 것이 확인되어 실제 현장에서 이를 보완하기 위한 방법들을 제안하였다.

• The Plant Pathology Journal
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• 제18권6호
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• pp.317-322
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• 2002

An isolate of Odontoglossum ringspot virus (ORSV) was identified from Cymbidium var. 'Grace Kelly' showing ringspot symptom on the floral and leaf parts, and was denoted as cymbidium ringspot isolate (ORSV-CR). In ultrathin sections of leaf tissue from diseased Cymbidium plants, clusters of virus particles were observed in the vacuole and cytoplasm. In the Western blot hybridization, the virus strongly reacted with ORSV-specific antiserum indistinguishable from ORSV, suggesting that the vims is serologically identical with ORSV. ORSV-CR sap was inoculated onto 20 species belonging to 12 genera. Systemic infection occurred in Cymbidium sp., Nicotiana benthamiana and N. clevelandii, the host of which was found to be different from that of ORSV-Cy, the Korean strain of ORSV. The analysis of coat protein (CP) gene showed that ORSV-CR was highly homologous to the known isolates of ORSV, with over 95.6% identity in amino acid level. Phylogenetic tree analysis of CP showed that ORSV-CR was clustered with the known ORSV isolates, suggesting that ORSV is a very stable tobamovirus.

• 한국약용작물학회지
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• 제23권6호
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• pp.439-445
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• 2015

Background : Correct identification of Panax species is important to ensure food quality, safety, authenticity and health for consumers. This paper describes a high resolution melting (HRM) analysis based method using internal transcribed spacer (ITS) and 5.8S ribosomal DNA barcoding regions as target (Bar-HRM) to obtain barcoding information for the major Panax species and to identify the origin of ginseng plant. Methods and Results : A PCR-based approach, Bar-HRM was developed to discriminate among Panax species. In this study, the ITS1, ITS2, and 5.8S rDNA genes were targeted for testing, since these have been identified as suitable genes for use in the identification of Panax species. The HRM analysis generated cluster patterns that were specific and sensitive enough to detect small sequence differences among the tested Panax species. Conclusion : The results of this study show that the HRM curve analysis of the ITS regions and 5.8S rDNA sequences is a simple, quick, and reproducible method. It can simultaneously identify three Panax species and screen for variants. Thus, ITS1HRM and 5.8SHRM primer sets can be used to distinguish among Panax species.

• ALGAE
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• 제30권3호
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• pp.217-222
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• 2015

Pythium species (Pythiales, Oomycetes) are well known as the algal pathogen that causes red rot disease in Pyropia / Porphyra species (Bangiales, Rhodophyta). Accurate species identification of the pathogen is important to finding a scientific solution for the disease and to clarify the host-parasite relationship. In Korea, only Pythium porphyrae has been reported from Pyropia species, with identifications based on culture and genetic analysis of the nuclear internal transcribed spacer (ITS) region. Recent fungal DNA barcoding studies have shown the low taxonomic resolution of the ITS region and suggested the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene as an alternative molecular marker to identify Pythium species. In this study, we applied an analysis of both the ITS and cox1 regions to clarify the taxonomic relationships of Korean Pythium species. From the results, the two closely related Pythium species (P. chondricola and P. porphyrae) showed the same ITS sequence, while the cox1 marker successfully discriminated P. chondricola from P. porphyrae. This is the first report of the presence of P. chondricola from the infected blade of Pyropia yezoensis in Asia. This finding of the algal pathogen provides important information for identifying and determining the distribution of Pythium species. Further studies are also needed to confirm whether P. chondricola and P. porphyrae are coexisting as algal pathogens of Pyropia species in Korea.

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2003년도 정기총회 및 추계학술발표회
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• pp.97.1-97
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• 2003

An antagonistic bacterium, KJ1R5,, to Phytophthora capsici was obtained from root interior of a healthy pepper plant. To identify the bacterial antagonist, 16S rDNA sequence analysis, Biolog system, fatty acid methyl-esters (FAMEs), and physiological and biochemical characterization were conducted. The determined 165 rDNA sequence of KJ1R5, showed higher similarities to those of a group consisting of several Chryseobacterium strains with 95.2, 95.2, and 95,1％ similarity to C. defluvii, Chryseobacterium sp. FR2, and C. scophthalmum, respectively, In addition, Halounella gailinarum, Bergeyella zoohelcum, and Riemerella anatipestifer are another group for KJ1R5, with 94.1, 89.7, and 87.2％ similarities, respectively When identification of the antagonistic bacterium, KJ1R5, was conducted using BIOLOG system, the strain KJ1R5, was identified as Flavobacterium tirrenicum (similarity； 0.75％). Fatty acid profiles of the strain KJ1R5, were composed mainly of iso-17：0 w9c and iso-15：0 and identified as Chryseobacterium balustinum (similarity 0.524％). KJ1R5, was Gram-negative, regular short rods ranging from 0.8 $\mu\textrm{m}$ to 1.0 $\mu\textrm{m}$ and had no flagella. Phenotypic characterization of the antagonistic bacterium indicated that KJ1R5, were included in the genus Chreseobacterium, which belongs to the family Flavobacteriaceae. The strain was distinguished from these six existing species. These results indicated that strain might be placed as a new species in the genus Chryseobacterium.

• Plant Breeding and Biotechnology
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• 제5권2호
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• pp.123-133
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• 2017

AP2/EREBP gene family consists of transcription factor genes with a conserved AP2 DNA-binding domain and is involved in various biological processes. AP2/EREBP gene families were identified through genome-wide searches in five Cucurbitaceae species including cucumber, wild cucumber, melon, watermelon, and bitter gourd, which consisted of more than 100 genes in each of the five species. The gene families were further divided into five groups including four subfamilies (ERF, DREB, AP2 and RAV) and a soloist group. Among the subfamilies, DREB subfamily which is known to be related to abiotic stress response was more analyzed and a total of 25 genes were identified as Cucurbitaceae homologues of Arabidopsis CBF/DREB1 genes which are important for abiotic stress-response and tolerance. In silico expression profiling using RNA-Seq data revealed diverse expression patterns of cucumber AP2/EREBP genes. AP2/EREBP gene families identified in this study will be valuable for understanding the stress response mechanism as well as facilitating molecular breeding in Cucurbitaceae crops.

• 스마트미디어저널
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• 제13권7호
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• pp.36-44
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• 2024

Identifying plant species and diseases is crucial for maintaining biodiversity and achieving optimal crop yields, making it a topic of significant practical importance. Recent studies have extended plant disease recognition from traditional closed-set scenarios to open-set environments, where the goal is to reject samples that do not belong to known categories. However, in open-world tasks, it is essential not only to define unknown samples as "unknown" but also to classify them further. This task assumes that images and labels of known categories are available and that samples of unknown categories can be accessed. The model classifies unknown samples by learning the prior knowledge of known categories. To the best of our knowledge, there is no existing research on this topic in plant-related recognition tasks. To address this gap, this paper utilizes knowledge distillation to model the category space relationships between known and unknown categories. Specifically, we identify similarities between different species or diseases. By leveraging a fine-tuned model on known categories, we generate pseudo-labels for unknown categories. Additionally, we enhance the baseline method's performance by using a larger pre-trained model, dino-v2. We evaluate the effectiveness of our method on the large plant specimen dataset Herbarium 19 and the disease dataset Plant Village. Notably, our method outperforms the baseline by 1% to 20% in terms of accuracy for novel category classification. We believe this study will contribute to the community.