• Microbiology and Biotechnology Letters
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• v.47 no.1
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• pp.105-115
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• 2019

Saline or alkaline condition in soil inhibits growth of most crop plants and limits crop yields in many parts of the world. Augmenting an alkaline soil with alkali-tolerant bacteria capable of promoting plant growth can be a promising approach in expanding fertile agricultural land. Near-shore environments of Dokdo Island, a remote island located in the middle of the East Sea, appear to have patches of seawater-influenced haloalkaline soil that is unsupportive for growth of conventional plants. To exploit metabolic capacities of alkali-tolerant bacteria for promoting plant growth in saline or alkaline soils, we isolated of alkali-tolerant bacteria from near-shore soil samples in Dokdo and investigated properties of the isolates. Alkali-tolerant bacteria were selectively cultivated by inoculating suspended and diluted soil samples on a plate medium adjusted to pH 10. Fifty colonies were identified based on their $GTG_5$-PCR genomic fingerprints and 16S rRNA gene sequences. Most isolates were affiliated to alkali-tolerant and/or halotolerant genera or species of the phyla Firmicutes (68%), Proteobacteria (30%) and Actinobacteria (2%). Unlike the typical soil bacterial flora in the island, alkali-tolerant isolates belonged to only certain taxa of terrestrial origin under the three phyla, which have traits of plant growth promoting activities including detoxification, phytohormone production, disease/pest control, nitrogen-fixation, phosphate solubilization or siderophore production. However, Firmicutes of marine origin generally dominated the alkali-tolerant community. Results of this study suggest that haloalkaline environments like Dokdo shore soils are important sources for plant growth promoting bacteria that can be employed in bio-augmentation of vegetation-poor alkaline soils.

• Journal of Ginseng Research
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• v.45 no.4
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• pp.527-534
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• 2021

Background: Phenological studies are a prerequisite for accomplishing higher productivity and better crop quality in cultivated plants. However, there are no phenological studies on Panax ginseng that improve its production yield. This study aims to redefine the phenological growth stages of P. ginseng based on the existing Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale and proposes a disease control reference. Methods: This study was conducted at the Korea Ginseng Corporation Experiment Station in Gyeonggi province, South Korea. Phenological observations were performed once weekly or twice monthly, based on the developmental stages. The existing BBCH scale with a three-digit code was used to redefine and update P. ginseng's phenological growth codes. Results: The phenological description is divided into eight principal growth stages: three for vegetative growth (perennating bud, aerial shoot, and root development), four for reproductive growth (reproductive organ development, flowering, fruit development, and fruit maturation), and one for senescence according to the extended BBCH scale. A total of 58 secondary growth stages were described within the eight principal growth stages. Under each secondary growth stage, four mesostages are also taken into account, which contains the distinct patterns of the phenological characteristics in ginseng varieties and the process of transplanting seedlings. A practical management program for disease control was also proposed by using the BBCH code and the phenological data proposed in this work. Conclusion: The study introduces an extended BBCH scale for the phenological research of P. ginseng.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.581-596
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• 2020

Purpose: purpose of this study was to propose the web application platform which can be to detect and discriminate various diseases and pest of tomato plant based on the large amount of disease image data observed in the facility or the open field. Methods: The deep learning algorithms uesed at the web applivation platform are consisted as the combining form of Faster R-CNN with the pre-trained convolution neural network (CNN) models such as SSD_mobilenet v1, Inception v2, Resnet50 and Resnet101 models. To evaluate the superiority of the newly proposed web application platform, we collected 850 images of four diseases such as Bacterial cankers, Late blight, Leaf miners, and Powdery mildew that occur the most frequent in tomato plants. Of these, 750 were used to learn the algorithm, and the remaining 100 images were used to evaluate the algorithm. Results: From the experiments, the deep learning algorithm combining Faster R-CNN with SSD_mobilnet v1, Inception v2, Resnet50, and Restnet101 showed detection accuracy of 31.0%, 87.7%, 84.4%, and 90.8% respectively. Finally, we constructed a web application platform that can detect and discriminate various tomato deseases using best deep learning algorithm. If farmers uploaded image captured by their digital cameras such as smart phone camera or DSLR (Digital Single Lens Reflex) camera, then they can receive an information for detection, identification and disease control about captured tomato disease through the proposed web application platform. Conclusion: Incheon Port needs to act actively paying.

• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.96-105
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• 2022

Background: Pyrethroid insecticides account for more than 30% of the global insecticide market and are frequently used in agricultural settings and residential and public pest control among the general population. While several animal studies have suggested that exposure to pyrethroids can alter glucose homeostasis, there is only limited evidence of the association between environmental pyrethroid exposure and diabetes in humans. Objectives: This study aimed to report environmental 3-phenoxybenzoic acid (3-PBA) concentrations in urine and evaluate its association with the risk of diabetes in Korean adults. Methods: We analyzed data from the Korean National Environmental Health Survey (KoNEHS) Cycle 2 (2012~2014) and Cycle 3 (2015~2017). A total of 10,123 participants aged ≥19 years were included. Multiple logistic regressions were used to calculate the odds ratios (ORs) for diabetes according to log-transformed urinary 3-PBA levels. We also evaluated age, sex, education, monthly income, marital status, alcohol drinking, physical activity, urinary cotinine, body mass index, and sampling season as potential effect modifiers of these associations. Results: After adjusting for all the covariates, we found significant dose-response relationships between urinary 3-PBA as quartile and the prevalence of diabetes in pooled data of KoNEHS Cycles 2 and 3. In subgroup analyses, the adverse effects of pyrethroid exposure on diabetes were significantly stronger among those aged 19~39 years (p-interaction<0.001) and those who consumed high levels of cotinine (p-interaction=0.020). Conclusions: Our findings highlight the potential diabetes risk of environmental exposure to pyrethroids and should be confirmed in large prospective studies in different populations in the future.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

• The Plant Pathology Journal
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• v.40 no.3
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• pp.310-321
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• 2024

Tomato yellow leaf curl virus (TYLCV) and tomato spotted wilt virus (TSWV) are well-known examples of the begomovirus and orthotospovirus genera, respectively. These viruses cause significant economic damage to tomato crops worldwide. Weeds play an important role in the ongoing presence and spread of several plant viruses, such as TYLCV and TSWV, and are recognized as reservoirs for these infections. This work applies a comprehensive approach, encompassing field surveys and molecular techniques, to acquire an in-depth understanding of the interactions between viruses and their weed hosts. A total of 60 tomato samples exhibiting typical symptoms of TYLCV and TSWV were collected from a tomato greenhouse farm in Nonsan, South Korea. In addition, 130 samples of 16 different weed species in the immediate surroundings of the greenhouse were collected for viral detection. PCR and reverse transcription-PCR methodologies and specific primers for TYLCV and TSWV were used, which showed that 15 tomato samples were coinfected by both viruses. Interestingly, both viruses were also detected in perennial weeds, such as Rumex crispus, which highlights their function as viral reservoirs. Our study provides significant insights into the co-occurrence of TYLCV and TSWV in weed reservoirs, and their subsequent transmission under tomato greenhouse conditions. This project builds long-term strategies for integrated pest management to prevent and manage simultaneous virus outbreaks, known as twindemics, in agricultural systems.

• Korean Journal of Environmental Agriculture
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• v.33 no.4
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• pp.395-402
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• 2014

BACKGROUND: Azadirachta indica Extract(AIE) containing azadirachtin as active ingredient have been used worldwide as environment-friendly organic material having pest control properties. However, the extracts prepared with different solvent and from different plant site is very diverse and have different toxicity. METHODS AND RESULTS: In this study, the four week repeated oral dose toxicity test of aqueous AIE in Sprague-Dawley rats was carried out to investigate the toxic effect of liver, main toxicity target organ of AIE. The male and female rats were divided into 4 groups, respectively; control(0 g/Kg bw), low-dose group(0.5 g/Kg bw), middle-dose(1.0 g/Kg bw) and high-dose group(2.0 g/Kg bw). As a results, relative liver weight increased with dose-dependent of AIE(p<0.05). Serum LDH in all AIE-treated groups were significantly lower than the control in male rats(p<0.05). However, serum GOT and GPT were significantly increased in all male AIE-treated groups in male rats(p<0.05) and, in particular, increase of serum GPT in dose-dependent manner raise the possibility of liver damage. Even through serum GLU was increased significantly in high-dose group in male rats compared to control, there were no significant differences of urinary GLU among all groups(p<0.05). In addition, histopathological examination of the liver did not reveal any lesions in all AIE-treated groups. CONCLUSION: In conclusion, 4 weeks of the repeated oral administration of AIE 2.0 g/Kg to rats has resulted no toxic response in liver. Therefore, AIE was no indicated to have any toxic effect in the SD rats, when it was orally administrated below the dosage 2.0 g/Kg/day for 4weeks.

• Korean journal of applied entomology
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• v.51 no.3
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• pp.271-280
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• 2012

Twenty-two families and 39 species of insect pests were surveyed on five families and 20 species of greenhouse vegetables in Jeonbuk province. The species of insect pests and the families of plants infested were seven families and 10 species on Chenophodiaceae, 16 families and 25 species on Brassicaceae, nine families and 10 species on Apiaceae, six families seven species on Liliaceae, and 13 families and 29 species on Compositae. Spodoptera exigua H$\ddot{u}$bner and Spodoptera litura Fabricius occurred on all vegetables. Additionally, Frankliniella intonsa Trybom, Trialeurodes vaporariorum Westwood, Myzus persicae Sulzer, and Phytomyza horticola Goureau occurred on all vegetables except Liliaceae(Allium tuberosum Rottl. and Allium fistulosum L.). Thirteen species of insect pests including Hymenia recurvalis Fabricius occurred only one vegetables, indicating that they were monophagous. The main insect pests of Chenophodiaceae were M. persicae, H. recurvalis, S. exigua and S. litura whereas Dolycoris baccarum Linn$\acute{e}$, Trialeurodes vaporariorum Westwood, Trichoplusia ni H$\ddot{u}$bner, and P. horticola were not recorded. On Brassicaceae were Brevicoyne brassicae Linn$\acute{e}$, M. persicae, Phaedon brassicae Baly, Phyllotreta striolata Fabricius, Plutella xylostella Linn$\acute{e}$, Hellula undalis Fabricius, S. litura, Pieris rapae Linn$\acute{e}$, Artogeia rapae Linn$\acute{e}$, and Athalia rosae ruficornis Jakovlev, but six species including Frankliniella intonsa Trybom were not recorded. The degree of damage by insect pests on Apiaceae was low, five species including Tetranychus kanzawai kishida, F. intonsa, T. vaporariorum, S. litura, and P. horticola were not recorded. The main insect pests on Liliaceae were Thyatira tabaci Lindeman, Acrolepiopsis sapporensis Matsumura, S. exigua, and Liriomyza chinensis Kato. The damage to Compositae by insect pests was relatively low except that of S. litura.

• Korean Journal of Microbiology
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• v.48 no.4
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• pp.284-292
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• 2012

To date, chemical control remains the most common way to reduce beet armyworm (Spodoptera exigua) populations. However, this insect has become more tolerant or resistant to many chemical insecticides and the insect larvae usually hide inside hollow, tube-like leaves of host plant so they were difficult to kill by spraying insecticides. The use of viral and bacterial insecticide to solve these problems has not been successful because of their novel feeding habit. To overcome these problems, in this study, the biological characteristics and virulence of an entomopathogenic fungus isolated from the cadaver of larvae beet armyworm were investigated. Isolated entomopathogenic fungus was identified as Nomeraea rileyi (Farlow) Samson by morphological examinations and genetic identification using sequences of the ITS, ${\beta}$-tubulin gene and EF1-${\alpha}$ regions. This fungus was named as N. rileyi SDSe. Virulence tests against 3rd larvae of beet armyworm were conducted with various conidial suspensions from $1{\times}10^4$ to $10^8$ conidia/ml of N. rileyi SDSe in laboratory conditions. Mortality rate of beet armyworm showed from 20 to 54% and the virulence increased with increasing conidial concentrations. Although N. rileyi SDSe showed low mortality rate against beet armyworm, it is expected that N. rileyi SDSe will be used effectively in the integrated pest management programs against the beet armyworm.

• Korean journal of applied entomology
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• v.54 no.3
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• pp.191-197
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• 2015

Fruit drop due to Eurytoma maslovskii infestations of Japanese apricot (Prunus mume) is a serious economic issue in most parts of Jeonnam Province, with the exception of the coastal areas such as Wando, Shinan, Yeosu, and Muan. The average incidence of fruit drop was 67% in 2013 and 33.3% in 2014. E. maslovskii larvae overwinter inside the pits of Japanese apricots. Larval survival rates decrease to less than 30% after a rainy summer season. The eggs are long oval of 0.68 mm, 0.29 mm and ivory white. Mature larva is of 6.56 mm, 3.18 mm. Free pupa are black, adult females and males of 6.97 mm, 4.90 mm lengths, respectively, while the ovipositor is 0.64 mm in length. Adult emergence occurs from early April to early May, when Japanese apricot fruits are from 4 mm to 17 mm in diameter. Adults persist for 13.5 d after emergence, and the sex ratio of females to males was found th be 45.9:54.1. Although up to four eggs may be oviposited per fruit, only one larva will ultimately survive, ans the larvae are cannibalistic. The period during which E. maslovskii is able to oviposit on Japanese apricots only lasts from mid- to late April (fruit diameter: 12~16 mm). When the diameter of the fruit is >16 mm, the pit of the Japanese apricot hardens and larvae have difficultly penetrating the stone. Therefore, the most effective method of controlling this pest is to spray orchards with a control agent 2~3 times, at 5 d intervals, beginning in mid- April.