• 한국멀티미디어학회논문지
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• 제25권11호
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• pp.1653-1671
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• 2022

Crop diseases affect crop production, more than 30 billion USD globally. We proposed a classification study of crop species and diseases using deep learning algorithms for corn, cucumber, pepper, and strawberry. Our study has three steps of species classification, disease detection, and disease classification, which is noteworthy for using captured images without additional processes. We designed deep learning approach of deep learning convolutional neural networks based on Mask R-CNN model to classify crop species. Inception and Resnet models were presented for disease detection and classification sequentially. For classification, we trained Mask R-CNN network and achieved loss value of 0.72 for crop species classification and segmentation. For disease detection, InceptionV3 and ResNet101-V2 models were trained for nodes of crop species on 1,500 images of normal and diseased labels, resulting in the accuracies of 0.984, 0.969, 0.956, and 0.962 for corn, cucumber, pepper, and strawberry by InceptionV3 model with higher accuracy and AUC. For disease classification, InceptionV3 and ResNet 101-V2 models were trained for nodes of crop species on 1,500 images of diseased label, resulting in the accuracies of 0.995 and 0.992 for corn and cucumber by ResNet101 with higher accuracy and AUC whereas 0.940 and 0.988 for pepper and strawberry by Inception.

• The Plant Pathology Journal
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• 제40권4호
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• pp.408-413
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• 2024

The emergence of rice black-streaked dwarf virus (RBSDV) poses a significant threat to global cereal crop cultivation, necessitating the urgent development of reliable detection and quantification techniques. This study introduces a reliable approach for the precise and sensitive quantification of the RBSDV in cereal crop samples, employing a reverse transcription digital polymerase chain reaction (RT-dPCR) assay. We assessed the specificity and sensitivity of the RT-dPCR assay proposed for precise RBSDV detection and quantification. Our findings demonstrate that RT-dPCR was specific for detection of RBSDV, with no cross-reactivity observed with other viruses infecting cereal crops. The RT-dPCR sensitivity was over 10 times that of RT-quantitative PCR (RT-qPCR). The detection limit of RT-dPCR was 0.096 copies/㎕. In addition, evaluation of RT-dPCR assay with field samples was conducted on 60 different cereal crop samples revealed that RT-dPCR (45/60) exhibited superior accuracy compared with RT-qPCR (23/60). In this study, we present a specific and accurate RT-dPCR assay for the detection and quantification of RBSDV.

• 한국작물학회지
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• 제50권spc1호
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• pp.228-230
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• 2005

형광 염료와 레이저 겔스캐너 장비를 이용하여 변성아크릴 아마이드 겔에서 전기 영동된 DNA를 신속하고 간편한 방법으로 기존의 은염색법과 비슷한 감도로 검출하고자 하였다. 변성아크릴아마이드 겔을 형광 염료인 SYBR Green (Molecular Probes)이나 Vistra Green (Amersham Bioscience) 0.01 X 희석액 (pH 8)으로 염색한 후 480nm 레이져, 520nm filer 옵션으로 스캔하여 DNA를 검출하였으며, 검출감도는 기존의 은염색법과 비슷하면서 염색 단계를 한 단계로 줄일 수 있었다.

• 산업공학
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• 제16권2호
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• pp.248-257
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• 2003

In a heated rolling process of a steel mill where steel plates are pressed to a sheet coil by spreading and expanding, an irregularly-shaped head portion as well as a tail portion of the sheet coil need to be cropped. Any crop which is not clearly cut and separated from the sheet coil may cause critical damages to the facilities of the following processes. As the cropping process is performed very fast, human eyes are not proper for continuous monitoring of the cropping process. To solve this problem, we have developed a machine-vision based crop-drop detection system. The system also measures lengths of major and minor axes for the crops and thereby determines the proper crop size to minimize steel sheet losses.

• The Plant Pathology Journal
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• 제38권3호
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• pp.194-202
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• 2022

Erwinia amylovora and Erwinia pyrifoliae cause fire blight and black-shoot blight, respectively, in apples and pears. E. pyrifoliae is less pathogenic and has a narrower host range than that of E. amylovora. Fire blight and black-shoot blight exhibit similar symptoms, making it difficult to distinguish one bacterial disease from the other. Molecular tools that differentiate fire blight from black-shoot blight could guide in the implementation of appropriate management strategies to control both diseases. In this study, a primer set was developed to detect and distinguish E. amylovora from E. pyrifoliae by conventional polymerase chain reaction (PCR). The primers produced amplicons of different sizes that were specific to each bacterial species. PCR products from E. amylovora and E. pyrifoliae cells at concentrations of 10⁴ cfu/ml and 10⁷ cfu/ml, respectively, were amplified, which demonstrated sufficient primer detection sensitivity. This primer set provides a simple molecular tool to distinguish between two types of bacterial diseases with similar symptoms.

• Journal of Multimedia Information System
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• 제7권1호
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• pp.17-24
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• 2020

Rice (Oryza Sativa) is an important source of food for the people of our country, even though of world also .It is also considered as the staple food of our country and we know agriculture is the main source country's economy, hence the crop of Rice plays a vital role over it. For increasing the growth and production of rice crop, ground-breaking technique for the detection of any type of disease occurring in rice can be detected and categorization of rice crop diseases has been proposed in this paper. In this research paper, we perform comparison between two classifiers namely MDC and Bayes' classifiers Survey over different digital image processing techniques has been done for the detection of disease in rice crops. The proposed technique involves the samples of 200 digital images of diseased rice leaf images of five different types of rice crop diseases. The overall accuracy that we achieved by using Bayes' Classifiers and MDC are 69.358 percent and 81.06 percent respectively.

• The Plant Pathology Journal
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• 제30권4호
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• pp.416-424
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• 2014

Sweet potato is grown extensively from tropical to temperate regions and is an important food crop worldwide. In this study, we established detection methods for 17 major sweet potato viruses using single and multiplex RT-PCR assays. To investigate the current incidence of viral diseases, we collected 154 samples of various sweet potato cultivars showing virus-like symptoms from 40 fields in 10 Korean regions, and analyzed them by RT-PCR using specific primers for each of the 17 viruses. Of the 17 possible viruses, we detected eight in our samples. Sweet potato feathery mottle virus (SPFMV) and sweet potato virus C (SPVC) were most commonly detected, infecting approximately 87% and 85% of samples, respectively. Furthermore, Sweet potato symptomless virus 1 (SPSMV-1), Sweet potato virus G (SPVG), Sweet potato leaf curl virus (SPLCV), Sweet potato virus 2 ( SPV2), Sweet potato chlorotic fleck virus (SPCFV), and Sweet potato latent virus (SPLV) were detected in 67%, 58%, 47%, 41%, 31%, and 20% of samples, respectively. This study presents the first documented occurrence of four viruses (SPVC, SPV2, SPCFV, and SPSMV-1) in Korea. Based on the results of our survey, we developed multiplex RT-PCR assays for simple and simultaneous detection of the eight sweet potato viruses we recorded.

• The Plant Pathology Journal
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• 제23권4호
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• pp.260-265
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• 2007

Testing a large number of samples from field monitoring and routine indexing is cumbersome and the available virus detection tools were labor intensive and expensive. To circumvent these problems we established tissue blot immunoassay (TBIA) method an alternative detection tool to detect Barley mild mosaic virus (BaMMV) and Barley yellow mosaic virus (BaYMV) infection in the field and greenhouse inoculated plants for monitoring and routine indexing applications, respectively. Initially, leaf and stem were tested to determine suitable plant tissue for direct blotting on nitrocellulose membrane. The dilutions of antibodies were optimized for more efficient and economical purposes. Results showed that stem tissue was more suitable for direct blotting for it had no background that interferes in the reaction. Therefore, this technique was referred as direct stem blot immunoassay or DSBIA, in this study. Re-used diluted (1:1000) antiserum and conjugate up to 3 times with the addition of half strength amount of concentrated antibodies was more effective in detecting the virus. The virus blotted on the nitrocellulose membrane from stem tissues kept at room temperature for 3 days were still detectable. The efficiency of DSBIA and RT-PCR in detecting BaMMV and BaYMV were relatively comparable. Results further proved that DSBIA is a rapid, reliable and economical detection method suitable for monitoring BaMMV and BaYMV infection in the field and practical method in indexing large scale of barley materials for virus resistance screening.

• 식물병연구
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• 제21권4호
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• pp.315-320
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• 2015

Soybean mosaic virus(SMV)는 potyvirus 속에 속하며, 모자이크, 괴사, 기형 등의 병징을 야기하고 국내에서는 11개 계통(G1 to G7, G5H, G6H, G7H, G7a)이 보고되어있다. Reverse transcription loop-mediated isothermal amplification(RT-LAMP) 방법은 등온에서 유전자 증폭이 가능하게 하며, 이 방법은 PCR 과정이나 전기영동 없이도 바이러스에 감염된 식물을 검출할 수 있는 이점이 있다. RT-LAMP의 최적반응 조건은 $58^{\circ}C$, 60분으로 확인되었다. 특이성 검정을 위해 콩에서 발생하는 여러 바이러스들과 보유중인 SMV의 9 계통에서 그 특이성을 확인하였다. 그 결과 SMV에 대한 RT-LAMP primer들의 종 특이성이 확인되었으며, SMV의 계통들에 대해서도 적용이 가능한 것으로 확인되었다. 항온수조와 heating block과 같은 간편한 등온 장치에서 재현성을 확인하기 위해 Thermocycler 기기와 비교하여 증폭 여부를 확인한 결과 반응의 차이는 나타나지 않았다. RTLAMP 반응 이후, 반응물을 전기영동과 SYBR Green I을 이용하여 자연광과 UV광에서 증폭 여부를 확인하였다. 그 결과 전기 영동, 자연광, portable UV light와 UV transilluminator에서 모두 반응이 확인되었다.

• The Plant Pathology Journal
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• 제34권4호
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• pp.327-334
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• 2018

Northern corn leaf spot and southern corn leaf blight caused by Cochliobolus carbonum (anamorph, Bipolaris zeicola) and Cochliobolus heterostrophus (anamorph, Bipolaris maydis), respectively, are common maize diseases in Korea. Accurate detection of plant pathogens is necessary for effective disease management. Based on the polyketide synthase gene (PKS) of Cochliobolus carbonum and the nonribosomal peptide synthetase gene (NRPS) of Cochliobolus heterostrophus, primer pairs were designed for PCR to simultaneously detect the two fungal pathogens and were specific and sensitive enough to be used for duplex PCR analysis. This duplex PCR-based method was found to be effective for diagnosing simultaneous infections from the two Cochliobolus species that display similar morphological and mycological characteristics. With this method, it is possible to prevent infections in maize by detecting infected seeds or maize and discarding them. Besides saving time and effort, early diagnosis can help to prevent infections, establish comprehensive management systems, and secure healthy seeds.