• Journal of Korea Multimedia Society
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• v.25 no.11
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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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.spc1
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• pp.228-230
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• 2005

The denature polyacrylamide gel stain silver nitrate is used for routine nucleic acid detection. More sensitive stains, such as Vistra Green, SYBR Green are available to address a broad range of DNA applications requiring lower detection limits in polyacrylamide gel formats. Gel Scanners, laser-scanning instruments, provide sensitive fluorescence detection of DNA gel stains. We established one step fluorescent impregnation enhanced sensitivity with simple, rapid and low cost. We have applied this fluorescent staining procedure for the routine analysis of DNA profiles generated by SSR amplification.

• IE interfaces
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• v.16 no.2
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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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• v.38 no.3
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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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• v.7 no.1
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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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• v.30 no.4
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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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• v.23 no.4
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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.

• Research in Plant Disease
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• v.21 no.4
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• pp.315-320
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• 2015

Soybean mosaic virus (SMV) is a prevalent pathogen that causes significant yield reduction in soybean production worldwide. SMV belongs to potyvirus and causes typical symptoms such as mild mosaic, mosaic and necrosis. SMV is seed-borne and also transmitted by aphid. Eleven SMV strains, G1 to G7, G5H, G6H, G7H, and G7a were reported in soybean varieties in Korea. A reverse transcription loop-mediated isothermal amplification (RT-LAMP) method allowed one-step detection of gene amplification by simple procedure and needed only a simple incubator for isothermal template. This RT-LAMP method allowed direct detection of RNA from virus-infected plants without thermal cycling and gel electrophoresis. In this study, we designed RT-LAMP primers named SML-F3/B3/FIP/BIP from coat protein gene sequence of SMV. After the reaction of RT-LAMP, products were identified by electrophoresis and with the detective fluorescent dye, SYBR Green I under daylight and UV light. Optimal reaction condition was at $58^{\circ}C$ for 60 min and the primers of RT-LAMP showed the specificity for nine SMV strains tested in this study.

• The Plant Pathology Journal
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• v.34 no.4
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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.

• Journal of Applied Biological Chemistry
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• v.44 no.2
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• pp.92-94
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• 2001

A simple protocol for the detection of opines, cucumopines and mikimopines using a general horizontal or vertical get electrophoresis system for protein or DNA separation in the laboratory are demonstrated. This electrophoresis method can also be applied to other opines as long as correct detection reagent and buffer system are used.