• 보존과학연구
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• s.21
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• pp.5-55
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• 2000

The cultural properties are damaged by various causes according to the characteristics of material, the condition of preservation, and the period of time. Especially, biodeterioration makes lots of damages in organic properties than inorganic ones. The damages of wooden cultural properties by insects usually are caused by the three orders; Isoptera, Coleoptera, and Hymenoptera. As the result of investigation on the state of 141 buildings of wooden cultural properties in 1999, some of them were damaged by many kinds off actors; wasp, powder post beetle, cigarette beetle, termite, decay, and physical cracking. And it was found that the patterns of damages were related to species-specific habits of insects. There are several methods of pest control for the prevention of wooden cultural properties from damages caused by insects. Those are as follows; physical control, chemical control, biological control, and integrated pest management. When insects and fungi were detected at the wooden buildings, the fumigation is best treatment to stop biodeterioration. And then, wood materials also need to be treated with insecticidal and antiseptic chemicals to avoid a reinfestation, because the fumigant is volatile. The six commercial chemicals which are applied to the insecticidal and antiseptic treatment of wooden cultural properties were purchased to test their abilities. According to the comparative results of efficacy of them in laboratory, chemical D showed excellent efficacy in all items, including antiseptic and termiticidal items. The goal of these pest controls is to protect wooden buildings from insects and microorganisms. The most effective method used currently is chemical control(fumigation, insecticidal and anticeptic chemical treatment), but it has to be treated periodically to control pest effectively. Recently environmentally-friendly control methods such as bait system or biological treatments are replacing traditional barrier treatments using large amounts of chemicals. Especially, termite is a social insect which makes a colony. Although a building with fumigation treatment is safe for a while, once attacked building has a risk of damage by reinfestation of termite. Therefore, to control termites from damaged building, the entire colony including reproductives(queen and king) and larvae around buildings must beeliminated. Bait system can be used as a preventive measure in early detection of them through termites colony monitoring and baiting. It would be the most effective for termite control if bait system would be used together with the chemical controls.

• Journal of Korean Society of Forest Science
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• v.104 no.2
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• pp.332-335
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• 2015

Taphrina wiesneri, a pathogen of cherry witches' broom, is highly pathogenic to Prunus yedoensis Matsumura which are widely planted in parks and streets in South Korea. In order to control the disease, it is crucial to know the life cycle of the fungus. We attempted to detect the fungus tentatively overwintering in shoots and branches of cherry trees both having witches' broom and healthy before flowering and leafing in spring using PCR with species-specific primer set (TwITSF and TwITSR). Genomic DNAs were extracted from the symptomatic and the asymptomatic shoots or branches. Results indicated that T. wiesneri is present in leaf buds and inner bark not only in symptomatic branches but also in the asymptomatic branches in diseased trees. However, the fungus was not detected in flower buds of the symptomatic trees and any samples of healthy trees.

• Smart Media Journal
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• v.12 no.7
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• pp.9-17
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• 2023

Plant diseases and pests affect the growth of various plants, so it is very important to identify pests at an early stage. Although many machine learning (ML) models have already been used for the inspection and classification of plant pests, advances in deep learning (DL), a subset of machine learning, have led to many advances in this field of research. In this study, disease and pest inspection of abnormal crops and maturity classification were performed for normal crops using YOLOX detector and MobileNet classifier. Through this method, various plant pest features can be effectively extracted. For the experiment, image datasets of various resolutions related to strawberries, peppers, and tomatoes were prepared and used for plant pest classification. According to the experimental results, it was confirmed that the average test accuracy was 84% and the maturity classification accuracy was 83.91% in images with complex background conditions. This model was able to effectively detect 6 diseases of 3 plants and classify the maturity of each plant in natural conditions.

• Journal of Biosystems Engineering
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• v.40 no.4
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• pp.417-427
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• 2015

Purpose: This study investigated different band selection methods to classify spectrally similar data - obtained from aerial images of healthy citrus canopies and citrus greening disease (Huanglongbing or HLB) infected canopies - using small differences without unmixing endmember components and therefore without the need for an endmember library. However, large number of hyperspectral bands has high redundancy which had to be reduced through band selection. The objective, therefore, was to first select the best set of bands and then detect citrus Huanglongbing infected canopies using these bands in aerial hyperspectral images. Methods: The forward feature selection algorithm (FFSA) was chosen for band selection. The selected bands were used for identifying HLB infected pixels using various classifiers such as K nearest neighbor (KNN), support vector machine (SVM), naïve Bayesian classifier (NBC), and generalized local discriminant bases (LDB). All bands were also utilized to compare results. Results: It was determined that a few well-chosen bands yielded much better results than when all bands were chosen, and brought the classification results on par with standard hyperspectral classification techniques such as spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF). Median detection accuracies ranged from 66-80%, which showed great potential toward rapid detection of the disease. Conclusions: Among the methods investigated, a support vector machine classifier combined with the forward feature selection algorithm yielded the best results.

• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1254-1269
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• 2023

This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction. A large amount of data is required to train CNNs effectively. Still, since UAVs capture only a limited number of images, we propose a data augmentation method that can effectively increase data. And most occupancy prediction predicts occupancy by designing a CNN-based object detector for an image and counting the number of recognized objects or calculating the number of pixels occupied by an object. These methods require complex occupancy rate calculations; the accuracy depends on whether the object features of interest are visible in the image. However, in this study, CNN is not approached as a corn object detection and classification problem but as a function approximation and regression problem so that the occupancy rate of corn objects in an image can be represented as the CNN output. The proposed method effectively estimates occupancy for a limited number of cornfield photos, shows excellent prediction accuracy, and confirms the potential and scalability of deep learning.

• Journal of the Korean Society of Food Culture
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• v.10 no.1
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• pp.45-56
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• 1995

A study has been performed on the cockroach knowledge and perception of managers, employees and consumers, and the cockroach control management in food service institutions. A total of 759 subjects including 101 managers, 293 employees and 365 consumers was surveyed in Seoul and Pusan areas from July 1994 to September 1994. The results obtained are as follows: The mean rates of the cockroach knowledge (i.e. 62.26/100.0) and perception (i.e. 23.67/30.0) of the consumers were significantly (p<0.001) lower than those of the managers (i.e. 68.87/100.0 and 25.30/30.0, respectively) and the employees (i.e. 69.09/100.0 and 26.99/30.0, respectively). In the cockroach detection rates, however, much higher rate was seen in the consumer group (i.e. 79.5%) than the manager (i.e. 43.3%) and the employee (i.e. 48.5%) groups. Forty and seventy percents of the subjects have suffered from allergies and nuisance by cockroaches, respectively. The cockroach control was performed by 75.5% of the food service institutions and 70.8% of them contracted with pest control operators to reduce the cockroach populations. The cockroach control methods of the operators were aerosol (40.7%) and insecticidal baits (30.5%). Only 33.7% of the institutions had the budgets for the cockroach control. For public health, the managers and the employees of the institutions need to be educated about cockroaches and hygiene. Also, it is suggested that cockroaches be regularly controlled by professional pest control operators.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.51-58
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• 2012

Scirtothrips Dorsalis (Thysanoptera: Thripidae) recently has been recognized as a major source of the pest damage in the citrus fruit orchards. So its arrival has been predicted periodically but it is difficult to identify adults of the pest with the naked eyes because of their size smaller than the 0.8mm. In this paper, we propose a method to detect candidate areas for automatic identification of Scirtothrips Dorsalis on forecasting traps. The proposed method uses a histogram-based template matching where the composite image synthesized with the gray-scale image and the gradient image is used. In our experiments, images are acquired by the optical microscopy with 50 magnifications. To show the usefulness of the proposed method, it is compared with the method we previously suggested. Also, the performances when the proposed method is applied to noise-reduced images and gradient images are examined. The experimental results show that the proposed method is approximately 14.42% better than our previous method, 41.63% higher than the case that the noise-reduced image is used, and 21.17% higher than the case that the gradient image is used.

• Korean journal of applied entomology
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• v.61 no.4
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• pp.639-640
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• 2022

A Ypsolophid moth Saridoscelis sphenias Meyrick was recorded in 2020 first in Korea, and specimens were collected from Jindo and Wando in Jeonam province from 2016 to 2017. This moth uses host plants such as Pieris japonica (Thunb.) D. Don ex G. Don, Vaccinium bracteatum Thunb. and Leucothoe grayana Maxim. var oblongifolia (Miq.). This species was discovered once in a blueberry orchard in Jeju in August 2014, and since then it has been regarded as not an established species because of no further detection. However, S. sphenias was found again in blueberry orchards grown in vinyl houses in Jeju city and Seogwipo city in 2018 and 2019. Since 2020, this pest has also been found on field-grown blueberries. Hatched larvae first bored into new shoots and fed inside, and the mid-aged larvae escaped from the inside of shoots, attached several shoots with webs, and fed on the leaves in the group. It is considered that S. sphenias will become a severe pest on blueberries; thus, we report the basic life cycle here.

• Journal of Applied Biological Chemistry
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• v.57 no.4
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• pp.341-345
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• 2014

Fate of fenarimol, chlorothalinol, and ethoprophos sprayed to control disease and pest was studied in a agroforest culture field of Jangsu-gun, Jeollabuk-do, Korea. Concentrations of fenarimol, chlorothalinol, and ethoprophos in runoff water ranged mostly to 0.2 mg/L at the first rainfall-runoff event. And then was rapidly decreased than detection limit at 60 days after the application. The fenarimol and chlorothalonil residue in soil was dissipated to below detection limit at 30 days after the application. But ethoprophos was decreased to below detection limit at 135 days after the application. The concentrations of experimental pesticides were highly detected in agroforest culture field than in open culture field. It is assumed that experimental pesticides were strongly adsorbed by organic matter such as fulvic acid and humic acid.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.426-429
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• 2007

One of the widely used applications of remote sensing studies is environmental change detection and biodiversity conservation. The study area Hustai Mountain is situated in the transition zone between the Siberian taiga forest and Central Mongolian arid steppe. Hustai National Park carries out one of several reintroduction programs of takhi (wild horse or Equus ferus przewalskii) from various zoos in the world and it represents one of a few textbook examples of successful reintroduction of an animal extinct in the wild. In this paper we describe the results of an analysis on the change of remaining forest area over the 7-year period since Hustai Mountain was designated as a protected area for reintroduction to wild horses. Today the forested area covers approximately 5% of the Hustai National Park, mostly the north-facing slopes above 1400 m altitude. Birch (Betula platyphylla) and aspen (Populus tremula) trees are predominant in the forest. We used Landsat ETM+ images from two different years and multi temporal MODIS NDVI data. Land types were determined by supervised classification methods (Maximum Likelihood algorithm) verified with ground-truthing data and the Land Change Modeler (LCM) which was developed by Clark Labs. Forested area was classified into three different land types, namely the forest land, mountain meadow and mountain steppe. The study results illustrate that the remaining birch forest has rapidly changed to fragmented forest land and to open areas. Underlying causes for such a rapid change during the 15-year period may be manifold. However, the responsible factors appear to be the drying off and outbreak of forest pest species (such as gypsy moth or Lymantria dispar) in the area.