• Journal of agriculture & life science
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• v.44 no.6
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• pp.91-99
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• 2010

We used a multiplex PCR primer set composed of 11 microsatellite (MS) markers and two sexing markers for gender detection. Genomic DNA extracted from hair roots of 3,510 Hanwoo were genotyped. Based on the 11MS markers, no animals had identical genotypes(TGLA227, BM2113, TGLA53, ETF10, SPS115, TGLA122, ETH3, ETH225, BM1824 and INRA23). The expected probability of identity among genotypes of random individuals (PI), the probability of identity among genotypes from random half-sibs ($PI_{half-sibs}$) and among genotypes of random individuals, and the probability of identity among genotypes from random sibs ($PI_{sibs}$) were estimated as $1.31{\times}10^{-23}$, $2.52{\times}10^{-16}$and $1.09{\times}10^{-6}$, respectively using the API-CALC program, version 1.0. We successfully completed the genotype analysis of 3,510 Hanwoo with a 3.93% genotyping failure rate. It was revealed that extracting DNA from the hair root was a time-efficient and cost-effective method to collect specimens for DNA isolation from live animals. This method also minimized stress for the animals during specimen collection. Among the hair roots from the back, belly, upper tail and lower tail, 5~13 hair roots of the lower tail led to the best genotype analysis results. Finally, we established a 96-well-format method of DNA preparation applicable for high- throughput genotype analysis.

• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.392-399
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• 2021

This study was conducted to research the status of pesticide residues in a total of 114 herbs and spices obtained from January to October 2020. 341 pesticide residues were analyzed by the multi class pesticide multiresidue methods using GC-MSMS, GC-ECD, GC-NPD, LC-MSMS, LC-PDA, and LC-CAS. As a result of analysis, 36 pesticide residues were found, and detection rate was 31.6%. Of them, seven samples were detected over Maximum Residue Limits (MRLs) and the unsuitable level in pesticide was 6.1%. The herbs and spices exceeding MRLs include coriander (2 times), mint (2 times), basil (once), rosemary (once), and boraye (once). According to an analysis of 341 pesticide residues, 22 pesticides were detected 52 times and 8 pesticides were found to exceed the MRLs. The pesticides exceeding MRLs were ingredients such as etofenprox, flufenoxuron, fluquinconazole, iprodione, lufenuron, paclobutrazol, phenthoate, and spiromesifen.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

• Journal of Food Hygiene and Safety
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• v.33 no.6
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• pp.466-473
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• 2018

An analytical method of sodium polyacrylate in processed food products was developed and monitored by using size-exclusion chromatography. GF-7M HQ column and UV/VIS detector were selected based on peak shape and linearity. Flow rate, column oven temperature, and mobile phase were selected as 0.6 mL/min, $45^{\circ}C$, and 50 mM sodium phosphate buffer of pH 9.0, respectively. Samples for analysis of sodium polyacrylate were extracted with 50 mM sodium phosphate buffer of pH 7.0 for 3 hr at $20^{\circ}C$ and 150 rpm. Analytical method validation revealed proper selectivity and calibration curve was selected in the range of 50-500 mg/L, and correlation coefficient of calibration curve was more than 0.9985. Limit of detection of sodium polyacrylate was 10.95 mg/kg and limit of quantification was 33.19 mg/kg. Accuracy and coefficient of variation for sodium polyacrylate analysis was 99.6-127.6%, 3.0-8.3% for intra-day and 94.3-121.9%, 1.3-2.6% for inter-day, respectively. Sodium polyacrylate was detected in 40 samples among monitored 125 processed food products. Detected contents were less than 0.2%, limited by the Food Additives Code. Results suggest the established size-exclusion chromatography method could be used to analyze sodium polyacrylate in processed food products.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.36-49
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• 2019

The objectives of this study were to extract "Field Survey Based Infection Tree of Pine Wilt Disease(FSB_ITPWD)" and "Object Classification Based Infection Tree of Pine Wilt Disease(OCB_ITPWD)" from the Research Forest at Kangwon National University, and evaluate the spatial distribution characteristics and occurrence intensity of wood infested by pine wood nematode. It was found that the OCB optimum weights (OCB) were 11 for Scale, 0.1 for Shape, 0.9 for Color, 0.9 for Compactness, and 0.1 for Smoothness. The overall classification accuracy was approximately 94%, and the Kappa coefficient was 0.85, which was very high. OCB_ITPWD area is approximately 2.4ha, which is approximately 0.05% of the total area. When the stand structure, distribution characteristics, and topographic and geographic factors of OCB_ITPWD and those of FSB_ITPWD were compared, age class IV was the most abundant age class in FSB_ITPWD (approximately 55%) and OCB_ITPWD (approximately 44%) - the latter was 11% lower than the former. The diameter at breast heigh (DBH at 1.2m from the ground) results showed that (below 14cm) and (below 28cm) DBH trees were the majority (approximately 93%) in OCB_ITPWD, while medium and (more then 30cm) DBH trees were the majority (approximately 87%) in FSB_ITPWD, indicating different DBH distribution. On the other hand, the elevation distribution rate of OCB_ITPWD was mostly between 401 and 500m (approximately 30%), while that of FSB_ITPWD was mostly between 301 and 400m (approximately 45%). Additionally, the accessibility from the forest road was the highest at "100m or less" for both OCB_ITPWD (24%) and FSB_ITPWD (31%), indicating that more trees were infected when a stand was closer to a forest road with higher accessibility. OCB_ITPWD hotspots were 31 and 32 compartments, and it was highly distributed in areas with a higher age class and a higher DBH class.

• Journal of Life Science
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• v.29 no.6
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• pp.653-661
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• 2019

The first small interfering RNA (siRNA) therapeutics have recently been approved by the Food and Drug Administration in the U.S., and the demand for a new RNA therapeutics bioanalysis method-which is essential for pharmacokinetics, including the absorption, distribution, metabolism, and excretion of siRNA therapeutics-is rapidly increasing. The stem-loop real-time qPCR (RT-qPCR) assay is a useful molecular technique for the identification and quantification of small RNA (e.g., micro RNA and siRNA) and can be applied for the bioanalysis of siRNA therapeutics. When the anti-HPV E6/E7 siRNA therapeutic was used in preclinical trials, the established stem-loop RT-qPCR assay was validated. The limit of detection was sensitive up to 10 fM and the lower limit of quantification up to 100 fM. In fact, the reliability of the established test method was further validated in three intra assays. Here, the correlation coefficient of $R^2$>0.99, the slope of -3.10 ~ -3.40, and the recovery rate within ${\pm}20%$ of the siRNA standard curve confirm its excellent robustness. Finally, the circulation profiles of siRNAs were demonstrated in rat serum, and the pharmacokinetic properties of the anti-HPV E6/E7 siRNA therapeutic were characterized using a stem-loop RT-qPCR assay. Therefore, the stemloop RT-qPCR assay enables accurate, precise, and sensitive siRNA duplex quantification and is suitable for the quantification of small RNA therapeutics using small volumes of biological samples.

• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.11-21
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• 2019

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the SN explosion. To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes around the world and monitors the images of 60 nearby galaxies at distances D < 50 Mpc to a cadence as short as a few hours. The target galaxies are bright in near-ultraviolet (NUV) with $M_{NUV}$ < -18.4 AB mag and have high probabilities of hosting SNe ($0.06SN\;yr^{-1}$ per galaxy). With this strategy, we expect to detect the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling us to detect the shock-heated emission from a progenitor star with a radius as small as $0.1R_{\odot}$. The accumulated data will be also useful for studying faint features around the target galaxies and other science projects. So far, 18 SNe have occurred in our target fields (16 in IMSNG galaxies) over 5 years, confirming our SN rate estimate of $0.06SN\;yr^{-1}$ per galaxy.

• Journal of Plant Biotechnology
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• v.46 no.3
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• pp.228-235
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• 2019

Apple (Malus pumila) is one of the most economically important fruits in Korea. but virus infection has decreased the sustainable production of apples and caused serious problems such as yield loss and poor fruit quality. Virus or viroid infection including apple chlorotic leaf spot virus (ACLSV), apple stem pitting virus (ASPV), apple stem grooving virus (ASGV), apple mosaic virus (ApMV) and apple scar skin viroid (ASSVd) have been also reported in Korea. In many cases, as apple gets infected with virus and viroid with no specific symptoms, the damage and symptoms caused by the viruses are not detected. In our research, viruses in the rootstock were eliminated for a virus-free apple dwarfing rootstock of M.9 and M.26. The virus elimination methods were apical meristem culture, thermotherapy ($37^{\circ}C$, 6 weeks) and chemotherapy($Ribavirin^{(R)}$). The detection of apple viruses was accomplished by Enzyme-linked Immuno-Sorbent Assay (ELlSA) and reverse transcription-polymerase chain reaction (RT-PCR). RT- PCR method was 10 ~ 30% more sensitive than the ELISA method. The efficiency of virus elimination was enhanced in apical meristem culture method. The acquisition rate of virus-free apple dwarfing rootstocks was 30 ~ 40% higher in apical meristem culture. After the meristem culturing of M.9, the infection ratio of ACLSV, ASPV and ASGV was 45%, 60% and 50%, respectively. In the apple dwarfing rootstock of M.26, the infection ratio of ACLSV, ASPV and ASGV was 40%, 55% and 55%, respectively. Based on this study, the best method for the production of virus-free apple dwarfing rootstocks was the apical meristem culture.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.97-106
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• 2022

Listeria monocytogenes (L. monocytogenes) is one of gram-positive foodborne pathogens with a very high fatality rate. Unlike most foodborne pathogens, L. monocytogenes is capable of growing at low temperatures, such as in refrigerated foods. Thus, various physical and chemical prevention methods are used in the manufacturing, processing and distribution of food. However, there are limitations to the methods such as possible changes to the food quality and the consumer awareness of synthetic preservatives. Thus, the aim of this study was to evaluate the anti-listeria activity of lactic acid bacteria (LAB) isolated from kimchi and characterize the bacteriocin produced by Lactococcuslactis which is one of isolated strains from kimchi. The analysis on the anti-listeria activity of a total of 36 species (Lactobacillus, Weissella, Lactobacillus, and Lactococcus) isolated from kimchi by the agar overlay method revealed that L. lactis NJ 1-10 and NJ 1-16 had the highest anti-listeria activity. For quantitatively analysis on the anti-listeria activity, NJ 1-10 and NJ 1-16 were co-cultured with L. monocytogenes in Brain Heat Infusion (BHI) broth, respectively. As a result, L. monocytogenes was reduced by 3.0 log CFU/mL in 20 h, lowering the number of bacteria to below the detection limit. Both LAB strains showed anti-listeria activity against 24 serotypes of L. monocytogenes, although the sizes of clear zone was slightly different. No clear zone was observed when the supernatants of both LAB cultures were treated with proteinase-K, indicating that their anti-listerial activities might be due to the production of bacteriocins. Heat stability of the partially purified bacteriocins of NJ 1-10 and NJ 1-16 was relatively stable at 60℃ and 80℃. Yet, their anti-listeria activities were completely lost by 60 min of treatment at 100℃ and 15 min of treatment at 121℃. The analysis on the pH stability showed that their anti-listeria activities were the most stable at pH 4.01, and decreased with the increasing pH value, yet, was not completely lost. Partially purified bacteriocins showed relatively stable anti-listeria activities in acetone, ethanol, and methanol, but their activities were reduced after chloroform treatment, yet was not completely lost. Conclusively, this study revealed that the bacteriocins produced by NJ 1-10 and NJ 1-16 effectively reduced L. monocytogenes, and that they were relatively stable against heat, pH, and organic solvents, therefore implying their potential as a natural antibacterial substance for controlling L. monocytogenes in food.