International Agency for Research on Cancer (IARC) has classified it as a possible carcinogen and World Health Organization (WHO) has suggested 50 ng/mL as a guideline value for 1,4-dioxane. Considering the toxicity of 1,4-dioxane and ingestion rate of drinking water, the monitoring of 1,4-dioxane in drinking water in Nakdong river is very important. We analyzed 1,4-dioxane four times per year for the 12 samples of treated water and 4 samples of raw water in Nakdong river in Korea from 2000 to 2007 and surveyed the trend of concentrations of 1,4-dioxane. As a results of analysis, 1,4-dioxane was detected from 0.24 to 240.2 ng/mL in treated water and from 0.39 to 81.9 ng/mL in raw water from 2000 to 2007. The average concentrations are 22.68 ng/mL and 19.15 ng/mL in treated water and raw water, respectively. The detected concentrations was decreased but frequency of detection was not changed since establishment of regulation in 2004. Results of comparison of 95 percentile excessive cancer risk of 1,4-dioxane in treated and raw water were each $6.63{\times}10^{-6}$, $3.17{\times}10^{-6}$ before 2004 and $2.10{\times}10^{-6}$, $1.22{\times}10^{-6}$ after 2004. Also, comparing the detected concentration and frequency for each season, these were more detected the concentration and frequency for 1,4-dioxane in treated and raw water from winter to spring.
In this study, the effect of MnSO4 on the insecticidal crystal (IC) produced by Bacillus thuringiensis for a rapid detection medium was analyzed. The strains used included one B. thuringiensis reference (KCTC 1511) and nine wild-type strains. The IC in B. thuringiensis was detected following the method published by the Ministry of Food and Drug Safety in Korea. In the nutrient agar to which 0.005% MnSO4 was added, IC was observed on two of the three plates after 48 hours of incubation and on all three plates after 120 hours. In AK agar, IC was observed on one and two of the three plates after 48 and 96 hours of incubation, respectively. These results indicated that 0.005% MnSO4 nutrient agar is more appropriate than AK agar for production of IC in B. thuringiensis. The effect of various MnSO4 concentrations on IC production was studied after 24 hours of incubation. IC was produced on 1 of the 10 plates with 0.000% MnSO4 nutrient agar, 2 of the 10 plates with 0.001% MnSO4 nutrient agar, and 3 of the 10 plates with 0.002% MnSO4 nutrient agar. IC was not observed for the other nutrient agars containing 0.003%-0.009% MnSO4. These results indicated that nutrient agar with 0.002% MnSO4 led to the most rapid production of IC by B. thuringiensis after 24 hours of incubation. However, the conditions for IC production by B. thuringiensis depended on the incubation conditions and strain activity. Therefore, further studies are needed to verify the effects of 0.002% MnSO4 on the production of IC by various Bacillus thuringiensis strains.
Jaerin Lee;Hyemin Park;Keunyoung Ryu;Keunyoung Ryu;Suyeon Choi;Eunhye Cho;Baesik Cho;Jinhee Kim
Journal of Food Hygiene and Safety
/
v.38
no.3
/
pp.99-111
/
2023
The purpose of this study was to provide basic data for setting more detailed standards for baby food and to provide food information that can be used in real-world settings. We purchased 80 snacks and 40 drinks for infants and toddlers from supermarkets and online markets and analyzed tar color, artificial sweeteners, mycotoxins, and nutritional components (e.g., sucrose, sodium, and calcium). Fortunately, it was confirmed that both tar color and sodium saccharin, which do not have detection criteria for labeled foods for infants and toddlers, were not detected. However, acesulfame potassium was detected at 0.07 g/kg in one snack sample. As for myxotoxins, aflatoxin (B1, B2, G1, and G2) and ochratoxin A were not detected. Fumonisin B1, fumonisin B2, and zearalenone were detected in the ranges of 9.78-78.94 ㎍/kg, 5.58-11.73 ㎍/kg, and 2.96-8.83 ㎍/kg, respectively, but only in snacks. Sucrose was detected in 65 of the snacks (0.02-40.94 g/net weight [g]) and in 24 of the drinks (0.12-27.60 g/net weight [g]). Minerals were detected in most of the samples, and in four snacks, the zinc content per net exceeded the tolerable upper intake level for infants. Sixteen snacks exceeded the food standards for sodium content for infants and toddlers, but none of them were labeled as food for infants and toddlers in the product manufacturing report, such that the corresponding standards could not be applied. Therefore, it seems necessary to establish institutional improvements, such as strengthening labeling standards, so that the currently enforced standards can be appropriately applied, and establishing standards for labeled foods for infants and toddlers.
To investigate residual pesticide levels in agricultural products contained in Meal-kits, 27 Meal-kit products were collected from marts, Meal-kit shops, and online stores in Incheon City, South Korea. Seventy-six vegetable and thirty-seven mushroom products were analyzed for residual levels of 339 pesticides. Residual pesticides were detected in 23 out of 76 vegetables and were not present in the 37 mushroom products. The residual pesticide detection rate was 20.4% (23/113 cases). The pesticides famoxadone 0.034 mg/kg (standard: 0.01 mg/kg or less, PLS) and fenpyroximate 0.302 mg/kg (standard: 0.01 mg/kg or less, PLS) exceeded their maximum residue levels (MRL). This survey revealed that various types of pesticides remain in agricultural products in Meal-kits. Due to the nature of Meal-kit products, there is no separate standard for residual pesticides in agricultural products. Therefore, continuous monitoring of residual pesticides is necessary.
Soryeon Park;Sanghun Son;Jaegu Bae;Doi Lee;Dongju Seo;Jinsoo Kim
Korean Journal of Remote Sensing
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v.39
no.5_1
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pp.655-667
/
2023
Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R2), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R2 of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.
This study aims to analyze the development and current trends of AI-based medical imaging devices commercialized in South Korea. As of September 30, 2023, there were a total of 186 AI-based medical devices licensed, certified, and reported to the Korean Ministry of Food and Drug Safety, of which 138 were related to imaging. The study comprehensively examined the yearly approval trends, equipment types, application areas, and key functions from 2018 to 2023. The study found that the number of AI medical devices started from four products in 2018 and grew steadily until 2023, with a sharp increase after 2020. This can be attributed to the interaction between the advancement of AI technology and the increasing demand in the medical field. By equipment, AI medical devices were developed in the order of CT, X-ray, and MR, which reflects the characteristics and clinical importance of the images of each equipment. This study found that the development of AI medical devices for specific areas such as the thorax, cranial nerves, and musculoskeletal system is active, and the main functions are medical image analysis, detection and diagnosis assistance, and image transmission. These results suggest that AI's pattern recognition and data analysis capabilities are playing an important role in the medical imaging field. In addition, this study examined the number of Korean products that have received international certifications, particularly the US FDA and European CE. The results show that many products have been certified by both organizations, indicating that Korean AI medical devices are in line with international standards and are competitive in the global market. By analyzing the impact of AI technology on medical imaging and its potential for development, this study provides important implications for future research and development directions. However, challenges such as regulatory aspects, data quality and accessibility, and clinical validity are also pointed out, requiring continued research and improvement on these issues.
The benzo[a]pyrene in edible oils is extracted using methods such as Liquid-liquid, soxhlet and ultrasound-assisted extraction. However these extraction methods have significant drawbacks, such as long extraction time and large amount of solvent usage. To overcome these drawbacks, this study attempted to improve the current complex benzo[a]pyrene analysis method by applying the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method that can be analyzed in a simple and short time. The QuEChERS method applied in this study includes extraction of benzo[a]pyrene into n-hexane saturated acetonitrile and n-hexane. After extraction and distribution using magnesium sulfate and sodium chloride, benzo[a]pyrene is analyzed by liquid chromatography with fluorescence detector (LC/FLR). As a result of method validation of the new method, the limit of detection (LOD) and quantification (LOQ) were 0.02 ㎍/kg and 0.05 ㎍/kg, respectively. The calibration curves were constructed using five levels (0.1~10 ㎍/kg) and coefficient (R2) was above 0.99. Mean recovery ratio was ranged from 74.5 to 79.3 % with a relative standard deviation (RSD) between 0.52 to 1.58 %. The accuracy and precision were 72.6~79.4 % and 0.14~7.20 %, respectively. All results satisfied the criteria ranges requested in the Food Safety Evaluation Department guidelines (2016) and AOAC official method of analysis (2023). Therefore, the analysis method presented in this study was a relatively simple pretreatment method compared to the existing analysis method, which reduced the analysis time and solvent use to 92 % and 96 %, respectively.
Sejeong Bae ;Bokyung Son ;Taejun Sung ;Yeonsu Lee ;Jungho Im ;Yoojin Kang
Korean Journal of Remote Sensing
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v.39
no.5_3
/
pp.1009-1029
/
2023
Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R2 of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R2 of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.
Nam Young Kim;Eun-Ji Park;So-Ra Park;Jung Mi Lee;Yong Hyun Jung;Hae Jung Yoon
Journal of Food Hygiene and Safety
/
v.38
no.5
/
pp.361-372
/
2023
Organotin pesticide is used as an acaricide in agriculture and may contaminate livestock products. This study aims to develop a rapid and straightforward analytical method for detecting organotin pesticides, specifically azocyclotin, cyhexatin, and fenbutatin oxide, in various livestock products, including beef, pork, chicken, egg, and milk, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The extraction process involved the use of 1% acetic acid in a mixture of acetonitrile and ethyl acetate (1:1). This was followed by the addition of anhydrous magnesium sulfate (MgSO4) and anhydrous sodium chloride. The extracts were subsequently purified using octadecyl (C18) and primary secondary amine (PSA), after which the supernatant was evaporated. Organotin pesticide recovery ranged from 75.7 to 115.3%, with a coefficient of variation (CV) below 25.3%. The results meet the criteria range of the Codex guidelines (CODEX CAC/GL 40). The analytical method in this study will be invaluable for the analysis of organotin pesticides in livestock products.
Major components of lac coloring include laccaic acids A, B, C, and E. The Korean Food Additive Code regulates the use of lac coloring and prohibits its use in ten types of food products including natural food products. Since no commercial standards are available for laccaic acids A, B, C, and E, a standard for lac pigment itself was used to separate laccaic acids from the lac pigment molecule. A standard for each laccaic acid was then obtained by fractionation. To obtain pure lac pigment for use in food by High performance Liquid Chromatography Photo Diode Array (PDA), a C8 column yielded the best resolution among various tested columns and mobile phases. A qualitative analytical method using High Performance Liquid Chromatography (HPLC) Tandem Mass(LC-MS/MS) was developed. The conditions for fast and precise sample preparation begin with extraction using methanol and 0.3% ammonium phosphate, followed by concentration. The degree of precision observed for the analyses of ham, tomato juice and Red pepper paste was 0.3-13.1% (Relative Standard Deviation (RSD%)), degree of accuracy was 90.3-122.2% with r2=0.999 or above, and recovery rate was 91.6-114.9%. The limit of detection was 0.01-0.15 ㎍/mL, and the limits of quantitation ranged from 0.02 to 0.47 ㎍/mL. Lac pigment was not detected in 117 food products in the 10 food categories for which the use of lac pigment is banned. Multiple laccaic acids were detected in 105 food products in 6 food categories that are allowed to use lac color. Lac pigment concentrations range from 0.08 to 16.67 ㎍/mL.
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