• Journal of Food Hygiene and Safety
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• v.35 no.1
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• pp.23-30
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• 2020

This study investigated the migration levels of lead (Pb), cadmium (Cd), and arsenic (As) from food contact articles (glassware, ceramics, enamelware, and earthenware) into a food stimulant (4% v/v, acetic acid). Migration tests were performed at 25℃ for 24 h and all analyses were performed using Inductively-Coupled Plasma Mass Spectrometry (ICP-MS). The method was validated by linearity of calibration curves, limit of detection (LOD), limit of quantification (LOQ), recovery, precision, and uncertainty. In glassware, the migration concentrations ranged from not-detected (N.D.) to 752.21 ㎍/L and N.D. to 1.99 ㎍/L for Pb and Cd, respectively. In ceramics, the migration concentrations ranged from N.D. to 1,955.86 ㎍/L, N.D. to 74.06 ㎍/L, and N.D. to 302.40 ㎍/L for Pb, Cd, and As, respectively. In enamelware, the migration concentrations ranged from N.D. to 4.48 ㎍/L, N.D. to 7.00 ㎍/L, and N.D. to 52.00 ㎍/L for Pb, Cd, and Sb, respectively. In earthenware, the migration concentrations ranged from N.D. to 13.68 ㎍/L, N.D. to 0.04 ㎍/L, and N.D. to 6.71 ㎍/L for Pb, Cd, and As, respectively. All results were below the migration limits of Korea standards and specifications for food utensils, containers, and packages.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.821-831
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• 2013

Recently image velocimetries, including particle image velocimetry (PIV) and surface image velocimetry (SIV), are often used to measure flow velocities in laboratories and rivers. The most difficult point in using image velocimetries may be how to determine the sizes of the interrogation areas and the measurement uncertainties. Especially, it is a little hard for unskilled users to use these instruments, since any standardized measuring techniques or measurement uncertainties are not well evaluated. Sometimes the user's skill and understanding on the instruments may make a wide gap between velocity measurement results. The present study aims to evaluate image velocimetry's uncertainties due to the changes in the sizes of interrogation areas and searching areas with the error analyses. For the purpose, we generated 12 series of artificial images with known velocity fields and various numbers and sizes of particles. The analysis results showed that the accuracy of velocity measurements of the image velocimetry was significantly affected by the change of the size of interrogation area. Generally speaking, the error was reduced as the size of interrogation areas became small. For the same sizes of interrogation areas, the larger particle sizes and the larger number of particles resulted smaller errors. Especially, the errors of the image velocimetries were more affected by the number of particles rather than the sizes of them. As the sizes of interrogation areas were increased, the differences between the maximum and the minimum errors seemed to be reduced. For the size of the interrogation area whose average errors were less than 5%, the differences between the maximum and the minimum errors seemed a little large. For the case, in other words, the uncertainty of the velocity measurements of the image velocimetry was large. In the viewpoint of the particle density, the size of the interrogation area was small for large particle density cases. For the cases of large number of particle and small particle density, however, the minimum size of interrogation area became smaller.

• Journal of Food Hygiene and Safety
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• v.30 no.3
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• pp.265-271
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• 2015

This study was done in order to investigate the naturally occurring levels of nitrate and nitrite in livestock products. Total samples of 458 consisting of meats (n = 223), processed meat products (n = 51), raw milks (n = 30), processed milk products (n = 142), eggs (n = 5) and processed egg products (n = 7) were analyzed for contents of nitrate and nitrite by ion chromatography (IC). That methods showed good results in terms of linearity, limit of detection (LOD), limit of quantitation (LOQ), recovery, reproducibility and uncertainty. Nitrate and nitrite were detected in 167 and 40 samples, respectively. The nitrate levels (mg/kg) were not detected (ND)~40.23 for modified milks, ND~37.97 for sauce meats, ND~32.40 for process cheeses, ND~31.50 for processed egg products, ND~27.73 for dry milks, ND~24.76 for sausages, ND~22.45 for bacons, ND~21.55 for natural cheeses, ND~20.82 for hams and fermented milks, ND~13.57 for eggs, ND~12.77 for butters, ND~9.31 for milks and ND~3.88 for meats while the nitrite levels (mg/kg) were ND~17.35 for processed egg products and ND~1.92 for meats. In conclusion, the result of this study of nitrate and nitrite in livestock products could be used as one of scientific base datum to determine whether they are naturally occurring or not, including ingredients and their percentage, manufacturing processes, other papers relating to naturally occurring levels of them, and so on.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1281-1293
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• 2021

The recent launch of the GOCI-II enables South Korea to have the world's first capability in deriving the ocean color data at geostationary satellite orbit for about 20 years. It is necessary to develop a consistent long-term ocean color time-series spanning GOCI to GOCI-II mission and improve the accuracy through validation using in situ data. To assess the GOCI-II's early mission performance, the objective of this study is to compare the GOCI-II Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and remote sensing reflectances (R_rs) through comparison with the GOCI data. Overall, the distribution of GOCI-II Chl-a corresponds with that of the GOCI over the Yellow Sea, Korea Strait, and the Ulleung Basin. In particular, a smaller RMSE value (0.07) between GOCI and GOCI-II over the summer Ulleung Basin confirms the GOCI-II data's reliability. However, despite the excellent correlation, the GOCI-II tends to overestimate Chl-a than the GOCI over the Yellow Sea and Korea Strait. The similar over-estimation bias of the GOCI-II is also notable in CDOM. Whereas no significant bias or error is found for R_rs at 490 nm and 550 nm (RMSE~0), the underestimation of R_rs at 443 nm contributes to the overestimation of GOCI-II Chl-a and CDOM over the Yellow Sea and the Korea Strait. Also, we show over-estimation of GOCI-II R_rs at 660 nm relative to GOCI to cause a possible bias in Total suspended sediment. In conclusion, this study confirms the initial reliability of the GOCI-II ocean color products, and upcoming update of GOCI-II radiometric calibration will lessen the inconsistency between GOCI and GOCI-II ocean color products.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.609-625
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• 2022

Validation of satellite data products is critical for subsequent analysis that is based on the data. Particularly, performance of ocean color products in turbid and shallow near-land ocean areas has been questioned for long time for its difficulty that stems from the complex optical environment with varying distribution of water constituents. Furthermore, validation with ship-based or station-based measurements has also exhibited clear limitation in its spatial scale that is not compatible with that of satellite data. This study firstly performed validation of major GOCI-II products such as remote sensing reflectance, chlorophyll-a concentration, suspended particulate matter, and colored dissolved organic matter, using the in-situ measurements collected from ship-based field campaign. Secondly, this study also presents preliminary analysis on the use of drone images for product validation. Multispectral images were acquired from a MicaSense RedEdge camera onboard a UAV to compensate for the significant scale difference between the ship-based measurements and the satellite data. Variation of water radiance in terms of camera altitude was analyzed for future application of drone images for validation. Validation conducted with a limited number of samples showed that GOCI-II remote sensing reflectance at 555 nm is overestimated more than 30%, and chlorophyll-a and colored dissolved organic matter products exhibited little correlation with in-situ measurements. Suspended particulate matter showed moderate correlation with in-situ measurements (R²~0.6), with approximately 20% uncertainty.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.164-178
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• 2022

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.3
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• pp.175-182
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• 2022

Heavy metals can be intentionally or unintentionally introduced into plastic food utensils, containers, and packaging (PFUCP) as additives or contaminants, which can be ingested with food by humans. Here, seven-heavy metals (lead, cadmium, nickel, chromium, antimony, copper, and manganese) with toxicity concerns were selected, and risk assessment was done by establishing their migration from 137 PFUCP products made of 16 materials distributed in Korea. Migration of heavy metals was examined by applying 4% acetic acid as a food simulant (70℃, 30 minutes) to the PFUCP products. Inductively coupled plasma mass spectrometry (ICP-MS) was employed for the analysis of migrated heavy metals, and the reliability of quantitative results was confirmed by checking linearity, LOD, LOQ, recovery, precision, and expanded uncertainty. As a result of monitoring, heavy metals were detected at a level of non-detection to 8.76 ± 11.87 ㎍/L and most of the heavy metals investigated were only detected at trace amounts of less than 1 ㎍/L on average. However, antimony migrated from PET products was significantly higher than other groups. Risk assessment revealed that all the heavy metals investigated were safe with a margin of exposure above 311. Collectively, we demonstrated that heavy metals migrated from PFUCP products distributed in Korea appear to be within the safe range.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.