• Korean journal of applied entomology
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• v.59 no.3
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• pp.265-275
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• 2020

In this study, we analyzed the nutritional ingredients of drone pupae (16^th to 20^th instar old) to evaluate the value of bee products and provide basic data for product diversification, and the extracts prepared using these pupae were tested for physiological activity. According to the analysis of the general ingredients of the freeze-dried powder of these bee pupae, the moisture, crude protein, crude fat, and crude ash was 1.69 ± 0.07%, 48.52 ± 0.20%, 23.41 ± 0.14%, and 4.05 ± 0.02%, respectively. Vitamin C and vitamin E were 14.92 ± 0.52 mg/100 g and 6.06 ± 0.11 mg α-TE/100 g, respectively. Regarding minerals, the highest content of K (1349.13 ± 34.57 mg/100 g) and P (1323.55 ± 43.85 mg/100 g) was observed and Ca and Fe were 55.43 ± 1.51 mg/100 g and 5.49 ± 0.19 mg/100 g, respectively. The fatty acids of the water extracted freeze-dried pupae powder accounted for approximately 59.62 of saturated fatty acids and 40.38 of unsaturated fatty acids, and high-quality fatty acids such as palmitic acid (C16:0) was 35.49 ± 0.08 and oleic acid (C18:1, n-9) was 35.91 ± 0.22 (g/100 g total fatty acids). The total amino acid content was 38.99 ± 2.63 g/100 g and the free amino acid was a total of 5129.04 mg/100 g, of which 1257.68 mg/100 g was proline and 759.12 mg/100 g glutamic acid. The DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity of the drone pupae extract showed values of 0.8 for distilled water extract, 3.2 for 50% EtOH extract, 6.4 for 70% EtOH extract, and approximately 90% for 32 ㎍/mL for 100% EtOH extract. These results suggest that the main compound contributing to the antioxidant activity is a polar compound, and it is highly likely to be a low-molecular protein or a free amino acid. In conclusion, the honey bee drone pupa is excellent as a food resource and can be utilized as a new functional material for food and functional food.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1299-1310
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• 2018

In this study, we analyzed distribution and movement trends using in-situ observations and particle tracking methods to understand the movement of the drift ice in the Arctic Ocean. The in-situ movement data of the drift ice in the Arctic Ocean used ITP (Ice-Tethered Profiler) provided by NOAA (National Oceanic and Atmospheric Administration) from 2009 to 2018, which was analyzed with the location and speed for each year. Particle tracking simulates the movement of the drift ice using daily current and wind data provided by HYCOM (Hybrid Coordinate Ocean Model) and ECMWF (European Centre for Medium-Range Weather Forecasts, 2009-2017). In order to simulate the movement of the drift ice throughout the Arctic Ocean, ITP data, a field observation data, were used as input to calculate the relationship between the current and wind and follow up the Lagrangian particle tracking. Particle tracking simulations were conducted with two experiments taking into account the effects of current and the combined effects of current and wind, most of which were reproduced in the same way as in-situ observations, given the effects of currents and winds. The movement of the drift ice in the Arctic Ocean was reproduced using a wind-imposed equation, which analyzed the movement of the drift ice in a particular year. In 2010, the Arctic Ocean Index (AOI) was a negative year, with particles clearly moving along the Beaufort Gyre, resulting in relatively large movements in Beaufort Sea. On the other hand, in 2017 AOI was a positive year, with most particles not affected by Gyre, resulting in relatively low speed and distance. Around the pole, the speed of the drift ice is lower in 2017 than 2010. From seasonal characteristics in 2010 and 2017, the movement of the drift ice increase in winter 2010 (0.22 m/s) and decrease to spring 2010 (0.16 m/s). In the case of 2017, the movement is increased in summer (0.22 m/s) and decreased to spring time (0.13 m/s). As a result, the particle tracking method will be appropriate to understand long-term drift ice movement trends by linking them with satellite data in place of limited field observations.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.1
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• pp.48-55
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• 2009

Seasonal variations of microalgal biomass and community composition in both the sediment and the seawater were investigated by HPLC pigment analysis in an estuarine muddy sandflat of Gwangyang Bay from January to November 2002. Based on the photosynthetic pigments, fucoxanthin, diadinoxanthin, and diatoxanthin were the most dominant pigments all the year round, indicating that diatoms were the predominant algal groups of both the sediment and the seawater in Gwangyang Bay. The other algal pigments except the diatom-marker pigments showed relatively low concentrations. Microphytobenthic chlorophyll ${\alpha}$ concentrations in the upper layer (0.5 cm) of sediments ranged from 3.44 (March at the middle site of the tidal flat) to 169 (July at the upper site) mg $m^{-2}$, with the annual mean concentrations of $68.4{\pm}45.5,\;21.3{\pm}14.3,\;22.9{\pm}15.6mg\;m^{-2}$ at the upper, middle, and lower tidal sites, respectively. Depth-integrated chlorophyll ${\alpha}$ concentrations in the overlying water column ranged from 1.66 (November) to 11.7 (July) mg $m^{-2}$, with an annual mean of $6.96{\pm}3.04mg\;m^{-2}$. Microphytobenthic biomasses were about 3${\sim}$10 times higher than depth-integrated phytoplankton biomass in the overlying water column. The physical characteristics of this shallow estuarine tidal flat, similarity in taxonomic composition of the phytoplankton and microphytobenthos, and similar seasonal patterns in their biomasses suggest that resuspended microphytobenthos are an important component of phytoplankton biomass in Gwangyang Bay. Therefore, considering the importance of microphytobenthos as possible food source for the estuarine benthic and pelagic consumers, a consistent monitoring work on the behavior of microphytobenthos is needed in the tidal flat ecosystems.