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신대근,양한술,민병록,Carlos Narciso-Gaytan,Marcos X. Sanchez-Plata,Ciro A. Ruiz-Feria 한국축산식품학회 2011 한국축산식품학회지 Vol.31 No.5
To evaluate the antioxidant effects of vitamin C, vitamin E and sorghum bran, alone or in combination on chicken sausages,9 kg of chicken thigh meat was prepared. All thigh meat was divided into seven different batches as follows; no antioxidant (CON); vitamin C (VTC), vitamin E (VTE) or sorghum bran (SOR) at 0.02%; or three different combination ratios of vitamin C, vitamin E and sorghum bran at 0.02% (VT2, 2:1:1; VT4, 4:1:1; VT6, 6:1:1). All cooked sausages were stored at 4oC, and six sausages per treatment were used for chemical analysis on five different storage days. As the addition of vitamin E was increased, sausages stored for 10 d had decreased redness; thereby, VTE showed the lowest CIE a^* (p<0.05). Sausages mixed with vitamins and sorghum bran combinations had lower peroxide and free fatty acid values (p<0.05) when compared to sausages without antioxidants. The TBARS were the lowest in sausages containing vitamin C, vitamin E and sorghum bran at 6:1:1 ratio, and they significantly differed to CON, VTC and SOR treatments (p<0.05). Therefore, our results suggest that meat mixed with vitamins and sorghum bran had more antioxidant activity than the meat mixed with only antioxidant vitamins or without antioxidants.
A New Application of Unsupervised Learning to Nighttime Sea Fog Detection
신대근,김재환 한국기상학회 2018 Asia-Pacific Journal of Atmospheric Sciences Vol.54 No.4
This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the 3.7 μm and 10.8 μm channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation–maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.
사료의 지방산 조성이 돈육의 이화학적 및 관능적 특성에 미치는 영향
신대근,김윤지,이무하,강통삼 ( D . K . Shin,Y . J . Kim,M . H . Lee,T . S . Kang ) 한국축산학회 1998 한국축산학회지 Vol.40 No.5
This study was carried out to evaluate the physicochemical and sensory characteristics of pork and to found consumer`s preferences for types of unsaturate fatty acids fatified pork by feeding various levels of dietary unsaturated fatty acids(w-UFA) with 8% fat in the diet. Landrace-Yorkshire-Large White crossbreds pigs weighing 70kg were randomly assigned to 5 treatments(ω3: ω6: ω9= 1:1.5:2(A), 1:2:3(B), 1:1:1(C), 1:2:1(D), 1:3:1(E)) and a control(F). When the ratio of the unsaturated fatty acids was 1:2:1, moisture content was highest and crude protein content lowest among the treatments. Crude fat content was highest in C. However, crude ash content did not differ significantly. In physicochemical analysis, the treatment C showed average in drip loss and VBN value compared to the other treatments. In fatty acid analysis of pork loin, all the treatments except E were higher than F, D was significantly high in the UFA contents(p$lt;0.001). In sensory evaluation, the intensities of juiciness and tenderness were high in C, but the intensity of flavor was lowest although it was not significant statistically and then the fatty acids composition of feed hadn`t much influenced flavor. But, in acceptability, all the items except tenderness showed significant differences(p$lt;0.05 and p$lt;0.01). From the sensory test, the loins from pigs fed the diets high in m6 fatty acid showed highs preference than the loins from pigs fed the diet high in m 9 fatty acid in the all items such as juiciness, tenderness, flavor, fishy and acceptability. Conclusively, The loins from D(ω3: ω6: ω9 = 1:2:1) showed the highest preferences among loins from treatments in respect of physicochemical and sensory characteristics.
YES-AQ 캠페인 기간 중 기상 1호에서 광학입자계수기로 관측한 서해상 에어로졸 물리 특성
신대근,김정은,정주용,유희정 한국대기환경학회 2022 한국대기환경학회지 Vol.38 No.2
In order to identify the source of pollutants flowing into the Korean Peninsula and predict their impact, it is necessary to understand the characteristics of aerosols over the Yellow Sea. The Korea Meteorological Administration (KMA) has been conducting aerosol observations over the Yellow Sea in spring through the annual YEllow Sea Air-Quality (YES-AQ) joint observation campaign since 2018. In this study, aerosols in the Yellow Sea in spring were classified into the Background Particle Group (BPG), Fine particle Dominant Group (FDG), and Coarse particle Dominant Group (CDG) based on the particulate matter less than 10 μm (PM2.5) and the particulate matter less than 10 μm (PM10) mass concentrations obtained from the ship-based Optical Particle Counter (OPC) measurements. Statistical tools, such as the Gaussian mixture model and Gaussian kernel analysis, were utilized to classify the groups effectively. In company with, we presented various threshold values for the ratio of fine and coarse particles that can be easily distinguishing the FDG from the CDG. The BPG accounted for approximately 50% of the total data, and showed mean mass concentrations of 24.0 μg/m³ and 15.1 μg/m³ for PM10 and PM2.5, respectively. In the case of the CDG, PM10 and PM2.5 indicated the highest frequencies around 50 μg/m³ and 15 μg/m³, whereas they showed the highest frequencies around 45 μg/m³ and 35 μg/m³, respectively, for the case of the FDG. Our study provides criteria for easily discriminating natural and anthropogenic aerosols from OPC data in the Yellow Sea. In addition, it contributes to enhancing the reliability of aerosol analysis through mutual complementation with other instrument or analysis methods in unstable ship observation environment.