페놀은 보통 대기로 배출되며 반감기가 비교적 짧은 물질로서 환경에 농축되는 경우는 드물다. 하지만, 누출사고가 발생되어 수계나 토양에 오염될 경우 페놀에 오염된 농수산물의 안전성을 확보하기 위하여 페놀을 정확하게 검출할 수 있는 시험법을 확립하고자 하였다. 식품 중 페 놀을 초음파추출기로 추출하고 GPC로 정제하여 GC/MS 로 분석하는 시험법을 확립하였으며, 시험법의 유효성 확인을 위한 실험 결과들이 AOAC 가이드라인에서 제시하 는 Criteria를 만족함으로써 시험법의 신뢰성을 확보할 수 있었다. 확립된 시험법은 식품 중 페놀의 오염조사 및 이행률 조사에 활용될 수 있다.

항산화 기능은 암이나 심혈관질환 발생을 억제하는 것으로 보고되고 있어서 다양한 식물들에 대해서 항산화 효 과가 연구되고 있다. 그러나, 채소류에 대해서는 항산화 효과에 대한 광범위한 조사는 이루어지지 않아 단지 몇몇 천연 항산화제만이 식품 산업에서 이용되고 있다. 따라서, 본 연구에서는 식품 산업에서 다양한 천연 항산화제를 이용 할 수 있도록, 여러 가지 채소류에 대해 항산화 활성을 조사하여 채소류 중 항산화 효과에 대한 과학적 자료를 제공하기 위해 수행되었다. 24 품목의 채소류를 대상으로 총 275개의 시료를 구입하여 항산화 효과를 측정하였다. 총 페놀 함량(TPCs)은 gallic acid를 대조 표준용액으로 Folin- Ciocalteu 시약을 사용하여 비색법으로 측정하였으며 DPPH 라디컬 소거능은 IC50(DPPH 라디칼을 50% 저해하는데 필요한 추출물의 농도) 농도로 측정하였다. 조사 결과 여러 가지 채소류에 대한 총 페놀 함량은 0.32~49.26 μg/kg 였으며 DPPH 라디컬 소거 활성은 0.0~2.43 mg/mL로 조사 되었다. 본 연구에서 조사된 채소류 중 항산화 효과가 가장 좋은 채소는 2가지 항산화 측정 방법에서 모두 마늘 이였다.

The current standard for testing tetrodotoxin (TTX) in foodstuffs is the mouse bioassay (MBA) in Korea as in many other countries. However, this test suffers from potential ethical concerns over the use of live animals. In addition, the mouse bioassay does not test for a specific toxin thus a sample resulting in mouse incapacitation would need further confirmatory testing to determine the exact source toxin (e.g., TTX, STX, brevotoxin, etc.). Furthermore, though the time of death is proportional to toxicity in this assay, the dynamic range for this proportional relationship is small thus many samples must be diluted and new mice be injected to yield a result that falls within the quantitative dynamic range. Therefore, in recent years, there have been many efforts in this field to develop alternative assays. High performance liquid chromatography (HPLC) coupled with mass spectrometry (MS) has been emerged as one of the most promising options. A LC-MS-MS method involves solid-phase extraction (SPE) and followed by analysis using an electrospray in the positive ionization mode and multiple reactions monitoring (MRM). To adopt LC-MS-MS method as alternative standard for testing TTX, we performed a validation study for the quantification of TTX in puffer fish. This LC-MS-MS method showed good sensitivity as limits of detection (LOD) of 0.03~0.08 μg/g and limits of quantification (LOQ) of 0.10~0.25 μg/g. The linearity (r2) of tetrodotoxin were 0.9986~0.9997, the recovery were 80.9~103.0% and the relative standard deviations (RSD) were 4.3~13.0%. The correlation coefficient between the mouse bioassay and LC/MS/MS method was higher than 0.95.

An isocratic high performance liquid chromatography (HPLC) method for routine analysis of deoxynivalenol in noodles was validated and estimated the measurement uncertainty. Noodles (dried noodle and ramyeon) were analyzed by HPLC-ultraviolet detection using immunoaffinity column for clean-up. The limits of detection (LOD) and quantification (LOQ) were 7.5 μg/kg and 18.8 μg/kg, respectively. The calibration curve showed a good linearity, with correlation coefficients r² of 0.9999 in the concentration range from 20 to 500 μg/kg. Recoveries and Repeatabilities expressed as coefficients of variation (CV) spiked with 200 and 500 μg/kg were 82 ± 2.7% and 87 ± 1.3% in dried noodle, and 97 ± 1.6% and 91 ± 12.0% in ramyeon, respectively. The uncertainty sources in measurement process were identified as sample weight, final volume, and sample concentration in extraction volume as well as components such as standard stock solution, working standard solution, 5 standard solutions, calibration curve,matrix, and instrument. Deoxynivalenol concentration and expanded uncertainty in two matrixes spiked with 200 μg/kg and 500 μg/kg were estimated to be 163.8 ± 52.1 and 435.2 ± 91.6 μg/kg for dried noodle, and 194.3 ± 33.0 and 453.2 ± 91.1 μg/kg for ramyeon using a coverage factor of two which gives a level of statistical confidence with approximately 95%. The most influential component among uncertainty sources was the recovery of matrix, followed by calibration curve.

3-MCPD created in manufacture process was regulated in our country about soy sauce and HVP. The latest paper reported that Bound 3-MCPD is created as intermediate. Germany common risk assesment reported that Bound 3-MCPD must be reduced because Bound 3-MCPD can be created in estimation circle when this is hydrolyzed in human body, but the data about the toxity of Bound 3-MCPD is lack. Therefore, We analysis about 209 items food such as soy sauce, seasoning food and meat-eating manufactured goods using bound 3-MCPD analysis method developed recently. As result of survey, bound 3-MCPD detected in 8 items among 44 traditional sauce (0.02~0.28ppm), 8 of soup 12 items (0.01~0.96ppm), in 22 items of sauce 60 items (0.01~0.55ppm), in 16 items of meateating manufactured foods 30 items (0.04~0.18ppm), in 20 items of snack cookies 28 items (0.09~1.43ppm), in 8 in roasted oil foods 10 items (0.04~1.22ppm), in 6 items of peanut processed food 10 items (0.06~0.25ppm), in 1 of vegetable cream 15 items (0.05ppm). Detected level was lower than the result of monitored by other countries.

We used fluorescence detector to analyse total aflatoxins (G1, G2, B1, B2) with TFA (Trifluoroacetic acid) derivation method and PHRED (Photochemical reactor enhanced detection) method. PHRED method was superior in reproduction and convenience, but TFA derivation method was superior in selectivity and sensitivity. The recovery rate of aflatoxin B1, B2, G1 were more than 80%, and G2 was more than 70%. The detection limit of B1,B2, G1 and G2 were respectively 0.05, 0.05, 0.2 and 0.1 μg/kg. Confirmed method was used to analyse total aflatoxins in total 316 items as 9 kinds 137 dried fruits and 10 kinds 179 spices. By the result, Aflatoxins were detected in 27dried fruits (19.7%) and in 87 spices (48.6%).

A high performance computing cluster for astronomical computations has been built at Korea Astronomy Observatory. The 64 node cluster interconnected with Gigabit Ethernet is composed of 128 Intel Xeon processors, 160 GB memory, 6 TB global storage space, and an LTO (Linear Tape-Open) tape library. The cluster was installed and has been managed with the Open Source Cluster Application Resource (OSCAR) framework. Its performance for parallel computations was measured with a three-dimensional hydrodynamic code and showed quite a good scalability as the number of computational cells increases. The cluster has already been utilized for several computational research projects, some of which resulted in a few publications, even though its full operation time is less than one year. As a major resource of the K∗Grid testbed, the cluster has been used for Grid computations, too.