본 실험은 비 전리방사선인 가시광선을 조사한 미생물에서의 생리적 대사특징을 연구하였다. 이 실험에 사용된 미생물은 화학합성미생물인 Phodospirillum Rubrum KS-301이었다. glucose의 회분발효를 수행하였고 발효결과는 테이터의 기초가 되었다. 첫째, 비 전리방사선인 가시광선을 조사를 안 할 때의 잔류 glucose(기질량)량을 5.03 g/L -2.17 g/L로 감소하면은 균체량은 1.08 g/L - 3.14 g/L로 수소생성량은 0.02 g - 0.19 g로 증가 하였다. 둘째, 비 전리방사선인 가시광선을 조사 할 때의 잔류 glucose(기질량)을 13.17 g/L - 5.2 g/L로 감소하면은 균체량은 4.7 g/L - 10.57 g/L로 수소생성량은 0.186 g - 0.3 g로 증가 하였다. 이 실험결과를 종합해 볼 때 비 전리방사선인 가시광선을 조사한 미생물에서의 생리적 대사특정으로는 가시광선을 미생물에게 조사한 결과 생명의 활동이 활발하게 일어나고 있음을 알았고 그 반대로 다양한 연구논문에 따르면 감마선, 엑스선, 전자선을 조사한 미생물에서는 세포치사나 세포의 기능적, 형태학적 장해를 나타내었음을 알 수가 있었다.

Sulfur hexafluoride has an extremely high global warming potential (GWP) because of strong absorption of infraredradiation and long atmospheric lifetime which cause the global warming effect. This study is to identify the effects ofdestruction and removal efficiency of SF6 by the addition of conditioning agent (oxygen, water vapor and hydrogen) whenusing the high ionization energy. The irradiation intensity of ionization energy was 2mA, 5mA, 10mA and 15mA. TheSF6 was completely removed with H2O and H2 gas injection at 2mA. Main by-products were HF and F2 gases. HF andF2 gas formation was increased with irradiation intensity increasing. Most of the by-products of particle were sulfur andmetal sulfate.

This study assessed the analysis method for measuring volatile organic silicon compounds (namely as siloxanes) by usinggas chromatography with flame ionization detector. Calibration standard gas was made in a laboratory by using six volatileorganic silicons as model gas. Two different types of working gas were prepared to evaluate quality control in GC-FIDanalysis. Less than 0.2 RSD% of repeatability of retention time was observed in the analysis of calibration standard gas. Inthe linearity test, the highest coefficient of determination (R2) was found to be 0.997 for L2 among volatile organic siliconcompounds. This study demonstrated that quantification of volatile organic silicon compounds can be performed by usingGC-FID analysis with direct injection mode, and the GC calibration can be covered by the gas-phase standard method.

SF6 (sulfur hexafluoride) gas has an extremely high global warming potential (GWP) because of strong absorption of infrared radiation and long atmospheric lifetime which cause the global warming effect. The objective of this study is to identify the effects of destruction and removal efficiency (DRE) of SF6 by the addition of oxygen, water vapor and hydrogen. The applied dose of ionization energy was 1,028 kGy(5 mA). The initial concentrations of SF6, O2, H2O and H2 gases were 1,000 ppm, 1,000 ppm, 3,000 ppm, 3,000 ppm, respectively. The DRE was increased about 2 times with O2 gas injection. The SF6 was completely removed with H2O and H2 gas injection. By-products formed by SF6 destruction were mainly HF and F2 gases. In addition, SF2, NF3, N2O, SO2, SO2F2, and NOx gases were produced.

Cereal seeds, sorghum, foxtail millet, hog millet, adlay, and corn are traditionally used as health assistant as well as energy supplying food in Korea. While beneficial phytochemicals to human have revealed in cereals, the information on peptides from cereals is far less accumulated than major reserve protein. Here, we analyzed peptide profiles using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) in cereal seeds for construction of peptide information and attempted to develop peptide biomarkers for cereal identification. To optimize the analysis condition of SELDI-TOF MS, the effect of dilution factor on binding affinity to protein chips was tested using CM10 and Q10 arrays. Peptide clusters were significantly different at the level of 0.01 p-value. Peak spectra were the most stable in 1:50 of dilution factor in both chip arrays. Numbers of detected peak of 5 cereal seeds were 131 in CM10 and 74 in Q10 array. Each cereal was grouped as a cluster and well discriminated into different cluster in the level of 0.01 p-value. Numbers of potentially identified peptide biomarkers are 11, 13, 9, 5 and 12 in sorghum, foxtail millet, hog millet, adlay and corn, respectively. This study demonstrates that each cereal seed have own distinguishable specific peptides although their function are not identified yet in this study. In addition, the proteomic profiling using SELDI-TOF MS techniques could be a useful and powerful tool to discover peptide biomarker for discrimination and assess crop species, especially under 20 kDa.

Discovery, identification, and informatics of low molecular weight peptide are extensively rising in the field of proteomics research. In this study, we analyzed protein profiles to discover peptide based biomarker for twelve different soybean seeds with three different agronomic types using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). For optimization of SELDI-TOF MS in soybean seed proteome analysis, four different extraction buffers were tested with urea solubilization buffer, thiourea/urea solubilization buffer, phenol extraction buffer, and modified trichloroacetic acid (TCA)/acetone precipitation/urea solubilization extraction buffer. Two different type of ProteinChip arrays, cation exchange (CM10) and anion exchange (Q10), applied to profile peptides. Among the four different extraction buffers, phenol extraction was selected to protein extraction methodology. Numbers of detected peak cluster in twelve soybean seeds were 125 at CM10 and 90 at Q10 array in the mass range from 2 to 40 kDa. Among them, 82 peak clusters at CM10 and 33 peak clusters at Q10 array showed significantly different peak clusters at p<0.00004 (CM10) and p<0.00005 (Q10) among twelve different soybean cultivars. Moreover, 29 peak clusters at CM10 and 17 peak clusters at Q10 array were detected in all cultivars as an ‘universally existed peptide’. In comparison with three different agronomic types, total of 55 peak clusters (CM10) and 23 peak clusters (Q10) were significantly different peak clusters at p<0.00004 and p<0.0001, respectively. In these probability levels, soybean seeds were well discriminated into different cultivar and different type with each other. Also we could find several specific peptide biomarkers for agronomic type.