To analyze trace-level, reduced sulfur compounds (RSC) in ambient air, gas chromatography (GC) is used as the commonest method. The GC-based analysis is generally conducted by transferring samples via direct injection into GC or by the combined treatment of cryofocusing (CF) and thermal desorption (TD). In this study, experimental bias involved in GC analysis is examined by evaluating the calibration properties of each transfer approach. To this end, the detection properties of RSCs were evaluated with respect to the two major variables of sample concentration and sample volume. The recovery rate of TD application was also discussed based on the most recent findings in which its recovery rate is compared against the results derived by the direct injection method. The overall results suggest that the TD-based analysis of RSCs can be optimized by unifying the experimental conditions between sample and standard gases.

In order to accurately analyze trace-level, reduced sulfur compounds (RSC) in ambient air, one needs to rely on the thermal desorption technique (TD) to atone for the limited sensitivity of direct gas chromatography (GC) analysis. In this study, the relative performance of GC/PFPD system combined with TD unit was evaluated to help accurately determine RSC based on the comparative analysis of two types of calibration approaches. Hence, calibration results of RSCs were compared by controlling sample transfer system (air server (AS) and TD unit) between the two contrasting calibration approaches such as: incremental-loading of a given standard with the fixed standard concentration (FSC) vs. supply of standards made at multiple concentration points at the fixed standard volume (FSV). The results of our study indicate that RSC calibration is affected fairly sensitively by sample loading conditions of the AS/TD system. It is hence necessary to delicately control the TD operation conditions for the accurate quantification of RSCs, when GC/PFPD system with TD is employed for RSC analysis.

This study was investigated to develop mass evaluation system for the contents of crude protein, oil and fatty acid in soybean germplasm using NIRS. NIRS equations were created with 345 soybeans, multiple correlation coefficients of crude protein, oil, palmitic, stearic, oleic, linoleic and linolenic acid between data obtained from NIRS and quantitative analysis were 0.983, 0.969, 0.592, 0.514, 0.978, 0.961 and 0.957, respectively. Equation statistics indicated that contents of crude protein, oil and unsaturated fatty acid except palmitic and stearic acid in soybean seed were suitable for determination by NIRS. Those NIRS equations were applied to examine crude protein, oil and unsaturated fatty acid of 854 soybean landraces from Korea. The average contents and ranges of crude protein and oil were 39.2% with a range of 33.7-47.0% and 15.0% with a range of 9.8-20.3%, individually. In addition, those of oleic, linoleic and linolenic acid were 21.4% with a range of 12.1-30.2%, 55.6% with a 47.8-62.3% and 8.1% with a range of 5.9-10.7% respectively. We conducted quantitative analysis to reconfirm with IT154552 (45.1%) and IT023955(46.9%) above 45% of crude protein, the results were similar from NIRS (45.2%, 47.0%). NIRS data for protein from this study made no difference with lab data, which would be useful for mass evaluation. There was negative correlation (-0.203) between crude protein and oil, positive correlation (0.379) between crude oil and oleic acid, and significantly negative correlation (-0.879) between oleic and linoleic acid.

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.

연구용 NIR 장비에서 수집된 벼 생엽의 질소 함량 검량 식 및 데이터베이스를 현장용 NIR 장비에 검량식을 이설,검증함으로서 현장 적용 가능성을 평가하기 위해 수행한 결과는 다음과 같다.1. 2003년부터 2009년까지 스펙트럼을 수집한 시료 중선발 된 A 데이터 세트(개체수 454점)의 총 질소범위는 2.041%～4.933%, 2012년 수집된 B 데이터 세트(258점)는 2.180%～3.690%이며 각각의 전체 평균은3.497%, 2.712%였다.2. A, B 데이터 세트에서 유도된 검량식 결과 결정계수(R2)는 각각 0.845, 0.777,표준오차(SEC)는 0.196, 0.126,SECV는 0.238, 0.150이었다.3. 연구용 NIR 장비 400 nm～2500 nm 파장에서 얻어진데이터베이스를 현장용 NIR 장비 1200 nm～2400 nm파장에 맞게 잘라 이설한 후 2012년 데이터베이스에업데이트 확장한 후 작성된 검량식 결과 결정계수(R2)는 0.880, 표준오차(SEC)는 0.191이었다.4. 연구용 NIR 장비에 구축된 데이터베이스를 현장용NIR 장비에 맞춰 데이터베이스를 확장 업데이트하고검량식을 이설한 결과 연구용 장비와의 표준오차는0.005%로 거의 동일한 수준의 결과를 얻었다.

벼 영양진단에서 중요한 성분인 생체잎의 질소함량을 NIRS를 이용하여 신속하고 정확하게 분석하기 위해 최적의 검량식 작성에 관한 일련의 시험을 실시한 결과는 다음과 같다. 벼 생체엽 질소함량 검량식의 결정계수는 익산, 정읍, 부안지역이 각각 0.879, 0.858, 0.819였다. Outlier를 제거한 후 검량식을 다시 작성한 결과 0.896, 0.878, 0.88~% 로 각각 0.017, 0.02, 0.061씩 향상되었다. Merge 기능을 이용하여 검량식을 합병한 후 검량식을 다시 작성한 결과 0.971로 정확도가 더욱 향상되었다. 벼 생체엽의 질소함량 검량식에 의한 분석값과 습식분석 평균값의 차이는 0.001~% 를 나타냈다. 이와 같은 결과로서 건조와 분쇄과정을 생략하기 때문에 시료의 변질을 막을 수 있고 시간과 비용을 줄일 수 있는 벼 생잎의 질소농도 측정이 근적외분석기술에 의해 가능할 것으로 판단되었다.

Using Fuji apple fruits cultivated in Kyungpook prefecture, the calibration model for firmness evaluation of fruits by near infrared(NIR) reflectance spectroscopy was developed, and the various influence factors such as instrument variety, measuring method, sample group, apple peel and selection of firmness point were investigated. Spectra of sample were recorded in wavelength range of 1100∼2500nm using NIR spectrometer (InfraAlyzer 500), and data were analyzed by stepwise multiple linear regression of IDAS program. The accuracy of calibration model was the highest when using sample group with wide range, and the firmness mean values obtained in graph by texture analyser(TA) were used as standard data. Chemometrics models were developed using a calibration set of 324 samples and an independent validation set of 216 samples to evaluate the predictive ability of the models. The correlation coefficients and standard error of prediction were 0.84 and 0.094kg, respectively. Using developed calibration model, it was possible to monitor the firmness change of fruits during storage frequently. Time, which was reached to firmness high value in graph by TA, is possible to use as new parameter for freshness of fruit surface during storage.