• 한국응용과학기술학회지
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• 제16권2호
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• pp.155-161
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• 1999

Red pepper powder (Capsicum annum L.) is an important seasoning as a kimchi ingredient in korea and most korean consumer tend to eat the korean red pepper powder as the better than other oriental country such as China. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China) of red pepper powder. The objective of this study is to determine if NIR technique could be used to discriminate between the korean red pepper powder and non-korean red pepper powder according to seed content and maxing ratio in red pepper powder by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographical origin of red pepper powder by near infrared spectroscopy and chemometrics were performed. It has been observed discriminant analysis with PLS is adequate to determinate the geographical origin of red pepper powder. It tend to difficult the discrimination of geographical origin according to increase the seed content of red pepper powder. The accuracy of discrimination in mixed red pepper powder was range from 95.2% to 100%.

• 한국환경농학회지
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• 제39권3호
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• pp.263-272
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• 2020

BACKGROUND: This paper describes the successful discrimination of GM crops from the respective wild type (WT) controls using spectroscopy and chemometric analysis. Despite the many benefits that GM crops, their development has raised concerns, particularly about their potential negative effects on food production and the environment. From this point of view, the introduction of GM crops into the market requires the development of rapid and accurate identification technologies to ensure consumer safety. METHODS AND RESULTS: The development of a GM crop discrimination model using spectroscopy involved the pre-processing of the collected spectral information, the selection of a discriminant model, and the verification of errors. Examples of GM versus WT discrimination using spectroscopy are available for soybeans, tomatoes, corn, sugarcane, soybean oil, canola oil, rice, and wheat. Here, we found that not only discrimination but also cultivar grouping was possible. CONCLUSION: Since for the determination of GM crop there is no pre-defined pre-processing method or calibration model, it is extremely important to select the appropriate ones to increase the accuracy in a case-by-case basis.

• Journal of Biosystems Engineering
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• 제40권2호
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• pp.153-158
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• 2015

Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data from line-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models were developed to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals were line-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region of Interest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) were selected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA) methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctly classify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showed that the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1% for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCA models for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.

• Journal of Plant Biotechnology
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• 제33권3호
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• pp.161-169
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• 2006

식물대사체학은 식물세포, 조직, 기관, 혹은 개체수준에서 주어진 시간과 조건에서 발견되는 모든 대사물질을 밝히고, 시간의 경과 혹은 조건의 변화에 따른 metabolic profiling의 변화를 연구하는 식물학 분야이다. 식물대사체학은 생물에 대한 전체론적 접근을 위한 가장 최근에 발달된 omics분야의 하나로서 일종의 시스템 생물학이다. 전체론적 접근과 이해를 위해서 대사체학은 metabolic profiling의 계량화학 혹은 다변량분석 방법을 자주 사용한다. 식물학분야에서 대사체학은 애기장대나 벼와 같은 모델식물에 tag를 도입하여 형질전환시킨 돌연변이체에 대해 DNA microarray와 함께 사용하여 유전자의 기능을 밝히는데 유용하게 사용된다. 본 총설에서는 식물대사체학의 기본 개념과 1H NMR 혹은 FTIR으로 얻은 metabolic profiling의 다변량분석에 대한 실용적인 사용법을 소개하고자 하였다.

• 대한화학회지
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• 제65권4호
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• pp.254-259
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• 2021

The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R², and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918-18.055, 9.014-23.825, and 9.040-13.350 mg/g of dry sample, respectively.

• 농업과학연구
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• 제47권4호
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• pp.995-1010
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• 2020

In this study, a multivariate analysis model of partial least square regression (PLSR) was developed to predict the moisture content of green peppers using hyperspectral imaging (HSI). In HSI, illumination is essential for high-quality image acquisition and directly affects the analytical performance of the visible near-infrared hyperspectral imaging (VIS/NIR-HSI) system. When green pepper images were acquired using a direct lighting system, the specular reflection from the surface of the objects and their intensities fluctuated with time. The images include artifacts on the surface of the materials, thereby increasing the variability of data and affecting the obtained accuracy by generating false-positive results. Therefore, images without glare on the surface of the green peppers were created using a polarization filter at the front of the camera lens and by exposing the polarizer sheet at the front of the lighting systems simultaneously. The results obtained from the PLSR analysis yielded a high determination coefficient of 0.89 value. The regression coefficients yielded by the best PLSR model were further developed for moisture content mapping in green peppers based on the selected wavelengths. Accordingly, the polarization filter helped achieve an uniform illumination and the removal of gloss and artifact glare from the green pepper images. These results demonstrate that the HSI technique with a polarized lighting system combined with chemometrics can be effectively used for high-throughput prediction of moisture content and image-based visualization.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1041-1041
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• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

• 한국축산식품학회지
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• 제42권2호
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• pp.240-251
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• 2022

Fat deposition in animal muscles differs according to the genetics and muscle anatomical locations. Moreover, different fat to lean muscle ratios (quality grade, QG) might contribute to aroma development in highly marbled beef. Scientific evidence is required to determine whether the abundance of aroma volatiles is positively correlated with the amount of fat in highly marbled beef. Therefore, this study aims to investigate the effect of QG on beef aroma profile using electronic nose data and a chemometric approach. An electronic nose with metal oxide semiconductors was used, and discrimination was performed using multivariate analysis, including principal component analysis and hierarchical clustering. The M. longissimus lumborum (striploin) of QG 1++, 1+, 1, and 2 of Hanwoo steers (n=6), finished under identical feeding systems on similar farms, were used. In contrast to the proportion of monounsaturated fatty acids (MUFAs), the abundance of volatile compounds and the proportion of polyunsaturated fatty acids (PUFAs) decreased as the QG increased. The aroma profile of striploin from carcasses of different QGs was well-discriminated. QG1++ was close to QG1+, while QG1 and QG2 were within a cluster. In conclusion, aroma development in beef is strongly influenced by fat deposition, particularly the fat-to-lean muscle ratio with regard to the proportion of PUFA. As MUFA slows down the oxidation and release of volatile compounds, leaner beef containing a higher proportion of PUFA produces more volatile compounds than beef with a higher amount of intramuscular fat.

• 분석과학
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• 제24권6호
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• pp.519-526
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• 2011

본 연구에서는 위장관에 작용하는 트리메부틴말레인산염을 주성분으로 하는 서방정의 제조 과정 중 혼합과정의 혼합 진행 정도의 확인에 근적외분광분석법과 라만분광분석법을 적용하였다. 서방정의 제조의 혼합 과정에서 소량의 부형제로 콜로이달실리콘디옥사이드, 탈크, 스테아르산, 스페타르산마그네슘을 넣어 혼합하는 과정에서, 각 혼합 시간 별, 혼합기 내에서 구역 별 혼합물 시료를 채취한 후 주성분(active ingredient)인 트리메부틴말레인산염의 양을 HPLC로 분석하였고, 동시에 채취한 시료의 근적외스펙트럼과 라만스펙트럼을 측정하여 PCA (Principal Component Analysis)를 수행하였다. 혼합기로는 U자형 혼합기를 사용하였고, 상, 중, 하와 좌, 우 각각 6개의 영역에서 시료를 채취하여 주성분과 부형제의 분포에 따른 혼합물의 균일도를 확인하고자 하였다. HPLC법으로는 소량의 부형제의 혼합을 주성분을 분석하는 것으로 시간에 따른 혼합도를 확인할 수 없는 반면, 근적외스펙트럼과 라만 스펙트럼에서는 주성분과 각각의 부형제의 특징적인 피크들을 확인할 수 있었고, 이러한 특징적인 흡광도를 가진 영역을 이용하여 전체 혼합물에서의 부형제 영향에 의한 변화를 PCA를 수행하여 혼합의 진행 정도를 성공적으로 확인하였다. 산란의 영향에 의한 바탕선의 변이를 제거하기 위해 전처리 방법으로는 미분을 사용하였고, 근적외스펙트럼에서는 5000-7500 $cm^{-1}$를 사용하였고, 라만스펙트럼에서는 1000-1500 $cm^{-1}$를 이용하여, PCA를 수행하였을 때 효과적으로 혼합의 진행정도를 확인할 수 있었다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4105-4105
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• 2001

Near infrared spectroscopy (NIRS) was employed to qualify and quantify on survival, the injury rate and apoptosis of the human breast cancer cell line MCF-7 cells. MCF-7 cells were cultured in RPMI medium supplemented with 10% FCS in a 95% air and 5% CO2 atmosphere at 37$^{\circ}C$. For the viable cells preparation, cells were de-touched by 0.1% of trypsin treatment and washed with RPMI supplemented with 10% FCS medium by centrifugation at 1000 rpm for 3min. For the dead cells preparation, cells were de-touched by a cell scraper. The cells were counted by a hemacytometer, and the viability was estimated by the exclusion method with frypan blue dye. Each viable and dead cells were suspended in PBS (phosphate bufferred saline) or milk at the cell density desired. For the quantitative determination of cell death by measuring the LDH (lactate dehydrogenase) activity liberated from cells with cell membrane injuries, LDH-Cytotoxic Test Wako (Wako, Pure Pharmaceutical Co. Ltd., Japan) was used. We found that NIRS measurement of MCF-7 cells at the density range could evaluate and monitor the different characteristics of living cells and dead cells. The spectral analysis was performed in two wavelength ranges and with 1,4, 10 mm pathlength. Different spectral data pretreatment and chemometrics methods were used. We applied SIMCA classificator on spectral data of living and dead cells and obtained good accuracy when identifying each class. Bigger variation in the spectra of living cells with different concentrations was observed when compared to the same concentrations of dead cells. PLS was used to measure the number of cells in PBS. The best model for measurement of dead cells, as well as living cells, was developed when raw spectra in the 600-1098 nm region and 4 mm pathlength were used. Smoothing and second derivative spectral data pretreatment gave worst results. The analysis of PLS loading explained this result with the scatter effect found in the raw spectra and increased with the number of cells. Calibration for cell count in the 1100-2500 nm region showed to be very inaccurate.