• 한국응용과학기술학회지
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• 제16권1호
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• pp.21-24
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• 1999

Sesame seed (Sesamum indicum L.) is an important seasoning in Korea and most korean consumer tend to eat the korean sesame seed as the best than other ones produced in oriental countries such as China and Japan. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China and so on) of sesame seeds. Near-infrared spectroscopy among the many kinds of techniques could provide a rapid screening, low cost solution to discriminate geographical origin of sesame seed. The objective of this study is to determine if NIR technique could be used to discriminate between the korean sesame seed and non-korean sesame seed by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographic origin of sesame seeds were discriminated relative accurately according to geographical origin using PLS regression method.

• 약학회지
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• 제48권3호
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• pp.171-176
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• 2004

This study was described for measuring clinically relevant levels of glucose in undiluted plasma and whole blood by near-infrared (NIR) spectroscopy. Result from an initial measurement of major blood components powder was over-lapped the absorption bands of glucose at 1500-1600 nm. However, the NIR data of blood components were clearly separated by principle component analysis (PCA) space. By the use of partial least squares (PLS) regression, glucose concentrations in undiluted plasma and whole blood could be determined with standard errors of prediction (SEP) of 15 mg/dl and 76 mg/dl, respectively. Although these blood components possessed strong absorption bands that overlapped with the absorption bands of glucose, successful calibration models could be carried out.

• 약학회지
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• 제48권3호
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• pp.177-181
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• 2004

Non-invasive blood glucose measurement from mouse tail was performed by near-infrared (NIR) spectroscopy. Three groups; normal, type I diabetes (insulin dependent diabetes mellitus, IDDM), type II diabetes (non-insulin dependent diabetes mellitus, NIDDM) group, were studied over a 10 weeks period with the collection of near-infrared (NIR) spectra. Spectral variations from long-term measurement (10 weeks) from dramatic and nonlinear changes in the optical properties of the live tissue sample were compensated by chemometrics techniques such as principle component analysis (PCA) and partial least squares (PLS) regression. The effect from mouse body temperature changes on NIR spectral data was also considered. This study showed that the compensation of variations from long-term measurement and temperature changes improved calibration accuracy of non-invasive blood glucose measurement.

• 한국광학회지
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• 제20권6호
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• pp.346-353
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• 2009

요당과 요단백은 소변검사의 중요한 항목으로 스트립을 사용하는 화학적 방법에 의하여 측정되어왔다. 본 연구에서는 중적외선 분광학을 이용하여 이 두 성분의 농도를 측정하였다. 샘플은 상용 합성뇨를 사용하였으며 여기에 추가적으로 글루코즈와 알부민, 그리고 가장 큰 영향의 간섭물질인 적혈구의 세 성분의 농도를 서로 상관관계 없이 조절하여 만들었다. 부분최소자승회귀법을 바탕으로 각 성분의 농도 예측을 위한 최적 파장대역을 구하였다 (글루코즈 980 - 1150/cm, 알부민 1400 - 1570/cm). 다른 성분에의한 간섭은 예측오차를 증가시켰으며, 특히 알부민의 경우에는 글루코즈와 적혈구에 의한 영향이 크게 나타났다. 타 성분의 유무에 따라서 글루코즈 농도가 0 ${\sim}$ 1000 mg/dl인 범위에서의 예측오차는 29.85 ${\sim}$ 45.19 mg/dl 이며 알부민 경우에는 0 ${\sim}$ 500 mg/dl 범위에서 예측오차는 14.0 ${\sim}$ 93.11 mg/dl 이였다. 본 연구는 몇 단계의 범위만을 제시하는 스트립을 이용한 기존의 요검사 보다 더욱 정량적 평가가 가능한 대안으로 사료되었다.

• 분석과학
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• 제12권5호
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• pp.375-381
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• 1999

본 연구는 기존에 사용되고 있는 음주측정기의 부정확성과 비위생적인 면을 개선하기 위한 비침습적인 알코올 측정기를 개발하기 위해 근적외선분광분석법을 적용하였다. 먼저 근적외선분광분석법으로 혈중 알코올을 측정하기 위한 전 단계로 순수한 알코올을 0.01~0.1%의 농도로 함유한 검체를 측정하였다. MLR(multiple linear regression)방법을 통한 통계적 처리에서 1360, 2256, 2012, 그리고 1358 nm의 네 파장을 선택했을 때 SEC(standard error of calibration)은 0.0039, multiple R은 0.99를 나타냈다. 혈중 알코올 시료 측정시 MLR을 적용했을 때 2266과 2326 nm 파장을 선택했을 경우 가장 유의성 있는 결과를 나타냈다. 또 다른 통계적 방법인 PLSR(partial least squares regression)의 경우 이차 미분 스펙트럼의 1100~1340, 1500~1796, 그리고 2064~2300 nm의 범위에서 4개의 factor를 사용했을 때 0.030의 SEP값을 나타냈다. 이로서 근적외선분광분석법을 이용하여 혈액 중의 알코올을 신속하게 분석할 수 있는 가능성을 제시하였다.

• 한국토양비료학회지
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• 제37권4호
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• pp.259-265
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• 2004

사과의 영양진단에서 사과잎 분석을 신속히 하기 위한 방법을 모색하기 위해 생잎과 건조잎을 이용해 근적의 스펙트럼을 측정하고 이를 질소 함량과의 최적의 상관관계를 도출하기 위해 부분소자승(PLS)과 주성분회귀(PCR)과 같은 다변량 분석법을 이용하여 비파괴 검량식을 작성하였다. 또한 검량식 작성에서 비파괴 측정 정확도를 향상시키기 위하여 smoothing, mean normalization, multiplicative scatter correction (MSC). derivative 등의 다양한 데이터 전처리 조작을 수행하여 정확도 향상 가능성을 조사하였다. 사과 건조잎의 비파괴 측정 가능성을 조사한 결과 PLS-1 모델에서 Norris first derivate하였을 태 RMSEP가 $0.6999g\;kg^{-1}$ 로 가장 좋았으며, 생잎은 Savitzky-Golay first derivate하였을 때에 RMSEP 가 $1.202g\;kg^{-1}$으로 가장 좋았다. 건조잎의 PCR 모델은 mean normalization 처리 후 Savitzky-Golay first derivative하였을 때가 RMSEP 가 $0.553g\;kg^{-1}$, 이었으며 생잎에서도 RMSEP는 $1.047g\;kg^{-1}$로 나타났다. 이와 같은 견과로서 사과의 생잎과 건조잎의 분석이 근적외분석기술에 의해 가능할 것으로 판단된다.

• Asian-Australasian Journal of Animal Sciences
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• 제18권4호
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• pp.580-583
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• 2005

We have evaluated the application of spectroscopy using an insertion-type fiber-optic probe and a sensor at wavelengths from 400 to 1,100 nm to the measurement of milk fat content on dairy farms. The internal reflectance ratios of 183 milk samples were determined with a fiber-optic spectrophotometer at 5$^{\circ}C$, 20$^{\circ}C$ and 40$^{\circ}C$. Partial least squares (PLS) regression was used to develop calibration models for the milk fat. The best accuracy of determination was found for an equation that was obtained using smoothed internal reflectance data and three PLS factors at 20$^{\circ}C$. The correlation coefficients between predicted and reference milk fat at 5$^{\circ}C$, 20$^{\circ}C$ and 40$^{\circ}C$ were r=0.753, r=0.796 and r=0.783, respectively. The predictive explained variances ($Q^2$) of the final model, moreover, were more than 0.550 at all temperatures, and the regression coefficients of determination ($R^2$) were more than 0.6 (60%). Our results indicate that milk has different internal reflectance measured in the range of visible and near infrared wavelengths (400 to 1,100 nm), depending on its fat content.

• 한국식품조리과학회지
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• 제32권4호
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• pp.413-425
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• 2016

Purpose: This study was conducted to understand the factors that affect the acceptance of gluten-free rice pasta samples prepared with added buckwheat, mungbean, and acorn starches, and to compare sensory characteristics of samples with those of 100% semolina pasta. Methods: Descriptive analysis of pasta was conducted by 12 trained panels. Acceptance test was carried out by 40 consumers using 7-point hedonic scale. Collected data was statistically analyzed by principal component analysis, and partial least squares regression analysis. Results: Quantitative descriptive analysis showed that increasing amount of buckwheat, mungbean, and acorn starches resulted in significant improvement in gluten-free rice pasta properties, especially texture, hardness, chewiness, roughness, and al dente with increasing amount of sample starches, and decreased adhesiveness. In acceptance test, appearance and texture of gluten-free rice pasta with mungbean starch were preferred than pasta made with 100% rice. Flavor and taste was preferred in pasta with buckwheat starch than other pasta samples. Rice pasta with 30% buckwheat starch showed the highest score in overall acceptance among rice samples. Conclusion: This study suggested that adding mungbean starch could improve texture of gluten-free pasta, and adding buckwheat starch would improve taste and flavor of gluten-free rice pasta.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1245-1245
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1152-1152
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.