• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1162-1162
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• 2001

Whereas NIR spectroscopy has been applied in agriculture for more than 20 years, few studies refer to those plant substances occurring only in smaller amounts. Nevertheless there is a growing interest today to support efficiently activities in the production of high-quality medicinal and spice plants by this fast and non-invasive method. Therefore, it was the aim of this study to develop new NIR methods for the reliable prediction of secondary metabolites found as valuable substances in various plant species. First, sophisticated NIR methods were established to perform fast quality analyses of intact fennel, caraway and dill fruits deriving from single-plants [1]. Later on, a characterization of several leaf drugs and the corresponding fresh material has been successfully performed. In this context robust calibrations have been developed for dried peppermint, rosemary and sage leaves for the determination of their individual essential oil content and composition [2]. A specially adopted NIR method has been developed also for the analysis of carnosic acid in the leaves of numerous rosemary and sage gene bank accessions. Carnosic acid is an antioxidative substance for which several health promoting properties including cancer preservation are assumed. Also some other calibrations have been developed for non-volatile substances such as aspalathin (in unfermented rooibos leaves), catechins (in green tea) and echinacoside (in different Echinacea species) [3]. Some NIR analyses have also been successfully performed on fresh material, too. In spite of the fact that these measurements showed less accuracy in comparison to dried samples, the calibration equations are precise enough to register the individual plant ontogenesis and genetic background. Based on the information received, the farmers and breeders are able to determine the right harvest time (when the valuable components have reached their optimum profile) and to select high-quality genotypes during breeding experiments, respectively. First promising attempts have also been made to introduce mobile diode array spectrometers to collect the spectral data directly on the field or in the individual natural habitats. Since the development of reliable NIRS methods in this special field of application is very time-consuming and needs continuous maintenance of the calibration equations over a longer period, it is convenient to supply the corresponding calibration data to interested user via NIRS network. The present status of all activities, preformed in this context during the last three years, will be presented in detail.

• 한국식품저장유통학회지
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• 제24권1호
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• pp.145-152
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• 2017

본 연구에서는 전통 재래식 콩된장의 제조공정을 과학적으로 해석하기 위한 연구의 일환으로 생메주의 건조 및 발효과정에 있어서 수분함량과 단백질 분해에 의한 아미노산 생성과정을 근적외 분광법으로 쉽게 판단 할 수 있는지 그 가능성을 조사하였다. 생메주를 일정한 크기($3{\times}4{\times}3cm$)로 잘라서 수분이 30%가 되도록 $25^{\circ}C$ 항온기에 3주간 발효시킨 모델계 발효메주를 만들어 가시광-근적외 스펙트럼을 측정하여 해석하였다. 발효가 진행됨에 따라 수분이 감소되면서 수분과 관련이 있는 1,430 nm대의 흡광도가 감소 및 시프트 되는 것이 관찰되었고, 발효기간이 길어질수록 아미노산과 관련이 있는 2,050 nm대의 흡광도가 증가하는 것을 관찰 할 수 있었다. 전통 재래식 발효메주를 속부분과 겉부분으로 분리하여 1,000-2,250 nm에서의 가시광 스펙트럼과 근적외 스펙트럼 데이터로 판별분석한 결과, 겉부분과 속부분이 잘 판별되었고, 가시광 보다는 근적외 영역에서 잘 구분되었다. 이들 전통메주중의 아미노산 농도를 비파괴 측정하기 위해 PLSR한 결과 $R^2$은 0.9 이상이며, RMSECv 0.23%로 나타났으며, 전통메주중의 수분함량도 $R^2$ 0.81, RMSECv 0.83%이어서 근적외 분광법으로 전통메주의 품질을 비파괴 측정 가능할 것으로 판단되었다.

• 산업식품공학
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• 제15권2호
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• pp.136-142
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• 2011

본 연구에서는 정상 콩과 이에 혼입되는 이물질을 판별하기 위해 900 nm에서 1800 nm의 파장대역에서 단색화장치가 장착된 근적외선 분광장치를 이용하여 획득된 콩과 이물질의 반사 스펙트럼의 세기를 이용하여 각각의 판별예측모델을 개발하고 그 성능과 판별정확도를 검증해보았다. 정상콩 60 립과 이물질 60 점을 각각 2 회 반복하여 측정한 총 240 개의 반사스펙트럼에 대해서 모델 개발용인 calibration group으로 168 개를, 나머지 72 개는 개발된 모델을 예측하는 prediction group으로 나누어 사용하였다. 획득된 스펙트럼은 광원의 불안정함, 시료의 크기와 형태에서 기인되는 여러 변이들을 최소화하기 위해 다양한 수학적인 전처리를 적용하였으며 판별예측모델의 개발을 위해 PLS-DA와 SIMCA 방법을 사용하여 모델의 예측 성능과 판별율을 검토하였다. PLS-DA에서 모델 개발에 사용된 84 개의 정상 콩 스펙트럼 CLASS I은 적용된 모든 전처리에서 100%의 판별율을 보여주었으며 이물질 스펙트럼 CLASS II에서도 SNV 전처리를 제외하고는 모두 100% 이물질로 판별하여 분류하였다. 개발된 PLS-DA의 모델에 대한 prediction group의 검증에 있어서는 평균값 정규화 전처리 방법이 정상 콩과 이물질에서 100% 판별율을 보여주었다. SIMCA를 이용한 이물질 판별예측모델 개발은 PLS-DA와 비교할 때 상대적으로 저조한 판별율 결과를 나타냈으며 최대값 정규화와 일정 범위값 정규화의 전처리 방법을 적용한 모델이 평균 판별율 94.4%로 다소 양호한 결과를 보여주었다. 따라서 콩에 혼입되어 있는 이물질을 판별하는 시스템을 개발하는 데 있어서 근적외선 분광장치를 이용하여 획득한 반사도 스펙트럼은 PLS-DA로 판별예측모델을 개발하고 최적의 전처리 방법을 적용한다면 콩과 이물질의 선별시에 보다 나은 판별율을 얻을 수 있을 것이다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1523-1523
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• 2001

The wine industry requires practical methods for objectively measuring the composition of both red wine grapes on the vine to determine optimal harvest time; and of freshly harvested grapes for efficient allocation to vinery process streams for particular red wine products, and to determine payment of contract grapegrowers. To be practical for industry application these methods must be rapid, inexpensive and accurate. In most cases this restricts the analyses available to measurement of TSS (total soluble solids, predominantly sugars) by refractometry and pH by electropotentiometry. These two parameters, however, do not provide a comprehensive compositional characterization for the purpose of winemaking. The concentration of anthocyanin pigment in red wine grapes is an accepted indicator of potential wine quality and price. However, routine analysis for total anthocyanins is not considered as a practical option by the wider wine industry because of the high cost and slow turnaround time of this multi-step wet chemical laboratory analysis. Recent work by this ${group}^{l,2}$ has established the capability of near infrared (NIR) spectroscopy to provide rapid, accurate and simultaneous measurement of total anthocyanins, TSS and pH in red wine grapes. The analyses may be carried out equally well using either research grade scanning spectrometers or much simpler reduced spectral range portable diode-array based instrumentation. We have recently expanded on this work by collecting thousands of red wine grape samples in Australia. The sample set spans two vintages (1999 and 2000), five distinct geographical winegrowing regions and three main red wine grape varieties used in Australia (Cabernet Sauvignon, Shiraz and Merlot). Homogenized grape samples were scanned in diffuse reflectance mode on a FOSE NIR Systems6500 spectrometer and subject to laboratory analysis by the traditional methods for total anthocyanins, TSS and pH. We report here an analysis of the correlations between the NIR spectra and the laboratory data using standard chemometric algorithms within The Unscrambler software package. In particular, various subsets of the total data set are considered in turn to elucidate the effects of vintage, geographical area and grape variety on the measurement of grape composition by NIR spectroscopy. The relative ability of discrete calibrations to predict within and across these differences is considered. The results are then used to propose an optimal calibration strategy for red wine grape analysis.

• Journal of the Korean Wood Science and Technology
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• 제43권6호
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• pp.701-713
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• 2015

소나무와 금강송의 수종 분류를 위해 근적외선(NIR) 분광법과 주성분분석(PCA) 및 부분최소자승법 판별분석(PLS-DA)을 결합하여 수종 분류 모델을 설계하였다. 측정된 모든 NIR 스펙트럼을 이용하여 PCA를 실시한 결과 소나무와 금강송의 수종 분류는 불가능하였다. 그러나 2차 미분된 스펙트럼을 이용하여 시험편의 단면과 심 변재 구분에 따른 수종 분류에서는 변재부에서 수종 분류가 가능하였으며, 특히 방사단면의 변재에서는 명확하게 수종이 분류되었다. 그리고 개발된 PLS-DA 예측 모델을 통해 명확한 수종 분류가 가능하였다. 2차 미분으로 전처리된 스펙트럼을 이용하였을 때 가장 좋은 분류 결과 얻을 수 있었다. 2차 미분 스펙트럼을 이용한 예측 모델은 100%의 분류 정확도를 나타내었으며, 예측 모델의 $R_p{^2}$ 값은 0.86, RMSEP는 0.38로 나타났다. 전처리하지 않은 스펙트럼과 2차 미분 스펙트럼을 이용한 예측 모델의 신뢰도는 유사하였다. 근적외선 분광법과 부분최소자승법 판별분석을 결합한 수종 분류 모델은 소나무와 금강송의 분류에 적합하였다.

• 분석과학
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• 제23권3호
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• pp.304-311
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• 2010

종이기록물의 특성을 평가하고 일반적으로 사용되는 파괴적인 방법이었다. 이를 개선하기 위하여 비파괴적인 방법인 근적외선 분광법(Near infrared spectroscopy, NIRS)을 적용하였다. 국가기록원이 보유하고 있는 종이 중에서 복사지, 봉투용지, 백상지, 신문용지, 한지 등과 1960년대~1980년대 각종 종이기록물 총 28점을 시료로 이용하였고, 종이기록물의 특성 평가항목인 열단장, 내절강도, pH, 함수율을 분석하였다. 그리고 각 시료에 대한 NIR스펙트럼을 구하여 가장 최적의 검량곡선을 작성하고, 이 검량곡선의 직선성, 스펙트럼 범위, 재현성 등을 검토하여 본 분석의 정확성을 검증하였다. 각 항목별 상관관계($R^2$)와 표준예측오차(standard error of prediction, SEP)는 열단장은 $R^2$=91.44, SEP=0.508, 내절강도 $R^2$=92.62, SEP=0.281, 함수율은 $R^2$=94.09, SEP=0.931, pH는 $R^2$=94.79, SEP= -0.0631로 양호하였다. 근적외선분광법은 종이시료를 파괴하지 않고 신속하게 특성을 평가할 수 있는 방법의 가능성을 보여주었다.

• Journal of Biosystems Engineering
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• 제29권6호
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• pp.539-543
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• 2004

The purpose of this study was to develop a real-time sensor for beef freshness. Contents of biogenic amines (BA), saccharides and proteins were highly related with freshness on the beef meats. Relations of those chemical contents and NIR spectra were studied. Tyramine showed the best correlation coefficient at 1250nm. Correlation between VBN (volatile basic nitrogen) and K value, which were both freshness measurement method, was determined by the PCR (principle component regression). The correlation model had the values of $R^2=0.989$ and SEC=1.78, respectively. The model was validated at $R^2=0.963$ and SEP=2.285, respectively.

• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2-2
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• pp.67.3-68
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• 2003

The purpose of this study is to improve repeatability of a non-invasive blood glucose measurement. The portable NIR system that was newly integrated by our lab includes a tungsten halogen lamp, a specialized reflectance fiber optic probe and a photo diode array type InGaAs detector, which was developed by a microchip technology based on the lithography. Reflectance NIR spectra of finger tip were recorded by using a fiber optic probe. The probe was fixed in the system and subjects put their finger on the probe head. (omitted)

• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2-2
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• pp.218.3-218.3
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• 2003

In this study, a FT-NIR spectroscopy was used to determine skin moisture. NIR diffuse reflectance spectra were collected from separated dorsal and abdominal hairless mouse skin. Partial least squares regression (PLSR) was applied to develop calibration models that determine the water content. The seven spectra regions, such as 833-2500, 1100-2250, 1100-1750, 1750-2250, 1200-1600, 1800-2200, and 1200-2200 except 1600-1800 nm, were investigated for the best model by PLSR. The developed model predicted skin moisture for validation set with a standard errors of prediction (SEP) of 4.43%, when used 833-2500 nm. (omitted)

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1528-1528
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• 2001

Ginseng cultivated in different country or growing condition has generally different components such as saponin and protein, and it relates to efficacy and action. Protein content assumes by nitrogen content in ginseng radix. Nitrogen content could be determined by chemical analysis such as kjeldahl or extraction methods. However, these methods require long analysis time and result environmental pollution and sample damage. In this work we investigated possibility of non-destructive determination of nitrogen content in ginseng radix using near-infrared spectroscopy. Ginseng radix, root of Panax ginseng C. A. Meyer, was studied. Total 120 samples were used in this study and it was consisted of 6 sample sets, 4, 5 and 6-year-old Korea ginseng and 7, 8 and 9-year-old China ginseng, respectively. Each sample set has 20 sample. Nigrogen content was measured by electronic analysis. NIR reflectance spectra were collected over the 1100 to 2500 nm spectral region with a InfraAlyzer 500C (Bran+Luebbe, Germany) equipped with a halogen lapmp and PbS detector and data were collected every 2 nm data point intervals. The calibration models were carried out by multiple linear regression (MLR) and partial least squares (PLS) analysis using IDAS and SESAME software. Result of electronic analysis, Korean ginseng were different mean value in nitrogen content of China ginseng. Ginseng tend to generally decrease the nitrogen content according as cultivation year is over 6 years. The MLR calibration model with 8 wavelengths using IDAS software accurately predicted nitrogen contents with correlation coefficient (R) and standard error of prediction of 0.985 and 0.855%, respectively. In case of SESAME software, the MLR calibration with 9 wavelength was selected the best calibration, R and SEP were 0.972 and 0.596%, respectively. The PLSR calibration model result in 0.969 of R and 0.630 of RMSEP. This study shows the NIR spectroscopy could be applied to determine the nitrogen content in ginseng radix with high accuracy.