• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3102-3102
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• 2001

Constituents of several .representative seaweeds, such as wakame Undaria pinnatifida; hijikia Hizikia fusifome; and kombu Laminaria japonica, were found to have fairly large reaction rates determined by quenching experiments of emission spectra in the near-infrared region (1max: 1270 nm) from singlet oxygen (102). Emission spectra of singlet oxygen generated from an aqueous solution of Rose Bengal under irradiation with a green laser (330 nm) were measured by a near-infrared (NIR) emission spectrometer constructed in our laboratory. The quenching experiments were as follows: Intensities of emission spectra were measured in the absence (I0) and in the presence of the seaweed constituents (I): Ratios of I0/I were plotted against every concentration of the quenchers (Stern-Volmer plots) which gives a straight line. The slope of each line gives a kqt value which gives a quenching constant kq value (an antioxidative constant against singlet oxygen) when the t value (half-life time of singlet oxygen in the solvent used) was given. The determined reaction rates are between 103-105 (g/l)-ls-1; the larger ones are as large as that of ascorbic acid, 8.4 ${\times}$ 104 (g/1)-ls-1. Most of these seaweed constituents also showed antioxidative activity against auto-oxidation and superoxide as well as their immunological enhancing activity. These results suggest a possibility that dietary fibers which are supposed to prevent the large-intestine cancer by their physical properties may prevent the cancer, at least in parts, by their chemical, antioxidative activity.

• 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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• 제47권1호
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• pp.101-109
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• 2019

This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near-infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air-drying the lumber, the NIR spectra (wavelength = 780-2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky-Golay $2^{nd}$ derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky-Golay $2^{nd}$ derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky-Golay $2^{nd}$ derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1285-1285
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• 2001

For NIR measurements of papers normally diffuse reflectance accessories are used which can provide a large sampling area. The in-line process control FT-NIR spectrometer MATRIX-E enables the contactless measurement of paper samples of low silicone coat weights on label-stocks in a paper converting factory. For this study concentrations of silicone between 0 and 2 g/$m^2$ on various paper substrates were included in a quantitative method. The aim was to achieve an absolute value for the deviation from the target value of 1 g/$m^2$ during continuous movement of the paper with velocities around 400 numinute. Influences from the uncoated paper type due to supplier, color, opacity, area densities, pre-coating as well as different compounds of the agent silicone were investigated and it was found that all these papers can be represented in one PLS-model. Especially the fact that silicone as an element is present in clay coated papers is of no consequence to the measurements with MATRIX-E. Moreover during in-line installations the variation of the moisture contents in the moving paper due to variable machine velocities as well as the reflecting material of the cylinder have to be considered. It is shown that the result of the in-line calibration has the same prediction ability compared to lab scale results(Root Mean Square Error of Cross-Validation RMSECV = 0.034 g/$m^2$).

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1193-1193
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• 2001

For NIR measurements of papers normally diffuse reflectance accessories are used which can provide a large sampling area. The in-line process control FT-NIR spectrometer MATRIX-E enables the contactless measurement of paper samples of low silicone coat weights on label-stocks in a paper converting factory. For this study concentrations of silicone between 0 and 2 g/㎡ on various paper substrates were included in a quantitative method. The aim was to achieve an absolute value for the deviation from the target value of 1 g/㎡ during continuous movement of the paper with velocities around 400 m/minute. Influences from the uncoated paper type due to supplier, color, opacity, area densities, pre-coating as well as different compounds of the agent silicone were investigated and it was found that all these papers can be represented in one PLS-model. Especially the fact that silicone as an element is present in clay coated papers is of no consequence to the measurements with MATRIX-E. Moreover during in-line installations the variation of the moisture contents in the moving paper due to variable machine velocities as well as the reflecting material of the cylinder have to be considered. It is shown that the result of the in-line calibration has the same prediction ability compared to lab scale results (Root Mean Square Error of Cross-Validation RMSECV = 0.034 g/㎡).

• Journal of Preventive Medicine and Public Health
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• 제39권2호
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• pp.165-170
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• 2006

Objectives : The determination of oxalate in urine is required for the diagnosis and treatment of primary hyperoxaluria, idiopathic stone disease and various intestinal diseases. We examined the possibility of using Fourier transform near-infrared (FT-NIR) spectroscopy analysis to quantitate urinary oxalate. The practical advantages of this method include ease of the sample preparation and operation technique, the absence of sample pre-treatments, rapid determination and noninvasiveness. Methods : The range of oxalate concentration in standard urine solutions was $0-221mg/{\ell}$. These 80 different samples were scanned in the region of 780-1,300 nm with a 0.5 nm data interval by a Spectrum One NTS FT-NIR spectrometer. PCR, PLSR and MLR regression models were used to calculate and evaluate the calibration equation. Results : The PCR and PLSR calibration models were obtained from the spectral data and they are exactly same. The standard error of estimation (SEE) and the % variance were $10.34mg/{\ell}$ and 97.86%, respectively. After full cross validation of this model, the standard error of estimation was $5,287mg/{\ell}$, which was much smaller than that of the pre-validation. Furthermore, the MCC (multiple correlation coefficient) was 0.998, which was compatible with the 0.923 or 0.999 obtained from the previous enzymatic methods. Conclusions : These results showed that FT-NIR spectroscopy can be used for rapid determination of the concentration of oxalate in human urine samples.

• Journal of the Korean Wood Science and Technology
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• 제45권2호
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• pp.202-212
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• 2017

This study was to establish the interrelation between chemical compositions and near infrared (NIR) spectra for the classification on distinguishability of domestic gymnosperms. Traditional wet chemistry methods and infrared spectral analyses were performed. In chemical compositions of five softwood species including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cypress (Chamaecyparis obtusa), and cedar (Cryptomeria japonica), their extractives and lignin contents provided the major information for distinction between the wood species. However, depending on the production region and purchasing time of woods, chemical compositions were different even though in same species. Especially, red pine harvested from Naju showed the highest extractive content about 16.3%, whereas that from Donghae showed about 5.0%. These results were expected due to different environmental conditions such as sunshine amount, nutrients and moisture contents, and these phenomena were also observed in other species. As a result of the principal component analysis (PCA) using NIR between five species (total 19 samples), the samples were divided into three groups in the score plot based on principal component (PC) 1 and principal component (PC) 2; group 1) red pine and Korean pine, group 2) larch, and group 3) cypress and cedar. Based on the chemical composition results, it was concluded that extractive content was highly relevant to wood classification by NIR analysis.

• Journal of Biosystems Engineering
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• 제39권3호
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• pp.184-193
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• 2014

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of $R{_V}{^2}$, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ${\pm}0.487%$ wb, and 10.00, respectively. Conclusions: These results demonstrated that NIR spectroscopy and a PLSR model could be useful techniques for measuring rapidly and non-destructively the moisture content in red pepper powder.

• Journal of Biosystems Engineering
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• 제38권4호
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.