• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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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.

• Food Engineering Progress
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• v.15 no.2
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• pp.136-142
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• 2011

The objective of this research was to classify intact soybeans and foreign objects using near-infrared (NIR) spectroscopy. Intact soybeans and foreign objects were scanned using a NIR spectrometer equipped with scanning monochromator. NIR spectra of intact soybeans and foreign objects in the wavelength range from 900 to 1800 nm were collected. The classification of intact soybeans and foreign objects were conducted by using partial least-square discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) multivariate methods. Various types of data pretreatments were tested to develop the classification models. Intact soybeans and foreign objects were successfully classified by the PLS-DA prediction model with mean normalization pretreatment. These results showed the potential of NIR spectroscopy combined with multivariate analysis as a method for classifying intact soybeans and foreign objects.

• Analytical Science and Technology
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• v.23 no.3
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• pp.304-311
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• 2010

Near Infrared Spectroscopy (NIRs) has been applied for rapid and nondestructive paper measurement by replacing the current destructive method to the property of paper. Current standard methods for the property of paper were pH, moisture, breaking length, and folding endurance, which data were compared with spectrum of FT-NIR spectrometer. Various paper products such as copy, envelope, white, newspaper, as well as old paper produced around 1960~1980 were used as the sample. The correlation ($R^2$) and standard error of prediction (SEP) results for breaking length, folding endurance, moisture and pH are $R^2$=0.914, SEP=0.508, $R^2$=0.926, SEP=0.281, $R^2$=0.941, SEP=0.931, pH $R^2$=0.949, SEP= -0.0631, respectively. This result show that NIRs can be applied to practical application for nondestructive analysis of paper records materials.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4101-4101
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• 2001

Information of body composition (fat and protein) in living animal is important to determine the nutrients requirement. Deuterium oxide (D2O) dilution techniques, as one of isotope dilution techniques have been useful for the prediction of body composition. However, the determination of D2O concentration is time consuming and complicated. Therefore this study was conducted to develop a new method to predict D2O concentration in plasma using near infrared spectroscopy technique (NIRS). Four dairy cows in early lactation were used. They were fed total mixed ration containing conr silage, timothy hay, and concentrates to make 17.0%CP and 14.0 MJDE/kgDM. Dosing D2O was at week 1,3 and 5 after parturition. After dosing D2O, the blood was collected from hour 0 to 72. Blood samples were then centrifuge at 3,000 rpm for 10 minutes to obtain plasma. D2O concentration was analyzed by gas chromatograph (deuterium oxide analyzable system, HK102, Shokotsusyou) after extracted from plasma by liophilization. Plasma sample was scanned by NIRS using Pacific Scientific (Neotec) model 6500 (Perstorp Analytical, Silver Spring, MD) in the range of wavelength from 1100 to 2500 nm. Calibration equation was developed using multiple linear regression. Sample from one animal (cow #550; n: 74) was used for developing the calibration while the rest three animals were used for validating the equation. The range, R and SEC of the calibration set samples were 135-925 ppm, 0.93 and 48.1 ppm, respectively. Validation of the calibration equation for three individual cows was done and the average of NIR predicted value of D2O at each collection time from three weeks injection showed a high correlation. The range, r and 53 of plasma from cow #474 were 322-840 ppm,0.93 and 53.1; cow #478 were 146-951 ppm,0.95 and 39.8; cow #942 were 313-885 ppm,0.95 and 37.2, respectively. Judgement of accuracy based on ratio of standard deviation and standard error in validation set samples (RPD) for cow #474, #478 and #942 were 2.2,4.3 and 3.4, respectively. The error in application due to the variation between individual was considered smaller than the bias from collection period, however, this prediction can be overcome with correction of standard zero-minute concentration of blood. The results of this preliminary study on the use of NIRS for determination of D2O in plasma showed very promising as shown by a convenient and satisfy accuracy. Further study on various physiological stage of animal should be done.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1520-1520
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• 2001

Food adulteration is a serious consumer fraud and a potentially dangerous practice. Regulatory authorities and food processors require a rapid, non-destructive test to accurately confirm authenticity in a range of food products and raw materials. Olive oil is prime target for adulteration either on the basis of the processing treatments used for its extraction (extra virgin vs virgin vs ordinary oil) or its geographical origin (e.g. Greek vs Italian vs Spanish). As part of an investigation into this problem, some preliminary work focused on the ability of near infrared spectroscopy to discriminate between virgin olive oils from separate regions of the Mediterranean i. e. Crete and the Peloponese. A total of 46 oils were collected: 18 originated in Crete and 28 in the Peloponese. Oils were stored in a temperature-controlled room at 2$0^{\circ}C$ prior to spectral collection at room temperature (15-18$^{\circ}C$). Samples (approximately 0.5$m\ell$) were placed in the centre of the quartz window in a camlock reflectance cell; the gold-plated baking plate was then gently placed into the cell against the glass so as to minimize the formation of air bubbles. The rear of the camlock cell was then screwed into place producing a sample thickness of 0.5mm. Spectra were recorded between 400 and 2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. Spectral collection took place over 2-3 days. Data were analysed using both WINISI and The Unscrambler software to investigate the possibility of discriminating between the oils from Crete and the Peloponese. A number of data pre-treatments were used and discriminant models were developed using discriminant PLS (WINISI & Unscrambler) and SIMCA (Unscrambler). Despite the small number of samples involved, a satisfactory discrimination between these two oil types was achieved. Graphical examination of principal component scores for each oil type also holds out the possibility of separating oils from either Crete and the Peloponese on the basis of districts within each region. These preliminary data suggest the potential of near infrared spectroscopy to act as a screening technique for the confirmation of geographic origin of extra virgin olive oils. The sample presentation strategy adopted uses only small volumes of material and produces high quality spectra.

• Korean Journal of Food Science and Technology
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• v.34 no.3
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• pp.356-360
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• 2002

The honey samples harvested in 1996, 1997, and 1998 were used for calibration and validation. NIR spectra were obtained using NIR spectrometer and quartz glass device with gold coating diffuser. Multiple linear regression and partial least square were used for calibrations. The correlation coefficient (RSQ) and standard error of prediction (SEP) obtained for moisture were 0.997 and 0.1%, respectively. The RSQ and SEP for fructose and glucose were 0.926 and 0.951%, and the SEP were 0.54% and 0.52% respectively. The validation results for sucrose, maltose, HMF definition, and acidity of honey were considered to be sufficient for practical use RSQ and SEP for SCIR were 0.950 and $1.08%_{\circ}$, respectively. These results are indications of the rapid determination of purity of the honey through NIR analysis.

• Proceedings of the Korean Society of Crop Science Conference
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• 1998.04a
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• pp.73-74
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• 1998

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.2
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• pp.165-171
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• 2022

The SiO₂/TiO₂ multilayer thin films used for narrow band pass filter were fabricated using E-beam evaporation method. The narrow band pass filter was used to enhance the resolution of spectroscopy and sensor applications with near infrared (NIR) light source. The narrow band pass filter with multilayer thin films were designed with Essential Macleod program. The multilayers of SiO₂/TiO₂ with 32 layers were deposited on the silicon encapsulation of IR with peak wavelength (λ_p) of 660 nm and NIR LEDs with λ_p of 830 nm, 880 nm, and 955 nm. After NIR light passed through the narrow band pass filter, the full width of half maximum of 33.4~48.6 nm became narrow to 20~24 nm owing to the absorption of photons with short or long wavelength of designed band of 20 nm. The SiO₂/TiO₂ band pass filter fabricated in this study can be used for sensor, optoelectronics, and NIR spectroscopy applications.

• Journal of Biosystems Engineering
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• v.23 no.1
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• pp.49-56
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• 1998

The objectives of this study were to develop models to predict the contents of moisture and protein of single kernel of brown rice based on visible/NIR (near-infrared) spectroscopic technique. The reflectance spectra of rice were obtained in the range of the wavelength 400 to 2,500 nm with 2 nm intervals. Multiple linear regression(MLR) and partial least squares (PLS) were used to develop the models. The MLR model using the first derivative spectra(10 nm of gap) with Standard Normal Variate and Detrending (SNV and Drt.) preprocessing showed the best results to predict moisture content of the sin린e kernel brown rice. To predict the protein content of a single kernel of brown ricer the PLS model used the raw spectra with multiplicative scatter correction(MSC) preprocessing over the wavelength of 1,100~1,500 nm.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.2
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• pp.263-267
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• 2001

Beef samples of loin eye area from New Zealand, USA and three quality grades of Hanwoo were analyzed using near infrared spectrophotometer with reference values from laboratory optical Chromameter to determine effective spectrum range and mathematical treatment for determination of color values. $R^2s$ of prediction models were not improved much by calibrating with whole light range (400~2500 nm) compared to using visible range (400~1100 nm). Standard errors of calibration and prediction were influenced by possible bias due to sampling non-homogeneous sample sources. However, partial differentiation in the first order was more stable against sampling biases than second derivatives of the spectra. Lightness value was little different among the five sample sources of beef. Beef samples from USA were brighter and more reddish than beefs of Hanwoo or from New Zealand (p<0.05). Yellowness of USA beef was the highest followed by beef from New Zealand, which was also higher than Hanwoo beefs of three quality grades (p<0.05).