• Title/Summary/Keyword: NIR (near-infrared) spectra

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Compensation of Variation from Long-Term Spectral Measurement for Non-invasive Blood Glucose in Mouse by Near-Infrared Spectroscopy (근적외분광분석법을 이용한 생쥐꼬리에서의 비침습 혈당 정량시 장기간 측정에 따른 변이 요인의 보정)

  • 백주현;강나루;우영아;김효진
    • YAKHAK HOEJI
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    • v.48 no.3
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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.

Nondestructive Quantification of Intact Ambroxol Tablet using Near-infrared Spectroscopy (근적외분광분석법을 사용한 암브록솔 정제의 비파괴적 정량분석)

  • 임현량;우영아;김도형;김효진;강신정;최현철;최한곤
    • YAKHAK HOEJI
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    • v.48 no.1
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    • pp.60-64
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    • 2004
  • Near-infrared (NIR) spectroscopy was used to determine rapidly and nondestructively the content of ambroxol in intact ambroxol tablets containing 30 mg (12.5% m/m nominal concentration) by collecting NIR spectra in range 1100-1750 nm. The laboratory-made samples had 10.3∼15.9% m/m nominal ambroxol concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR) with autoscaling. Model validation was performed by randomly splitting the data set into calibration and validation data set (7 samples as a calibration data set and 5 samples as a validation data set). The developed NIR method gave results comparable to the known values of tablets in a laboratorial manufacturing Process, standard error of calibration (SEC) and standard error of prediction (SEP) being 0.49% and 0.49% m/m respectively. The method showed good accuracy and repeatability NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.

Partial Least Squares Analysis on Near-Infrared Absorbance Spectra by Air-dried Specific Gravity of Major Domestic Softwood Species

  • Yang, Sang-Yun;Park, Yonggun;Chung, Hyunwoo;Kim, Hyunbin;Park, Se-Yeong;Choi, In-Gyu;Kwon, Ohkyung;Cho, Kyu-Chae;Yeo, Hwanmyeong
    • Journal of the Korean Wood Science and Technology
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    • v.45 no.4
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    • pp.399-408
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    • 2017
  • Research on the rapid and accurate prediction of physical properties of wood using near-infrared (NIR) spectroscopy has attracted recent attention. In this study, partial least squares analysis was performed between NIR spectra and air-dried specific gravity of five domestic conifer species including larch (Larix kaempferi), Korean pine (Pinus koraiensis), red pine (Pinus densiflora), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa). Fifty different lumbers per species were purchased from the five National Forestry Cooperative Federations of Korea. The air-dried specific gravity of 100 knot- and defect-free specimens of each species was determined by NIR spectroscopy in the range of 680-2500 nm. Spectral data preprocessing including standard normal variate, detrend and forward first derivative (gap size = 8, smoothing = 8) were applied to all the NIR spectra of the specimens. Partial least squares analysis including cross-validation (five groups) was performed with the air-dried specific gravity and NIR spectra. When the performance of the regression model was expressed as $R^2$ (coefficient of determination) and root mean square error of calibration (RMSEC), $R^2$ and RMSEC were 0.63 and 0.027 for larch, 0.68 and 0.033 for Korean pine, 0.62 and 0.033 for red pine, 0.76 and 0.022 for cedar, and 0.79 and 0.027 for cypress, respectively. For the calibration model, which contained all species in this study, the $R^2$ was 0.75 and the RMSEC was 0.37.

Somatic cell counts determination in cow milk by near infrared spectroscopy: A new diagnostic tool

  • Tsenkova, R.;Atanassova, S.;Kawano, S.;Toyoda, K.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.4104-4104
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    • 2001
  • Milk somatic cell count (SCC) is a recognized indicator of cow health and milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm to measure SCC content of cow milk was investigated. A total of 196 milk samples from 7 Holstein cows were collected for 28 days, consecutively, and analyzed for fat, protein, lactose and SCC. Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in a wavelength range from 1100 to 2500 nm. The calibration for logSCC was performed using partial least square (PLS) regression and different spectral data pretreatment. The best accuracy of determination was found for equation, obtained using smoothed absorbance data and 10 PLS factors. The standard error of calibration was 0.361, calibration coefficient of multiple correlation 0.868, standard error of prediction for independent validation set of samples 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. The accuracy of logSCC determination by NIR spectroscopy would allow health screening of cows, and differentiation between healthy and mastitic milk samples. When the spectral information was studied it has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. In the case of mastitis, when the disease occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk.

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INLINE NEAR INFRARED (NIR) SPECTROSCOPY FOR PROCESS CONTROL IN POLYMER EXTRUSION

  • Rohe, Thomas;Koelle, Sabine;Becker, Wolfgang;Eisenreich, Norbert;Eyerer, Peter
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1082-1082
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    • 2001
  • Extrusion is one of the most important processes in polymer industry. The characterization of the polymer melt during processing will improve this process noticeably, One possibility of characterizing the actual processed polymer melt is the inline near infrared (NIR) spectroscopy, With this method several polymer properties can be observed during processing, e.g. composition, moisture ormechanical properties of the melt. For this purpose probes for transmission and reflection measurements have been developed, withstanding the high temperatures and pressures appearing during extrusion process (tested up to 300$^{\circ}C$ and 10 ㎫). For the transmission system an optical bypass was developed to eliminate disturbing spectral influences and hence increase the long term stability, which is the prerequisite for an industrial application. Measurements in transmission and reflection produced comparable results (or blending processes, where the prediction error was less than 1%. An optimum RMSEP of only 0.24% was found for preprocessed polymer blends measured in transmission on a laboratory extruder. A transflection measurement allowed for the first time the recording of relevant NIR-spectra in the screw area of an extruder. The application to a (PE+PP) blending process delivered promising results. This new measurement mode allows the observation of the ongoing processes within the screw area, which is of maximum Interest for reactive extrusion processes. Due to economic reasons the calibration transfer between different extrusion systems is also of high importance. Investigations on simulated and real-world spectra showed that a calibration transfer is possible. A new method alternatively to the well-known direct standardization procedures was developed, which is based on an automatic data pretreatment. This procedure delivers comparable results for the calibration transfer. Overall this paper presents concepts, components and algorithms for the inline near infrared (NIR) spectroscopy for polymer extrusion, which allows the use of it in a real industrial extrusion process.

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Mastitis Detection by Near-infrared Spectra of Cows Milk and SIMCA Classification Method

  • Tsenkova, R.;Atanassova, S.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1248-1248
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    • 2001
  • Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and considerable compositional changes in milk, reducing milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm and chemometric method for classification to detect milk from mastitic cows was investigated. A total of 189 milk samples from 7 Holstein cows were collected for 27 days, consecutively, and analyzed for somatic cells (SCC). Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in the spectral range from 1100 to 2500nm. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. The classification of the samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two concentration of SCC - 200 000 cells/ml and 300 000 cells/ml, respectively, were used as thresholds fer separation of healthy and mastitis cows. The best detection accuracy was found for models, obtained using 200 000 cells/ml as threshold and smoothed absorbance data - 98.41% from samples in the calibration set and 87.30% from the samples in the independent test set were correctly classified. SIMCA results for classes, based on 300 000 cells/ml threshold, showed a little lower accuracy of classification. The analysis of changes in the loading of first PC factor for group of healthy milk and group of mastitic milk showed, that separation between classes was indirect and based on influence of mastitis on the milk components. The accuracy of mastitis detection by SIMCA method, based on NIR spectra of milk would allow health screening of cows and differentiation between healthy and mastitic milk samples. Having SIMCA models, mastitis detection would be possible by using only DIR spectra of milk, without any other analyses.

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Quantification of Naproxen in Pharmaceutical Formulation using Near-Infrared Spectrometry (근적외 분광분석법을 이용한 나프록센 정제의 정량분석)

  • Kim Do Hyung;Woo Young Ah;Kim Hyo Jin
    • YAKHAK HOEJI
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    • v.49 no.1
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    • pp.1-5
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    • 2005
  • Near-infrared (NIR) spectroscopy has been widely applied in various field, since it is nondestructive and no sample preparation is required. In this paper, NIR spectroscopy was used for the determination of naproxen in a commercial pharmaceutical preparation. NIR spectroscopy was used to determine the content of naproxen in intact naproxen tablets containing 250 mg ($65.8\%$ nominal concentration) by collecting NIR spectra in the range of $1100{\sim}1750nm$. The laboratory-made samples had $46.1{\sim}85.5\%$ nominal naproxen concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR). Model validation was performed by randomly splitting the data set into calibration and validation data set (63 samples as a calibration data set and 42 samples as a validation data set). The developed NIR calibration gave results comparable to the known values of tablets in a laboratorial manufacturing process with standard error of calibration (SEC) and standard error of prediction (SEP) of $1.06\%\;and\;1.04\%$, respectively. The NIR method showed good accuracy and repeatability. NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.

NEAR-INFRARED STUDIES ON STRUCTURE-PROPERTIES RELATIONSHIP IN HIGH DENSITY AND LOW DENSITY POLYETHYLENE

  • Sato, Harumi;Simoyama, Masahiko;Kamiya, Taeko;Amari, Trou;Sasic, Slobodan;Ninomiya, Toshio;Siesler, Heinz-W.;Ozaki, Yukihiro
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1281-1281
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    • 2001
  • Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

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Quantitative analysis by the CARNAC procedure

  • Davies, Anthony M.C.;Fearn, Tom
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1124-1124
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    • 2001
  • CARNAC is a procedure for obtaining quantitative analysis of a sample by comparison of the NIR spectra of the unknown sample with a database of a large number of samples with NIR spectral and compositional data. The method depends on the compression of the NIR database followed by a modification of the compressed data which emphasizes the required analyte. The method identifies a few very similar samples and the value of the required analyte is calculated from a weighed average of the analyte values for the selected similar samples. The method was originally described at Chambersburg IDRC in 1986 and in the Proceedings of the FT Conference of 1987. This contribution will describe recent work on utilising new methods for both compression and modification.

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Dissolution Test for Indomethacin by the Portable Near-Infrared(NIR) System

  • Kim, Do-Hyung;Lim, Hun-Rang;Chang, Soo-Hyun;Woo, Young-Ah;Kim, Hyo-Jin
    • Proceedings of the PSK Conference
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    • 2002.10a
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    • pp.399.3-399.3
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    • 2002
  • Near-infrared (NIR) system was used to determine rapidly and simply indomethacin in buffer solution for a dissolution test for tablets and capsules. Indomethacin standards were prepared ranging from 10 to 50ppm using mixture of phosphate buffer(pH 7,2) and water(1:4), The near infrared(NIR) transmittance spectra of indomethacin standard solutions were collected by using a quartz cell in 1 mm and 2mm pathlength, Partial least-square regression (PLSR) was explored to develop calibration models over the spectral range 1100-1700nm. (omitted)

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