Near-infrared analysis components

Near-Infrared Spectroscopy. Near-infrared (NIR) spectroscopy is a technique that has been around for some time but, like NMR spectroscopy, has only recently been improved and developed for on-line applications. Near-infrared analysis (NIRA) is a nondestructive technique that is versatile in the sense that it allows many constituents to be analyzed simultaneously 112, 113). The NIR spectrum of a sample depends upon the anharmonic bond vibrations of the constituent molecules. This condition means that the temperature, moisture content, bonding changes, and concentrations of various components in the sample can be determined simultaneously. In addition, scattering by particles such as sand and clay in the sample also allows (in principle) the determination of particle size distributions by NIRA. Such analyses can be used to determine the size of droplets in oil-water emulsions. 

H. Mark, Data Analysis Multilinear Regression and Principal Component Analysis, in Handbook of Near-Infrared Analysis (D. Bums and E. Ciurczak, eds.), Marcel Dekker, New York, 1992. 

J. J. Rose, T. Pmsik, and J. Mardekian, Near Infrared Multi-Component Analysis of Parenteral Products Using the InfraAlyzer 400, /. Parenter. Sci. Technol, 36(2), 71 (1982). 

Mark, H. (1992). Data analysis Multilinear regression and principle component analysis. In Handbook of Near-Infrared Analysis (D. A. Burns and E. W. Ciurczak, Eds.), pp. 107-158. Dekker, New York. 

Rose, J.J. and Prusik, T. et al.. Near-infrared mult-component analysis of parenteral products using the infraanalyzer 400, J. Parenter. Sci. TechnoL, 36(2), 71-78, 1982. 

Oil content is the most important chemical determination for snacks. This is generally determined by near-infrared analysis. When properly calibrated, NIRA instruments determine fat and other chemical components in several seconds. However, instrument calibration and recahbration are critical for reliable analyses. 

Dale, J.M., Klatt, L.N., "Principal Component Analysis of diffuse Near-Infrared Reflectance Data From Paper Currency", / /)/. Spec. 1989 (43) 1399-1405. 

Samola and Urleb [15] reported qualitative and quantitative analysis of OTC using near-infrared (NIR) spectroscopy. Multivariate calibration was performed on NIR spectral data using principle component analysis (PCA), PLS-1, and PCR. 

Naphthalene-2,3-dicarboxaldehyde Nicotinamide adenine dinucleotide N-Acetylneuraminic acid 4-Fluoro-7-nitrobenzoxadiazole Naphthalene-2,3-dicarboxaldehyde Nondestructive readout Near infrared Near infrared fluorescence Nuclear magnetic resonance 2-Nitrophenyl oxalate 1,1 -Oxalyldiimidazole Polycyclic aromatic hydrocarbon Principal component analysis Photosensitized chemiluminescence Pentachlorophenyl oxalate Polymerase chain reaction... 

A.D. Patel, P.E. Luner and M.S. Kemper, Quantitative analysis of polymorphs in binary and multi-component powder mixtures by near-infrared reflectance spectroscopy, Int. J. Pharm. 206, 63-74. Erratum in Int. J. Pharm., 212, 295 (2000). 

Municipal solid waste Near infrared Oxidation induction time Partial least square Post-consumer recyclate Post-consumer waste Principal component analysis Principal component regression Root-mean-square error of prediction... 

Arnold MA, Small GW, Xiang D, Qui J, Murhammer DW. Pure component selectivity analysis of multivariate calibration models from near-infrared spectra. Analytical Chemistry 2004, 76, 2583-2590. 

The analytical utility of near-infrared spectroscopy can be demonstrated by an analysis of mixtures composed of glucose, lactate, urea, alanine, ascorbate, and triacetin in a pH 6.8 aqueous phosphate buffer.6 The chemical structures of these test compounds are presented in Figure 13.2. These components were selected to represent different classes of molecules expected in typical biological matrices. Glucose represents carbohydrates lactate represents small organic acids urea is a... 

Other spectrophotometric techniques have been reported for the analysis of spironolactone. Near infrared diffuse reflectance first-derivative spectroscopy was used for determination of spironolactone in pharmaceutical dosage forms [30]. Readings were taken at 15 nm intervals, and then 81 absorbance readings were imput into a computer for principal component analysis. 

The analysis of chlorine trifluoride has been routinely performed by a gas chromatographic technique using a specifically designed corrosion resistant instrument. Well-defined chromatographic peaks are obtained for chlorine trifluoride and all normally expected components, except hydrogen fluoride. The hydrogen fluoride content is determined by an independent near infrared method. 

A fiber optic probe was used by Blanco et al. for analysis of spasmoctyl samples with the active compound otilonium bromide and cellulose, maize starch, sodium starch glycolate, and glyceryl palmitostearate as excipients. Another study from this group covered the identification, qualification of the substance, and the quantification of the active component. A library search with a comparison to the near-infrared spectra of 163 pharmaceuticals was involved. An on-line monitoring for the determination of the endpoint of polymorph conversions in pharmaceutical processes was recently described further investigations into this field were published and are noted previously. ... 

J. R. Mansfield et al., Fuzzy C-Means Clustering and Principal Component Analysis of Time Series from Near-Infrared Imaging of Forearm Ischemia, Computerized Med. Imaging and Graphics, 21(5), 299 (1997). 

Near-infrared (NIR) spectroscopy is becoming an important technique for pharmaceutical analysis. This spectroscopy is simple and easy because no sample preparation is required and samples are not destroyed. In the pharmaceutical industry, NIR spectroscopy has been used to determine several pharmaceutical properties, and a growing literature exists in this area. A variety of chemoinfometric and statistical techniques have been used to extract pharmaceutical information from raw spectroscopic data. Calibration models generated by multiple linear regression (MLR) analysis, principal component analysis, and partial least squares regression analysis have been used to evaluate various parameters. 

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