Near-infrared analysis NIRA

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. 

Materials characterization techniques, ie, atomic and molecular identification and analysis, are discussed in articles the tides of which, for the most part, are descriptive of the analytical method. For example, both infrared (ir) and near infrared analysis (nira) are described in Infrared and raman SPECTROSCOPY. Nudear magnetic resonance (nmr) and electron spin resonance (esr) are discussed in Magnetic spin resonance. Ultraviolet (uv) and visible (vis), absorption and emission, as well as Raman spectroscopy, circular dichroism (cd), etc are discussed in Spectroscopy (see also Chemh.itmtnescence Electro-analytical technique Immunoassay ZvIass spectrometry Microscopy Microwave technology. Plasma technology and X-ray technology). 

Stark, E., Luchter, K., and Margoshes, M., Near-infrared analysis (NIRA) a technology for quantitative and qualitative analysis, Appl. Spectrosc. Rev., 22(4), 335-399, 1986. 

It is important to remind ourselves again at this point that the error of the data indicated in Figure 8.4b and Figure 8.5 is only in the Y (dependent) variable. In the vast majority of cases we deal with in near-infrared analysis (NIRA), this situation is found to obtain. Regression theory states that the standard error of estimate (SEE), the measure of error in the regression, should be equal to the error of the dependent variable. Indeed, it is because there is so little error in the instrumental measurements on NIRA that multiple regression analysis is an appropriate mathematical tool for calibrating the instruments. 

Important applications of near-infrared analysis (NIRA) are found in the beverage and nutritional formula industries. Technologies have been described for near-infrared (NIR) determinations of constituents in alcoholic beverages such as beer, wines, and distilled spirits nonalcoholic beverages such as fruit juices, coffees, teas, and soft drinks and other products such as infant and adult nutritional formulas. Some of these applications are described in this chapter. 

D. A. Bums and E. W. Ciurczak, Identification of Raw Materials by NIRA, Handbook of Near-Infrared Analysis, 3rd ed., CRC Press, Boca Raton, FL, 2007. 

The acronym NIRA, or near-infrared analysis, is a term that implies the use of computer algorithms and multivariate data-handling techniques to provide either qualitative or quantitative analysis of a sample (or samples). NIRS includes a single spectral measurement and as such is a more generic definition. For example, an optical engineer involved in the design of a MR instrument would be involved with NIRS but not necessarily NIRA. 

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. 

Near Infrared Reflectance Analysis (NIRA) is in use at over 5000 sites for the analysis of multiple constituents in food and other products. The technology is based upon correlation transform spectroscopy, which combines NIR spectrophotometry and computerized analysis of a "learning set" of samples to obtain calibrations without the need for detailed spectroscopic knowledge of factors being analyzed. The computer can obtain spectral characteristics of the analyte (based upon a correlation with data from an accepted reference analysis) without separation of the sample s constituents. 

For all of the above reasons, studies of relationships between mineral sites and mineral reactivity would be simplified, and the confidence in the findings increased, if statistically testable methods were to be used to identify key variables and to test hypotheses. Near infrared reflectance analysis (NIRA) is such a method. It was developed by Karl Norris in the 1960 s to quantitate the concentration of key constituents in multicomponent mixtures such as wheat (22). 

To determine the oil, water, and solids contents simultaneously, sophisticated statistical techniques must usually be applied, such as partial least-squares analysis (PLS) and multivariate analysis (MVA). This approach requires a great deal of preparation and analysis of standards for calibration. Near-infrared peaks can generally be quantified by using Beer s law consequently, NIRA is an excellent analytical tool. In addition, NIRA has a fast spectral acquisition time and can be adapted to fiber optics this adaptability allows the instrument to be placed in a control room somewhat isolated from the plant environment. 

A. Picarelli, M. Greco, F. Di Giovambattista, A. Ramazzotti, C. Cedrone, E. Coarzziari, and A. Torsoli. Quantitative determination of faecal fat, nitrogen and water by means of a spectrophotometric technique near infrared reflectance analysis (NIRA). Assessment of its accuracy and reproducibility compared with chemical methods. Clin. Chim. Acta 234 147 (1995). 

Due to the absorption bands in NIR being weaker than in UV-Vis absorption, NIR spectrometry is not as useful for quantitative measurements but offers better qualitative analysis because of improved selectivity. NIR techniques can handle both liquid and solid samples. Near infrared reflectance analysis (NIRA) has found wide application in process analysis, especially for highly absorbing compounds such as foodstuffs Coal, grain, pulp and paper products and some pharmaceuticals can also be determined by NIRA ". The reflectance from the sample is reported relative to reflectance from a standard reference surface. 

In contrast to the well-known difficulties of traditionally applied quantitative IR spectroscopy of mixtures in solid (powdered) samples, the near-infrared reflectance analysis (NIRA) technique [32] has gained importance over the last decade and can now be implemented on a variety of commercially available Instruments In a number of applications to Industrial, agricultural and pharmaceutical analyses. Both the NIRA instruments equipped with grating monochromators and those fitted with filter systems feature built—In microprocessors with software suited to the Intrinsic characteristics of this spectroscopic alternative. Filter Instruments generate raw optical data for only a few wave-... 

E. V. Valdes, L. G Young, I. McMillan, and J. E. Winch, Analysis of Hay, Haylage, and Corn Silage Samples by Near Infrared Reflectance Spectroscopy, in Proc. Inti Symp. on NIRA, Technicon Instrs., Tarrytown, NY, 1984. 

R. J. Bear and J. F. Frank, Analysis of Nonfat Dry Milk Using Near Infrared Reflectance Spectroscopy, Proc. 2nd Annual NIRA Symposium, Technicon, Tarry-town, New York, 1982. 

R. Frankhuizen, The Use of NIRA for Quality Control of Dairy Products, Proc. 8th Int. Symposium on Near Infrared Reflectance Analysis, Technicon, Tarrytown, New York, 1985. 

Near-infrared reflectance analysis is a useful technique for characterizing textile raw materials, fiber, yarns, and fabrics. It is a nondestructive quantitative analysis that is simple to use and allows rapid testing of the sample. Its ability to measure multiple components of the sample simultaneously and eliminate extensive sample preparation are major advantages of NIRA in the characterization of textile materials. Many innovative mathematical treatments, for example, discriminant analysis and spectral reconstruction, have been developed by instrument manufactures and software companies. These instruments not only aid in the quantitative analysis of the data but also allow morphological investigations of fibers and yarns and rapid, qualitative identification of specific sample sets. 

Burns, D.A. and H. Mark., Indicator Variables in NIRA How to Use Them, in 7th Int. Symposium on Near Infrared Reflectance Analysis NIRA, Technicon. 1985. Tarrytown, NY. 

NIRS has been used for qualitative identification of textile fibres, polymer microstructure and composition studies, determination of finishes on textile fibres and colour deviations in dye batches. As shown in Table 1.18, near-infrared reflectance analysis (NIRA) is useful for characterising textile raw materials, fibres, yarns, and fabrics and is an excellent means to obtain real-time process/product information in textile manufacturing [312]. The nondestructive quantitative analysis is simple to use and... 

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