Near-infrared spectroscopy qualitative evaluation

S.S. Sekulic, J. Wakeman, P. Doherty and P.A. Hailey, Automated system for the on-line monitoring of powder blending processes using near-infrared spectroscopy Part II. Qualitative approaches to blend evaluation, J. Pharm. Biomed. Anal, 17, 1285-1309 (1998). 

This chapter has provided an introduction to a number of industrial (and related) fields which utilize infrared spectroscopy as an analytical technique. This method is widely used in the pharmaceutical industry for the qualitative and quantitative analysis of active and non-active ingredients. The food industry uses information from the mid- and near-infrared regions to carry out qualitative and quantitative analysis. Agricultural applications, such as the evaluation of grain, and the pulp and paper industries, were introduced and near-infrared spectroscopy was demonstrated as an important approach in these fields. Paints are variable mixtures and infrared spectroscopy provides an effective technique for the identification of the components of paints. Examples of environmental applications of infrared spectroscopy, including gases and pollutants, were also discussed. 

W. Windig and J. Guilment, Automated System for On-Line Monitoring of Powder Blending Processes Using Near-Infrared Spectroscopy. Part II Qualitative Approaches to Blend Evaluation, Anal. Chem., 63,1425 (1991). 

DRIFT spectroscopy of microscopic amounts of dye mixtures extracted from small textile samples has been reported raw and pretreated data matrices were interpreted with the use of chemomet-rics (PCA, SIMCA, FC) [145]. DRIFTS can readily detect 200 ng quantities of pure, standard dyes. Bridge et al. [42] have qualitatively characterised acid dyes (Cl Acid Red 17, Red 18, Red 44, Red 88, Blue 45 and Yellow 17) applied to wool and nylon. Near-infrared diffuse reflectance spectroscopy was evaluated for its ability to analyse solid antioxidant blends [146]. These opaque materials do not transmit near-IR light. This fast method effectively predicts weight percentage composition with a precision comparable to the currently accepted HPLC method of analysis, and can identify blend types and contaminated materials. 

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