Infrared spectroscopy spectral calibration

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. 

T. Isaksson and T. Ntes, Selection of samples for calibration in near-infrared spectroscopy. Part II selection based on spectral measurements, Appl Spectrosc., 44, 1152-1158 (1990). 

Isaksson, T. and Naes, T., Selection of Samples for Calibration in Near-Infrared Spectroscopy. Part II Selection Based on Spectral Measurements Appl. Spectrosc. 1990, 44, 1152-1158. 

J. Workman, Near Infrared Spectroscopy A Comparison of Random Versus Spectrally Selected Calibration Sets for Use in Forage Quality Evaluation, in Proc. Forage and Grasslands Conf, Athens, Georgia, Am. For. Grass. Conn., Lexington, KY, pp. 132-136 (1986). 

Be consistent in the use of cells, windows, crystals, and sampling accessories for your standards and unknowns. For example, KBr and NaCl are both commonly used window materials in infrared spectroscopy, but have different optical properties. If a calibration is developed with a sample cell containing KBr windows, and unknown spectra are obtained with a cell with NaCl windows, the unmodeled spectral difference may be enough to introduce error into the predicted concentrations. 

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. 

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