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M. Kansiz, K.C. Schuster, D. McNaughton, B. Lendl:
"Sequential Injection/Mid-Infrared Spectroscopic Analysis of an Acetone-Butaniol-Ethanol Fermentation: Analyte Cross-Correlation Effects";
Spectroscopy letters (eingeladen), 38 (2005), S. 677 - 702.

Mid-infrared spectroscopy together with Sequential Injection Analysis (SIA) and Partial Least Squares (PLS) regression analysis was used to monitor Acetone-Butanol-Ethanol (ABE) fermentations under different fermentation conditions. Five analytes were simultaneously predicted (acetone, acetate, butyrate, n-butanol and glucose). In order to compare the overall model prediction ability, a relative average of the RMSEP across all five analytes was employed. To form a PLS model devoid of any cross-correlations between analytes, a synthetic calibration data set was created by the SIA system. As a test of their robustness, PLS models from synthetic samples and those from real fermentation samples were compared and used to predict samples from the opposite data set and from independent "acid-crash" fermentations, The PLS model developed from the synthetic samples, proved to be far more robust and accurate and used fewer factors than PLS models from the real fermentations which were found to contain analyte cross correlations. The use of synthetic data, enabled more accurate selection of factors and showed the importance of investigating spectral regression coefficients plots to aid and confirm appropriate factor selection In addition, an alternative method of factor selection was proposed, utilising a "similarity measure" between the regression coefficient plots of factors for certain analytes and their standard spectra. Predictions utilising this method of factor selection over the common "minimum from an error vs factor" plot, proved to be more accurate and use far fewer factors.

http://aleph.ub.tuwien.ac.at/F?base=tuw01&func=find-c&ccl_term=AC05937478