Journal
ANALYTICA CHIMICA ACTA
Volume 571, Issue 2, Pages 167-174Publisher
ELSEVIER
DOI: 10.1016/j.aca.2006.04.070
Keywords
determination original and real extract; alcohol content; beers; artificial neuronal networks; partial least squares; combination of spectroscopic techniques; near-infrared; middle-infrared; attenuated total reflectance
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The combination of infrared (MIR) and near-infared (NIR) spectroscopy has been employed for the determination of important quality parameters of beers. such as original and real extract and alcohol content. A population of 43 samples obtained from the Spanish market and including different types of beer, was evaluated. For each technique, spectra were obtained in triplicate. In the case of NIR a 1 mm pathlength quartz flow cell was used. whereas attenuated total reflectance measurements were used in MIR. Cluster hierarchical analysis was employed to select calibration and validation data sets. The calibration set was composed of 15 samples, thus leaving 28 for validation. A critical evaluation of the prediction capability of multivariate methods established from the combination of NIR and MIR spectra was made. Partial least squares (PLS) and artificial neural networks (ANN) were evaluated for the treatment of data obtained in each individual technique and the combination of both. Different parameters of each methodology were optimized. A slightly better predictive performance was obtained for NIR-MIR combined spectra, and in all the cases ANN performs better, than PLS. which may be interpreted from tire existence of some non-linearity in the data. The root-mean-sqare-error of prediction (RMSEP) values obtained for the combined NIR-MIR spectra for the determination of real extract, original extract and ethanol were 0.076% w/w, 0.14% w/w and 0.09 1% v/v. (c) 2006 Elsevier B.V. All rights reserved.
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