Screening analysis of beer ageing using near infrared spectroscopy and the Successive Projections Algorithm for variable selection

► Near infrared spectroscopy (NIR) is used for screening analysis of aged beers. ► Variable selection is accomplished by using the Successive Projections Algorithm (SPA). ► Only one wavenumber is selected for screening analysis of non-alcoholic or alcoholic beers. ► NIR and SPA-LDA can be used for q...

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Veröffentlicht in:Talanta (Oxford) 2012-01, Vol.89, p.286-291
Hauptverfasser: Ghasemi-Varnamkhasti, Mahdi, Mohtasebi, Seyed Saied, Rodriguez-Mendez, Maria Luz, Gomes, Adriano A., Araújo, Mario Cesar Ugulino, Galvão, Roberto K.H.
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Sprache:eng
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Zusammenfassung:► Near infrared spectroscopy (NIR) is used for screening analysis of aged beers. ► Variable selection is accomplished by using the Successive Projections Algorithm (SPA). ► Only one wavenumber is selected for screening analysis of non-alcoholic or alcoholic beers. ► NIR and SPA-LDA can be used for quality control of beer samples. This work proposes a method for monitoring the ageing of beer using near-infrared (NIR) spectroscopy and chemometrics classification tools. For this purpose, the Successive Projections Algorithm (SPA) is used to select spectral variables for construction of Linear Discriminant Analysis (LDA) classification models. A total of 83 alcoholic and non-alcoholic beer samples packaged in bottles and cans were examined. To simulate a long storage period, some of the samples were stored in an oven at 40°C, in the dark, during intervals of 10 and 20 days. The NIR spectrum of these samples in the range 12,500–5405cm−1 was then compared against those of the fresh samples. The results of a Principal Component Analysis (PCA) indicated that the alcoholic beer samples could be clearly discriminated with respect to ageing stage (fresh, 10-day or 20-day forced ageing). However, such discrimination was not apparent for the non-alcoholic samples. These findings were corroborated by a classification study using Soft Independent Modelling of Class Analogy (SIMCA). In contrast, the use of SPA-LDA provided good results for both types of beer (only one misclassified sample) by using a single wavenumber in each case, namely 5550cm−1 for non-alcoholic samples and 7228cm−1 for alcoholic samples.
ISSN:0039-9140
1873-3573
DOI:10.1016/j.talanta.2011.12.030