Data-fusion for multiplatform characterization of an italian craft beer aimed at its authentication

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• 作者：Alessandra Biancolillo ; Remo Bucci ; Antonio L. Magrì ; Andrea D. Magrì ; Federico Marini ; ^{fmmonet@hotmail.com" class="auth_mail} ; ^{federico.marini@uniroma1.it" class="auth_mail}
• 关键词：Craft beers ; Chemometrics ; Classification ; Partial least squares-discriminant analysis (PLS-DA) ; Soft independent modeling of class analogies (SIMCA) ; Data fusion
• 刊名：Analytica Chimica Acta
• 出版年：11 April, 2014
• 年：2014
• 卷：820
• 期：Complete
• 页码：23-31
• 全文大小：1818 K

文摘

Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies - in particular, the mid-level one - to integrate the data from the different platforms allowed the correct classification of all the training and validation samples.