title: Data-fusion for multiplatform characterization of an Italian craft beer aimed at its authentication.
abstract: 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.
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", Rome, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Biancolillo
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", Rome, Italy.
authors.forename: Remo
authors.initials: R
authors.lastname: Bucci
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", Rome, Italy.
authors.forename: Antonio L
authors.initials: AL
authors.lastname: Magrì
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", Rome, Italy.
authors.forename: Andrea D
authors.initials: AD
authors.lastname: Magrì
authors.affiliation: Department of Chemistry, University of Rome "La Sapienza", Rome, Italy. Electronic address: fmmonet@hotmail.com.
authors.forename: Federico
authors.initials: F
authors.lastname: Marini
keywords: Chemometrics; Classification; Craft beers; Data fusion; Partial least squares-discriminant analysis (PLS-DA); Soft independent modeling of class analogies (SIMCA)