A mid level data fusion strategy for the Varietal Classification of Lambrusco PDO wines

Nowadays the necessity to reveal the hidden information from complex data sets is increasing due to the development of high-throughput instrumentation. The possibility to jointly analyze data sets arising from different sources (e.g. different analytical determinations/platforms) allows capturing th...

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Bibliographic Details
Published in:Chemometrics and intelligent laboratory systems 2014-10, Vol.137, p.181-189
Main Authors: Silvestri, M., Elia, A., Bertelli, D., Salvatore, E., Durante, C., Li Vigni, M., Marchetti, A., Cocchi, M.
Format: Article
Language:English
Subjects:
Data-fusion
EEM
HPLC-DAD
Lambrusco
Multiset-MCR
NMR
PARAFAC
PLS-DA
Varietal-classification
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Summary:Nowadays the necessity to reveal the hidden information from complex data sets is increasing due to the development of high-throughput instrumentation. The possibility to jointly analyze data sets arising from different sources (e.g. different analytical determinations/platforms) allows capturing the latent information that would not be extracted by the individual analysis of each block of data. Several approaches are proposed in the literature and are generally referred to as data fusion approaches. In this work a mid level data fusion is proposed for the characterization of three varieties (Salamino di Santa Croce, Grasparossa di Castelvetro, Sorbara) of Lambrusco wine, a typical PDO wine of the district of Modena (Italy). Wine samples of the three different varieties were analyzed by means of 1H-NMR spectroscopy, Emission-Excitation Fluorescence Spectroscopy and HPLC-DAD of the phenolic compounds. Since the analytical outputs are characterized by different dimensionalities (matrix and tensor), several multivariate analyses were applied (PCA, PARAFAC, MCR-ALS) in order to extract and merge, in a hierarchical way, the information present in each data set. The results showed that this approach was able to well characterize Lambrusco samples giving also the possibility to understand the correlation between the sources of information arising from the three analytical techniques. •MidLevel data fusion simultaneously allows interpretation of data of different nature.•Data fusion provides better results for the classification of Lambrusco PDO wines.•Sample characterization is enhanced using different sources of information.•Multi-way, multiset and bilinear methods were used to extract informative features.
ISSN:0169-7439
1873-3239
DOI:10.1016/j.chemolab.2014.06.012