Journal
ANALYTICA CHIMICA ACTA
Volume 1126, Issue -, Pages 52-62Publisher
ELSEVIER
DOI: 10.1016/j.aca.2020.06.014
Keywords
Electrophoresis capillary; Multidimensional fluorescence spectroscopy; Three-way data modeling; Multi-level data fusion; Classification
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Funding
- Univ. Nacional de La Pampa
- CONICET (Consejo Nacional de Investigaciones Cientificas y Tecnicas) [0111]
- ANPCyT (Agencia Nacional de Promocion Cientifica y Tecnologica) [PICT 2017-0340, PICT-2018-04496]
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Capillary electrophoresis with diode array detection (CE-DAD) and multidimensional fluorescence spectroscopy (EEM) second-order data were fused and chemometrically processed for geographical and grape variety classification of wines. Multi-levels data fusion strategies on three-way data were evaluated and compared revealing their advantages/disadvantages in the classification context. Straightforward approaches based on a series of data preprocessing and feature extraction steps were developed for each studied level. Partial least square discriminant analysis (PLS-DA) and its multi-way extension (NPLS-DA) were applied to CE-DAD, EEM and fused data matrices structured as two-way and three-way arrays, respectively. Classification results achieved on each model were evaluated through global indices such as average sensitivity non-error rate and average precision. Different degrees of improvement were observed comparing the fused matrix results with those obtained using a single one, clear benefits have been demonstrated when level of data fusion increases, achieving with the high-level strategy the best classification results. (C) 2020 Elsevier B.V. All rights reserved.
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