Artículo
Multi-level Data Fusion Strategies for Modeling Three-way Electrophoresis Capillary and Fluorescence Arrays Enhancing Geographical and Grape Variety Classification of Wines
Autor/es | Ríos-Reina, Rocío
Azcarate, Silvana M. Camiña, José M. Goicoechea, Héctor C. |
Departamento | Universidad de Sevilla. Departamento de Nutrición y Bromatología, Toxicología y Medicina Legal |
Fecha de publicación | 2020 |
Fecha de depósito | 2023-03-03 |
Publicado en |
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Resumen | 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 ... 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. |
Agencias financiadoras | Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Argentina Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT). Argentina |
Identificador del proyecto | PIP-2015 Nº 0111
PICT 2017-0340 PICT-2018-04496 |
Cita | Ríos-Reina, R., Azcarate, S.M., Camiña, J.M. y Goicoechea, H.C. (2020). Multi-level Data Fusion Strategies for Modeling Three-way Electrophoresis Capillary and Fluorescence Arrays Enhancing Geographical and Grape Variety Classification of Wines. Analytica Chimica Acta, 1126, 52-62. https://doi.org/10.1016/j.aca.2020.06.014. |
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