Literature DB >> 12769516

Virgin olive oil quality classification combining neural network and MOS sensors.

Diego L García-González1, Ramón Aparicio.   

Abstract

A model based on neural networks has been designed to detect lampante virgin olive oils, a category of olive oil that cannot be consumed without a previous refining process according to the current regulation of the European Communities. The response of 7 metal oxide sensors analyzing 114 olive oil samples has been used in the design, training, and internal validation of the neural network with only 4.5% error in validation. The designed mathematical model, the equations of which are fully described, has been validated also with an external set of 13 samples of diverse varieties and geographical origins with 100% correct classification.

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Year:  2003        PMID: 12769516     DOI: 10.1021/jf021217a

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  2 in total

1.  Analyzing the Organoleptic Quality of Commercial Extra Virgin Olive Oils: IOC Recognized Panel Tests vs. Electronic Nose.

Authors:  Irene Chacón; Javier Roales; Tânia Lopes-Costa; José M Pedrosa
Journal:  Foods       Date:  2022-05-19

2.  Headspace Gas Chromatography Coupled to Mass Spectrometry and Ion Mobility Spectrometry: Classification of Virgin Olive Oils as a Study Case.

Authors:  María García-Nicolás; Natalia Arroyo-Manzanares; Lourdes Arce; Manuel Hernández-Córdoba; Pilar Viñas
Journal:  Foods       Date:  2020-09-14
  2 in total

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