Supervised pattern recognition in food analysis

Luis A. Berrueta, Rosa M. Alonso-Salces, Károly Héberger

Research output: Review article

634 Citations (Scopus)

Abstract

Data analysis has become a fundamental task in analytical chemistry due to the great quantity of analytical information provided by modern analytical instruments. Supervised pattern recognition aims to establish a classification model based on experimental data in order to assign unknown samples to a previously defined sample class based on its pattern of measured features. The basis of the supervised pattern recognition techniques mostly used in food analysis are reviewed, making special emphasis on the practical requirements of the measured data and discussing common misconceptions and errors that might arise. Applications of supervised pattern recognition in the field of food chemistry appearing in bibliography in the last two years are also reviewed.

Original languageEnglish
Pages (from-to)196-214
Number of pages19
JournalJournal of Chromatography A
Volume1158
Issue number1-2
DOIs
Publication statusPublished - júl. 27 2007

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Organic Chemistry

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