Honey characterization and adulteration detection by pattern recognition applied on HPAEC-PAD profiles. 1. Honey floral species characterization

Journal of Agricultural and Food Chemistry

Volumn 51, Issue 11, 2003, Pages 3234-3242

  Cordella, Christophe B Y ^a,c   Militão, Julio S L T ^b   Clément, Marie Claude ^a   Cabrol Bass, Daniel ^c  

^a Healthy Pigs Production and Experimentation Section   (France)

^b UNIVERSIDADE FEDERAL DE RONDÔNIA   (Brazil)

^c UNIVERSITÉ CÔTE D'AZUR   (France)

Author keywords

Adulteration; Artificial neural networks; Chemometrics; Food characterization; Honey; LDA; Pattern recognition; PCA; Sugar profiles

Indexed keywords

SUGAR;

ALGORITHM; AMPEROMETRY; ANION EXCHANGE CHROMATOGRAPHY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMOMETRIC ANALYSIS; FOOD INDUSTRY; HONEY; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

ALGORITHMS; ANALYSIS OF VARIANCE; CHROMATOGRAPHY, HIGH PRESSURE LIQUID; CHROMATOGRAPHY, ION EXCHANGE; FLOWERS; HONEY; NEURAL NETWORKS (COMPUTER); POLYSACCHARIDES;

EID: 0037609681     PISSN: 00218561     EISSN: None     Source Type: Journal    
DOI: 10.1021/jf021100m     Document Type: Article

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