Classification of olive oils using high throughput flow 1H NMR fingerprinting with principal component analysis, linear discriminant analysis and probabilistic neural networks

Analytica Chimica Acta

Volumn 552, Issue 1-2, 2005, Pages 13-24

  Rezzi, Serge ^a   Axelson, David E ^b   Héberger, Károly ^a,c   Reniero, Fabiano ^a   Mariani, Carlo ^d   Guillou, Claude ^a  

^a JOINT RESEARCH CENTRE   (Italy)

^b MRi Consulting   (Canada)

^c CHEMICAL RESEARCH CENTER   (Hungary)

^d Stazione Sperimentale per le Industrie degli Oli e dei Grassi   (Italy)

Author keywords

Artificial neural networks; Authenticity; Chemometrics; Linear discriminant analysis; Multivariate methods; NMR; Principal component analysis

Indexed keywords

LEAST SQUARES APPROXIMATIONS; NUCLEAR MAGNETIC RESONANCE; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS;

MULTIVARIATE ANALYSIS; NMR FINGERPRINTING;

VEGETABLE OILS;

OLIVE OIL;

ANALYTIC METHOD; ARTIFICIAL NEURAL NETWORK; CHEMOMETRICS; CONFERENCE PAPER; CORRELATION ANALYSIS; FILTER; GEOGRAPHY; LINEAR DISCRIMINANT ANALYSIS; MULTIVARIATE ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROTON NUCLEAR MAGNETIC RESONANCE; RANDOMIZATION; REGRESSION ANALYSIS; SAMPLING; SOUTHERN EUROPE;

EID: 26844440852     PISSN: 00032670     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aca.2005.07.057     Document Type: Conference Paper

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