Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

Food Chemistry

Volumn 217, Issue , 2017, Pages 735-742

  Georgouli, Konstantia ^a   Martinez Del Rincon, Jesus ^a   Koidis, Anastasios ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

Adulteration; Continuous statistical modelling; Dimensionality reduction; Extra virgin olive oil; FT IR; RAMAN; Rapid detection; Spectroscopy

Indexed keywords

NEAREST NEIGHBOR SEARCH; OLIVE OIL; SPECTROSCOPY; STATISTICAL METHODS;

ADULTERATION; DIMENSIONALITY REDUCTION; EXTRA VIRGIN OLIVE OIL; RAMAN; RAPID DETECTION; STATISTICAL MODELLING;

PATTERN RECOGNITION;

EXTRA VIRGIN OLIVE OIL; HAZELNUT OIL; UNCLASSIFIED DRUG; VEGETABLE OIL; OLIVE OIL;

ANALYTIC METHOD; ARTICLE; CHEMICAL ANALYSIS; CONTINUOUS LOCALITY PRESERVING PROJECTION TECHNIQUE; HAZELNUT; INFRARED SPECTROSCOPY; K NEAREST NEIGHBOR; PATTERN RECOGNITION; RAMAN SPECTROMETRY; REDUCTION; STATISTICAL MODEL; ANALYSIS; CHEMISTRY; EVALUATION STUDY; FOOD CONTAMINATION; PROCEDURES;

FOOD CONTAMINATION; MODELS, STATISTICAL; OLIVE OIL; PLANT OILS; SPECTROSCOPY, FOURIER TRANSFORM INFRARED; SPECTRUM ANALYSIS, RAMAN;

EID: 84986596486     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2016.09.011     Document Type: Article

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