Quantifying binary and ternary mixtures of monovarietal extra virgin olive oils with UV-vis absorption and chemometrics

Sensors and Actuators, B: Chemical

Volumn 234, Issue , 2016, Pages 115-121

  Aroca Santos, Regina ^a   Cancilla, John C ^a   Pérez Pérez, Ana ^a   Moral, Ana ^b   Torrecilla, José S ^a  

^a UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

^b UNIVERSIDAD PABLO DE OLAVIDE   (Spain)

Author keywords

Artificial neural networks; Extra virgin olive oil; Linear regression; Pigments

Indexed keywords

BINARY MIXTURES; BINS; INFRARED SPECTROPHOTOMETERS; LINEAR REGRESSION; MIXTURES; NEURAL NETWORKS; PIGMENTS; REGRESSION ANALYSIS;

BINARY AND TERNARY MIXTURES; CHEMOMETRIC APPROACH; EXTRA VIRGIN OLIVE OIL; GENERALIZATION CAPABILITY; K FOLD CROSS VALIDATIONS; MEAN ABSOLUTE ERROR; MULTIPLE LINEAR REGRESSION MODELS; VISIBLE SPECTROSCOPY;

OLIVE OIL;

EID: 84968624601     PISSN: 09254005     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.snb.2016.04.094     Document Type: Article

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