Comparison of Principal Component Regression (PCR) and Partial Least Square (PLS) methods in prediction of raw milk composition by VIS-NIR spectrometry. Application to development of on-line sensors for fat, protein and lactose contents

19th IMEKO World Congress 2009

Volumn 4, Issue , 2009, Pages 2498-2502

  Muñiz, Rocío ^a   Pérez, Miguel A ^a   De La Torre, Cristina ^a   Carleos, Carlos E ^a   Corral, Norberto ^a   Baro, Jesús A ^b  

^a UNIVERSITY OF OVIEDO   (Spain)

^b UNIVERSITY OF VALLADOLID   (Spain)

Author keywords

Milk composition; On line sensors; PCR; PLS; Spectrometry

Indexed keywords

ECONOMIC VALUES; FAT CONTENTS; FRESH MILKS; LOW-COST SYSTEMS; MILK COMPOSITION; NUTRITIONAL PROPERTIES; ON-LINE SENSOR; PARTIAL LEAST SQUARE (PLS); PARTIAL LEAST-SQUARES REGRESSION; PCR; PLS; PRINCIPAL COMPONENT REGRESSION; RAW MILK; SPECTRAL REGION; STANDARD MEASUREMENTS; TOTAL PROTEIN; VISIBLE AND NEAR INFRARED;

INFRARED DEVICES; NUTRIENTS; PROTEINS; REGRESSION ANALYSIS; SENSORS; SPECTROMETRY; SUGARS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84871544561     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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