Application of Electronic Nose with Multivariate Analysis and Sensor Selection for Botanical Origin Identification and Quality Determination of Honey

Food and Bioprocess Technology

Volumn 8, Issue 2, 2015, Pages 359-370

  Huang, Lingxia ^a   Liu, Hongru ^b   Zhang, Bo ^b   Wu, Di ^b  

^a ZHEJIANG UNIVERSITY   (China)

^b ZHEJIANG UNIVERSITY   (China)

Author keywords

Botanical origin; Electronic nose; Honey; Multivariate analysis; Quality; Sensor selection

Indexed keywords

ASCORBIC ACID; FOOD PRODUCTS; FRUCTOSE; GLUCOSE; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; IMAGE QUALITY; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; LIQUID CHROMATOGRAPHY; MULTIVARIANT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; QUALITY CONTROL; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; TITRATION; ALGORITHMS;

BOTANICAL ORIGIN; HONEY; LEAST SQUARES SUPPORT VECTOR MACHINES; LINEAR REGRESSION METHODS; MULTI VARIATE ANALYSIS; PARTIAL LEAST SQUARES REGRESSIONS (PLSR); SENSOR SELECTION; SUCCESSIVE PROJECTIONS ALGORITHMS (SPA);

ELECTRONIC NOSE;

EID: 84926621003     PISSN: 19355130     EISSN: 19355149     Source Type: Journal    
DOI: 10.1007/s11947-014-1407-6     Document Type: Article

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