Predicting the anthocyanin content of wine grapes by NIR hyperspectral imaging

Food Chemistry

Volumn 172, Issue , 2015, Pages 788-793

  Chen, Shanshan ^a   Zhang, Fangfang ^a   Ning, Jifeng ^a   Liu, Xu ^a   Zhang, Zhenwen ^a   Yang, Shuqin ^a  

^a NORTHWEST A F UNIVERSITY   (China)

Author keywords

Anthocyanins; Near infrared hyperspectral imaging; Partial least squares regression; Support vector regression; Wine grapes

Indexed keywords

ANTHOCYANIN CONTENT; NEAR-INFRARED HYPERSPECTRAL IMAGING; NIR HYPERSPECTRAL IMAGING; PARTIAL LEAST SQUARES REGRESSION; SUPPORT VECTOR REGRESSION (SVR); WINE GRAPES;

ANTHOCYANINS;

ANTHOCYANIN;

ARTICLE; GRAPE; HARVEST PERIOD; IMAGING; NEAR INFRARED HYPERSPECTRAL IMAGING; NEAR INFRARED IMAGING SYSTEM; NEAR INFRARED SPECTROSCOPY; NONHUMAN; PARTIAL LEAST SQUARES REGRESSION; PH; PREDICTION; RED WINE; SUPPORT VECTOR MACHINE; ANALYSIS; CHEMISTRY; PROCEDURES; REGRESSION ANALYSIS; THEORETICAL MODEL; VITIS; WINE;

ANTHOCYANINS; HYDROGEN-ION CONCENTRATION; LEAST-SQUARES ANALYSIS; MODELS, THEORETICAL; SPECTROSCOPY, NEAR-INFRARED; VITIS; WINE;

EID: 84908409016     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2014.09.119     Document Type: Article

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