Dynamic prediction models for alkaloid content using NIR technology for the study and online analysis of parching in Areca Seed

Food Chemistry

Volumn 126, Issue 2, 2011, Pages 725-730

  Xue, Jintao ^a   Wu, Chunjie ^c   Wang, Leilei ^a   Jiang, Su ^b   Huang, Guo ^b   Zhang, Jiliang ^c   Wen, Silan ^a   Ye, Liming ^a  

^a SICHUAN UNIVERSITY   (China)

^b Bruker Instruments Ltd   (China)

^c CHENGDU UNIVERSITY OF TRADITIONAL CHINESE MEDICINE   (China)

Author keywords

Areca Seed; NIR; PLS; The dynamic content; The parching

Indexed keywords

ARECA SEED; NIR; PLS; THE DYNAMIC CONTENT; THE PARCHING;

CALIBRATION; ERRORS; FORECASTING; INFRARED DEVICES; MATHEMATICAL MODELS; MEAN SQUARE ERROR; SEED;

QUALITY CONTROL;

ALKALOID; ARECAIDINE; ARECOLINE; GUVACINE;

ARTICLE; BETEL NUT; CALIBRATION; CORRELATION COEFFICIENT; NEAR INFRARED REFLECTANCE SPECTROSCOPY; NONHUMAN; ONLINE ANALYSIS; PARTIAL LEAST SQUARES REGRESSION; PLANT SEED; PREDICTION; QUALITY CONTROL; TEMPERATURE; TIME; VALIDATION STUDY;

ARECA;

EID: 78650679737     PISSN: 03088146     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodchem.2010.11.036     Document Type: Article

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