Quantitative analysis of bayberry juice acidity based on visible and near-infrared spectroscopy

Applied Optics

Volumn 46, Issue 25, 2007, Pages 6391-6396

  Shao, Yongni ^a   He, Yong ^a   Mao, Jingyuan ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL MODELS; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; REFLECTION; REGRESSION ANALYSIS; VISIBILITY;

BAYBERRY JUICE ACIDITY; LEARNING RATE; NETWORK PARAMETERS; SPECTRAL REFLECTIVITY DATA;

NEAR INFRARED SPECTROSCOPY;

EID: 36148946042     PISSN: 1559128X     EISSN: 15394522     Source Type: Journal    
DOI: 10.1364/AO.46.006391     Document Type: Article

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