期刊
FOOD CHEMISTRY
卷 114, 期 3, 页码 1135-1140出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2008.10.076
关键词
Quantification; Bayberry juice; Near-infrared spectroscopy; Partial least-squares regression
资金
- National Natural Science Foundation of China [60778024, 30825027]
- National Key Technology RD Program [2006BAD11A12]
Bayberry plays an important role in the nutrition and is a very important fruit-product. It has a high economic and officinal value. In this study, glucose, fructose and sucrose in bayberry juice were detected and quantified using near-infrared (NIR) spectroscopy. The HPLC method was assumed to provide the reference value of the analyte for calibration. Partial least-squares regression (PLSR) was used to construct calibration models with different pre-processing methods. The number of PLS factors was optimised. The results show PLS models are good for predicting glucose, fructose and sucrose concentrations in bayberry juice, and their prediction accuracy can be improved by using derivative process with the exception of the glucose. The best models were mostly given by the second derivative processed spectra, especially for sucrose with the determination coefficient, R-2 of 0.9931. This demonstrates the potential of NIR spectroscopy to quickly detect these components simultaneously in bayberry juice with the reference method of HPLC. (C) 2008 Elsevier Ltd. All rights reserved.
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