FOOD SCIENCE ›› 2009, Vol. 30 ›› Issue (8): 147-150.doi: 10.7506/spkx1002-6630-200908029

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Prediction Analysis of Reducing Sugar Content in Honey Using Fourier Transform Near-infrared Spectroscopy

CHEN Lan-zhen1,2 XUE Xiao-feng1 CHEN Fang1 ZHAO Jing1 YE Zhi-hua2,* ZHONG Yan-ping3   

  1. (1. Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China
    2. Institute of Quality Standard and Testing Technology for Agro-products, Chinese Academy of Agricultural Sciences, Beijing
    100081, China 3. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China)
  • Received:2008-04-22 Revised:2008-07-09 Online:2009-04-15 Published:2010-12-29
  • Contact: YE Zhi-hua2,* E-mail: zhihuaye@mail.caas.net.cn

Abstract:

For exploring a rapid determination of reducing sugars, a correlation model of near-infrared spectrum and reducing sugar content in honey was established and the reducing sugar contents in honey samples were predicted by using Fourier transform near-infrared spectroscopy (FT-NIR) combined with partial least squares (PLS). The spectra of honey sample with reducing sugars content between 61.3% and 75.22% were scanned and the 11992.1 cm-1 to 7494.6 cm-1 spectrum was selected. Through preprocess of second derivative and 10 factors, the model was established by using PLS. The results of cross validation showed that the model of the calibration coefficient of determination (Rcal), root mean standard error of estimation (RMSEE), validation coefficient of determination (RCV), root mean standard error cross validation (RMSECV) are 99.71 %, 0.27 %, 98.44 % and 0.45 %, respectively. The model was used to verify samples and the statistical results showed that there is no significant difference between the predictive and chemical values. Altogether, this method is fast and accurate for quantitative analysis of reducing sugars content in mass honey samples.

Key words: honey, reducing sugars, Fourier transform near-infrared spectroscopy, partial least squares

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