蜂蜜文献
拉曼光谱法无损检测蜂蜜中的果糖和葡萄糖含量
[ 8/8 ]导读:应用拉曼光谱结合化学计量学方法对蜂蜜果糖和葡萄糖含量进行了定量分析。
Non-destructive detecting fructose and glucose content of honey withRaman spectroscopy
Li Shuifang1, Zhang Xin2, Li Jiaojuan1, Shan Yang3※, Huang Zizhi1
(1. College of Science, Central South University of Forestry and Technology, Changsha 4l0004, China;
2. Longping Branch Graduate School, Central South University, Changsha 410125, China;
3. Hunan Food Test and Analysis Center, Changsha 410125, China)
Abstract: Raman spectroscopy combined with chemometric methods was used to rapidly measure the content of fructose and glucose in honey. Seventy-five authentic honey samples from sixteen floral origins were obtained directly from bee-keepers in ten provinces of China from 2008 to 2010. The samples were stored at 6-8℃ in the laboratory before their analysis. Honey were liquefied in a water bath at 55℃ and manually stirred to ensure homogeneity before spectral measurements. Spectra of honey samples were recorded using an i-Raman spectrometer (BWS 415-785H, B&W TEK Inc., USA), which was equipped with a fiber-optic Raman probe, a thermoelectric cooled CCD detector with 2048 pixels and a 785 nm laser with a maximum output power of 495 mW in the signal range of 175-2 600 cm-1. The instrumental spectral resolution was 3 cm-1. Integration time was 15 s. Seventy-four samples were divided into 55 calibration sets and 19 validation sets by Kennard-Stone algorithm. AirPLS (adaptive iteratively reweighted penalized least squares) was used to correct the baseline of spectroscopy. CARS (competitive adaptive reweighted sampling) was used to screen variables. Thirty-one and forty-six variables were obtained from 1150 variables by CARS for glucose and fructose, respectively. Quantitative calibration models were developed with linear partial least squares (PLS) regression and non-linear support vector machine (SVM) regression, respectively. These models were used to predict the validation set samples. The prediction accuracies obtained from both glucose and fructose were satisfied by PLS model and SVM model. Correlation coefficient (R)of predicted values versus HPLC measured values and root mean square error of prediction (RMSEP) were 0.902 and 1.401 obtained from SVM model for fructose, respectively, which were higher than the values obtained by PLS model (R=0.892, RMSEP=1.604). PLS model’s R and RMSEP were 0.968 and 0.669 for glucose, respectively, which were higher than SVM model’s values (R=0.933, RMSEP=1.410). Raman spectroscopy combined with chemometric methods is a rapid and non-destructive method, which can be applied to measure the content of fructose and glucose in honey.
Key words: nondestructive examination; Raman spectroscopy; glucose; honey; content of fructose; PLS; SVM
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