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当前位置: 首页 > 文章 > 基于短波近红外光谱技术的原蜜高果糖浆掺假度鉴别 南京农业大学学报 2014,37 (6) 165-170
Position: Home > Articles > Determination of raw honey adulterated with high fructose corn syrup based on short wave near-infrared spectroscopy Journal of Nanjing Agricultural University 2014,37 (6) 165-170

基于短波近红外光谱技术的原蜜高果糖浆掺假度鉴别

作  者：
陈桂云;吴威;黄玉萍;陈坤杰
单  位：
南京农业大学工学院
关键词：
蜂蜜;短波近红外光谱;掺假;高果糖浆
摘  要：
虽然全波段近红外光谱信息量丰富,但应用成本过高。发展短波近红外蜂蜜掺假鉴别技术,更能适应中国蜂蜜市场频繁检测需要。将高果糖浆掺入9种原蜜,制备得153个不同掺假度的样本。以透射方式采集了样本600~1 100 nm波段的近红外光谱。用Rc/SECV值作为定标因子确定并优化模型,用预测指数RP/SEP值评价模型预测能力。在保留外部评价同时定义模型综合评价指数C对优选的10个模型予以综合评价。用tansig函数和logsig函数作为网络隐含层和输出层转化函数,建立鉴别蜂蜜高果糖浆掺假度的短波近红外人工神经网络模型。结果表明:遴选出的最优模型(组合小波去噪、一阶导数、均值中心化和基线校正预处理,欧氏距离KS分类,690~1 019 nm波段,ANN主因子数和隐含层节点数为15和12),其综合评价指数C=4.690,模型可评判为好。校正集和测试集的决定系数分别达到了0.939和0.970。结论:深入挖掘短波近红外信息,用以定量鉴别蜂蜜掺假程度在技术上具有可行性。可据此开发更节约的短波近红外便携仪用于市场中蜂蜜掺假检测。
译  名：
Determination of raw honey adulterated with high fructose corn syrup based on short wave near-infrared spectroscopy
作  者：
CHEN Guiyun;WU Wei;HUANG Yuping;CHEN Kunjie;College of Engineering,Nanjing Agricultural University;
关键词：
honey;;short wave near-infrared spectroscopy;;adulteration;;high fructose corn syrup
摘  要：
It is more feasible to develop a short wave near-infrared spectroscopy for its lower cost than entire NIR spectroscopy in China honey market,although the latter is much richer in information. The aim of this study is to quantitatively determine raw honey adulterated with high fructose corn syrup using short wave NIR spectroscopy. 153 samples with different degree of adulteration were prepared by adding high fructose corn syrup into the nine raw honeys. Near-infrared spectra of all these samples were recorded in transmittance mode from 600 to 1 100 nm. The function for hidden layer of network was tansig and that for output layer was logsig.The artificial neural network model was developed based on short wave near-infrared spectroscopy using the value of Rc/SECV as calibration index and using that of RP/SEP as index to assess its adaptability. A kind of more comprehensive evaluation index was defined as supplement to the external evaluation of the selected ten models. The ANN model with parameter of Euclidean KS classification,wavelet denoising,1st derivative,centering and baseline correction of spectral data,690- 1 019 nm and ANN 15,12 was finally assessed good since its total evaluation index was 4. 690. The determination coefficient of its calibration set and test set reached 0. 939 and 0. 970,respectively. Conclusions: The result showed the feasibility of quantitative identification of adulterated honey using short wave near-infrared spectroscopy by data mining,which might contribute to the development of lower-cost portable NIR spectrometers of short wave range for identifying adulterated honey.

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