| 基于近红外光谱法快速鉴别转基因油研究 |
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| 引用本文： | 朱建国,王雅静,尹知沁,谢雷英,王娜,曹铎.基于近红外光谱法快速鉴别转基因油研究[J].光学仪器,2020,42(4):61-66. |
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| 作者姓名： | 朱建国 王雅静 尹知沁 谢雷英 王娜 曹铎 |
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| 作者单位： | 上海理工大学 材料科学与工程学院，上海 200093;中国科学院上海技术物理研究所 红外物理国家重点实验室，上海 200083;上海节能镀膜玻璃工程技术研究中心，上海 200083;上海师范大学 数理学院，上海 200234;中国科学院上海技术物理研究所 红外物理国家重点实验室，上海 200083;上海节能镀膜玻璃工程技术研究中心，上海 200083;中国科学院上海技术物理研究所 红外物理国家重点实验室，上海 200083;上海节能镀膜玻璃工程技术研究中心，上海 200083;上海科技大学 物质学院，上海 200120;中国科学院上海技术物理研究所 红外物理国家重点实验室，上海 200083;上海节能镀膜玻璃工程技术研究中心，上海 200083;复旦大学 信息科学与工程学院，上海 200433 |
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| 基金项目： | 国家重点研发专项（2017YFC0111400）；国家自然科学基金（11874376）；上海市科学与技术委员会项目（18590712600、18DZ2282200、19DZ2293400、19ZR1465900） |
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| 摘 要： | 采用近红外光谱法对转基因油/非转基因油的混合溶液进行研究。对采集到的原始光谱分别进行多元散射校正（MSC）、一阶导数（FD）、移动窗口平滑（MWS）、Savitzky-Golay平滑一阶导数（SG1）预处理。研究比较了不同预处理方法对转基因油/非转基因油支持向量机（SVM）建模判别分析的影响，其中MSC预处理后的模型预测效果最好，准确率为91.6%。为了进一步提高模型的精度与稳定性，采用连续投影算法（SPA）对全波长进行特征波长筛选。利用筛选后的15个特征波长输入到SVM中，预测准确率提高到98.3%。实验结果表明，采用近红外光谱法，可以实现对转基因油/非转基因油快速检测，不仅适用于纯转基因油的鉴别，也适用于非转基因油中掺入转基因油的鉴别。
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| 关 键 词： | 转基因油 近红外光谱 支持向量机（SVM） |
| 收稿时间： | 2020/3/9 0:00:00 |
Research on fast identification of transgenic oil based on near infrared spectroscopy |
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| ZHU Jianguo,WANG Yajing,YIN Zhiqin,XIE Leiying,WANG N,CAO Duo.Research on fast identification of transgenic oil based on near infrared spectroscopy[J].Optical Instruments,2020,42(4):61-66. |
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| Authors: | ZHU Jianguo WANG Yajing YIN Zhiqin XIE Leiying WANG N CAO Duo |
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| Affiliation: | School of Materials Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;Shanghai Engineering Research Center of Energy-Saving Coatings, Shanghai 200083, China;Department of Physics, Shanghai Normal University, Shanghai 200234, China;State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;Shanghai Engineering Research Center of Energy-Saving Coatings, Shanghai 200083, China;State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;Shanghai Engineering Research Center of Energy-Saving Coatings, Shanghai 200083, China;School of Material Science, Shanghai University of Science and Technology, Shanghai 200120, China;State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;Shanghai Engineering Research Center of Energy-Saving Coatings, Shanghai 200083, China;School of Information Science and Engineering, Fudan University, Shanghai 200433, China |
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| Abstract: | Near-infrared spectroscopy was used to study the mixed solution of transgenic oil/non-transgenic oil. The acquired original spectra were pretreated with multiple scattering correction (MSC), first-order derivative (FD), moving window smoothing (MWS) and savitzky-golay smoothing first-order derivative (SG1). The effects of different pretreatment methods on the discriminant analysis of transgenic oil/non-transgenic oil support vector machine (SVM) modeling were compared. The model after MSC pretreated has the best prediction effect, and the accuracy rate is 91.6%. In order to further improve the accuracy and stability of the model, the successive projections algorithm (SPA) is used to select the characteristic band. We input the 15 feature wavelengths after SPA selection into the SVM, and the prediction accuracy is 98.3%. The experimental results show that the near-infrared transmission spectrum combined with stoichiometry can achieve rapid and non-destructive detection of transgenic oil/non-transgenic oil, not only suitable for the identification of pure genetically modified oils, but also for the identification of non-transgenic oils that are mixed with genetically modified oils. |
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