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基于光电化学生物传感器的人工大豆毛油中PC含量快速检测研究

Rapid Detection of PC Content in Artificial Soybean Crude Oil Based on Photoelectric Chemical Biosensor

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【作者】 王宁; 李琳; 罗淑年; 王立琦; 王伟宁; 于殿宇;

【Author】 WANG Ning;LI Lin;LUO Shunian;WANG Liqi;WANG Weining;YU Dianyu;College of Food Engineering, Harbin University of Commerce;Jiusan Food Co., Ltd.;College of Computer and Information Engineering, Harbin University of Commerce;College of Food Science, Northeast Agricultural University;

【通讯作者】 王立琦;

【机构】 哈尔滨商业大学食品工程学院; 九三食品股份有限公司; 哈尔滨商业大学计算机与信息工程学院; 东北农业大学食品学院;

【摘要】 为实现对大豆毛油脱胶过程中磷脂含量的实时监测,在光电化学生物传感器的基础上,设计了一种人工大豆毛油中磷脂酰胆碱(Phosphatidylcholine, PC)含量的实时检测系统。结果表明,二氧化锡纳米颗粒(SnO2 nanoparticles, SnO2 NPs)/聚硫堇(Polythionine, PTh)/胆碱氧化酶(Choline oxidase, ChOx)(SnO2 NPs/PTh/ChOx)已成功复合在氧化铟锡(Indium tin oxide, ITO)电极上,该复合电极可对人工大豆毛油中的PC含量产生良好的光电流信号,最大光电流强度为4.60μA。利用电化学工作站采集了100个不同PC含量人工大豆毛油样本的光电流信号,并通过小波变换去噪及偏最小二乘回归模型(Partial least squares regression, PLSR)对100个样品的数据进行处理,该测试集模型的决定系数R2为0.89,预测均方根误差(Root mean square error error of prediction, RMSEP)为24.98 mg/L,相对标准偏差(Relative standard deviation, RSD)为0.13%,说明模型稳定可靠。利用LabVIEW开发了人工大豆毛油中PC含量的实时检测系统,并对其性能进行测试。结果发现,该系统的RSD小于4.00%,且与电化学工作站的检测结果相近,有效简化了检测步骤。

【Abstract】 In order to realize real-time monitoring of phospholipid content in soybean oil degumming process, a real-time detection system for phosphatidylcholine(PC) content in artificial soybean crude oil was developed based on photoelectric chemical biosensor. The result showed that SnO2 nanoparticles(SnO2 NPs)/Polythionine(PTh)/Choline oxidase(ChOx)(SnO2 NPs/PTh/ChOx) was successfully combined on indium tin oxide(ITO) electrode, and the composite electrode could produce good photocurrent signal for PC content in artificial soybean crude oil. The maximum photocurrent intensity was 4.60 μA. In addition, the photocurrent signals of 100 artificial soybean crude oil samples with different PC content were collected by electrochemical workstation, and the data of 100 samples were processed by wavelet transform denoising and partial least squares regression model(PLSR). The coefficient of determination R2 of the test set model was 0.89, the root mean square error of prediction(RMSEP) was 24.98 mg/L, and the relative standard deviation(RSD) was 0.13%, indicating that the model was stable and reliable. A real-time detection system for PC content in artificial soybean crude oil was developed by using LabVIEW and its performance was tested. The results showed that the RSD of the system was less than 4.00%, which was similar to the detection result of the electrochemical workstation, and the detection step was effectively simplified. In conclusion, the research result provided some theoretical support for real-time monitoring of residual phosphorus in soybean oil during oil degumming in industrial field. These findings can help optimize the extraction and refining process of soybean oil and improve production efficiency, which had important implications for its application in the food and industrial sectors.

【基金】 国家自然科学基金项目(32072259)
  • 【文献出处】 农业机械学报 ,Transactions of the Chinese Society for Agricultural Machinery , 编辑部邮箱 ,2025年11期
  • 【分类号】O657.1;TS225.13;TP212.3
  • 【下载频次】36
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