食品检测中的光谱技术应用研究进展  

Review on the Application of Spectroscopy Technology in Food Detection

作　　者：李鑫星[1,2] 张迎港 马殿坤 田建军 张保军[3] 陈静[4] LI Xin-xing;ZHANG Ying-gang;MA Dian-kun;TIAN Jian-jun;ZHANG Bao-jun;CHEN Jing(Beijing Laboratory of Food Quality and Safety,College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China;Energy and Environment Engineering Institute,Nanchang Institute of Technology,Nanchang 330044,China;College of Food Science and Engineering,Inner Mongolia Agricultural University,Huhhot 010018,China;School of Logistics,Beijing Wuzi University,Beijing 101149,China)

机构地区：[1]中国农业大学信息与电气工程学院食品质量与安全北京实验室,北京100083 [2]南昌理工学院新能源与环境工程学院,江西南昌330044 [3]内蒙古农业大学食品科学与工程学院,内蒙古呼和浩特010018 [4]北京物资学院物流学院,北京101149

出　　处：《光谱学与光谱分析》2023年第8期2333-2338,共6页Spectroscopy and Spectral Analysis

基　　金：内蒙古自治区科技项目(2022YFDZ0020);国家自然科学基金项目(61802411)资助。

摘　　要：随着时代发展,人们对饮食要求越来越高,从“能吃饱”逐渐变成“要吃好”。目前人们对食品安全问题十分重视,因此,迫切需要一种无损、快捷的食品检测技术以满足人们的需求。光谱技术能够根据待测食品样本的物理结构和化学成分推算出其物质特性和组成成分,在掺伪检测、新鲜度检测以及有害物质残留检测等方面,应用前景广阔。与食品检测中的传统检测技术相比,光谱技术具有迅速、精度高、没有样品损耗以及重复性好等优点,已经成为食品检测中重要的发展方向。该文整理了国内外近5年来食品检测中的光谱技术应用相关研究文献,重点在数据预处理方法、特征波段选择算法以及数据建模方法三个方面对食品检测中的光谱技术应用进行系统综述。该文所论述食品检测中光谱技术的应用主要采用多元散射校正(MSC)、标准正态变换(SNV)以及SG平滑算法对所采集光谱数据预处理;采用连续投影算法(SPA)、主成分分析(PCA)以及竞争性自适应重加权采样(CARS)进行特征波段选择;采用偏最小二乘(PLS)、支持向量机(SVM)以及人工神经网络(ANN)对检测结果数据进行分析。同时总结展望了食品检测中光谱技术应用的发展方向:光谱检测技术与多种食品检测技术相互融合将会成为未来发展方向;将光谱与在线检测技术相结合,实现对食品样本在线实时检测,将会取得更有价值的检测结果;研发便携式光谱检测设备,将会更方便地进行食品现场检测,检测效率将会显著提升,并且具有很大市场潜力。With the progress of society,people s dietary requirements are constantly improving,which is gradually changed from the previous“eat full”to today s“eat well”.People are paying more attention to food safety.Therefore,fast and non-destructive food detection technology is needed to meet the imminent demand for food safety.Spectral technology can calculate the material characteristics and composition of food samples according to their physical structure and chemical composition.It has a broad application prospect in adulteration detection,freshness detection,and residue detection of harmful substances.Compared with the traditional detection technology in food detection,spectral technology has the advantages of rapid,high precision,no sample loss,and good repeatability,and it has become an important development direction in food detection.In this paper,related domestic and international literature on spectral techniques applied to food detection in the last five years is discussed,focusing on data pretreatment method,characteristic band selection algorithm and data modeling method to systematically review the application and progress of spectral technology in food detection.In this paper,the application of spectral technology in food detection is discussed,including the preprocessing of spectral data by multiplicative scatter correction(MSC),standard normal variate transform(SNV),and Savitzky-Golay smoothing(SG)algorithm;successive projections algorithm(SPA),principal component analysis(PCA),and competitive adaptive reweighted sampling(CARS)were used to select characteristic bands;partial least squares(PLS),support vector machine(SVM),and artificial neural network(ANN)were used to analyze collected data.Simultaneously,this paper summarizes the prospects for the application of spectral technology in food detection:the integration of spectral detection technology and a variety of food detection technology will become a new development direction in the future;combining spectral detection technology with on-line

关 键 词：光谱技术 食品检测 光谱数据处理 预测模型 

分 类 号：O433.4[机械工程—光学工程]