叶菜中痕量农药残留的光谱无损检测技术研究—基于红外光谱、激光诱导荧光及拉曼光谱

项目名称： 叶菜中痕量农药残留的光谱无损检测技术研究—基于红外光谱、激光诱导荧光及拉曼光谱

项目编号： No.31271612

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 农业科学

项目作者： 刘木华

作者单位： 江西农业大学

项目金额： 73万元

中文摘要： 农产品农药残留的光谱无损检测方法具有无需前处理、绿色、实时的优势。在完成了脐橙表面农药残留光谱无损检测的国家基金基础上，进一步提出采用多种光谱技术、纳米增强信号和设法降低复杂农产品本体光谱信息影响新方法来无损检测叶菜中痕量农残的课题。 项目以原始叶菜和将叶菜进行激光解离微区（近似无损伤）后的气体成分等两类样本为对象,典型农药残留为检测目标。 采用具有痕量检测能力的紫外激光诱导荧光及拉曼光谱、红外光谱获取原始叶菜和激光解离后叶菜气体成分的光谱数据；应用波谱学原理解析农残种类信息、平滑序列非正交幅频方法来处理光谱数据；信号微弱差异计算及概率圆分析方法来最大程度降低农产品本体信息的影响，藉此获得农残微弱光谱信号，并研究痕量农药残留含量预测的建模方法。 课题将获得无损检测叶菜中痕量农残的光学系统组建方案和检测方法。该技术还可用于大批量、所需劳动力大的脐橙等柑桔类的痕量农残检测中。

中文关键词： 农药残留；无损检测；表明增强拉曼光谱；密度泛函理论；痕量检测

英文摘要： The methods that nondestructive detect pesticide residues in agricultrual product based on spectroscopy have the advantage of no pre-treating,green and real-time. After completing a project of Chinese Natrual Science Funding about detecting pesticide residues in navel orange surface using spectra,we will ahead propose a improved methods nondestructive to detect trace pesticide residues in leaf vegetables by muti-kinds of spectroscopy technology,nano-particle enhanced sigal and removed more background sigal. Two kinds of samples including original leaf vegetable and gas from leaf after laser ablation will be detected,and some typical pesticide residues will be the aim of detecting. Spectral signal of two kinds of samples are obtained by UV laser-induced fluorescence/raman spectroscopy and infrared spectroscopy which are good techniques of trace-detection.The information about pesticide residues will be analysised by applying spectroscopy principle and spectra data will be processed by applying non-orthogonal amplitude frequency analysis of the smoothed squences (NAFASS). The probability circles analysis and statistical detection of the hidden distortions in spectra will be used to removed most of background singal in order to discrease the effect of the leaf vegetables body and get the weak spectral singal of pe

英文关键词： pesticide residue；nondestructive detection；surface enhanced raman Spectroscopy；density functional theory；trace pesticide residues detection