叶菜和猪肉中重金属元素的PLEAFS快速无损痕量检测方法研究

The quality and safety of agricultural products has become the prominent problems to be solved in our country. Especially heavy metals pollution in agricultural products is more and more serious.The previous project "nondestructive detection of heavy metals in fruit by laser induced breakdown spectroscopy(LIBS)" funded by National Natural Science Foundation of China(NSFC) has been finished by our group.To further improve the sensitivity and stability of rapid detection in agricultural products, plume laser excited atomic fluorescence spectroscopy (PLEAFS) is proposed as a new analysis method. PLEAFS has lower detect limit,which can reach ppb order of magnitude. In this project, leaf vegetable and fresh pork will be used as detective samples and the heavy metals Pb, Cd,Cr,Hg, and As will be detected in vegetable and meat. The surface of agricultural products (detected samples) will be ablated by pulse laser with lower energy,and the plume will be produced by micro substance ablated(nondestructive approximately ). Atomic fluorescence will be excited and produced by 193nmArF laser with higher energy.And the fluorescence spectra will be collected by ICCD spectrometer. The keypoints,such as plume density of atomization, mechanism of 193nm laser exciting heavy metals, will be reseached.The spectra with sharp spectral line and excellent SNR(Signal to Noise Ratio) will be obtained by optimizing collection delay, width and other experimental parameters. Then optimized experiment device for PLEAFS will be built up, and the spectral emission lines for all kinds of element will be recognized.The spectral data will be preprocessed and the characteristic variable will be extracted. The predicted model will be constructed based on many kinds chemometrics such as principal component analysis (PCA), partial least squares regression(PLS), artificial neural net(ANN),support vector machine (SVM) and other appropriate methods. This new method with rapid, nondestructive and environmentally friendly properties in detecting heavy metals of agricultural products will be obtained based on the PLEAFS technology, and this method have many merits ,such as better accuracy, low detect limit, high sensitivity and stability ,which is suitable for trace detection of toxic heavy metals in farm products,and the results can apply to the national standard.

农产品重金属污染日趋严重,现有的快速无损方法达不到痕量检测的需求。在课题组已结题的国家自然科学基金"水果中有害重金属元素的激光诱导击穿光谱无损检测技术研究"基础上，为进一步提高快速痕量检测的稳定性和灵敏度，拟研究检测限达ppb级的激光激发气体羽原子荧光光谱（PLEAFS）新方法。 项目以生活常用必需品叶菜和猪肉中重金属元素铅、镉、铬、汞、砷为研究对象。拟采用合适的低能激光从样品表层烧蚀出微量检测物（近似无损）形成气体羽，再用193nmArF高能激光激发气体羽产生原子荧光并采集光谱。重点探究使检测物质原子化最优的气体羽密度、193nm激光能激发出多种痕量重金属元素特征光谱的机理；通过优化光谱采集延时、采集门宽等系统参数，获得谱线尖锐和信噪比优的光谱；利用光谱数据预处理、特征变量提取并结合合适的化学计量学方法建立精准检测模型。项目完成后将为农产品质量安全的快速、无损、痕量检测提供新手段。

食品重金属安全问题频发，蔬菜和肉类是人们常食的两大类农产品，其重金属超标现象不可忽视，加强对蔬菜和肉类食品中重金属残留量的检测是民心所向，大势所趋。为了克服常规的化学检测方法周期长、成本高、有污染等不足，本项目探索了具有快速、无损、绿色、多元素同时检测等诸多优势的激光诱导击穿光谱（LIBS）及LIBS融合原子荧光光谱的激光激发气体羽原子荧光光谱(PLEAFS)分析方法，并辅助以微波辅助、磁约束、空间约束、双光束LIBS、各种合适的光谱数据预处理及模型构建方法，旨在提高样品中典型重金属元素LIBS分析稳定性、灵敏度和准确度。分别以新鲜蕹菜（空心菜）及白菜中的重金属Pb、Cr、Cu，四季小白菜中的Pb、Cd，土豆中的Pb、Cr,猪肉中Cd、Pb和Cr元素为对象，项目执行过程中主要取得了以下几方面的成果：（1）分析了LIBS系统参数对样品中典型重金属元素LIBS光谱质量的影响，并优化了光谱采集延时、激光能量、双光束激光间脉冲间隔、微波辅助能量等系统参数；（2）探索了样品含水量、均匀性等特性对LIBS分析信号的影响，并比较了对样品采用真空干燥及压片处理，光谱灵敏度提升的效果；（3）采用基线校正、多元散射校正、变量标准化、滤波等各种合适的光谱数据预处理方法，分析比较了光谱平滑、去噪结果；（4）通过单变量分析、偏最小二乘法等多种定量模型分析方法，比较了重金属元素预测精度。以上成果在Journal of Analytical Atomic Spectrometry等国内外核心刊物上发表论文18篇，其中SCI收录9篇；申请发明专利2项，授权实用新型专利2项；获得江西省自然科学二等奖1项；培养在读硕士4名，毕业硕士6名，完成了项目的预期目标。但直接采用LIBS方法在线实时分析样品重金属仍然存在一定的挑战性，今后的工作需要继续从农产品中痕量重金属元素的LIBS检测机理上深层次，进一步提升LIBS方法在快速、绿色、实时检测方面的潜力。项目工作，探索了蔬菜和猪肉中典型重金属元素的LIBS光谱特性及定性、定量分析方法，为食品安全风险预警提供新的解析理论和快速检测依据。