稻米重金属残留量的可调谐共振增强LIBS检测机理与分析方法研究

Heavy metal pollution in agricultural products including rice is becoming more and more serious. The conventional methods like AAS need consume chemical reagents and may induce some pollutants into ecosystems. Furthermore, the equipment is costly and clumsy, and lacks convenience in field analysis. Under this circumstance, it is a pressing moment in monitoring the safety of heavy metals in rice and other farm products by suitable means. It is well known that the existing green and rapid methods in determining heavy metals residue in rice can not meet the demand of trace detection.On the basis of the study by laser induced breakdown spectroscopy (LIBS) in our group for many years, to improve the sensitivity of rapid and trace detection, the new method named tunable resonant enhancing LIBS with ppb LOD will be carried out . The typical toxic heavy metals Pb,Cd,Cr and others in rice are selected as analytical targets. The suitable ablative laser will be utilized to ablate micro matter nearly nondestructively from the sample surface, and forms the plume plasma .Again,tunable laser will excite plasma furthermore and induces atomic fluorescence. Finally, the spectra will be collected and analyzed. In this project, most important task is exploring the mechanism that resonant exciting laser enhances the signal of spectral lines in plasma from objective heavy metals. To improve the sensitivity of analytical lines, it is necessary to obtain better spectral lines and spectra with good S/N( signal to noise ratio) and other merits by optimizing the wavelength of exciting laser, laser energy, delay time between ablative laser and exciting laser, delay in collecting spectra, gate width and other corresponding parameters. The feasible spectral preprocessing, characteristic variable extraction and chemometrics analytical methods will be used to construct the accurate prediction model of heavy metals in rice. The completion of this project will provide novel means in rapid, green and trace detection of quality and safety in agricultural products by special spectroscopy with high sensitivity, and will offer the basis in real time monitor and evaluation of safety in farm products.

传统化学方法检测稻米重金属无法达到快速绿色的要求，在课题组多年来对农产品质量安全激光诱导击穿光谱(LIBS)检测研究基础上，拟研究一种能对大米重金属残留量进行快速、绿色、检测限达ppb级的可调谐共振增强LIBS新方法。以稻米中重金属Pb、Cd、Cr等元素为研究对象，采用一束烧蚀激光从样品表层烧蚀出近似无损的微量检测物形成气体羽等离子体，再用可调谐激光激发等离子体产生原子荧光并采集光谱。重点探究共振激发激光增强样品等离子体中目标元素谱线信号的机理；通过优化激发激光波长、激光能量、两激光间延时、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，以提高分析谱线灵敏度；利用各种适用的光谱数据预处理、特征变量提取及化学计量学分析方法建立稻米重金属含量预测模型。项目的完成将为农产品质量安全快速、绿色、痕量检测提供高灵敏光谱分析新手段，为农产品安全实时监测和评估提供依据。

稻米重金属污染物的传统化学检测方法耗时长、污染环境，急需寻求一种绿色、快速的检测方法。激光诱导击穿光谱(LIBS)的独特优势使其在物质成分检测中发挥越来越大的潜力，但LIBS检测限难以达到农产品痕量重金属检测的需求。在课题组多年LIBS检测研究基础上，提出了共振光激发增强LIBS灵敏度新方法。.搭建了可调谐共振增强LIBS系统平台，由于稻米基体复杂，重金属元素铅（Pb）、镉(Cd)、铬(Cr)、汞(Hg)、砷(As)受到的干扰因素多，可调谐共振增强LIBS系统平台对目标元素的灵敏、准确检测仍需要进一步探索。在LIBS系统平台基础上，尝试了双光束增强、微波辅助增强，灵敏度均有一定提升。采用单变量线性回归、偏最小二乘(PLS)拟合对样品的LIBS相对发射强度和化学检测的真实浓度进行了定量分析，结果表明采用PLS回归建立的模型精度更高，更为可靠。.项目对江西省环鄱阳湖大米污染情况进行了实地采样、测试、讨论，对选取的代表性稻米制作的糙米及其对应稻壳和抛光大米中镉(Cd)、铬(Cr)、铅(Pb)和铜(Cu)元素进行了双光束增强LIBS检测，并采用湿法消解联合原子吸收分光光度计( AAS)检测样品真实浓度。研究结果表明，双光束增强LIBS最低只能探测到浓度为2.32µg/g大米中Cd I 228.802nm特征谱线。所有的稻壳样品中都能探测到清晰的Cr特征谱线光谱，部分稻壳样品中能探测到Cu元素谱线。但是，大米中的Cu、Cr、Pb元素谱线则均未探测到。.此外，项目江西“铜都”水稻产区稻米为典型研究对象，分别从德兴、贵溪和铅山三个县采集了相同品种的稻米谷粒，并测试了稻壳LIBS光谱谱。结果显示，水稻稻壳样品的元素组成基本一致，Mg II 279.54和Ca II 393.366 nm LIBS特征谱线强度相似。且Mg、Si、Ca等矿物质元素及C、CN等有机元素资源丰富。但三组水稻稻壳间的Cu元素LIBS强度存在显著差异，这与AAS测定土壤中铜的参考浓度一致。表明样品中铜浓度的差异主要是受环境及污染物的影响，尤其是铜矿稻米产区。.项目的实施为农产品质量安全快速绿色检测提供参考，两年执行期内，发表SCI期刊论文3篇，培养硕士研究生3名。