蔬菜叶片重金属的LIBS定量化快速测量机理与模型研究

With the development of industry and agriculture and the aggravation of environmental pollution, heavy metal contamination in vegetables has become a bottleneck for the development of vegetable industry and a big threat to human health. Traditional methods for measurement of heavy metals in vegetables are time-consuming, expensive and destructive, and unable to realize fast measurement. The purpose of this project is to solve the worldwide difficult problem of in situ fast detection of heavy metals in fresh vegetables. In this study, LIBS (Laser Induced Breakdown Spectroscopy) technique is used to measure typical heavy metals in unprocessed, fresh vegetables. The mechanism and modeling methods would be studied, to lay a theoretical foundation for the development of portable instrument. The project studied the physical mechanism of laser ablation on vegetables at first. The local thermal equilibrium model that describes the ablation progress will be established, through analyzing the density of free electrons and the temperature of laser plasma. The LIBS spectral characteristics of heavy metals in vegetables, such as spectral peak positions, time evolution characteristics would be studied, and the effects of experimental parameters on spectral characteristics would be analyzed. Through analyzing the major noise sources and noise characteristics during the measurement, the pre-processing methods for LIBS spectrum would be studied to improve prediction accuracy. Based on the mechanisms and LIBS characteristics analyzed above, external calibration, internal calibration and calibration free models would be established, and the multivariate regression models would be studied.

随着工农业的发展和环境污染的加剧，重金属污染已成为制约蔬菜业发展的重要瓶颈并危害着人类的健康。传统的蔬菜重金属检测方法周期长、成本高、具有破坏性，不能实现快速检测。本项目瞄准这一科学难题，以LIBS（Laser Induced Breakdown Spectroscopy）技术为手段，以未经处理的新鲜叶片为测量对象，开展蔬菜中典型重金属的定量化测量机理和模型研究，为研制便携式蔬菜重金属检测仪器奠定理论基础。项目从激光击穿叶片的物理机制入手，通过自由电子密度和激光等离子体温度分析，建立描述击穿过程的局部热平衡模型；研究蔬菜重金属的LIBS光谱峰位、时间演化规律等特征，并明确实验参数对LIBS谱线的影响规律；分析测量中的噪声源和噪声特性，研究LIBS谱线的预处理方法以提高预测精度；通过物理机制和特性规律的分析，建立蔬菜重金属的内定标、外定标曲线和自由定标方法，并研究多元变量回归模型。

随着工农业的发展和环境污染的加剧，重金属污染已成为制约蔬菜业发展的重要瓶颈并危害着人类的健康。传统的蔬菜重金属检测方法周期长、成本高、具有破坏性，不能实现快速检测。本项目瞄准这一科学难题，以LIBS（Laser Induced Breakdown Spectroscopy）技术为手段，开展蔬菜中典型重金属的定量化测量机理和模型研究。.历经4年，项目重点开展了叶片等生物组织的激光诱导击穿物理机制研究、主要重金属的光谱峰位和时间演化规律等特征研究、测量中的噪声源和噪声特性研究、用于蔬菜重金属测量的多元变量回归模型研究等。在以下方面取得了重要进展：1）针对重金属含量较低、普通激光诱导击穿光谱灵敏度不够的问题，提出了光程提升、纳米粒子增强、磁约束和空间约束等信号增强方法，极大程度提高了激光诱导击穿光谱的检测灵敏度；2）针对重金属的不同存在形态，提出了一种激光诱导击穿光谱和红外光谱联用的方式，通过共用的光学结构同时实现红外信号、等离子体发射信号的解析，从而对分子光谱和原子光谱进行同步获取；3）借助于机器学习，研究了包括谱线归一化、内定标、多元非线性回归等方法，提高了光谱的重复能力，提高了检测精度；4）在机理研究基础上进一步研究系统的实现方法，构建了简易化的光学结构，研制了用于蔬菜重金属测量的传感器样机，并开展了室内外测量实验。.项目研究结果实现了蔬菜叶片重金属的快速测量，并研制了传感器件，对食品安全、产地环境控制具有重要意义。在项目支持下，在Sensors、Analytical Chemistry等权威杂志发表SCI论文12篇，申请发明专利9项，实用新型专利5项。项目成果获得北京市科学技术三等奖（农业环境精细化光学监测技术与产品）。项目的研究进一步获得中英牛顿基金和国家自然科学基金优秀青年基金资助。