LIBS结合单变量定标法对土壤中铅元素含量检测

重金属污染一直影响着人们的健康生活，如镉，铅和铜等的污染，故而土壤重金属的快速检测和如何预防，一直受各国学者关注和研究。传统土壤重金属检测方法（如原子吸收光谱法、X荧光光谱法等）样品预处理复杂，分析成本较高，易形成样品的二次污染，不能满足快速分析的要求。激光诱导击穿光谱（LIBS）是一种典型的原子发射光谱，它是基于分析物质中原子和离子受激发而发射的特征谱线信息，进而研究物质成分的分析方法。LIBS技术能够快速检测任何状态（固、液和气态）物质元素的成分和含量，被看作是未来化学检测和快速绿色分析领域的新兴技术。LIBS技术具有对样本简单预处理（或不需要处理）、多元素同步分析、远距离测量、适用性广等优势，被广泛用于生活生产的各个领域，已成为近年来国内外学者广泛关注和研究的热点之一。在农业信息快速感知的大背景下，以激光诱导击穿光谱技术为技术手段，以土壤重金属铅元素为研究对象，运用理论分析和数学建模相结合，建立了多种基于单变量定标曲线的土壤重金属铅检测模型，并进行了模型验证。自制15个已知的铅元素浓度梯度的谱线土壤样本，在获取了土壤LIBS数据之后，对其进行预处理对比，建立了基于谱峰强度、谱峰积分、洛伦兹拟合强度三种定标曲线模型，对土壤中铅元素含量进行定量分析，得出基于三种定标曲线模型对土壤中铅元素含量的预测决定系数R2分别为0.918 0，0.910 1和0.914 3，三种定标曲线分析方法的预测结果都较好，说明了LIBS结合单变量定标曲线法对土壤中铅含量的检测可靠性高。最后选取部分样本数据进行验证，结果较好。研究结果为研发便携式农田土壤污染物检测技术与装备提供技术支撑，也为农田精准管理和科学施肥奠定基础。

Detection of Pb Contents in Soil Using LIBS Coupled With Univariate Calibration Curve Methods

Heavy metal(like Pb,Cd,Cu,et al)in soil has affected the human health for a long time.So,the detection and prevention of soil Pb content have been a hot topic at home and abroad.Traditional methods of soil heavy metal detection,such as atomic absorption spectrometry(AAS),X fluorescence spectrometry(XRFS),are high cost,complicated,time-consuming,cannot meet the requirements of rapid analysis,and is easy to form secondary pollution of samples.Laser-induced breakdown spectroscopy(LIBS),a typical atomic emission spectrum,is a combination of laser technology and spectroscopic technology.It is based on the analysis of characteristic spectral line information that is excited to emit atoms and ions in a substance,and then compositions of the substance were studied.LIBS technology can rapidly detect the composition and content of material elements in any state(solid,liquid and gaseous).It is regarded as an emerging technology in the field of future chemical detection and rapid green analysis.LIBS technology has the advantages of simple pre-processing(or no processing required)for samples,multi-element simultaneous analysis,long-distance measurement,and wide applicability.Based on those advantages,it is widely used in various fields and viewed as one of the research hotspots.Under the background of agricultural informatization,the elements of Pb in the soil will be considered as the research carriers.And laser-induced breakdown spectroscopy(LIBS)technique combined with theoretical analysis and mathematical modeling will be employed to accurately detect the contents of Pb content.Then,the univariate calibration curve methods were built to predict heavy metal Pb content.Firstly,15 soil samples with known Pb concentration gradient were selected for analysis.Soil LIBS spectral data were pretreated with different pre-processing methods.Three models based on LIBS intensity,peak areas,Lorentz fit intensity after normalized corresponding Pb content was established and fitted to analyze Pb content in soil quantitatively.The results show that the R² of soil Pb content prediction based on three calibration curve models are 0.9180,0.9101 and 0.9143,respectively.The results of the three calibration curve analysis methods are good.It indicates that LIBS combined with univariate calibration curve method showed high reliability in detecting Pb in soil.The research results provide the theoretical foundation for developing the diagnosis and prevention technology of heavy metal contamination in soil and offer technical support for scientific spraying and precision management in agricultural production.