| 杨平,姚明印,黄林,胡慧琴,陈娟,张煜煜,胡淑芬,王 彩虹,刘木华.LIBS检测污染马铃薯中的Pb及偏最小二乘定量分析模型[J].光电子激光,2015,26(1):141~148 |
| LIBS检测污染马铃薯中的Pb及偏最小二乘定量分析模型 |
| Detection of Pb in potato by LIBS and the partial least square quantity analysis model |
| 投稿时间：2014-10-09 |
| DOI： |
| 中文关键词: 激光诱导击穿光谱(LIBS) 偏最小二乘法(PLS) 农产品 重金属 快速检 测 |
| 英文关键词:laser induced breakdown spectroscopy (LIBS) partial least squares (PLS) agric ultural product heavy metal rapid detection |
| 基金项目:国家自然科学基金(31460419,31271612)、江西省重大科技项目(20143ACB21013)、江西 省教育厅科技计划 (GJJ10681)、江西省学术带头人计划(09004004)、赣鄱“555”英才和大学生创新计划(201410410010)资助项目 (江西农业大学 生物光电技术及应用实验室,江西 南昌330045) |
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| 中文摘要: |
| 为了提高农产品中重金属的光学快速检测的精度, 运用偏最小二乘(PLS)法结合激光诱导击穿光谱(LIBS) 对马铃薯中的Pb含量进行了定量分析,探讨了数据预处理方法对模型精度的影响。针对 96个污染马铃薯样 品的LIBS数据,分别进行3点到17点平滑处理,然后将平滑后的数据分别进行标准正态 变量变换(SNV)、 多元散射校正(MSC)、均值中心化(MC)、一阶导数(FD)和二阶导数(SD)求导去噪预处理。采 用湿法消解结合原子吸收分光光度 计(AAS)获取样品中Pb元素的真实浓度,选择包含Pb特征谱线的401~417nm波段进行PLS建模,对比分 析模型的相关系数r、交互验证均方根误差(RMSECV)和预测均方根误 差(RMSEP)。结果表明,采用13点平滑、 均值中心化预处理的PLS模型的校准质量和预测效果最好,模型的r、RMSECV和RMSEP分别达到了0.9963、16.4 和11.5,说明选择合适的数据预处理方法能有效提高LI BS检测果蔬产品定量模型的质量。 |
| 英文摘要: |
| Lower detection accuracy restricts the development of laser induced b reakdown spectroscopy (LIBS). A partial least square (PLS) method is proposed to analyze the Pb content in pot atoes by LIBS.The PLS model is composed of two steps which include different smoothing points and standard nor mal variate transformation (or multiple scatter correction,or the mean centralized,or the first derivative of denoising,or second derivative of denoising),to pretreat the LIBS spectrum.Spectral data of the 96potatoes samp les are pretreated by different data smoothing from 3points to 17points.The samples of potatoes are pretreat ed by acid wet digestion,and the real content of Pb is obtained by atomic absorption spectrophotometer (AAS).Th e LIBS spectrum chooses the 401－417nm wavelength range which contains characteristic spectral lines of Pb.The main evaluation indexes of PLS models,such as correlation coefficient,root mean squared error of cross-va lidation and root mean square error of prediction,are compared and analyzed.The obtained three indexes of PLS model after 13points smoothing and processing of the mean center are reach 0.9963,6.4and 11.5,respectively.In one word,the calibration and prediction of t his quantity model are the best results.Select ing the appropriate data for preprocessing can effectively improve the quality o f agricultural products detected by LIBS. |
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