...
首页> 外文期刊>Spectrochimica Acta, Part B. Atomic Spectroscopy >Challenges in the quantification of nutrients in soils using laser-induced breakdown spectroscopy - A case study with calcium
【24h】

Challenges in the quantification of nutrients in soils using laser-induced breakdown spectroscopy - A case study with calcium

机译:使用激光诱导的击穿光谱法定量土壤中营养成分的挑战 - 一种钙的案例研究

获取原文
获取原文并翻译 | 示例
           

摘要

The quantification of the elemental content in soils with laser-induced breakdown spectroscopy (LIBS) is challenging because of matrix effects strongly influencing the plasma formation and LIBS signal. Furthermore, soil heterogeneity at the micrometre scale can affect the accuracy of analytical results. In this paper, the impact of univariate and multivariate data evaluation approaches on the quantification of nutrients in soil is discussed. Exemplarily, results for calcium are shown, which reflect trends also observed for other elements like magnesium, silicon and iron. For the calibration models, 16 certified reference soils were used. With univariate and multivariate approaches, the calcium mass fractions in 60 soils from different testing grounds in Germany were calculated. The latter approach consisted of a principal component analysis (PCA) of adequately pre-treated data for classification and identification of outliers, followed by partial least squares regression (PLSR) for quantification. For validation, the soils were also characterised with inductively coupled plasma optical emission spectroscopy (ICP OES) and X-ray fluorescence (XRF) analysis. Deviations between the LIBS quantification results and the reference analytical results are discussed. (C) 2018 Elsevier B.V. All rights reserved.
机译:由于基质效应强烈影响等离子体形成和Libs信号,具有激光诱导的击穿光谱(Libs)的土壤中的元素含量的定量是具有挑战性的。此外,微米标度下的土壤异质性会影响分析结果的准确性。本文讨论了单变量和多变量数据评估方法对土壤营养素量化的影响。示例性地,示出了钙的结果,其反映了镁,硅和铁等其他元素也观察到的趋势。对于校准模型,使用了16个经认证的参考土壤。计算了单变量和多变量的方法,计算了德国不同测试场地的60个土壤中的钙质量分数。后一种方法包括用于分类和识别异常值的充分预处理数据的主要成分分析(PCA),其次是部分最小二乘回归(PLSR)进行量化。为了验证,土壤还具有电感耦合等离子体光发射光谱(ICP OES)和X射线荧光(XRF)分析。讨论了LIBS量化结果与参考分析结果之间的偏差。 (c)2018 Elsevier B.v.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号