使用诱导合等离子体质谱法 (ICP-MS) 确定土壤来源类型 分析Pinus ponderosa灰
M Fernanda Delgado Cornelio1, Michael E Ketterer2, James A Jordan3
1Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware 19716, USA.
Applied spectroscopy
|August 12, 2025
概括
这项研究表明,树灰元素分析可以确定土壤的起源,有助于野火后的调查. 机器学习准确地区分了土壤类型和Pinus ponderosa灰,证明了它的法医潜力.
科学领域:
- 环境科学 环境科学
- 法医科学 法医科学 法医科学
- 地质化学 地质化学
背景情况:
- 野火在美国西部很普遍,使得火灾后的分析至关重要.
- 从树灰中确定土壤来源是一种新的法医方法.
- 现有的方法缺乏基于灰的土壤识别的强有力的分类.
研究的目的:
- 评估使用元素分析和化学测量的可行性,以确定土壤来自树灰的来源.
- 应用机器学习算法来根据土壤类型和地理来源对Pinus ponderosa灰进行分类.
- 建立一种用于野火后法医分析和环境监测的新方法.
主要方法:
- 在五种不同的土壤类型中种植的树木上的Pinus ponderosa针的基本分析.
- 在受控的实验室条件下干针.
- 化学测量技术的应用,包括预处理和机器学习算法 (例如PLS-DA),用于分类.
主要成果:
- 在Box-Cox转换后使用PLS-DA进行土壤类型识别的高分类准确性 (kappa = 0.98).
- 基于土壤类型和地理位置的灰样本的成功区分.
- 已证明ICP-MS和机器学习在来源确定方面的潜力.
结论:
- 树灰的元素分析与化学测量相结合是确定土壤来源的可行方法.
- 机器学习,特别是PLS-DA,在对法医应用的灰分类中提供了高准确度.
- 需要进一步的研究来解决更广泛的地理应用的变异性.
相关概念视频
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