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A foundational study of fire debris interpretation using quantitative measures of chromatographic features in gasoline and the use of graphical display to demonstrate data sufficiency
Forensic Chemistry ( IF 2.7 ) Pub Date : 2021-03-28 , DOI: 10.1016/j.forc.2021.100337
Brenda Christy , Kelsey Winters , Alexandria Rossheim , Reta Newman , Larry Tang

The analytical process for identifying ignitable liquids is based on fundamental chemical properties; however, the current interpretation of these properties as chromatographic data relies on subjective pattern recognition techniques. The subjectivity of these pattern recognition techniques increases with the presence of complex matrix contribution. To make the fire debris interpretation process more standardized and objective, a novel method is proposed for analyzing fire debris Gas Chromatography-Mass Spectrometry (GC–MS) data using quantitative measures of chromatographic features of interest. These features are represented by peak height ratios observed in the Total Ion Chromatograph and Extracted Ion Profiles.

Chromatographic features of interest in 150 gasoline samples were evaluated and 64 chromatographic peak height ratios were selected for study. Statistical analysis was conducted to determine the variation observed for each of these ratios in the gasoline samples and to determine the frequency of these features in negative matrix samples. This information was evaluated to determine relative significance, as represented by the assigned points for each of these features. When summed and used as plot values, these cumulative scores graphically display the separation of gasoline samples from negative matrix samples using this methodology. The scores were used to create a sufficiency graph, which is a graphical display detailing the totality of data supporting a potential gasoline identification. The sufficiency graph also identifies the “gray” area where analysts are more likely to form differing opinions.

The methodologies introduced are a step toward a documentation process that ensures greater transparency in fire debris examinations and comparisons. The methods generate a quantitative sufficiency graph for consistent data interpretation and documentation.



中文翻译:

使用汽油中色谱特征的定量测量和图形显示来证明数据充分性,从而对火残渣进行解释的基础研究

识别可燃液体的分析过程基于基本化学性质;但是,当前对这些特性作为色谱数据的解释依赖于主观模式识别技术。这些模式识别技术的主观性随着复杂矩阵贡献的存在而增加。为了使火灾碎片的解释过程更加规范和客观,提出了一种使用感兴趣的色谱特征的定量方法来分析火灾碎片的气相色谱-质谱(GC-MS)数据的新方法。这些特征由在总离子色谱仪和提取的离子分布图中观察到的峰高比表示。

对150个汽油样品中感兴趣的色谱特征进行了评估,并选择了64个色谱峰高比进行研究。进行统计分析以确定在汽油样品中每种比率所观察到的变化,并确定负矩阵样品中这些特征的频率。对这些信息进行评估以确定相对重要性,以这些特征中每个特征的分配点表示。当累加起来并用作绘图值时,这些累积得分将使用这种方法以图形方式显示汽油样品与阴性基质样品的分离程度。分数用于创建充足率图表,该图表是详细显示支持潜在汽油识别的数据总数的图形显示。

引入的方法是朝着文档化过程迈出的一步,该过程可确保火灾碎片检查和比较具有更高的透明度。该方法生成定量的充分性图,以进行一致的数据解释和记录。

更新日期:2021-04-02
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