Utilizing ICP-OES for Elemental Analysis of Soil Samples in Forensic Science

Soil is a crucial form of physical evidence in forensic investigations. Each type of soil possesses unique characteristics that serve as identifying markers, making it admissible as evidence in a court of law. The trace, major, and minor elements in the soil contribute to a distinctive elemental profile unique to each location. In this research, we aimed to classify and differentiate soil groups using ICP-OES for forensic science purposes. The study analyzed soil samples from various groups, including forest soil, orchard soil, and rice field soil. The results revealed that elements in the Ca, Mg, and Mn groups displayed high standard deviation values, while elements in the Zn, Cr, Cu, and Pb groups demonstrated low standard deviation values. Soil samples from two provinces in the central region of Thailand displayed similar elemental concentrations, whereas samples from the northeastern region showed distinct elemental concentrations compared to those from the central region. However, statistical analysis using one-way ANOVA to compare elemental concentrations across different soil types revealed no significant differences at the 0.05 level among the soil sample groups. Although ICP-OES is highly effective, its application in analyzing soil as chemical evidence may not always yield successful results in a single attempt. Repeated testing is often necessary to identify the most appropriate elements. It is recommended to examine the area's conditions and data on soil usage in the location where soil evidence is collected for comparison before selecting elements for analysis, as this helps minimize costs and save time.

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Publication Details

Journal
SWU eJournals System (Srinakharinwirot University)
Published
2024-12-28
Primary Topic
Laser Design and Applications
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article
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article

Utilizing ICP-OES for Elemental Analysis of Soil Samples in Forensic Science

SWU eJournals System (Srinakharinwirot University)
Laser Design and Applications
article

Utilizing ICP-OES for Elemental Analysis of Soil Samples in Forensic Science

article en

Abstract

Soil is a crucial form of physical evidence in forensic investigations. Each type of soil possesses unique characteristics that serve as identifying markers, making it admissible as evidence in a court of law. The trace, major, and minor elements in the soil contribute to a distinctive elemental profile unique to each location. In this research, we aimed to classify and differentiate soil groups using ICP-OES for forensic science purposes. The study analyzed soil samples from various groups, including forest soil, orchard soil, and rice field soil. The results revealed that elements in the Ca, Mg, and Mn groups displayed high standard deviation values, while elements in the Zn, Cr, Cu, and Pb groups demonstrated low standard deviation values. Soil samples from two provinces in the central region of Thailand displayed similar elemental concentrations, whereas samples from the northeastern region showed distinct elemental concentrations compared to those from the central region. However, statistical analysis using one-way ANOVA to compare elemental concentrations across different soil types revealed no significant differences at the 0.05 level among the soil sample groups. Although ICP-OES is highly effective, its application in analyzing soil as chemical evidence may not always yield successful results in a single attempt. Repeated testing is often necessary to identify the most appropriate elements. It is recommended to examine the area's conditions and data on soil usage in the location where soil evidence is collected for comparison before selecting elements for analysis, as this helps minimize costs and save time.

SWU eJournals System (Srinakharinwirot University)
Suan Dusit University (TH), Suan Sunandha Rajabhat University (TH)
Openalex Percentile: Top 61%
Laser Design and Applications
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Utilizing ICP-OES for Elemental Analysis of Soil Samples in Forensic Science · SWU eJournals System (Srinakharinwirot University) (2024) | TGRS Research Map | TGRS