Discrimination of soil samples using X-ray fluorescence combined with multivariate statistical tools

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Research Articles | Published:

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DOI: 10.1007/s42535-025-01539-w
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Keywords: Soil, Forensic, XRF, HCA, PCA, Discrimination


Abstract


Forensic soil analysis aims to identify the variations and source of origin of soil samples. This holds significant relevance for forensic geologists who investigate soil-related evidence. A total of 58 composite samples, 29 soil samples from the top surface and 29 from the depth surface samples were collected from different regions of Haryana, India. Various elements and their weight percentages were analysed by X-ray fluorescence (XRF). Multivariate statistical tools such as hierarchical clustering analysis (HCA) and principal component analysis (PCA) were performed to discriminate and classify soil samples. These statistical methods provided discrimination powers of 82.2% and 94.8% for top-surface soil samples, and 83.4% and 99.2% for depth samples, respectively. Among both methods, PCA offered clear discrimination of the soil samples. The findings demonstrated that elemental composition can effectively distinguish different soil types and trace their origins.

Soil, Forensic, XRF, HCA, PCA, Discrimination


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Author Information


RFSL, Sunaria, Rohtak, India