Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

Abstract:

:This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications.

journal_name

J Forensic Sci

authors

Bonetti J,Quarino L

doi

10.1111/1556-4029.12375

subject

Has Abstract

pub_date

2014-05-01 00:00:00

pages

627-36

issue

3

eissn

0022-1198

issn

1556-4029

journal_volume

59

pub_type

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