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- W1972286681 abstract "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 N ew J ersey in both the summer and fall seasons. Each sample was examined using particle‐size distribution, p H analysis in both water and 1 M CaCl 2 , 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 M ahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications." @default.
- W1972286681 created "2016-06-24" @default.
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- W1972286681 date "2014-02-06" @default.
- W1972286681 modified "2023-10-02" @default.
- W1972286681 title "Comparative Forensic Soil Analysis of New Jersey State Parks Using a Combination of Simple Techniques with Multivariate Statistics<sup>,</sup>" @default.
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- W1972286681 doi "https://doi.org/10.1111/1556-4029.12375" @default.
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