This work introduces a rapid and effective technique for the discrimination of smears of colored wax-based products (e.g., lipstick and shoe polish) on fabrics. Forty-two samples of commonly available wax-based products were analyzed. The analytical technique used was a combination of thin-layer chromatography (TLC) and direct microspectrophotometry (MSP) of the subsequent TLC plate. The resultant data was analyzed using self-organizing feature mapping (SOFM), an artificial neural network system. The combination of TLC and MSP facilitated the discrimination of all samples, and the SOFM system provided an easy-to-understand visual representation of the sample discrimination by type.
|Number of pages||11|
|Journal||Journal of Forensic Identification|
|Publication status||Published - Mar 2011|