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Comparison of Microspectrophotometry and Room-Temperature Fluorescence Excitation-Emission Matrix Spectroscopy for Non-Destructive Forensic Fiber Examination

NCJ Number
Andres D. Campiglia; Michael E. Sigman
Date Published
January 2015
21 pages
The key objectives of this research project were 1) to provide a rigorous statistical approach for the comparison of microspectrophotometry (MSP) and fluorescence microspectrophotometry (F-MSP) for the analysis of fibers of questioned and known origin; 2) to explore the potential of fluorescence spectroscopy based on data formats known as excitation emission matrices (EEMs); and 3) to investigate spectral changes that might occur in textile fibers as a result of exposure to environmental conditions.

When spectral information is used in the study of fiber evidence, variations within a fiber source lead to the recommendation that multiple spectra be collected from each fiber to properly characterize the sample. A positive association is determined when the questioned spectrum is consistent in all intensity values to at least one of the known spectra, and exclusion is determined when either the suspect spectrum is totally different to that of any known fiber, or it falls outside the range produced by the known spectra. Although this methodology is sufficient for comparison of profiles with obvious differences, the chemometric methods used in the current study show higher accuracies than the visual method commonly used in forensic laboratories. Also, the likelihood ratio method provides for a direct interpretation of the strength of the evidence when predicting a same source or different source conclusion. Current practices in forensic labs that involve fluorescence microscopy do not take advantage of the information content that exists in the spectral signature of textile fibers. The coupling of a microscope to a spectrofluorimeter allows for the acquisition of a complete training set of EEMs for fiber dye identification from an individual fiber. Accounting for the variance of the EEM spectra at different regions along the length of the fiber provides a useful training set that can be used as the basis for principal component cluster analysis. 10 tables and 5 figures