Chemical analysis of polymers used for 3D printing of firearms.

3D-printed firearms cause challenges in criminal investigations and forensic analysis because they are difficult to trace. Indeed, in addition to being "ghost guns", they may not produce all the conventional ballistic traces normally used for firearm identification. However, 3D-printed firearms produce other very specific traces, such as polymer traces which come from the polymers used to print the firearm. To date, only a few studies have focused on the analysis of polymer traces. This study therefore aims to characterize polymer traces from 3D-printed firearms, using non-destructive spectroscopic techniques readily available in most forensic laboratories (i.e., FTIR and Raman) and evaluate the potential for association of polymer specimens or traces with their source. To do so, the study was divided into four parts. First, the population study conducted among 3D printing companies and individuals practicing 3D printing has revealed that PLA and PLA+ are the most widely used polymer types in Quebec, Canada. Second, FTIR and Raman spectroscopic analysis of polymer samples collected during the population study has allowed the development of a reference polymer spectral database. The analysis and interpretation of these spectra revealed that polymer filaments present very low intravariability, but very high intervariability, due in part to the different polymer types and the pigments used to color them. The use of chemometric tools with the spectra showed that these two spectroscopic methods were highly discriminating. Third, test firing of 3D-printed firearms has allowed for the simulation of a scene involving this type of firearm and the collection of polymer traces generated. Fourth, the comparison of chemical signatures between polymer filaments and polymer traces has allowed for the evaluation of the potential for chemical association. This study highlights the added value of chemical analysis of 3D-printed firearms polymer traces in a criminal investigation by demonstrating that polymer filaments, the polymer from which a 3D-printed firearm is made, as well as polymer traces generated during firing, can be linked chemically and provide relevant information.

Validation of Mitra® VAMS® as a blood collection technique for trace elements analysis using ICP-MS/MS.

Background: Clinical dosage of toxic and essential elements in blood is well established and the collection method is still by venipuncture. This method has drawbacks and is not suited for everyone. Volumetric absorptive microsampling (VAMS) has been shown to have advantages over venipuncture. Materials & methods: Using inductively coupled plasma tandem mass spectrometry, a method for quantifying elements in whole blood sampled on VAMS was developed/validated. Method's performance was assessed by comparison with whole blood results. Results: Validation and performance assessment tests tend to show that most of the targeted elements provides accurate and reproducible results comparing to a method of reference. Conclusion: Overall, VAMS presents good preliminary results to eventually become an alternative to venipuncture for blood sampling for some trace elements analysis purposes.

On-site drug detection coasters: An inadequate tool to screen for GHB and ketamine in beverages.

With drug facilitated sexual assault (DFSA) being alleged in 15-20 % of sexual assault cases, drink spiking is a serious concern for several people, casting doubts over the expected safety at events in public spaces. On-site drug testing material is often touted as a solution, allowing attendees to test their drinks for the presence of certain so-called "date-rape drugs". In this manuscript, we aim to evaluate the efficiency of such a coaster device, manufactured by Drink Safe Technologies (Tallahassee, Florida, United States) and sold by Alco Prevention Canada (Laval, Québec, Canada), in detecting drink spiking by GHB and ketamine. From the onset, several generic arguments call into question the practicality of the test: limitations set by the manufacturer on drinks that can be tested, cost, waiting time, interpretation in suboptimal lighting and elevated limits of detection (LODs) compared to a standard recreational or impairing dose. More importantly, the test simply isn't effective at detecting the targeted drugs. The GHB test reagent was identified as bromocresol green using surface-enhanced Raman spectroscopy (SERS). Therefore, it does not detect GHB, but any matrix with a pH higher than 5.5. The ketamine test reagent was identified as cobalt thiocyanate, a non-specific chemical commonly used in colorimetric drug testing. Performance tests were carried with more than 22 drug-free and drug-spiked (≥125 % of the LOD) matrices, including solvent solutions (water, methanol), fixed pH solutions, and an array of popular drinks (including wine, beer, cocktails and spirits). While specificity in drug-free drinks was 100 % for both GHB and ketamine, provided that the manufacturer's limitations on drinks were respected, sensitivity in drug spiked drinks (at 150 % of the LOD) was 0 % for ketamine and between 31 % and 69 % for GHB, depending on whether one classifies inconclusive results as negatives or positives. We conclude that these coasters are an inadequate tool to screen for GHB and ketamine in beverages.

Recycled paints: Are they as variable as they seem?

Several paint companies recently included a range of recycled paints among their proposed products. These are produced from recovered waste and mixed according to their main binders and colors to produce new batches of lower quality at lower cost. As they are relatively new to the market, no comparative study of their differentiation has yet been realized. We therefore collected different production batches of recycled paints of 7 different colors (white, off-white, blue, green, yellow, gray and brown). The paints were analyzed optically, by microscopy, infrared and raman spectroscopy and pyrolysis GC/MS. The intended goal was to verify if the common knowledge about paint frequencies and discriminating power of analytical techniques still apply to recycled paints. We have observed that microscopy (presence of colored spots) and Pyrolysis GC/MS (high discriminating power) were the recommended techniques to discriminate between production batches. These differences were less pronounced in Infrared and Raman analysis, which on the other hand represent an average spectrum of the most frequent compounds mixed together. While the composition of the main components is statistically stable and reflects the most common binders and extenders used in paint within a population, the minor components are much more variable and provide an almost unique signature to each of the recycled paints, better recognized by Pyrolysis GC/MS than Infrared and Raman spectroscopies.

Collecting data on textiles from the internet using web crawling and web scraping tools.

Fibre population surveys are a necessary part of the forensic fibres examination field. They provide valuable information as to which fibres are the most popular and help estimate the likelihood of observing similar properties in a fibre unrelated to the event. The time needed to carry these types of studies is however a major obstacle to wider use. With the advent of e-commerce and digital computation, collecting information from digital sources and structuring it in a convenient way may provide meaningful information on fibres population. It has become more affordable for researchers who can now devote most of their time to extracting meaningful information from the structured data. In this article, we have used a scrapy and kibana/elastic search interface to crawl and scrape a major online clothes retailer. In less than 24 h we have extracted 68 text-based field describing a total of 24,701 clothes to help provide precise estimations of fibres types and color frequencies. We were able to provide data that cotton, polyester, viscose and elastane are the 4 main types of fibres used in the textile industry. Elastane, while being very popular in garments, rarely accounts for more than 10% of the mass while cotton accounts for up to 80% of content. The most common colors are white, black, and blue, with important dependencies to the fibre type. Through further statistics and examples we demonstrate that web scraping techniques have the potential to provide near real-time population studies that can greatly benefit forensic practitioners.

Differential shedding: A study of the fiber transfer mechanisms of blended cotton and polyester textiles.

One of the primary interests of forensic sciences is the study of traces, better conceived as silent witnesses to criminal activity whose existence is attributable to Locard's principle. Thus, textile fibers are commonly exploited as they are easily transferred during contact which can vary in intensity depending upon the type of activity that occurred. Regardless, current knowledge pertaining to fiber transfer mechanisms, particularly in regards to blended textiles, is limited. It is recognized that the intensity of the contact, the type of textile as well as the size and type of fibers composing it have a significant influence on the amount of fibers transferred. However, when the donor textile is blended (eg. 50% cotton, 50% polyester), it often happens that one of the two types of fibers is transferred in greater proportion to the receiving surface (eg. 80% cotton and 20% polyester). The percentages indicated on the manufactured label are however not representative of the respective proportions (based on the number of fibers) of each type of fiber composing the fabric, but rather the weight of each respective type of fiber used to fabricate the garment. Therefore, the amount of collected fibers (traces) cannot be easily correlated to the proportions indicated on the manufactured label used to describe the textile. The objective of this study was to test the transfer capacities of blended textiles of different cotton and polyester proportions by performing several simulations under controlled conditions (i.e. contact between two textiles with a constant force and speed). The results were then correlated to the fiber type, morphology, and size. Overall, the project contributes to improving the comprehension of fiber transfer mechanisms, and provides insight on the quantity and the proportions of fibers capable of being transferred between the donor and the recipient textiles following a specific type of action and contact (legitimate or otherwise).

Distribution of aerosol paint droplets in open- and closed-space environments: Towards activity level evaluation.

One way to determine the presence of a suspect on the scene of graffiti sprayed public territory, is by seeking the presence of aerosol paint droplets transferred to his clothing and accessories. Previous studies have evaluated the distribution of spray paint droplets in closed space, on clothing, and its persistence following washing. Yet, due to the difficulty in observing and counting them under a stereomicroscope, the previous studies had to limit the tests conducted and limit the amount of data collected. In this paper, we perform simulations of spraying using a fluorescent paint and a computer-automated extraction of features and counting of the droplets. With these tools we were able to perform many different tests in a relatively small amount of time and gather data about the density, distribution, and size of the droplets transferred. We discuss the obtained results and hypothesize that such evaluations of the transferred droplets would permit to distinguish between different scenarios at an activity level, such as the presence on the scene as a simple witness or bystander, versus the illicit action of spraying a graffiti or a tag.

Batch-to-batch variation in domestic paints: Insights into the newly commercialized recycled paints.

A few recent studies attempted to evaluate the differentiation of paints at a production batch level and reported results depending largely on the paint type. The discrimination from production batches is much more random than brands and/or models levels and subject to many unknowns, which suggests that a particular production batch can suddenly present a substantially different composition than the one produced right before or right after it. To add to this existing complexity, most of the paint companies now propose a range of recycled paints among their products. These recycled paints are composed of wastes collected by recycling plants, sorted by their color and binder type (i.e. latex, alkyds), and mixed together in large tanks to form the basis material for future formulations. Quality controls on these recycled batches are voluntarily less precise, and a higher variation is expected in esthetic and chemical properties of the paint. In this project, we collaborated with a North American paint producer that gave us access to its samples, paint formulations recipes, and a summary of the quality controls and corrections they performed on each production batches. The whole study was conducted blindfold and a final verification was made with the manufacturer to evaluate the accuracy of the results. The data set comprised two models of regular paints and two models of recycled paint. Five different production batches were collected per model for a total of 20 samples analyzed by Microscopy, Infrared spectroscopy, Raman spectroscopy, and Pyrolysis GC/MS.

Latent Fingermark Imaging by Single-Metal Deposition of Gold Nanoparticles and Surface Enhanced Raman Spectroscopy.

In forensic science, there is a high demand for a technique that allows the revelation of fingermarks invisible to the naked eye as well as the chemical information they contain. Here, we present a feasibility study consisting of using both the luminescence enhanced by surface plasmon of gold nanoparticles, and the surface enhanced Raman spectroscopy signal of fingermark chemical components to image latent fingermarks. A latent fingermark deposited on a transparent glass substrate was visually revealed using single-metal deposition employing gold nanoparticles. The resulting enhanced luminescence was monitored over a developed area of the latent fingermark, displaying light regions of 200-400 µm, corresponding to the fingermark ridges. The Raman signal of the fingermark's chemical components was enhanced into a measurable signal. Imaging those Raman peaks revealed the ridges pattern, attesting to the potential of our method. Since SMD is an end-of-sequence revelation technique for which further enhancement techniques do not exist, this work aims at demonstrating the feasibility of the technique in order to apply it on different systems, able to illuminate a complete surface of a few cm, and thus capable of both detecting contaminants in LFM and imaging features of the size of a complete LFM.

A random object-oriented population study of household paints measured by infrared spectroscopy.

Forensic paint analysis heavily relies on population studies and creation of databases for estimating frequencies of apparition and perform discrimination studies. An important part of the paint market is currently led by household paints, that can be recovered in cases of burglaries of forced entries. Here, we present a database of 166 household paint samples collected at random in a waste recycling plant, and measured by infrared spectroscopy. We provide general demographic information on the paint such as their type, brand, model, and color. Based on their infrared spectra, we present the differentiation among samples and the calculation of the discriminating power for various attributes. We compare our visual discrimination results with a principal component analysis. This study provides valuable information for paint evaluation and association evidence, but will also be used to create a searchable database to tentatively determine the chemical composition, brand, or model of a questionned specimen in absence of reference material.

Contribution of Raman and Surface Enhanced Raman Spectroscopy (SERS) to the analysis of vehicle headlights: Dye(s) characterization.

Although ubiquitous on accident scenes, the polymers from headlight optics are often neglected in hit-and-run cases, and their evidential value restrained to direct comparison once a corresponding vehicle is found. Multilayered automotive paint fragments are preferred for their access to corresponding databases (PDQ, EUCAP) to infer models and brands of cars. The potential of polymers headlights for providing forensic intelligence has never been exploited, principally due to the lack of diversity, of appropriate databases, and of case examples. The motives are very simple however. Headlight polymers suffer from a lack of differentiation, and about 90% of them are composed of polymethylmethacrylate (PMMA). The discriminating powers using techniques in sequence typically range from 30 to 60%. In this paper, we take advantage of the extreme sensitivity of Surface Enhanced Raman Spectroscopy (SERS) to analyze the dye composition of the polymer headlights. The measurements by standard Raman spectroscopy at 488, 633, and 785nm permits us to identify the polymer type with relative ease. 51 out of 53 samples are composed of PMMA, the two remaining being either Polycarbonate or Polybutylene terephthalate. Additionally, using SERS with silver colloids at 488 and 633nm, provides enhanced spectra of the dyes used in the composition with an extreme sensitivity and specificity. With SERS we are able to differentiate the majority of the headlights with a remarkable 90-100% discriminating power. Solvent Orange 60, Solvent Red 52 and Solvent Red 111 were successfully identified as dyes used in the manufacture of the headlights. These results demonstrate that a combined Raman-SERS approach has the potential to replace an otherwise lengthy sequence of many different analytical techniques. With one single instrument, we offer the possibility to combine an analysis of the polymer type, and of the dye components with high discriminating capabilities. These results open up new opportunities for exploiting headlight plastics in road accidents investigations. It has the potential to help in source attribution, and/or database building in a forensic intelligence perspective.

Competitive Binding Investigations and Quantitation in Surface-Enhanced Raman Spectra of Binary Dye Mixtures.

This research presents a study in surface-enhanced Raman quantitation of dyes present in mixtures of alizarin and purpurin using standard calibration curves and Langmuir isotherm calibration models. Investigations of the nature of competitive adsorption onto silver nanoparticles by centrifugation indicates that both dyes in the mixture interact with the nanoparticles simultaneously, but only the stronger adsorbing one is seen to dominate the spectral characteristics. Calibration can be carried out by careful selection of peaks characteristic to each dye in the mixture. Comparisons of peak height and peak area calibrations reveal that peak heights, when selected by the maximum value and accounting for peak shifts, prove the better model for quantitation. It is also shown that the microwave nanoparticle synthesis method produces stable nanoparticles with a shelf-life of at least one year that give very little variation within and between uses.

Towards a validation of surface-enhanced Raman scattering (SERS) for use in forensic science: repeatability and reproducibility experiments.

In order for a new analytical technique such as surface-enhanced Raman scattering (SERS) to be used in a routine manner, data and studies on the validation of the method are required. In that context, we performed a systematic study of the variability observed at different levels of the analytical procedure (i.e. respectively measurement, sampling, colloids aliquots, colloids batches, laboratories). Our goal is to provide data towards a qualitative validation of the technique for identification purposes. Three molecules of forensic interest were used as probes, respectively crystal violet, methamphetamine and 2,4,6-trinitrotoluene (TNT). We demonstrate that the method is repeatable with RSD and multivariate techniques (PCA). The % RSD at the different analytical stages vary between the molecules and the peaks considered. The repeatability is on the order of 2-6% for crystal violet, and 5-16% for TNT. Methamphetamine binds very weakly to the silver colloids giving much greater variability in the measurements (5-29%). We show that spectra measured in the same conditions (e.g. same laboratory and instrument), even a few days apart, are comparable and stable. The largest source of variation has been identified to be the measurement conditions and the associated random fluctuations in intensity (i.e. Brownian motion of the particles, solvent evaporation and concentration). The influence of the substrate is confirmed to be negligible. However, the reproducibility between different laboratories and different instruments introduced the largest source of variability (∼ 10-70%). Despite these factors, we demonstrate that qualitative identification of the species under analysis by measurement and comparison of peaks position is always successful even though quantitative analysis is, at present, difficult. Regardless of the amount of variability determined, the molecules could always be successfully identified, even on different instruments from different laboratories by utilizing the criterion proposed in the literature (i.e. 3:1 signal-to-noise ratio).

Combining spectroscopic data in the forensic analysis of paint: Application of a multiblock technique as chemometric tool.

A study (Muehlethaler et al. [9]) has demonstrated the application of chemometrics for the analysis of domestic red paints. The paints have been analyzed with IR and Raman spectroscopies. As a result of these analyses, exploratory techniques, such as principal component analysis (PCA) and hierarchical clusters analysis (HCA) have been applied to both IR and Raman spectra. This allowed to observe the structure of the data among those red paints, and infer potential groups among them and to propose a classification model based on their chemical composition. IR spectroscopy showed group patterns related mainly to the binder and extender composition of the paints, whereas Raman spectroscopy data were mainly related to the pigment composition. The aim of the present study is to evaluate the potential of a Multiblock algorithm applied to the same data set. The concept of Multiblock, as a chemometric tool, is to combine data from several different analytical techniques in order to visualize most of the information at once. IR and Raman spectroscopy are then considered as "blocks" of data of the same dataset. One algorithm called common component and specific weight analysis (CCSWA) has been used in order to produce independent PCAs for each block, and the combined (common) information in a score plot. The results of this study showed group patterns of the analyzed paints, related to both binder and pigment compositions in one single score plot. Moreover, the number of groups observed with the multiblock representation (20 groups) is higher than independent PCAs projections (12 and 7 groups for IR and Raman respectively). This new application of chemometrics showed a great potential in forensic science, as practitioners often use a combination of several analytical techniques in order to characterize samples. This could be helpful when multiple and complementary analytical techniques are used in order to characterize and compare paint samples.

Evaluation of infrared spectra analyses using a likelihood ratio approach: A practical example of spray paint examination.

Depending on the forensic disciplines and on the analytical techniques used, Bayesian methods of evaluation have been applied both as a two-step approach (first comparison, then evaluation) and as a continuous approach (comparison and evaluation in one step). However in order to use the continuous approach, the measurements have to be reliably summarized as a numerical value linked to the property of interest, which occurrence can be determined (e.g., refractive index measurement of glass samples). For paint traces analyzed by Fourier transform infrared spectroscopy (FTIR) however, the statistical comparison of the spectra is generally done by a similarity measure (e.g., Pearson correlation, Euclidean distance). Although useful, these measures cannot be directly associated to frequencies of occurrence of the chemical composition (binders, extenders, pigments). The continuous approach as described above is not possible, and a two-step evaluation, 1) comparison of the spectra and 2) evaluation of the results, is therefore the common practice reported in most of the laboratories. Derived from a practical question that arose during casework, a way of integrating the similarity measure between spectra into a continuous likelihood ratio formula was explored. This article proposes the use of a likelihood ratio approach with the similarity measure of infrared spectra of spray paints based on distributions of sub-populations given by the color and composition of spray paint cans. Taking into account not only the rarity of paint composition, but also the "quality" of the analytical match provides a more balanced evaluation given source or activity level propositions. We will demonstrate also that a joint statistical-expertal methodology allows for a more transparent evaluation of the results and makes a better use of current knowledge.

Forensic aspects of the weathering and ageing of spray paints.

This paper presents a preliminary study on the degradation of spray paint samples, illustrated by Optical, FTIR and Raman measurements. As opposed to automotive paints which are specifically designed for improved outdoor exposure and protected using hindered amine light absorbers (HALS) and ultra-violet absorbers (UVA), the spray paints on their side are much simpler in composition and very likely to suffer more from joint effects of solar radiation, temperature and humidity. Six different spray paint were exposed to outdoor UV-radiation for a total period of three months and both FTIR and Raman measurements were taken systematically during this time. These results were later compared to an artificial degradation using a climate chamber. For infrared spectroscopy, degradation curves were plotted using the photo-oxidation index (POI), and could be successfully approximated with a logarithmic fitting (R(2)>0.8). The degradation can appear after the first few days of exposure and be important until 2 months, where it stabilizes and follow a more linear trend afterwards. One advantage is that the degradation products appeared almost exclusively at the far end (∼3000cm(-1)) of mid-infrared spectra, and that the fingerprint region of the spectra remained stable over the studied period of time. Raman results suggest that the pigments on the other side, are much more stable and have not shown any sign of degradation over the time of this study. Considering the forensic implications of this environmental degradation, care should be taken when comparing samples if weathering is an option (e.g. an exposed graffiti compared to the paint from a fresh spray paint can). Degradation issues should be kept in mind as they may induce significant differences between paint samples of common origin.

Discrimination and classification of FTIR spectra of red, blue and green spray paints using a multivariate statistical approach.

The use of multivariate techniques was investigated in a forensic paint analysis context. The data set consisted of the infrared spectra of 74 spray paint cans, corresponding to three colors code, respectively red, green and blue. Two aspects of the forensic procedure are studied, respectively, the discrimination of paints coming from a market study through exploratory techniques, and the source prediction of unknown samples in database using classifiers. The exploratory discrimination capabilities of principal component analysis (PCA) and hierarchical clusters analysis (HCA) were compared to a visual comparison of the spectra. Iterative PCA was found to be the most adapted solution for exploratory analysis of the samples. Very few differences were found compared to a visual comparison of the samples and the statistical foundations behind the method ensure that no errors are due to a misclassification of the samples. Market studies and joint PCA also represent a significant gain of time. Following that, classification and prediction of future samples were evaluated by means of supervised techniques of classification such as linear/quadratic discriminant analysis (LDA/QDA), support vector machines (SVM), soft independent modeling of classes analogies (SIMCA) and partial least squares discriminant analysis (PLS-DA). SIMCA was the preferred method, as it provided the smallest false negative rates together with a correct classification rate of about 95%. From an investigative point-of-view the presence of false positives was considered acceptable, as it is preferable to have a longer list of possible sources but have confidence that the true source belongs to it.

Influence of the shaking time on the forensic analysis of FTIR and Raman spectra of spray paints.

In order to decide if replicated measurements of a trace fall within the intra-variability expected for reference paint samples, a forensic scientist has to understand and integrate all reasonable sources of variation. The origins of such variation in spectra can be various, but mainly include differences in components distribution (homogeneity of spraying) or differences originating from the manufacturing process (production batches). Instrumental variation can also be problematic for non-successive measurements. Infrared and Raman spectra were collected to study the homogeneity of the paint distribution after shaking a spray can for times of 0, 1, 2, 3, 4 and 5min. The results confirm that differences arise in both the spectroscopic techniques used in this study. Mainly, this survey shows that the problematic of shaking is particularly important when the pigment content can be detected from spray paint samples within the infrared domain. In these situations, the signal from the pigment might produce strong absorptions that vary with shaking time, leading to differences in relative intensities with respect to those attributed to the binder. For Raman spectroscopy, it has been shown that a gradient of pigment concentration is observable in some samples depending on the shaking time. The proportion of the signal due to the pigment increases with shaking times from 0 to 1min and diminishes afterwards, to finally reach stabilization around 3min of shaking. Not all samples are affected by these differences and it should always be evaluated on a case-by-case basis. From a statistical point-of-view, principal component analyses of the replicates show that the spectra are reproducible after 3min of shaking.

Survey on batch-to-batch variation in spray paints: a collaborative study.

This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (CH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.