Gasoline discrimination using infrared spectroscopy and virtual samples based on measurement uncertainty.

In a previous work, we proposed a methodology for pair-wise discrimination of gasoline samples by creating virtual samples based on physicochemical assays or distillation curves. Satisfactory results were achieved, although specialist and specific apparatus (not commonly available at police laboratories) were required. The present study goes a step further and for the first time investigates the possibility of infrared (IR) spectroscopy to enable a virtual samples-based methodology for comparison of gasoline samples in pairs. IR spectroscopy feasibility for in situ applications is attractive for forensic investigations. The performances of one handheld NIR device and one dual-range (FT-NIR and FT-IR) benchtop spectrometer were evaluated. The estimation of uncertainty in infrared spectral measurement (needed to generate virtual samples) is barely discussed in literature. So far, there are no literature reports describing quantification and comparison of measurement uncertainties for the spectral acquisitions evaluated here, especially regarding their use for generating virtual samples. A stepwise procedure to quantify uncertainties associated with IR spectral acquisition, at each wavenumber, is described. This method can be useful for understanding both the sources of variability in IR measurements and the system under investigation. Uncertainty estimation was based on experimental data and considered intermediate precision, repeatability and variations in sample temperature as sources of variability. Virtual samples were employed in a discrimination approach using SIMCA models. Results for portable NIR, FT-NIR and FT-IR data sets showed complete discrimination for 96.3%, 93.4% and 93.7% of the 1431 pairs of gasoline samples evaluated, respectively. These results were comparable and similar to those obtained for the physicochemical properties data set (95.7%), although slightly inferior to the result obtained for distillation curves (99.2%). Using IR non-destructive methods in this case could enable faster investigations and simpler analysis, especially for the low-cost handheld spectrometer. In a screening approach, atmospheric distillation assays can be employed only if infrared techniques are not capable of distinguishing the samples subject to comparison. In this work, a pair of samples was considered to be completely discriminated only when a null false positive error (FPR) was achieved, although a more flexible criterium may be acceptable in practice. Finally, the methodology could be extended to other applications where sample comparison is important.

Raman hyperspectral imaging and a novel approach for objective determination of the order of crossing ink lines.

The determination of the chronological order of crossing ink lines is a difficult problem in the examination of Questioned Documents. Modern methodologies are based on non-destructive chemical and physical analysis. However, the determination of the chronological sequence of crossing ink lines remains visual and subjective. This manuscript describes a study where Raman hyperspectral imaging is associated with different chemometric techniques and a novel method is applied for the objective determination of the chronological order of gel pen ink crossings. Eight blue and black gel pens of different brands were used to prepare 56 crossings on white paper. Raman mapping analyzed the entire crossing and the hyperspectral images were treated with k-means, Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS) and Partial Least Squares - Discriminant Analysis (PLS-DA). The order of crossings was determined visually and using a novel method that consisted in calculating the relative quantity of pixels of each ink in the crossing region that were equal or higher than an established threshold. Different thresholds were tested using mean and standard deviation. The MCR-ALS and the thresholds mean minus 1,96 of the standard deviation and the mean minus 2575 of the standard deviation determined correctly more than 70% of the crossings. This method proved to be more efficient than microscopy examination and more objective since no inconclusive determinations were obtained. The methodology is promising for entirely objective and highly effective determination of the chronological sequence of crossing ink lines.

Evaluating the potential of near infrared hyperspectral imaging associated with multivariate data analysis for examining crossing ink lines.

The determination of the chronological sequence of crossing ink lines is a recurrent issue in the forensic examination of questioned documents. This manuscript intends to evaluate the potential of hyperspectral imaging in the near infrared range (HSI-NIR) combined with multivariate data analysis for rapid, objective and nondestructive analysis of crossing ink lines made with black pens. Twenty-one black gel and ballpoint pens from different brands and models were employed to prepare crossing combinations in both orders in white office paper. An initial pre-selection and extraction step using the Principal Components Analysis (PCA) scores plot arranged as histograms was necessary for extracting the inks spectra. Then, Partial Least Squares-Discriminant Analysis (PLS-DA) was applied for selection of the most important variables. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) in the augmented form was performed using both the raw and the pre-processed spectra. However, the pre-processing of spectra resulted in incorrect identification of pixels in the inks distribution maps. The MCR-ALS results obtained using the raw spectra allowed the correct determination of the order of crossings in only one pair of gel-gel pen crossings. The remainder were either impossible to discriminate ink from paper or the skipping of one pen ink line led to incorrect determinations in one of the orders. In spite of the practical advantages of the HSI-NIR for document examination and the different chemometric approaches considered for surpassing some of the spectral limitations, the results obtained demonstrate the difficulties of using this technology for application in real forensic cases.

Determination of detergent and dispensant additives in gasoline by ring-oven and near infrared hypespectral imaging.

A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.