Fast profiling of cocaine seizures by FTIR spectroscopy and GC-MS analysis of minor alkaloids and residual solvents.

In this study, samples coming from large seizures of cocaine which took place in Italian Customs areas during 2011 and 2012 were examined. Minor alkaloids and residual solvents, analyzed by gas chromatography-mass spectrometry (GC-MS) and head space (HS)-GC-MS, respectively, were processed by principal component analysis (PCA), highlighting groupings of samples according to their chemical similarity. A hypothesis about the geographical origin of samples was also provided: most of them were compatible with Colombia as country of origin. Results of these analyses were used as starting point for the development of a "fast profiling" method, based on Fourier transform infrared spectroscopy (FTIR) and chemometric tools. Two models were developed and compared: KBr-FTIR and attenuated total reflection (ATR)-FTIR for comparative analysis of pure samples. Linear discriminant analysis (LDA) was applied to the model based on ATR-FTIR spectroscopy, obtaining a classification and a prediction ability both of 97.56% for pure samples. Finally, "cut" samples were tested as an external test set, and the assignment class provided by LDA was compared with results obtained by the analyses of alkaloids and residual solvents: in the case of samples added with only one substance, prediction errors began to occur for percentages of cocaine lower than 50%.

Origin assessment of EV olive oils by esterified sterols analysis.

In this study extra virgin olive oils of Italian and non-Italian origin (from Spain, Tunisia and blends of EU origin) were differentiated by GC-FID analysis of sterols and esterified sterols followed by chemometric tools. PCA allowed to highlight the high significance of esterified sterols to characterise extra virgin olive oils in relation to their origin. SIMCA provided a sensitivity and specificity of 94.39% and 91.59% respectively; furthermore, an external set of 54 extra virgin olive oils bearing a designation of Italian origin on the labelling was tested by SIMCA. Prediction results were also compared with organoleptic assessment. Finally, the poor correlation found between ethylesters and esterified sterols allowed to hazard the guess, worthy of further investigations, that esterified sterols may prove to be promising in studies of geographical discrimination: indeed they appear to be independent of those factors causing the formation of ethyl esters and related to olive oil production.

Identification of two cannabimimetic compounds WIN48098 and AM679 in illegal products.

Two synthetic cannabinoids have been identified, during a survey, as new adulterants; they might have been intended to be used as ingredients for smart drugs. The characterization of these compounds has been made by gas chromatography-mass spectrometry (GC-MS), Orbitrap high resolution mass spectrometry (HRMS) and nuclear magnetic resonance (NMR), leading to the identification of WIN48098, a compound disclosed as a new adulterant in herbal and powder products, and AM679, identified in Italy for the first time. Taking into account the high number of synthetic cannabinoids seized during the last year in Italy, how quickly they appear on the illegal market and the rapidity required for analytical results, a method was developed for the simultaneous quantitation of several synthetic cannabinoids, using gas chromatography-flame ionization detection (GC-FID).

Differentiation of unevaporated gasoline samples according to their brands, by SPME-GC-MS and multivariate statistical analysis.

One of the aims of fire investigations is to identify associations among accelerants according to their source. In this study, 50 gasoline samples--representing five brands--were analyzed using solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS). Chemometric procedures, such as principal component analysis (PCA) and discriminant analysis (DA), were applied to a data matrix obtained by the target compound chromatogram method, to discriminate samples according to their brand. PCA was successful in finding a natural grouping of samples according to their brand, suggesting that aromatic compounds were more useful than aliphatics for the purpose of this study. DA, if applied to aromatic compounds, gave both a classification ability and a prediction ability of 100%. The outstanding results obtained by this work provide the basis of a data matrix that could be used in real cases of arson to link a sample of unevaporated gasoline to its brand or refinery.