Monfreda Maria, Varani Francesco, Cattaruzza Fabrizio, Ciambrone Simona, Proposito Alessandro
Central Directorate for Product Analysis and Chemical Laboratories, Italian Customs and Monopolies Agency, via M. Carucci 71, 00143 Rome, Italy.
Central Directorate for Product Analysis and Chemical Laboratories, Italian Customs and Monopolies Agency, via M. Carucci 71, 00143 Rome, Italy.
Sci Justice. 2015 Dec;55(6):456-66. doi: 10.1016/j.scijus.2015.06.002. Epub 2015 Jun 16.
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%.
在本研究中，对2011年和2012年意大利海关区域内查获的大量可卡因样本进行了检测。分别通过气相色谱 - 质谱联用（GC - MS）和顶空（HS）-GC - MS分析的次要生物碱和残留溶剂，采用主成分分析（PCA）进行处理，根据样本的化学相似性突出显示样本分组情况。还提供了关于样本地理来源的假设：其中大多数样本的来源国与哥伦比亚相符。这些分析结果被用作开发基于傅里叶变换红外光谱（FTIR）和化学计量工具的“快速剖析”方法的起点。开发并比较了两种模型：用于纯样本比较分析的KBr - FTIR和衰减全反射（ATR）-FTIR。将线性判别分析（LDA）应用于基于ATR - FTIR光谱的模型，对于纯样本，分类和预测能力均达到97.56%。最后，对“切割”样本作为外部测试集进行测试，并将LDA提供的分类结果与生物碱和残留溶剂分析获得的结果进行比较：在仅添加一种物质的样本中，当可卡因含量低于50%时开始出现预测误差。
