School of Criminal Sciences, Faculty of Law, University of Lausanne, Batochime, Switzerland.
Forensic Sci Int. 2011 Jun 15;209(1-3):173-82. doi: 10.1016/j.forsciint.2011.01.025. Epub 2011 Feb 25.
The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm(-1) and 2730-3600 cm(-1), provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.
本工作旨在评估化学计量学方法和其他数学处理方法在光谱数据上的应用能力和局限性，特别是在油漆样品上的应用。光谱数据的独特性在于它们是多元的——有几千个变量——且高度相关。统计方法用于研究和区分样品。收集了 34 个红色油漆样品，通过红外和拉曼光谱进行了测量。数据预处理和变量选择表明，使用标准正态变量（SNV），同时通过从 650 到 1830 cm(-1) 和 2730-3600 cm(-1) 选择波长去除噪声变量，可以为红外分析提供最佳结果。然后，主成分分析（PCA）和层次聚类分析（HCA）被用作探索性技术，以提供数据、聚类或检测异常值结构的证据。使用 FTIR 光谱，主成分（PCs）对应于粘合剂类型和碳酸钙的存在/不存在。前四个 PCs 解释了总方差的 83%。对于拉曼光谱，当绘制前两个 PCs 时，我们观察到六个不同的聚类，分别对应于不同的颜料成分，它们分别占总方差的 37%和 20%。总之，化学计量学在油漆的法医学分析中的应用为客观决策提供了有价值的工具，可以减少可能的分类错误，并提高效率，具有节省时间的数据处理的稳健结果。
