Nespeca Maurilio Gustavo, Hatanaka Rafael Rodrigues, Flumignan Danilo Luiz, de Oliveira José Eduardo
Centro de Monitoramento e Pesquisa da Qualidade de Combustíveis, Biocombustíveis, Petróleo e Derivados (Cempeqc), São Paulo State University (UNESP), R. Prof. Francisco Degni 55 Quitandinha, 14800-900 Araraquara, SP, Brazil.
Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP), Campus Matão, Rua Estéfano D'avassi, 625 Nova Cidade, 15991-502 Matão, SP, Brazil.
J Anal Methods Chem. 2018 Feb 5;2018:1795624. doi: 10.1155/2018/1795624. eCollection 2018.
Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000-650 cm. The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time.
柴油质量评估对社会来说非常必要，但使用标准方法时成本和耗时都很高。因此，本研究旨在开发一种分析方法，能够通过衰减全反射傅里叶变换红外（ATR - FTIR）光谱法和多元回归方法——偏最小二乘法（PLS），同时测定八个柴油质量参数（密度、闪点、总硫含量、10%（T10）、50%（T50）和85%（T85）回收温度下的蒸馏温度、十六烷指数和生物柴油含量）。为此，使用标准方法测定了409个样品的质量参数，并在4000 - 650 cm范围内采集了它们的光谱。评估了使用多元滤波器、广义最小二乘加权（GLSW）和正交信号校正（OSC）来提高模型的信噪比。同样，测试了四种变量选择方法：手动排除、前向间隔PLS（FiPLS）、后向间隔PLS（BiPLS）和遗传算法（GA）。多元滤波器和变量选择算法生成了更拟合、更准确的PLS模型。根据验证，FTIR/PLS模型的准确性与参考方法相当，因此，所提出的方法可应用于柴油常规监测，以显著降低成本和分析时间。
