Abstract
This short communication presents a proper detection of illegal additives in Brazilian S-10/common diesel B7/5 using mid-infrared (MIR) spectroscopy and data driven soft independent modeling of class analogy (DD-SIMCA). The one-class classification chemometric model based on DD-SIMCA with MIR spectroscopic data was applied in the following analytical systems: (a) authentic Brazilian S-10 diesel B7 (BX is the amount of biodiesel blended) used as members of the unique target class and Brazilian S-10 diesel B7 adulterated by residual automotive lubricant oil (RALO) and residual solvent used in a dry wash (RSUDW) as non-members of the target class and (b) authentic Brazilian common diesel B5 used as a unique target class and Brazilian common diesel B5 adulterated by RALO, soybean oil and used frying oil (UFO) and contaminated with gasoline. DD-SIMCA model in data set described in (a) was able to properly classify all samples of Brazilian S-10 diesel B7 adulterated as non-members of the target class in the validation phase with a specificity of 100% and also all samples of authentic Brazilian S-10 diesel B7 were correctly accepted as members of the target class with test sensitivity equal 100%, although in the training phase one of the samples was rejected at 95% tolerance of the acceptance area, achieving training sensitivity equal 95%. In the data set described in (b) the modern DD-SIMCA model also achieved excellent results with 100% training sensitivity, test sensitivity and specificity. Finally, multivariate curve resolution-alternating least-squares (MCR-ALS) with the area correlation constraint and first-order MIR spectroscopic data was able to provide pure profiles such as: (i) concentration profiles allowed to quantify the amount of Jatropha biodiesels added in Brazilian S-10 diesel and (ii) spectral profiles allowed to identify the feedstock used in biodiesel production present in the biodiesel/diesel blend, which can provide further investigation for the European Union during the implementation of EU 2015/1513.
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