Biodiesel/Diesel Blends Classification with Respect to Base Oil Using NIR Spectrometry and Chemometrics Tools

Abstract

In this work, rapid and non-destructive methodology is proposed for screening of biodiesel/diesel blends with respect to the base oil, using near infrared spectroscopy and multivariate data analysis, since for both pure biodiesel and blends, the biodiesel/diesel are targets for tampering. Blends of diesel with cotton, sunflower and soybean oils were employed in this study. Two approaches were evaluated in the building of the classification model, using full-spectrum Soft Independent Modelling of Class Analogy (SIMCA), and Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA). The other approaches were the use of variable selection employing Genetic Algorithm (GA), Successive Projection Algorithm (SPA) and Stepwise all coupled with the LDA model. The results showed which preprocessed NIR spectra and chemometrics are a viable alternative the conventional methods that involve the consumption of large volumes of reagents. Multivariate data analysis methods using selected variables showed a better performance than the methods using a full spectrum.

Identification of biodiesel feedstock in biodiesel/diesel blends using digital images and chemometric methods

“…Recently, instrumental methods using near infrared (NIR) spectroscopy, 9 gas chromatography coupled with mass spectroscopy (CG-MS) 10 and mid-infrared (MIR) spectroscopy 11 have been employed to identify the biodiesel feedstock in biodiesel/diesel blends. However, the acquisition and/or maintenance of these instruments have a high cost, besides requiring trained analysts.…”

Chemometric approaches to resolving base oil mixtures

“…The chemometric analysis of base oils has been addressed in the literature; however, it focuses on classification and prediction of physical properties. [9][10][11] One unanswered problem is the estimation of the ratio of base stocks within formulated base oils using modern regression techniques. The aim of this study is to create a sample set of base oil mixtures using typical open market samples and analyse this using mass spectrometry.…”

Classification of biodiesel and fuel blends using gas chromatography – differential mobility spectrometry with cluster analysis and isolation of C18:3 me by dual ion filtering

“…Chemometric tools to classify or analyze biodiesels for chemical information have included principal component analysis (PCA) [17,18], PCA-projections to latent structures [14], partial least squares (PLS) [19,20], PLS combined with PCA, hierarchical cluster analysis (HCA), Knearest neighbor (KNN) [21], and support vector machines (SVM) with PLS/ multivariate adaptive regression splines (MARS) [22]. Other applications of chemometric methods include quantitative determinations of blends with biodiesel, petrodiesel, and a renewable hydrocarbon by NIR spectrometry [4,23], the percent composition in biodiesel/petrodiesel by GC×GC-TOFMS [11], evaluation of blend quality by proton NMR [24], classification of blends by FT-ICR 6 MS [22], and the determination of methyl esters in biodiesel blends using FTIR-ATR and FTNIR [25].…”