A PLS regression model using flame spectroscopy emission for determination of octane numbers in gasoline

This paper presents a method for the prediction of MON (Motor Octane Number) and RON (Research Octane Number) of automotive gasoline using flame emission spectroscopy and multivariate calibration (partial least squares). We obtained low values of RMSEC (root mean square error of calibration) and RMSEP (root mean square error of prediction), of 0.14 and 0.56, respectively for MON, while these values for RON were 0.34 and 0.9. The technique is simple and fast, does not require pretreatment of samples and still produces low octane rating errors, making it a good alternative to the standard method used in quality control of automotive gasoline.