A comparative study of diesel analysis by FTIR, FTNIR and FT-Raman spectroscopy using PLS and artificial neural network analysis

A low cost short wave near infrared spectrophotometer: Application for determination of quality parameters of diesel fuel

“…Furthermore, except for the T90 property, the values found for the root mean square error of prediction using external validation (RMSEP) were similar to or lower than the average errors commonly found using the official methods [15,16], proving the efficiency of the new spectrophotometer described here for the analysis of diesel samples. In comparison with other papers, the RMSEP values found were similar to [18] or lower than [19] those reported in papers dealing with the analysis of diesel by NIR spectroscopy using commercial and more expensive NIR instruments and analyzing a similar number of samples. One paper [20] presented results coming from analyses of a very higher number of diesel samples, but presenting also higher RMSEP values.…”

Quantitative Analysis of Lavender (<i>Lavandula angustifolia</i>) Essential Oil Using Multiblock Data from Infrared Spectroscopy

“…Vibrational spectroscopies such as NIR and MIR, when associated to multivariate analysis, have been proved to be a powerful tool in various product analyses like gasoline samples [1], diesels [2], fuel [3] [4], olive oils [5] [6] or lavandin essential oils [7]. These analytical spectroscopic methods, besides being shorter in time than the usual ones (ASTM methods), present good accuracy and precision; are non-destructive; and can be used for quality control.…”

Application of multivariate modelling and analysis on an integrated hydrocarbon sensor array system for marine surveys

“…[4,5] It has found its wide application in food industry and oil industry with the application ranging from prediction of cheese ripening time to the prediction of oil octane number and GC response factor. [6][7][8] Although there have been a number of literatures reporting the use of PLS to predict the analyte concentration, yet most of them deals with analyte solutions with idealized compositions [9] and are based on spectrophtometric information. [6,10,11] In contrast, this study fully utilizes and combines the advantages of different types of commercial chemical sensors and builds them into an arrayed system.…”