## 1 Introduction
[27] utilized Fourier-transform infrared spectroscopy (FTIR) coupled with linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) to differentiate fuel blends. The findings demonstrate that LDA and PLS-DA approaches are capable of distinguishing biodiesel samples ranging from 10% to 100%. However, the moisture in the fuel blend will affect its ability to be quantified by NIR spectroscopy [28]. UV-Vis spectroscopy provides limited information for compound analysis and is typically used in conjunction with other test methods. Fluorescence spectroscopy is susceptible to many interfering factors, such as photodecomposition and oxygen quenching, and the relationship between fluorescence and compound structure is not well defined. NMR spectroscopy is widely used for the structural analysis of various compounds due to its high accuracy. Nevertheless, this technique also has the disadvantages of a high temperature consumption, susceptibility to interference from other substances, and operational difficulties. Therefore, novel and reliable techniques are needed to overcome the limitations of traditional methods in measuring the amount of biodiesel present in diesel fuel blends. Raman spectroscopy not only displays sharp characteristic peaks corresponding to functional groups in various types of samples (liquids, solids and powders, etc. ), but also the positions and intensities of these peaks matched with the analyzed substances can sensitively reflect the intrinsic structural and variation information of the relevant substances, enabling their identification and characterization [29]. Raman spectroscopy is a non-destructive, fast method that eliminates the need for sample preparation [30,31]. This technique coupled with diverse chemometric methods [32, 33, 34] has been applied extensively for the identification of unknown substances in fields such as materials science, biology, pharmaceuticals, and food science [35, 36, 37, 38]. Furthermore, it has also been employed for the analysis of different types of fuels including gasoline, kerosene, and alcohol fuels [39, 40, 41]. For example, [PERSON] et al. [42] identified and quantified two biofuels (biodiesel and hydrotreated esters and fatty acids (HEFA)) and adulterants in petroleum diesel using multivariate curve resolution-alternating least squares (MCR-ALS) integrated with Raman spectroscopy. The quantitative model of biofuels developed had an RMSEP value of 0.70% and the RMSEPs for the concentration of adulterants were estimated with values below and up to 8%. The use of rugged and easy-to-use portable Raman spectrometers may offer more possibilities for the rapid and non-invasive identification of suspect samples, especially in field and real-time assessments. There is an urgent need for technology to quantitatively analyze adulterated biodiesel, which has not been reported in the previous literature. In this work, portable Raman spectroscopy combined with a synergistic interval partial least squares (siPLS) method that can accurately select the associated variables of the biodiesel characteristic peaks is proposed as a technique to quantify biodiesel. Firstly, Raman spectra were acquired from fuel samples with different adulterations to investigate the characteristic Raman spectra of different fuels. Then, various preprocessing methods were compared to establish suitable PLS calibration models. Additionally, several variable selection methods, including iPLS and biPLS, were compared to examine their effects on the calibration model and to validate the ability of different characteristic Raman spectral regions to quantify biodiesel. Finally, an optimal calibration model was constructed based on appropriate spectral preprocessing and model parameters. The aim of this work is to develop a rapid and non-destructive technique for the quantitative analysis of biodiesel using Raman spectroscopy combined with multiple regression (PLS) and variable selection techniques (siPLS).