## 1 Introduction  
Vegetable oils are complex mixtures containing a wide range of compounds. They are principally composed of diacylglycerols, triglycerides, and phospholipids (95-98%) and complex mixtures of minor compounds (2-5%) of a wide range of chemical components [1]. Triglycerides are a combination of glycerol and free fatty acids [2]. The composition and abundance of fatty acids and minor constituents present in vegetable oils depend on the plant species from which they were obtained. Moreover, within the same species, their composition may vary depending on the agronomic and climatic conditions, fruit or seed quality, the oil extraction process, and refining procedures [3]. Chromatographic techniques are the most common choice in the analysis of the edible oil samples. The differentiation of oil samples is based mostly on fatty acid profiles and volatile and semi-volatile compounds (organic acids, sugars, terpenoids). The information obtained from the analytical data can be difficult to interpret if a large number of edible oil samples of different origins, raw or refined, are analyzed. The use of multivariate statistical methods or chemometric techniques offers an opportunity to critically observe both the quantity and quality of data [4].  
Most of the analytical techniques used in the analysis of vegetable oils require a laborious special sample preparation step. This step is especially important, since individual operations related to the preparation of samples cannot lead to changes in their composition (oxidation process, decomposition, introduction of contaminants, proportional changes in individual components). They should also provide the best recovery of the analyzed components from the sample matrix and cannot introduce interfering substances. These techniques should also enable the obtainment of a representative sample for further analyses.  
Chromatographic methods, such as gas chromatography equipped with a flame-ionization detector (GC-FID), have been shown to be effective in the detection of fatty acids in oil samples. However, the requirement of standards, the need for the fatty acid methylation step, in order to be separated and analyzed, and the high input of time and labor make this analysis technique difficult.  
Different spectroscopic techniques have been developed for the quality evaluation and authentication of oils; due to large consumer interest in olive oils, these methods are clearly presented in regard to the olive oil analysis [5; 6]. Compared with the chromatographic procedures, they allow simple, nondestructive, time-saving investigations. Infrared spectroscopy is an excellent method for the investigation of vegetable oils and their parameters determinations (the variation of the infrared spectra can be correlated with the changes achieved in the oil parameters) [7]. At the same time, Raman spectroscopy is a successful technique for edible oil evaluation [8]. Due to the complexity of the matrix, both methods are employed in connection with the chemometrics for a rapid and valuable evaluation of the oils. Taking into consideration the development of new, easily operated portable Raman devices, and the development of new approaches based on a combination of Raman spectroscopy and Machine Learning algorithms for edible oil investigation [9], this technique is very promising for the control of different matrices (including vegetable oils).  
This study aims to compare the classification power of two analytical techniques for edible oil evaluation.