## 1 Introduction  
As stated in the International Olive Council (IOC) standard [1], virgin olive oils are obtained from the fruit of the olive tree (_Olea europaea_ L.) solely by mechanical or other physical means, under conditions that do not alter the oil. Virgin olive oil trading implies a previous compulsory assessment of its quality by chemical-physical analyses and organoleptic evaluation [2], leading to grade this food product into three commercial categories: extra virgin olive oil (EVOO), virgin olive oil (VOO) and lampante-non-edible olive oil (LOO). The current official method for the organoleptic assessment is the evaluation by the panel test [3]. This evaluation is important to get a global picture of the sensory properties of virgin olive oil and it is particularly precious and hardly replaceable when describing the sensory profile of EVOO under quality schemes, such as Protected Designation of Origin [4]. Although the panel test has been responsible for improving the quality of virgin olive oils in the last years [5], many authors agree on the controversies about this method [4; 5; 6]. As a matter of fact, since it was first introduced into European Regulations in 1991, it has undergone many revisions as the result of a continuous study of its performance [7]. Even so, the sensory panel test still presents some drawbacks linked to the method's nature, such as the limited number of samples assessed per day and misalignment between panels, among others [5]. It is also important to remember that the global production of virgin olive oil is growing at worldwide scale, while the number of recognized sensory panels is limited [6]. For all these reasons, setting up an instrumental screening tool that supports the sensory panel has become a need that should be fulfilled. In the last years, many works intended to achieve this purpose through different ways. Generally, volatile organic compounds (VOC) are the most pursued markers, due to their widely reported relationship with the sensory properties of virgin olive oil [8; 9; 10]. Their analysis has been performed by different methods, such as (i) gas chromatography-mass spectrometry (GC-MS) [11; 12; 13; 14], (ii) gas chromatography-ion mobility spectrometry (GC-TMS) [15; 16; 17; 18; 19], (iii) proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) [4; 20] and (iv) MS without a previous separation step [21; 22; 23; 24]. Rapid methods like flash gas chromatography (FGC) electronic nose have also been used for this purpose [25; 26]. In some cases, non-volatile compounds also related with sensory perception have been used to develop classification methods [22; 23; 27; 28]. All these analytical approaches have been combined with different chemometric tools to develop classification strategies, from basic ones to the most advanced ones such as deep learning [19] or data fusion techniques [22]. However, if the goal is to provide a fit-for-purpose tool that could eventually be applied in many laboratories to support the panel test, it is necessary to combine a suitable analytical method with a chemometric approach that is as simple as possible. In this sense, in a preliminary work [14], we presented a proof of concept for an instrumental screening tool based on virgin olive oil volatile fingerprinting by head space-solid phase micro extraction (HS-SPME) and GC-MS analysis. This analytical method is known to be simple, relatively fast, automatable, affordable and highly sensitive [13; 29; 30; 31]. Besides, that analytical tool is based on the use of raw chromatographic data, also called fingerprint, an approach that allows working with the full analytical information of samples, increasing the amount of information used in modelling as well as overcoming the identification and integration troubles of the conventional target approach [32]. In that work [14], a hierarchical model based on two binary partial least squares-discriminant analysis (PLS-DA) models was proposed as a classification strategy.