## 1 Introduction  
Sweet cherry (_Prunus avium_ L.) is a fruit that is appreciated worldwide and is economically attractive, providing a high income for producers. Indeed, the consumer demand has greatly increased in recent years, leading to a current increase of cherry agricultural production [1; 2]. Both sour and sweet cherries possess distinct flavors, depending on the cultivar, geographical origin, and fruit maturity, among other factors [3]. Cherries are mainly consumed fresh [3]. Besides their recognized good taste and appealing color, sweet cherries have nutritional and health-promoting characteristics due to their richness in organic acids, sugars, vitamins, minerals, volatile compounds, and antioxidants compounds (e.g., melatonin and dietary phenolic compounds), as well as their fiber content [2; 4; 5; 6; 7; 8]. The cherry fruit chemical composition has been extensively studied using both destructive and non-destructive conventional analytical techniques (physicochemical, spectroscopic, and chromatographic analyses). The generated data were treated using different chemometric tools, such as principal component analysis (PCA), linear discriminant analysis (LDA), and least square-support vector machines (LS-SVM). The results allowed, for example, assessing of the cultivar or botanical origin [5; 6; 7; 8; 9], the geographical origin [6; 10; 11], the maturity stage [3; 12], or the fruits' bruises degree [13]. The capability to discriminate the cherry cultivar based on the fruit evaluation, although usually requiring a destructive analytical procedure, is of utmost importance. The chemical and nutritional composition greatly depends on the cultivar, a characterization needed due to legal requirements related to the use of protected designation of origin (PDO) and protected geographical indication (PGI) designations [6; 9; 11]. It has been reported that conventional fruit quality parameters, bioactive compound compositions (e.g., phenolics and anthocyanins), volatile compounds, and antioxidant activity data [5; 8; 14; 15] would allow a fair unsupervised differentiation, using PCA, of different sweet cherry cultivars. Additionally, it was shown that physicochemical, spectroscopic, and chromatographic data (mineral composition, total soluble solids, titratable acidity, total polyphenols, color data, and volatile compounds), individually or after data fusion, would allow to satisfactorily discriminate sweet cherries according to the cultivar. The correct classification rates greatly depend on the type of data and the number of cultivars considered [6; 9; 10; 11]. On the other hand, DNA-based techniques have also been successfully applied in the identification and discrimination of cherry cultivars [1; 16; 17; 18]. However, these techniques are not green or user-friendly, require skilled technicians, are time-consuming, and are usually beyond the economic and technical possibilities of most sweet cherry producers, which are mainly micro and small familiar producers. On the other hand, electronic tongues (E-tongues) have been recognized as portable and cost-effective analytical tools for monitoring and quality control of several food matrices [19; 20; 21]. Several advantages are well-documented, which led to the development of commercial devices for routine analysis (e.g., Taste Sensing System model SA 402B and model TS-5000Z, from Intelligent Sensor Technology, Inc., Kanagawa, Japan; \(\alpha\)-Astree II device from AlphaMOS, Toulouse, France; and, Multiarray Chemical Sensor from McScience Inc., Suwon, Korea) [22]. In this context, the possible use of a sensor-based E-tongue to discriminate sweet cherries according to the cultivar was evaluated for the first time. In fact, the chemical and sensory characteristics of fruits can be reflected in the potentiometric profiles collected by lipid sensor membranes, as recently reported by the research team for table olives [23; 24; 25] and sweet peppers [26].