To perceive a huge number of odors from few hundreds ORs, the human olfactory system encodes odor identities by an olfactory scheme whereby one olfactory receptor (OR) recognizes multiple odorants while one odorant activates different combinations of ORs [1, 2]. Odors perceived in our environment are mainly the result of mixtures of odorants, but the specific mechanisms involved in their processing remain poorly understood [3]. In previous studies performed at INRAE-CSGA [4], the perception of a mixture of ethyl isobutyrate (Et iB, strawberry-like odor, STR) and ethyl maltol (Et-M, caramel-like odor, CAR) was investigated in comparison with a reference (allyl hexanoate, Al-H, pineapple-like odor, PNA) chosen to evoke an odor close to the one expected in the mixture. The binary specific mixture of Et-iB and Et-M was judged as more typical of a pineapple odor than the individual components. In line with some studies highlighting the significance of the biological function of odorant, that is to say their odor, to understand odorant discrimination [5, 6], we focused on 300 molecules described with at least one of the odors STR, CAR or PNA. In line with our recent work related to the analysis of a large odorants database [7], we applied the notion of "social network" as used in the social sciences to describe the network of odors associated to STR, CAR and/or PNA. The analysis of the odors network led to identify 9 STR-CAR and 4 STR-PNA molecules. Pharmacophore generations [8] were performed using the STR-CAR and STR-PNA sets. All the models generated from both the STR-CAR and the STR-PNA sets are made up of 2 Hydrogen Bond Acceptors (HBA). While STR-CAR model has only Hydrophobic feature (HY), there are 2 for STR-PNA model. Comparing the distances between features of the two models revealed a common distance close to 8 Å between the centers of at least one HY and one HBA. Additionally, the pharmacophore comparison of the two models shown a satisfactory mapping of the features. The obtained results are in accordance with the scheme of olfactory coding, and is consistent with the hypothesis wherewith molecules sharing the odors involved in a blending mixture could recognize a common set of ORs. Key words: odor notes, aroma blending mixture, network, pharmacophore 1. Buck, L. et al. (1991). Cell, 65, 175. 2. Malnic, B. et al. (1999). Cell, 96, 713. 3. Thomas-Danguin, T. et al. (2014). Front. Psychol., 5, 504. 4. Le Berre, E. et al. (2008). Chem. Senses, 33, 389. 5. Ma, L.M. et al. (2012). Proc. Natl. Acad. Sci. U. S. A., 109, 5481. 6. Poivet, E. et al. (2018). Sci. Adv., 4, eaao6086. 7. Tromelin, A. et al. (2018). Flavour Frag. J., 33, 106. 8. Clement, O.O. et al., in Pharmacophore perception, development and use in drug design, O.F. Güner (Ed.), International University Line, La Jolla, 2000, pp. 69.