The use of MOF-based sensors for the detection of odorants (i.e., VOCs responsible for an aroma perception) was firstly reported by Lee et al. Although their study does not employ SERS as the readout technique, it is of relevance to include it in this section to discuss the important aspects regarding VOC detection for aroma profiling. In their work, the authors have synthesized microcrystals of indium-based luminescent MOF In(OH)(BDC), which were then confined in a water/n-heptane interface (see Figure ). Then, a glass substrate was placed vertically in the mixture, and as the n-heptane evaporated, the MOF microcrystals self-assembled on the glass substrate. This process produced a film with >80% coverage of the glass slide, with thickness between 3-5 µm (depending on the overlapping of the microcrystals). The advantage of working with In(OH)(BDC) MOF is that upon excitation (in this case, with a 270 nm light source), the crystals exhibited a photoluminescent (PL) peak at 326 nm, probably rising from ligand-to-metal charge transfer process. Upon adsorption of the odorant, the π system associated with the charge transfer is disrupted, thus red shifting the PL peak, which was then used as transductor mechanism for the adsorption process. Now, as stated previously, when aiming to describe a complete aroma, there is a need for detecting more than just one adsorption event, but rather a specific pattern. Therefore, the authors employed also MOF-5 crystals which experimented a blue shift upon adsorption of the target analytes. Having then a set of two MOFs responding differently to the same substances, the PL peak shift for each of them was used as components in a PCA analysis, mapping the response towards the analytes, thus generating a pattern recognition for the aroma, as it can be seen in Figure . This strategy not only allowed for the detection of the particular odor of e.g., cumin or cinnamon, but also enabled the discrimination between structural isomers such as m-xylene, o-xylene, and p-xylene. For proving the versatility of this system, the photoluminescent In(OH)(BDC) MOF was also employed in a later work towards the development of a "biomimetic tongue", thus aiming to mimic the sense of taste. This MOF was also modified with (+)polyaniline, mimicking the activity of guanine nucleotide-binding protein receptor involved in taste transduction. 143 In a related approach, SERS was employed in several works towards the detection of odorants. Fairly recently, this method was explored in the development of a "biomimetic tongue" as a complement to a "biomimetic nose". Contrary to the previous example (where MOF was employed without using SERS as readout), the work of Leong et al. rely in SERS alone for the development of a multiplexing platform for identifying wine flavors. The strategy followed by the authors is schematized in Figure , where it can be seen that different chemical modifications of Ag nanocubes assembled by Langmuir Blodgett technique (acting as receptors) allowed generation of the so-called SERS super-profiles. Then, by employing machine-learning-driven chemometric models, the authors demonstrate not only the identification but also quantification of wine flavors. More into the details, Leong et al. chose five target analytes, as archetypical descriptors of typical wine flavors: menthol for aliphatic alcohols, linalool and limonene for terpenes, and 3mercaptohexyl acetate and 3-mercapto-1-hexanol for sulfur-bearing compounds. Then, the spectral variations on the SERS response associated with the differential interaction of the functional groups of the analytes and the functional groups introduced on the Ag nanocubes surface, were employed for PCA and Support Vector Machine Discriminant analysis (SVM-DA) analysis. The results showed that the SERS substrate was able to classify all the flavors with 100% accuracy. Finally, the SERS substrates were employed for the multiplex analysis of artificial wine matrices, prepared with water, ethanol, glycerol, and tartaric acid. Then, the authors analyzed fourteen combinations of different flavor concentrations and employed the associated SERS super-profiles as calibration and validation sets, and later tasted with six "unknown" samples, which were quantified with 95-100% accuracy.