## 4 Conclusions  
The integrated analytical strategy proposed in this study enables the successful definition of the aroma and taste blueprint of black tea infusions according to the recently introduced concept of the sensomics-based expert system. The results show how the tuning of analytical methods with molecular resolution toward sensory-relevant analytes belonging to different chemical fractions (apolar volatiles/semi-volatiles and polar non-volatiles) makes a valuable yet functional characterization of samples based on their sensorial peculiarities possible. Targeted analytes were identified and validated by sensomics as key aroma, key taste, and trigeminally active compounds of black teas. Their accurate quantification and normalization over odor or taste thresholds provide diagnostic blueprints of the product's sensory properties from which quality, origin, and thus economic values can be inferred.  
Since chemical blueprints are predictive of sensory properties, as an AI sensing tool, the current methodology supports industrial quality control laboratories with objective yet reliable differentiation and discrimination between teas of interest. The simultaneous quantification of 32 key analytes, in the absence of laborious sample preparation and with single chromatographic runs, generates a dataset ready for normalization over sensory thresholds that promptly projects into pictograms (i.e., the spider diagrams of Figures 2 and 4) the predictable sensory features of a product, facilitating or even replacing the sensory qualification of large sets of incoming batches. The reliability of this approach is especially usefulfor QC and QA laboratories and, as with any confirmation method, it is suitable for accreditation under ISO 17025 [48] with great advantages for certification and competitiveness in the food industry.  
The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/molecules29030565/s1](https://www.mdpi.com/article/10.3390/molecules29030565/s1)]([https://www.mdpi.com/article/10.3390/molecules29030565/s1](https://www.mdpi.com/article/10.3390/molecules29030565/s1)), Supplementary Table S1 ST1: analytes subjected to validation for AI flavor blueprinting of tea. Analytes are listed together with chromatographic information on retention times (\(t_{R}\) min), Target/Qualifier Ions (\(m/z\)) (GC-MS), detection wavelengths (nm) (LC-UV/DAD), calibration functions and determination coefficients (\(R^{2}\)), precision (repeatability and intermediate precision) (CV%), and accuracy results from spiked QC infusions at two levels expressed as percent recovery (% Rec). Accuracy was tested at +10 and +25 \(\mu\)g/L for aroma compounds and +10 and +25 mg/L for tastants and quality markers.  
Conceptualization, C.B. and C.C.; methodology, C.C. and F.M.; validation, F.M., A.C. and C.C.; formal analysis, F.M.; resources, C.B. and C.C.; data curation, F.M., A.C., A.F. and F.T.; writing--original draft preparation, F.M., C.C. and A.C.; writing--review and editing, C.C., A.C., A.F. and F.T.; visualization, F.M., A.C. and E.L.; supervision, C.C., E.L. and C.B.; funding acquisition, C.B. and C.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by Soremartec Italia srl (Alba, CN Italy) with the project entitled \"Advanced analytical approaches for _sensomic_ investigations of high-quality food matrices of vegetable origin\".  
Data will be made available on request.  
The authors declare no conflicts of interest.