## 4 Conclusions  
Coffee metabolomics research has primarily focused on green and roasted coffee beans from the two main varieties, _C. arabica_ and _C. canephora_. To the best of our knowledge, there are no metabolomic based studies about the characterization of coffee varieties considering both green and roasted coffee. Here, we have presented detailed and comprehensive information regarding the different metabolomic composition of seven Arabica coffee varieties, using an NMR-based metabolomic approach. For each variety, two points of fermentation time (12 h vs. 24 h) and two types of drying procedures (under shade and direct sun) have been considered. The analyses were performed both considering the entire spectra to evaluate the fingerprint of each variety, and on the identified metabolites, both for green and for roasted coffee beans. Figure 6: RF models on green coffee metabolites characterizing each variety according to the different drying procedures used: “under shade” and “direct sun”. (**a**) catuai rojo; (**b**) maracaturra; (**c**) bourbon; (**d**) caturra; (**e**) pacamara; (**f**) tekesic; (**g**) bourbon rojo. Mean decrease accuracy values are reported on the orthogonal axis of each plot. The results demonstrated that NMR spectra of both green and roasted coffee beans can be used to recognise coffee varieties with high accuracies (87.2% and 86% using, respectively green and roasted NMR spectra to build the model). Moreover, it was also possible to characterize, using this approach, the metabolomic profile of distinct coffee farms within the same restricted geographical area of Nicaragua cultivating the same varieties. Our results demonstrate that, even when coffee batches are processed following the same post-harvest procedure, the characteristic fingerprint of each farm could be derived with high predictive accuracies. The opportunity to quickly obtain NMR spectra with a minimal sample preparation, and to use them to classify samples according to the variety, makes the NMR-based metabolomic approach a suitable approach to recognize original products. Moreover, NMR spectroscopy may be considered as a \"magnetic tongue\" that analyses and predicts food flavours without being targeted and disruptive. Therefore, the effects of the time of fermentation and drying types were also evaluated, suggesting that both post-harvest procedures are capable of inducing changes in the metabolic profile of coffee beans that are responsible for different flavours in the cup. In particular, the amount of malic acid, which contributes to a tart acidulous and sour taste, is increased in 24 h of fermentation batches of CR, PA, TE, and BR; trigonelline, instead, related to a bitter taste, is increased in 12 h fermentation in CA, while the other varieties show weaker variation based on the treatments; formic acid which gives a sour/lemon taste, is increased in MC green beans at 24 h of fermentation, while it is decreased in BR cultivar at 24 h of fermentation. Caffeine content seems also to be slightly increased by longer fermentation time. The content of acetic acid, which contributes to a sour vinegar taste, seems to be higher, particularly in CR and PA if exposed to the sun drying, instead, for the other varieties, higher content can be obtained if beans are exposed under shade. The present study suggests that post-harvest treatment procedures can differently affect the amount of aroma precursors within distinct coffee varieties and that the kind of processing should be optimized specifically for each variety. The following are available online at [[https://www.mdpi.com/article/10.3390/app112411779/s1](https://www.mdpi.com/article/10.3390/app112411779/s1)]([https://www.mdpi.com/article/10.3390/app112411779/s1](https://www.mdpi.com/article/10.3390/app112411779/s1)), Figure S1: 1H NMR spectra of coffee beans. Figure S2: First two components of PCA score plots of 1H NMR bucketed spectra of green (a) and roasted (b) coffee beans. Figure S3: Random Forest multidimensional scaling (MDS) plots.