4.3. HS-SPME-GC-MS Method

Chocolate samples were analyzed by gas chromatography—mass spectrometry (GC-MS), using the equipment Agilent 7890B GC System, Equipped with a VF-23ms column (high polarity column, length: 30 m, diameter: 0.25 mm, film thickness: 0.25 µm). The GC inlet was at 250 °C, while the oven was set at an initial temperature of 40 °C for 5 min, then the temperature was increased to 200 °C with a gradient of 5 °C/min, to finally keep at 200 °C for 10 min [41]. Injection mode was performed manually, exposing the fiber after introducing the SPME needle. The fiber was left exposed for about 10 min and then removed from the inlet.

The SPME fiber selection was made by analyzing chocolate samples from three production lots of bitter chocolate samples (70% Cocoa content) from Theobroma Inversiones SAC. Two samples from different production lots are shown in Supplementary Figure S2. The divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS, black line) and the divinylbenzene/polydimethylsiloxane (DVB/PDMS, red line) fibers showed better performance than the carboxen/polydimethylsiloxane (CAR/PDMS, blue line) fiber due to the higher affinity of the latter to acetic acid. The DVB/CAR/PDMS was finally selected because, after 17 min, it showed better chromatographic peaks than DVB/PDMS fiber.

During SPME optimization, every sample was analyzed in triplicate, and blanks (i.e., no-exposed fiber injections) were run between every sample. Once the method was optimized, six additional chocolate samples were analyzed from production lots of two different years, i.e., 2018 and 2019; to identify key-VOCs that can differentiate northern and southern Peru regions. The number of blanks was reduced to 1 every three sample injections.

After obtaining the chromatograms and spectra of each sample, the signals were integrated using the GC-MS software. In each integration, the NIST 2.0 Mass Spectral Search Program database and the MS NIST 2011 Spectral Library were accessed to identify the compounds. This database allowed access to a list of probable compounds according to the percentage of equivalence between experimental and theoretical mass spectra. For the ninety-three chromatographic peaks, the compound’s name with the highest identification percentage of similarity to the mass spectrum was selected (minimum accepted 60%). Low identification percentage is typical with old quadrupole mass analyzer models since it only works with nominal masses. Therefore, to verify the compounds’ identity, we searched as well in peer-review references, where these putative signals were also identified in chocolate samples.