## 2 Results and Discussion
### Development of the Microextraction Methodologies
#### 2.2.1 Optimization of the HS-SPME Methodology  
The assays were performed through HS analysis of the glass flasks spiked with a standard mixture of the five BVOCs. By using a one-variable-at-a-time (OVAT) strategy, different parameters were evaluated, including the fiber type, the thermal desorption time, the equilibrium time and the thermostatization temperature. The microextraction efficiency was assessed through the signal response, using the ratio of each individual area to the IS area (A/A\({}_{\mathrm{IS}}\)). Figure 3 illustrates the microextraction efficiencies obtained for each parameter evaluated. Figure 1: Chemical structures of the target monoterpenoids studied in the present work. The optimization started with the selection of the best fiber coating (PDMS, PDMS/DVB, DVB/CAR/PDMS and CAR/PDMS) for the BVOCs analysis. All four SPME fibers extract through the sorption mechanism, where the analytes migrate to the coating phase through \(\pi\)-\(\pi\), hydrogen, dipole-dipole, hydrophobic and ionic interactions. The retention of the compounds also depends on their physicochemical properties, as well as on the coating's surface pore diameter [6]. In Figure 3a, the PDMS/DVB fiber showed a higher efficiency for the microextraction of all five BVOCs, as the response for the analytes was more than twice the response of the DVB/CAR/PDMS fiber and four times that of the CAR/PDMS fiber, which is in agreement with previous reports [7; 8]. Due the higher selectivity achieved, the SPME device is able to achieve the highest selectivity for the BS/CAR/PDMS fiber. Figure 3: Effect of fiber coating selectivity (**a**), thermal desorption time (**b**), equilibrium time (**c**) and HS temperature (**d**) on the enrichment of the five BVOCs obtained by HS-SPME/GC-MS. The error bars represent the standard deviation of three replicates. Figure 2: Experimental set-up for the HS-SPME (**a**) and HS-BA\({}_{\text{u}}\)E (**b**) assays. the PDMS/DVB fiber was chosen for the further studies. Afterwards, we proceeded to optimize the thermal desorption time. The results presented in Figure 3b show similar performances for both \(\alpha\)- and \(\beta\)-pinene, in which a slightly higher response was obtained at 5 min. This was also verified with 1,8-cineole. Meanwhile, for limonene and myrcene, better results were obtained at 3 and 4 min, respectively. Given that the results obtained for the latter three BVOCs (limonene, myrcene and 1,8-cineole) at 5 min still ensured remarkable performance (\(7.4\leq\mathrm{A_{i}}/\mathrm{A_{IS}}\leq 10.0\)), it was selected as the thermal desorption time for the remaining optimization procedures. Additionally, the selection of a higher desorption time may also prevent cross-contamination issues between analytical runs, ensuring a good clean-up of the fiber. Subsequently, we proceeded with the optimization of the equilibrium time. The SPME technique is a sorption-based microextraction approach, which means that the maximum amount of the analyte that the fiber can extract is achieved after reaching the equilibrium time [9]. As observed in Figure 3c, \(\alpha\)-pinene, \(\beta\)-pinene, myrcene and 1,8-cineole show better recoveries at 30 min, while limonene does so after 60 min of extraction. Nevertheless, for limonene, the RSD value of the assays performed at 60 min (RSD = 5.0%) is two times higher than the one obtained at 30 min (2.5%), which indicates more dispersion between replicates and, consequently, lower precision. Hence, 30 min of equilibrium time was maintained for further experiments. The last parameter of the optimization procedure included the assessment of the thermostatization temperature. The results showed that the HS microextraction efficiency of the procedure increases with the temperature for the monoterpenoids, except for \(\beta\)-pinene, where a slightly decrease occurs for the assays performed at temperatures higher than 40 \({}^{\circ}\)C (Figure 3d).