GC-MS fingerprints of mint essential oils

Abstract Essential oils from eleven Mentha species were obtained by Deryng hydrodistillation and analysed by GC–MS: 44 compounds were identified. The most abundant were menthone, isomenthone, menthol, carvone, piperitone oxide, D-limonene and eucalyptol. Chemometric similarity measures and principal component analysis were calculated, allowing comparisons based on secondary metabolite content. The fingerprints may be helpful in chemotaxonomy. Graphical Abstract


Introduction
The widely used Lamiaceae family includes about 220 genera and 3300 species. They are rich in polyphenols and well known for their antioxidant properties. The genus Mentha (Lamiaceae) comprises 25−30 species found in temperate regions of Eurasia, Australia, and South Africa [1][2][3]. Mentha has been known for its carminative, stimulative, stomachic, diaphoretic, antimicrobial, antiseptic, anesthetic, antiemetic, anti-inflammatory, and strong antioxidant properties. Mentha leaves, flowers and stems are used in traditional medicine as spasmolytics, antibacterial agents, promoters of gastric secretions, and relief for heavy colds. Mint has been also used in treatments of minor aches and sprains, as well as in nasal decongestants [3][4][5][6][7][8].
Aromatic essential oils are complex mixtures of volatile secondary plant metabolites characterized by strong odor [7]. They are primarily monoterpene and sesquiterpene hydrocarbons, their oxygenated derivatives, a variety of aliphatic oxygenated compounds, and a few aromatic compounds [10]. Essential oil monoterpene compositions differ giving different or hybrid species different smells [11].
One-dimensional GC has been the most common approach to unravelling food volatile and semi-volatile compositions. It is effective in separation of simple samples. With more complex mixtures many peaks result from two or more co-eluting compounds. This problem is solved by linking the gas chromatograph to a mass spectrometer (GC-MS), which gives single-component peak assignment and quantitation [16] and identifies multicomponent peaks by deconvolution. Obviously, library assignment of unknowns is more reliable (especially for more complex matrices) when high quality mass spectra of resolved compounds are obtained. Total separations are always desirable but often difficult [16,17].
The main aim of our work was to analyze terpenes and other compounds occurring in Mentha essential oils. GC-MS was used to construct fingerprints of Mentha species and varieties to facilitate their identification and assist in Mentha chemotaxonomy. Forty grams of dried, fragmented aerial parts of each Mentha sp. were placed in a 1000 mL round-bottom flask along with 600 mL distilled water and subjected to Deryng hydrodistillation for three hours (distillation yields in Table 1). The essential oils were collected in small vials and dried over anhydrous sodium sulfate. One drop of oil was dissolved in 2 mL of ethyl acetate and refrigerated until analysis.

GC-MS Analysis
GC-MS was performed as previously described [18]. A Shimadzu GC-2010 Plus GC coupled to a Shimadzu QP2010 Ultra mass spectrometer was used. Compounds were separated on a fused-silica capillary column (30 m, 0.25 mm i.d.) with a film thickness of 0.25 µm (Phenomenex ZB-5 MS). The oven temperature program initiated at 50°C, held for 3 min, then increased at 8-250°C min -1 , and held for 2 min. The spectrometer was operated in electron impact mode, the scan range was 40-500 amu, the ionization energy was 70 eV, and the scan rate was 0.20 s per scan. The injector, interface, and ion source were kept at 250, 250, and 220°C, respectively. Split injection (1 µL) was conducted with a split ratio of 1:20 and 1.0 mL min -1 helium was the carrier gas.
Retention indices were determined by comparison to a C8-C24 n-alkane homologous series under the same operating conditions. Compounds were identified using the Mass Finder spectral library (http://www.massfinder. com), and NIST MS data (http://webbook.nist.gov) [19]. Individual isolated compound identifications were also performed by comparison of their mass spectra and retention indices with authentic compounds and literature data [18].

Chemometric and PCA analysis
The GC-MS data were exported as jdx from Mass Finder ver. 2.3. These were transformed by ImageJ software to JPG files, then saved as 8000 × 1 pixel TIF pictures which allowed 32-bit precision. All 12 .TIF files were exported as CSV files into SpecAlign ver. 2.3 [19]. They were polynomial degree 2 Savitzky-Golay smoothed with window halfwidth 8 and denoised by the Symlet8 algorithm, threshold parameter = 0.5. Baselines were generated and subtracted from each chromatogram. Finally, all were exported as .csv files to ImageJ and transformed to TIF in which all 12 chromatograms were 8000 × 1 pixel pictures.
Unaligned chromatograms were analyzed by PCA using Molegro Data Modeller software. The input data was the matrix with 12 columns and 8000 lines.
Menthol is the most characteristic Mentha compound. Its highest concentration was in M. piperita var. Krasnodarskaja and other piperita varieties. The compound present in largest amount overall was menthone, representing over 10% of the total. It was present at high concentrations in M. piperita., piperita var. Krasnodarskaja and piperita var Cernolistnaja.
In addition to D-limonene and eucalyptol, M. spicata contains significant amounts of β-myrcene, β-burbonene, and large amounts of trans-dihydrocarvone and carvone. M. spiccata var. Crispa also contains a large amount of carvone, but differs from M. spiccata in the level of β-linalool and its higher α-pinene, β-pinene, p-cymene and β-ocymene content.
M. suaveolens contains about 4% D-limonene and about 3% 1-octen-3-acetate, which is present only in trace levels in other plants. M. longifolia differs from the other species; it contains more than 50% piperitone oxide, along with β-caryophyllene and carvacrol. Table 4 shows the similarity measures. High values of R, R 2 , Cos, nCos, Lum, Con, Str and MS-SSIM mean better matching; low values of Euc, Man, Che, Hau and AMMD also show better matching.  Table 4 suggests that these analyses can be used for identification. It also shows the M. spp. composition similarity. The PCA results in Fig. 3 confirm these conclusions. These similarities and differences can be used to identify mint species by fingerprinting.

Conclusions
The highest oil yields were from M. piperita var.  The similarity measures and PCA analysis show composition similarities and differences among Mentha species. GC-MS gives comprehensive information about essential oil composition and can construct herb fingerprints.