Volatile profiling in Rhus coriaria fruit (sumac) from three different geographical origins and upon roasting as analyzed via solid-phase microextraction

Plant material

R. coriaria fruits were collected manually in the full ripe stage from wild trees grown in Nablus, Palestine in October 2016, and were authenticated by Prof. Dr. Ibrahim Abou Reidah, Department of Chemistry, An-Najah National University, Nablus, Palestine. Commercial samples of R. coriaria fruits in the full ripe stage were purchased from El Hen Herbal Company (Amman, Jordan) and Haraz Drugstore (Cairo, Egypt). Voucher specimens were kept at the Department of Pharmacognosy, Faculty of Pharmacy, Cairo University, Egypt. Cold tea of the Palestinian sample was prepared by percolating 10 g of fresh cut fruits (without seeds) in 100 mL distilled water for 10 min, kept at 25 °C, then filtered on Whatman filter paper to remove plant debris. Roasting of the Palestinian sample was carried out by heating fresh cut fruits (without seeds) in an oven set at 120 °C for 20 min. Three replicates were analyzed for each sample. The fruits were stored at −20 °C till further analysis.

Chemicals and materials

SPME fibers of stableflex coated with divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS, 50/30 µm) (57328-U) or PDMS (polydimethylsiloxane) (57302) were purchased by Supelco (Oakville, ON, Canada). All other chemicals and standards were purchased from Sigma Aldrich (St. Louis, MO, USA).

Volatile analysis of fresh and roasted fruits

The HS-SPME volatile analysis was carried out as stated previously (Farag et al., 2017). Fruits (100 mg) were cut into halves, placed in SPME screw cap vials (1.5 ml) and spiked with (Z)-3-hexneyl acetate dissolved in water at a final concentration of 2 µg per vial. The SPME fiber was inserted manually into a vial containing seeds placed in an oven kept at 50 °C for 30 min. The fiber was subsequently withdrawn into the needle and then injected into the injection port of the gas chromatography-mass spectrometer (GC-MS). GC-Ms analysis was performed on a Schimadzu GC-17A gas chromatogram (Schimadzu, Tokyo, Japan) equipped with DB-5 column (30 m × 0.25 mm i.d. × 0.25 µm film thickness; Supelco) and coupled to a Schimadzu QP5050A mass spectrometer. The interface and the injector temperatures were both set at 220 °C. The following gradient temperature program was used for volatile analysis. The oven temperature was kept first at 40 °C for 3 min, then increased to 180 °C at a rate of 12 °C min⁻¹, kept at 180 °C for 5 min, and finally ramped up at a rate of 40 °C min⁻¹ to 240 °C and kept at this temperature for 5 min. The carrier gas helium was used at a total flow rate of 0.9 mL/min. Splitless injection mode was used for analysis considering the lower levels of volatiles in samples. SPME fiber was prepared for the next analysis by placing it in the injection port for 2 min at 220 °C to ensure complete elution of volatiles. Blank runs were made during sample analyses. The HP quadruple mass spectrometer was operated in EI mode at 70 eV. A scan range was set at m/z 40–500.

GC-MS data processing and multivariate analysis

Volatile components were identified by comparing their retention indices (RI) relative to n-alkanes (C6–C20), mass matching to NIST, Wiley Library Database and with standards whenever available. Peaks were first deconvoluted using AMDIS software (http://www.amdis.net/) prior to mass spectral matching. Volatile abundance data were prepared for multivariate data analysis by extraction using MET-IDEA software (Broeckling et al., 2006) for data extraction. Data were then subjected to principal component analysis (PCA), partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P version 13.0 software package (Umetrics, Umea, Sweden). Markers were subsequently identified by analyzing the S-plot, which was declared with covariance (p) and correlation (pcor). All variables were mean centered and scaled to Pareto variance.

Volatile analysis of fresh R. coriaria fruit (sumac) from three different geographical origins

GC-MS analysis (Tables 1 & 2, Fig. 1) of sumac fruits led to the identification of 74 volatile constituents, categorized in 10 different classes viz. alcohols, aromatics, esters, ethers, furan/aldehydes, hydrocarbons, ketones, monoterpene hydrocarbons, oxide and sesquiterpene hydrocarbons. A typical chromatogram of fresh and roasted sumac fruit aroma profiles is represented in Fig. 1. Initial detection of volatiles started from 0 minutes during chromatographic run but considering that no volatile peaks were detected until 5 min and with only one major peak for acetic acid (Fig. S1), MS detection started from 5 min for all specimens. Considering our interest in volatile terpenoids and hydrocarbons, 5 minutes delay is appropriate for this study. Acetic acid in sumac is likely to derive the tart taste for its fruit. Sesquiterpene hydrocarbons amounted for the most dominant class accounting for ca. 40–58% of the fresh sumac aroma with a total of 26 identified volatile constituents (Table 2). Next to sesquiterpenes, monoterpene hydrocarbons represented the most abundant class (ca. 17–34%) among specimens (Table 2). Other eight volatile classes detected amounted for less than 17% of sumac fruit total volatile blend (Table 2). Naphthalene and α-pinene were the major volatile forms in Jordanian and Palestinian specimens at ca. 15.8 and 16.7%, respectively. Whereas, monoterpene hydrocarbons viz., o-cymene 7.7%, β-ocimene 7.5% and limonene 7.3% were the chief components in fresh sumac fruit aroma derived from Egypt. Volatiles found at comparable levels in all three examined specimens included (E)-β-famesene and (Z, Z)-α-farnesene (sesquiterpene hydrocarbons) detected at ca. 6–8%. With regard to oxides, cineole amounted for 7.3% of Egyptian sumac aroma blend, at two fold the levels that were present in specimens from Jordan (3.2%) and Palestine (2.2%) (Table 1).

In contrast, roasted fruit aroma was predominated by furan/aldehydes at ca. 58% followed by sesquiterpene hydrocarbons at 27%. A dramatic change in fruits’ aroma profile was observed upon roasting, exemplified in high furan/aldehyde (58.1%) and ketone (6.1%) levels in roasted fruit concurrent with a marked decrease in the other eight volatile classes (Table 2). Roasted specimens were particularly enriched in furfural (34.3%) and (E)-nonanal (12.2%) followed by 3-thujanone (5.1%) (Table 1, Fig. 2). Sumac fruits are also used worldwide to prepare cold tea by simply soaking the fruit in cold water. Consequently, it was of interest to characterize the sumac cold tea aroma profile; a weak aroma profile was detected compared to fruit exemplified by much lower number of volatile components totaling 14 peaks (Fig. 2).

It should be noted that a relatively high standard deviation was observed for some minor constituents (Table 1) viz., β-linalool, styrene, octanal, nonanal and β-ocimene especially from the Jordanian specimen. Whether such large variance is associated with the experimental setup and detection method has yet to be determined by employing other detectors viz. the flame ionization detector. FID detection or automated SPME in volatiles’ extraction step can help minimize such variance.

Multivariate PCA and OPLS-DA analyses of fresh, roasted and cold tea of R. coriaria fruit volatile data

Multivariate PCA (Figs. 3 and 4 & Fig. S2) was carried out to explore the relative variability within the different specimens and to identify geographical origin’s (viz. Egypt, Jordan and Palestine) impact on fresh sumac fruit aroma in an untargeted manner. Multivariate data analyses additionally help in identifying potential markers for each fruit origin. Palestinian and Jordanian sumac specimens were found more or less clustered together on the right side of PC1 (positive score values). In contrast, Egyptian sumac was positioned on the left side of PC1 (Fig. 3A). A total of 74 volatiles’ abundance data were subjected to PCA analysis with two major principle components (PC1/PC2) accounting for 60% of the total variance. A PCA loading plot (Fig. 3B) revealed that α-pinene contributed the most positively along PC1 and PC2, being most abundant in Palestinian sumac in agreement with results presented in Table 1. In contrast, o-cymene and limonene located on the far negative side of PC1 were more enriched in Egyptian specimens. Roasting was found to influence sumac aroma profile more than the growth habitat as revealed from PCA analysis (Fig. 4A). Roasted specimens were positioned to the right side of PC1 (positive side) being most distant in composition, whereas fresh fruits and cold tea specimens were all positioned together on the left side of PC1 (negative side). The PCA model (Fig. 4A) was prescribed by PC1 and PC2 accounting for 45% and 24% of the variance, respectively. Unique aroma compounds found in roasted specimens included furfural and nonanal (Fig. 4B). To help identify volatile markers unique for roasted specimens, OPLS-DA (orthogonal projection to latent structures-discriminant analysis) was employed (Fig. S2). The OPLS-DA score plot of roasted versus unroasted fruit showed a clear segregation between roasted and fresh samples explaining 97% of the total variance (R2) and with a prediction goodness parameter Q2 = 95%. The respective S-plot (a remarkable parameter that compares the variable magnitude versus its reliability in OPLS) identified furfural and nonanal as markers of the roasting process (Fig. S2-B) and was in agreement with PCA analysis. The OPLS-DA model of cold sumac tea modelled against fresh fruit failed to provide a fit model as in the roasted specimen case, with lower R2 and Q2 values of 85% and 89% respectively (Fig. S2-C). In general, the aroma of sumac cold tea appeared to be more dominated by esters viz. bornyl acetate, nerol acetate and s esquiterpenes viz. (β)-caryophyllene and α-humulene, as revealed from derived the S-plot (Fig. S2-D).