Characterising volatiles in tea (Camellia sinensis). Part I: Comparison of headspace-solid phase microextraction and solvent assisted flavour evaporation

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Characterising volatiles in tea (Camellia sinensis). Part I: Comparison of headspace-solid phase microextraction and solvent assisted flavour evaporation

T

Hazel Laua, Shao Quan Liua, Yong Quan Xub, Benjamin Lassablierec, Jingcan Sunc, Bin Yuc,∗ a

Food Science and Technology Programme, Department of Chemistry, National University of Singapore, S14 Level 5, Science Drive 2 117542, Singapore Tea Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, 9 South Meiling Road, Hangzhou 310008, China c Mane SEA PTE LTD, 3 Biopolis Drive, #07-17/18/19 Synapse 138623, Singapore b

A R T I C LE I N FO

A B S T R A C T

Keywords: Tea Volatile HS-SPME SAFE GC-MS

In this work, headspace-solid phase microextraction (HS-SPME) was optimised to study the effect of grinding and brewing on tea volatiles. Grinding resulted in an apparent increase of tea volatiles, while the volatile profiles of tea leaves and infusions were qualitatively similar. Moreover, solvent-assisted flavour evaporation (SAFE) was applied for the analysis of tea volatiles. Its working conditions were systematically investigated by adjusting operating parameters (i.e. water bath temperature (20–35 °C), condenser temperature (20–50 °C) and salt addition (20% NaCl (w/w))). Higher water bath temperature, lower condenser temperature and the use of salt were observed to give better extraction. In conclusion, this study improved the knowledge of SAFE as an efficient sampling technique for complex matrices.

1. Introduction Tea (Camellia sinensis) is the most widely consumed beverage after water globally due to its health benefit and attractive flavour, which can be attributed to tea aroma volatiles (Robinson & Owuor, 1992). Although these volatiles in tea are only present at trace levels (Harbowy, Balentine, Davies, & Cai, 1997), there is growing interest in the isolation of these compounds because of their significant influence on sensory attributes (Baba & Kumazawa, 2014; Guth & Grosch, 1993; Kumazawa & Masuda, 2002). Moreover, recent reviews on tea volatiles have recognised the complexity of tea matrix caused by the presence of non-volatiles such as tea pigments and lipids (Yang, Baldermann, & Watanabe, 2013; Zheng, Li, Xiang, & Liang, 2016). Thus, the selection of an appropriate extraction method has become a prerequisite to advance the understanding of tea volatiles. Headspace-solid phase microextraction (HS-SPME) is efficient as it is a solventless approach, and is able to combine sample extraction and concentration in one step. As such, it is a popular method applied in tea analysis (Baptista, da P Tavares, & Carvalho, 1998; He et al., 2016). When HS-SPME is selective for highly volatile compounds, distillation may be considered to facilitate the extraction of the semi-volatiles. Commonly, distillation employs high temperatures which unquestionably distorts the aroma composition through thermal artefact ∗

formation (e.g. ester hydrolysis and Maillard reaction) (Chaintreau, 2001), while low pressure/vacuum distillation processes clearly reduce thermal side-effects. Solvent-assisted flavour evaporation (SAFE) is a vacuum distillation technique originally developed for the analysis of dairy products due to its ability to isolate volatiles from complex matrices containing fats (Engel, Bahr, & Schieberle, 1999). It is capable of producing extracts typical of the source (Elmore, 2015) and has been used in volatile and sensory correlation studies in some foods (Langos, Granvogl, & Schieberle, 2013; Willner, Granvogl, & Schieberle, 2013). Although there are increasing SAFE studies on volatile isolation since its inception in 1999, there has still been limited use in tea volatile analysis. Of these, one approach to tea analysis involved supplementation of SAFE with solvent extraction (Schuh & Schieberle, 2006), and most recently with the adsorptive column method (Baba & Kumazawa, 2014). Moreover, the optimisation of SAFE was only reported to be done on temperature effects using an organic solvent model (Mizukami & Yamaguchi, 2010), which failed to account for matrix effects in food samples. So, the comprehensive optimisation of SAFE parameters is still lacking. Therefore, the main objective of this research was to optimise HSSPME and SAFE sampling methodologies for tea volatile characterisation. Both of the methods were carefully examined, and their relevant parameters were systematically adjusted. Moreover, HS-SPME was

Corresponding author. Mane SEA PTE LTD, 3 Biopolis Drive, #07-17/18/19 Synapse 138623, Singapore. E-mail address: [email protected] (B. Yu).

https://doi.org/10.1016/j.lwt.2018.04.058 Received 5 October 2017; Received in revised form 13 December 2017; Accepted 18 April 2018 Available online 23 April 2018 0023-6438/ © 2018 Elsevier Ltd. All rights reserved.

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for compound identification. Separation of the volatiles was performed on an Agilent HP-INNOWax column (60 m × 250 μm × 0.25 μm) (Woodbridge, USA). Sample injection was automated using a CTC CombiPAL autosampler (Zwingen, Switzerland), and the operating conditions of the GC were as follows: injector temperature 250 °C; splitless mode; helium carrier gas; column flow rate 1.2 mL/min. The temperature gradient used began at 50 °C for 5 min, followed by an increase to 240 °C at 5 °C/min, and held at 240 °C for 40 min. The FID temperature was 300 °C, and the MSD was in the electron impact (EI) mode at 70 eV. Identification of the eluted compounds was tentatively achieved by matching the mass spectrum against an in-house database and NIST 14 MS library (Connecticut, USA), and further confirmed with the linear retention indices (LRI) of in-house standard compounds (food grade, purity > 95%) that were provided by Mane SEA Pte Ltd. LRI values on the HP-INNOWax column were determined using a mixture of Supelco C7-40 alkanes (Pennsylvania, USA), which were run under identical conditions. Due to the wide range of compounds found in tea, two internal standards (2-octanol and ethyl decanoate) were selected for semi-quantification in the present work for SAFE. The concentration of the compounds was expressed as ng/mL based on the relative FID peak area of the compounds (LRI ≤ 1559 against 2-octanol; LRI > 1559 against ethyl decanoate). All experiments were carried out in triplicate and the results were reported as mean values.

applied to investigate the differences in tea volatile profiles between tea leaf and infusion as well as the effect of grinding on the release of tea volatiles. 2. Materials and methods 2.1. Tea sample preparation In the present experiment, green tea was chosen to optimise extraction methods (HS-SPME and SAFE), which were subsequently applied to the comparative study of volatiles in various types of teas in the next part of the paper. The green tea obtained from Shenzhen Shenbao Huacheng Tech. Co., Ltd (Shenzhen, China) was harvested and processed in Wuyuan county of Jiangxi province of China on March 2017, and was stored at 5 °C in aluminium sachets until use. The ground tea (6.1% ≥ 850 μm, 850 μm ≤ 67.9% ≤ 425 μm, 425 μm ≤ 26.0% ≤ 177 μm, measured by sieve analysis) was prepared in liquid nitrogen using a Retsch mixer mill (Haan, Germany). 2.2. HS-SPME procedure The HS-SPME procedure used was described elsewhere (Wong, Yu, Curran, & Zhou, 2009). Two types of tea sample analyses were conducted by HS-SPME: 0.200 g of tea leaves (ground/unground) were placed in a 20-mL vial with PTFE-coated silicone septum (Agilent, California, USA); 0.200 g of tea leaves (ground/unground) were placed in a 20-mL vial with 2.000 g of room temperature ultrapure water from a Human Corporation Arioso Power Series water purifier (Seoul, Korea). Extraction of volatiles was carried out using a Supelco 85-μm Carboxen/Polydimethylsiloxane (CAR/PDMS) fibre (Pennsylvania, USA) at designated extraction temperatures (40, 60, 70, 80, and 90 °C) and extraction times (5, 15, 30, 45, 60, and 90 min). The fibre was then introduced to the GC injector for 1 min for the desorption of analytes, which were delivered to the GC column for subsequent separation and detection. Finally, the fibre was baked out for 5 min in the SPME fibreconditioning station after each extraction/desorption cycle to reduce the carryover of analytes.

3. Results and discussion 3.1. Optimisation of HS-SPME Growing interest in tea volatiles has prompted the use of quick screening methods, such as HS-SPME, which is a fast and qualitative method. In this section, extraction time and temperature were optimised in HS-SPME, which was applied to study the effects of grinding and brewing on the release of tea volatiles. 3.1.1. Effect of extraction temperature and time Existing HS-SPME optimisation studies on extraction time and temperature are primarily based on selection for the highest extraction efficiency (the total of peak areas) (Kim et al., 2007). In this study, volatiles identified as key contributors to green tea aroma profile including hexanal, cis-3-hexenol, linalool, geraniol, 2-phenylethyl alcohol, β-ionone, cis-jasmone and indole (Guth & Grosch, 1993; Kumazawa & Masuda, 2002) were selected as indicators to be monitored in the present work. In Fig. 1(a)-(d), a complex relationship was observed between extraction temperature and peak area. With increasing extraction temperature, while hexanal increased in the tea leaves, an inverse trend was observed in the tea infusions. The rest of the aroma chemicals were generally observed to increase with increasing extraction temperature. Similar observations were made for aroma-active volatiles in recent HSSPME tea studies (He et al., 2016). At 80 °C, cis-3-hexenol appeared to stop increasing, accompanied by continuous increments in geraniol, βionone and indole, which may be a result of thermally-related reactions as observed in previous studies (Kim et al., 2007). Furthermore, the poorest reproducibility was observed at 90 °C, partly due to the disturbance from steam. Thus, 80 °C was selected for further experiments. At 80 °C, higher extraction efficiencies were clearly shown in Fig. 2(a)-(d) as increasing peak areas with longer time periods, which may be attributed to an extended extraction of analytes by the fibre (Pawliszyn, 2000). While the longest time (90 min) provided the best extraction, it was decided that 60 min was selected as the optimal extraction time due to time efficiency during the practical operation. In the following experiment, extraction parameters were set at 80 °C for 60 min.

2.3. SAFE procedure Tea leaves (85.0 g) were infused with 850.0 g of deionised water (80 °C) in a covered 2 L glass beaker for 5 min, followed by filtration through a sieve and cooling of the filtrate in a covered glass beaker for 10 min. The internal standard solution was prepared as follows: 0.300 g of 2-octanol (Sigma Aldrich, USA) and 0.300 g of ethyl decanoate (Sigma Aldrich, USA) were added in 250 mL of HPLC grade ethanol (Sigma Aldrich, USA). 304.18 ng/mL of internal standard solution was added to the filtrate (for 500 mL of filtrate, 0.100 g of internal standard solution was added), and was stirred for 5 min. The filtrate was extracted at 5 × 10−6 mbar with the SAFE apparatus (Glasbläserei Bahr, Germany) maintained using an Edwards PFPE RV3 rotary vane pump (West Sussex, UK) and an Edwards Diffstak diffusion pump (West Sussex, UK). After thawing, the condensate was immediately extracted twice with the same volume of HPLC grade dichloromethane (VWR; Pennyslvania, USA), and was dried using anhydrous sodium sulfate (VWR; Pennyslvania, USA). The extract was then filtered and concentrated to 5 mL using a Buchi rotary evaporator (Flawil, Switzerland), and further concentrated to 1 mL using a nitrogen stream. The extract was stored at −20 °C until further analysis by GC-MS/FID. 2.4. GC-MS/FID analysis All of the analyses were carried out using an Agilent 7890B GC equipped with a flame ionisation detector (FID) for semi-quantitation and an Agilent 5977B mass selective detector (MSD) (California, USA)

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to tea leaves which induce volatile changes (e.g. increase in cis-3-hexenol) (Saijō & Takeo, 1973). Thus, this experiment aimed to clarify the impact of grinding on volatiles in tea. In the tea leaves, the extraction of volatiles was improved by grinding (Fig. 3). This may be attributed to the reduction of particle

3.1.2. Effect of grinding Research on the effects of grinding on tea has been primarily limited to non-volatiles such as theaflavins, amino acids and polysaccharides, which have shown profile variations with different degrees of grinding (Price & Spiro, 1985). Furthermore, grinding causes mechanical injuries

Fig. 1. Extraction temperature profiles of triplicate data of selected tea volatile compounds extracted using HS-SPME for 30 min: (a) Ground tea leaf; (b) Unground tea leaf; (c) Ground tea infusion; (d) Unground tea infusion.

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Fig. 1. (continued)

3.1.3. Effect of brewing As tea consumption is in the form of tea infusions, profiling volatiles from tea infusions is relevant to the understanding of the tea aroma perceived by consumers. This approach allows for the study of flavour development by identifying differences in volatiles between the tea leaves and tea infusions, which enables an understanding of flavour release during brewing. There were qualitative similarities between the

sizes resulting in increased surface area for extraction, which has been also been observed to enhance the extraction of non-volatiles in tea (Price & Spiro, 1985). However, this effect was not consistently seen in the tea infusions; the unground tea infusions contained higher amounts of hexanal, cis-3-hexenol and cis-jasmone than the ground tea infusions. The reduction of these volatiles may be due to participation in hydration reactions. 181

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to affect headspace volatile concentration which subsequently increased extraction efficiency (Magagna et al., 2017), but there are also compound-specific factors to consider. 2-Phenylethyl alcohol was detected in higher quantities in tea leaves (Fig. 3). However, due to its high solubility in water, it was poorly extracted into the headspace, accounting for the lower levels measured in the tea infusion.

tea leaf and tea infusion profiles, which are in agreement with one previous study which applied an alternative extraction method (Schuh & Schieberle, 2006). Variations between the tea leaves and tea infusions were observed for linalool, geraniol, β-ionone and indole, which were higher in the tea infusions compared to the tea leaves. The presence of water was shown

Fig. 2. Extraction time profiles of triplicate data of selected tea volatile compounds extracted using HS-SPME at 80 °C: (a) Ground tea leaf; (b) Unground tea leaf; (c) Ground tea infusion; (d) Unground tea infusion. 182

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Fig. 2. (continued)

distillation (Luo et al., 2013; Pennarun, Prost, & Demaimay, 2001), its effect has not been studied in tea analysis. In this research, water bath and condenser temperatures were optimised separately, followed by salt addition.

3.2. Optimisation of SAFE Increasing awareness of the relevance of volatiles to the sensory properties of tea prompted the selection of SAFE in this work, due to its ability to produce extracts characteristic of the sources (Elmore, 2015) by facilitating volatile separation from the tea matrix (Engel et al., 1999). While heating temperature has been recognised to affect

3.2.1. Effect of water bath temperature To understand the effect of water bath temperature, SAFE was 183

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Fig. 3. Comparison of triplicate data of selected tea volatile compounds extracted from tea leaf and infusion (ground and unground) extracted using HS-SPME at 80 °C for 60 min.

meaningful to study the trend associated with condenser temperature. In the present work, 35 °C was selected as the water bath temperature to optimise condenser temperature. In order to investigate the effect of condenser temperature, the condenser was applied at a range of temperatures (20, 30, 40, and 50 °C). Fig. 4(b) shows that the concentrations of the key volatiles progressively decreased with rising condenser temperatures, which is in contrast to the trend observed in the section above. 20 °C was found to have the best extraction efficiency and reproducibility. This could be due to the increased trapping of volatiles at lower condenser temperatures. However, with condenser temperatures below 20 °C, the SAFE experiments were not completed successfully as the sample was observed to enter the SAFE distillation head and collection flask (for a graphical representation, refer to the original publication on the design of SAFE apparatus (Engel et al., 1999)). With a reduction of water bath temperature to 20 °C, it was possible to use a lower condenser temperature since no sample entered our distillation head when the condenser was maintained at 15 °C. However, further temperature reduction of the condenser to 5 °C caused crystallisation in the outlet to the collection flask, which blocked the condensation of volatiles into the flask. To clarify the interlinked relationship of water bath and condenser temperatures, more trials will need to be conducted in future. In addition to the benefits of higher extraction efficiency at lower condenser temperatures, there are also lower operating costs as the consumption of liquid nitrogen is significantly reduced.

conducted at 20, 25, 30, and 35 °C respectively. From Fig. 4(a), the concentrations of the key volatiles were observed to either increase with rising water bath temperature, or remain relatively constant. Increased extraction efficiencies may be a result of thermally enhanced volatile vapourisation, being in agreement with findings from a study on temperature effects on SAFE (Mizukami & Yamaguchi, 2010). In contrast, hexanal, linalool, β-ionone and cis-jasmone concentrations were relatively constant, indicating that they may have been fully extracted at low temperatures. There have been multiple applications of reduced pressure distillation in tea volatile research, with heating temperatures mostly being around 30–40 °C (Kumazawa & Masuda, 2002; Mizukami, Sawai, & Yamaguchi, 2008). However, no attempts have been made to optimise this parameter. Moreover, some present distillation studies on the optimisation of water bath temperature have shown variations in total peak areas of aroma compounds (Luo et al., 2013) and aroma characteristics (Pennarun et al., 2001) with temperature changes, indicating the necessity of selecting a suitable water bath temperature. In this study, at temperatures above 35 °C, a cooked note was detected in the SAFE extract by sensory evaluation, indicating Maillard reaction-associated sugar degradation products such as furfural and 5-methylfurfural (Ho, Zheng, & Li, 2015). From these results, it was concluded that 35 °C was optimal due to the best extraction efficiency with limited thermal artefacts. 3.2.2. Effect of condenser temperature The condenser and water bath in the SAFE apparatus are commonly operated at the same temperature in most applications. While optimisation has been attempted for the water bath temperature (Mizukami & Yamaguchi, 2010), there has been no study on the effect of condenser temperature. Moreover, the SAFE apparatus differs from conventional vacuum distillation as it involves dropwise sample introduction. Due to this, the sample comes into contact with the condenser region twice; when the liquid sample goes through the first channel in the left condenser leg, and when the volatilised sample enters the condenser head through the second channel in the left condenser leg. Thus, SAFE is a more complex process than conventional distillation and it is

3.2.3. Effect of salt addition Salt addition has generally been recognised to improve extraction recovery by the salting out effect, in which analyte concentration in the equilibrium vapour is enhanced by the dissolution of a solid salt in the liquid phase containing volatiles. This may be due to vapour pressure reducing effects according to Raoult's law, which allows more volatiles to partition into the available headspace. Additionally, this has been attributed to possible interactions and structure-related effects in the liquid phase by the dissolved salt (Furter, 1992; Lei, Li, & Chen, 2003). However, the use of salt to optimise extraction is more well studied in

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Fig. 4. Extraction profiles of triplicate data of selected tea volatile compounds under different operational conditions extracted using SAFE: (a) Water bath temperature; (b) Condenser temperature; (c) Sample volume; (d) Salt addition.

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Fig. 4. (continued)

produced using vacuum distillation which utilises much lower temperatures to avoid artefact formation (Zhu et al., 2008). There were apparent differences observed between HS-SPME and SAFE in various categories of volatiles. The main alcohols extracted by SAFE were 1-penten-3-ol, 3-penten-2-ol and cis-2-pentenol, while HSSPME primarily extracted linalool, n-amyl alcohol and benzyl alcohol. The poorer extraction of acids from tea infusions compared to tea leaves may be attributed to their high solubility in water, similar to the trend exhibited by 2-phenylethyl alcohol as described earlier. Short chain acids from acetic acid to pentanoic acid were better extracted by HSSPME in tea leaves, while the medium chain acids from heptanoic acid onwards were detected in higher quantities in the SAFE extracts, corroborating that with increasing molecular weights, HS-SPME exhibits poorer extraction compared to SAFE, which is in agreement with findings from previous comparative studies between distillation and headspace extraction methods (Du et al., 2014; Garcia-Esteban et al., 2004).

HS-SPME (Teixeira, Mendes, Alves, & Santos, 2007), with limited application in distillation. Thus, this experiment aimed to contribute findings of the effect of salt addition on the extraction of flavour volatiles in distillation. The concentrations of the key volatiles were observed to increase by over 2-fold with the addition of 20% NaCl (w/w) (VWR; Pennyslvania, USA) to the tea sample (Fig. 4(c)). This could be due to the salting-out effect as mentioned previously. It was also observed that the more polar compounds such as 2-phenylethyl alcohol increased to a larger extent (∼6-fold) compared to non-polar compounds like hexanal (∼1.5-fold). Acids (e.g. acetic acid, propionic acid) in the tea were observed to increase significantly as well. This is in agreement with theoretical knowledge of the effects of the addition of an inorganic salt, which is known to have a larger effect on polar chemicals (Kolb & Ettre, 2006). Therefore, it is possible to use salt addition to enhance extraction efficiency in SAFE. 3.3. Comparison of HS-SPME and SAFE

4. Conclusion The volatile compounds extracted using HS-SPME and SAFE are listed in Table 1. The number of volatiles identified in SAFE was slightly more than that in HS-SPME. The existing studies have also shown differences in the volatile profiles of tea obtained from headspace and distillation extraction methods (Du et al., 2014; Sheibani, Duncan, Kuhn, Dietrich, & O'Keefe, 2016; Zhu, Li, & He, 2008). Distillation is able to facilitate high recoveries of semi-volatiles (Zhang et al., 2013), while HS-SPME is better for highly volatile compounds (Garcia-Esteban, Ansorena, Astiasaran, Martin, & Ruiz, 2004). While distillation recovers a higher proportion of higher molecular weight semi-volatiles which are likely to be less important for aroma partially due to their low volatility (Du et al., 2014), there is good repeatability for the extraction (Zhang et al., 2013). Furthermore, extracts close to the actual tea can be

After the optimisation of extraction temperature and time, HS-SPME was utilised to study the effects of grinding and brewing on tea volatiles. Grinding of the tea leaves generally improved the extraction of tea volatiles, and the volatile profiles of tea leaves and tea infusions were found to be qualitatively similar. In the present work, the parameters (water bath temperature, condenser temperature and salt addition) of SAFE were optimised. Compared to condenser temperature, water bath temperature was a more significant factor. On the other hand, salt addition was found to be the most effective factor enhancing extraction. Overall, this work provided further insight into the analysis of tea volatiles using HS-SPME as well as SAFE, which will be attempted in our next study.

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Table 1 Identification and semi-quantification (FID peak areas) of tea volatile compounds extracted using HS-SPME (80 °C for 60 min) and SAFE (water bath temperature of 35 °C, condenser temperature of 20 °C, sample volume of 500 mL). Compound

LRI

HS-SPME

SAFE

Tea Infusion

a

Dimethyl sulfide 2-Methylbutanal a Pentanal a 2,3-Pentanedione a,c Butyl acetate a Hexanal a,b,c 1-Penten-3-ol d 3-Penten-2-ol 1-Ethylpyrrole a Heptanal a Limonene a trans-2-Hexenal a, d 2-Pentylfuran a n-Amyl alcohol a,d trans-Ocimene a 2-Methylpyrazine a para-Cymene a Octanal a, c trans-2-Pentenol a,d cis-2-Pentenol a 2,3-Octanedione a 2,6-Dimethyl pyrazine a trans-2-Heptenal a 2,5-Dimethyl pyrazine a 6-Methyl-5-hepten-2-one a,d Hexanol a 2,3-Dimethyl pyrazine a cis-3-Hexenol a,c,d 2-Nonanone a 2-Ethyl-6-methyl pyrazine Nonanal a, c 2-Ethyl-5-methyl pyrazine a trans-2-Hexenol a 2,6-Diethyl pyrazine a 1-Octen-3-ol (a) cis-Linalool oxide (furanoid) a,d 1-Heptanol a 2-Ethyl-3,6-dimethyl pyrazine c Acetic acid a 2-Ethyl-3,5-dimethyl pyrazine b,c trans, cis-2,4-Heptadienal a,d trans-Linalool oxide (furanoid) a,d Furfural a 2-Methyl-3,5-diethyl pyrazine a trans, trans-2,4-Heptadienal a,c 2-Acetylfuran a trans,cis-3,5-Octadien-2-one a d-Camphor a Propionic acid a Linalool a,b,c,d Benzaldehyde a,d Octanol a 2-Methylpropanoic acid a trans,trans-3,5-Octadien-2-one a β-Caryophyllene a 5-Methylfurfural a 2-Undecanone a Hotrienol d Terpinen-4-ol a 2-Acetyl pyridine a β-Cyclocitral a cis-3-Hexenyl hexanoate a Phenylacetaldehyde a,b,c Safranal a Furfuryl alcohol a 2/3-Methyl butanoic acid a,b Acetophenone a α-Terpineol a cis-3-Hexenyl cis-3-hexanoate

464 944 1008 1073 1090 1102 1173 1183 1203 1204 1213 1241 1249 1265 1267 1289 1290 1308 1324 1332 1340 1345 1348 1351 1357 1364 1371 1397 1408 1407 1413 1414 1419 1456 1460 1462 1466 1467 1469 1483 1490 1491 1492 1512 1522 1535 1545 1545 1555 1559 1560 1569 1573 1597 1600 1605 1606 1625 1626 1639 1656 1676 1681 1682 1683 1685 1689 1720 1735

Tea Leaf

Tea Infusion

Peak Area

%

Peak Area

%

Concentration (ng/mL)

%

1573317 ± 202493 693559 ± 60005 711895 ± 74267 – – 389081 ± 154505 212748 ± 46044 – 199326 ± 69839 144339 ± 50573 339914 ± 35422 15769 ± 9703 111253 ± 49635 1448209 ± 213395 60342 ± 8891 65907 ± 16052 161194 ± 18362 99845 ± 31591 – 210357 ± 37257 408340 ± 72321 68056 ± 15592 110634 ± 21811 141646 ± 34652 284486 ± 56085 60706 ± 14851 – 157666 ± 18922 21529 ± 2514 41931 ± 12042 315211 ± 165824 30996 ± 7917 – – 436110 ± 37492 59470 ± 5113 – 81122 ± 4054 104839 ± 35071 21577 ± 1791 – 72236 ± 5997 115426 ± 44349 12212 ± 3160 111100 ± 89098 13125 ± 743 716449 ± 958271 29852 ± 39928 18438 ± 6172 1825408 ± 610979 656368 ± 562677 117209 ± 100478 – 81156 ± 17710 356 ± 144 29225 ± 11818 6059 ± 2450 343667 ± 253161 2994 ± 2205 – 520932 ± 87589 46838 ± 19011 167966 ± 35868 98803 ± 21099 – 9880 ± 2110 43026 ± 1926 75745 ± 8350 26157 ± 10835

9.18 ± 1.18 4.05 ± 0.35 4.15 ± 0.43 – – 2.27 ± 0.90 1.24 ± 0.27 0.00 ± 1.16 ± 0.41 0.84 ± 0.29 1.98 ± 0.21 0.09 ± 0.06 0.65 ± 0.29 8.45 ± 1.24 0.35 ± 0.05 0.38 ± 0.09 0.94 ± 0.11 0.49 ± 0.3 – 1.23 ± 0.22 2.38 ± 0.42 0.40 ± 0.09 0.65 ± 0.13 0.83 ± 0.20 1.66 ± 0.33 0.35 ± 0.09 – 0.92 ± 0.11 0.13 ± 0.01 0.24 ± 0.07 1.84 ± 0.97 0.18 ± 0.05 – – 2.54 ± 0.22 0.35 ± 0.03 – 0.47 ± 0.02 0.61 ± 0.20 0.13 ± 0.01 – 0.42 ± 0.03 0.67 ± 0.26 0.07 ± 0.02 0.65 ± 0.52 0.08 ± 0.00 4.18 ± 5.59 0.17 ± 0.23 0.11 ± 0.04 10.65 ± 3.56 3.83 ± 3.28 0.68 ± 0.59 – 0.47 ± 0.10 0.00 ± 0.17 ± 0.07 0.04 ± 0.01 2.00 ± 1.48 0.02 ± 0.01 – 3.04 ± 0.51 0.27 ± 0.11 0.98 ± 0.21 0.58 ± 0.12 – 0.06 ± 0.01 0.25 ± 0.01 0.44 ± 0.05 0.15 ± 0.06

1922136 ± 276208 1761373 ± 295780 2294205 ± 824400 – – 423719 ± 119760 708457 ± 229076 – 45144 ± 7644 519159 ± 87910 246419 ± 7186 13115 ± 10356 19688 ± 3220 596861 ± 161269 12181 ± 3291 47041 ± 8944 47500 ± 9032 102943 ± 19574 – 275169 ± 63644 135531 ± 31347 16004 ± 6585 122092 ± 55395 35989 ± 12356 48297 ± 6979 43986 ± 15102 – 144863 ± 44219 68744 ± 26881 21380 ± 7014 264725 ± 56624 23757 ± 6092 – – 136542 ± 38380 27966 ± 7861 – 92645 ± 23543 4497537 ± 1369060 3452 ± 1025 – 82844 ± 24608 68866 ± 16705 10031 ± 5640 27985 ± 10187 – 92381 ± 20679 33554 ± 24144 453974 ± 80329 337021 ± 34533 140450 ± 35383 164143 ± 24071 18690 ± 2395 32942 ± 5201 9990 ± 935 14376 ± 1345 – 35554 ± 7359 4248 ± 879 – 262669 ± 587 39250 ± 6531 65582 ± 19396 29147 ± 8621 – 135038 ± 28105 Trace 15232 ± 7034 3455 ± 740

9.61 ± 1.38 8.81 ± 1.48 11.47 ± 4.12 – – 2.12 ± 0.60 3.54 ± 1.15 – 0.23 ± 0.04 2.60 ± 0.44 1.23 ± 0.04 0.07 ± 0.05 0.10 ± 0.02 2.98 ± 0.81 0.06 ± 0.02 0.24 ± 0.04 0.24 ± 0.05 0.51 ± 0.10 – 1.38 ± 0.32 0.68 ± 0.16 0.08 ± 0.03 0.61 ± 0.28 0.18 ± 0.06 0.24 ± 0.03 0.22 ± 0.08 – 0.72 ± 0.22 0.34 ± 0.13 0.11 ± 0.04 1.32 ± 0.28 0.12 ± 0.03 – – 0.68 ± 0.19 0.14 ± 0.04 – 0.46 ± 0.12 22.49 ± 6.85 0.02 ± 0.01 – 0.41 ± 0.12 0.34 ± 0.08 0.05 ± 0.03 0.14 ± 0.05 – 0.46 ± 0.10 0.17 ± 0.12 2.27 ± 0.40 1.69 ± 0.17 0.70 ± 0.18 0.82 ± 0.12 0.09 ± 0.01 0.16 ± 0.03 0.05 ± 0.00 0.07 ± 0.01 – 0.18 ± 0.04 0.02 ± 0.00 – 1.31 ± 0.00 0.20 ± 0.03 0.33 ± 0.10 0.15 ± 0.04 – 0.68 ± 0.14 Trace 0.08 ± 0.04 0.02 ± 0.00

– – 140.22 ± 46.47 61.47 ± 18.90 4.66 ± 4.73 169.04 ± 52.68 1162.75 ± 357.36 3148.38 ± 918.49 73.93 ± 23.51 22.08 ± 7.02 2.53 ± 1.29 27.31 ± 8.05 – 277.35 ± 85.44 – 135.87 ± 35.24 – – 61.11 ± 21.30 689.17 ± 214.38 3.55 ± 1.40 205.51 ± 47.70 – 23.39 ± 6.31 76.02 ± 23.12 78.29 ± 26.14 8.08 ± 1.65 322.06 ± 95.37 – 9.36 ± 1.21 14.51 ± 4.53 58.48 ± 13.03 21.92 ± 6.60 1.62 ± 0.53 42.91 ± 12.41 77.18 ± 25.37 5.87 ± 1.52 43.01 ± 11.17 39.24 ± 18.78 15.8 ± 4.76 105.73 ± 31.09 64.19 ± 18.88 203.91 ± 59.96 – 326.3 ± 95.74 44.67 ± 13.16 215.69 ± 62.06 12.74 ± 4.66 19.76 ± 5.97 158.04 ± 47.77 316.08 ± 95.53 – – 47.15 ± 14.40 – 65.88 ± 17.68 – 83.83 ± 24.00 1.84 ± 0.46 0.59 ± 0.26 34.31 ± 10.38 – 185.74 ± 59.39 6.12 ± 1.96 23.51 ± 7.52 – 66.84 ± 31.62 33.32 ± 9.77 6.13 ± 1.46

– – 1.13 ± 0.31 0.50 ± 0.13 0.04 ± 0.03 1.36 ± 0.33 9.40 ± 2.57 25.42 ± 6.44 0.59 ± 0.15 0.18 ± 0.05 0.02 ± 0.01 0.22 ± 0.06 – 2.23 ± 0.64 – 1.10 ± 0.28 – – 0.49 ± 0.16 5.57 ± 1.52 0.03 ± 0.01 1.66 ± 0.42 – 0.19 ± 0.06 0.61 ± 0.18 0.63 ± 0.19 0.07 ± 0.01 2.61 ± 0.70 – 0.08 ± 0.01 0.12 ± 0.03 0.48 ± 0.11 0.18 ± 0.05 0.01 ± 0.01 0.35 ± 0.09 0.63 ± 0.20 0.05 ± 0.01 0.35 ± 0.09 0.32 ± 0.15 0.13 ± 0.04 0.85 ± 0.85 0.52 ± 0.12 1.64 ± 0.39 – 2.63 ± 0.64 0.36 ± 0.10 1.74 ± 0.44 0.10 ± 0.04 0.16 ± 0.05 1.28 ± 0.36 2.56 ± 0.72 – – 0.38 ± 0.10 – 0.54 ± 0.15 – 0.68 ± 0.20 0.02 ± 0.01 0.00 ± 0.00 0.28 ± 0.08 – 1.49 ± 0.39 0.05 ± 0.01 0.25 ± 0.19 – 0.54 ± 0.23 0.27 ± 0.08 0.05 ± 0.01

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Table 1 (continued) Compound

LRI

HS-SPME

SAFE

Tea Infusion

Pentanoic acid a Benzyl acetate a cis-Linalool oxide (pyranoid) a,b Geranial a trans-Linalool oxide (pyranoid) a,b Methyl salicylate a,d Hexanoic acid a,d Geraniol a,b,c,d Geranyl acetone a,c α-Ionone a Guaiacol a,c Benzyl alcohol a,d 2-Phenylethyl alcohol a Heptanoic acid a β-Ionone a cis-Jasmone a,c Maltol b 2-Acetylpyrrole a β-Ionone epoxide a Phenol a Nerolidol a Furaneol b,c Octanoic acid a para-Cresol a,b,c Nonanoic acid a 4-Vinyl guaiacol a,b,c cis-Theaspirone a Decanoic acid a Methyl anthranilate a,b,c Geranic acid a Dihydroactinidiolide a Dodecanoic acid a Indole a,b,c Coumarin a,b,c Vanillin a,b,c Caffeine

1755 1761 1762 1763 1782 1819 1864 1865 1878 1885 1895 1909 1948 1968 1975 1984 2006 2008 2033 2036 2054 2068 2076 2123 2181 2234 2238 2287 2289 2360 2422 2499 2502 2527 2617 3179

Tea Leaf

Peak Area

%

3676 ± 1749 2451 ± 1166 18909 ± 2635 32196 ± 4487 68654 ± 9441 21498 ± 6227 103378 ± 43042 249188 ± 28602 26939 ± 3092 202045 ± 23191 – 117799 ± 21025 221027 ± 29017 20093 ± 2638 763548 ± 100239 181114 ± 44578 11074 ± 3024 65622 ± 17746 147129 ± 40178 28069 ± 8702 32478 ± 10183 – 49054 ± 24437 4439 ± 1325 274825 ± 114636 12476 ± 1698 28903 ± 9572 5799 ± 2464 – 18743 ± 9215 95083 ± 35180 – 124549 ± 37996 Trace Trace 308581 ± 112456

0.02 ± 0.01 ± 0.11 ± 0.19 ± 0.40 ± 0.13 ± 0.60 ± 1.45 ± 0.16 ± 1.18 ± – 0.69 ± 1.29 ± 0.12 ± 4.45 ± 1.06 ± 0.06 ± 0.38 ± 0.86 ± 0.16 ± 0.19 ± – 0.29 ± 0.03 ± 1.60 ± 0.07 ± 0.17 ± 0.03 ± – 0.11 ± 0.55 ± – 0.73 ± Trace Trace 1.80 ±

0.01 0.01 0.02 0.03 0.06 0.04 0.25 0.17 0.02 0.14 0.12 0.17 0.02 0.58 0.26 0.02 0.10 0.23 0.05 0.06 0.14 0.01 0.67 0.01 0.06 0.01 0.05 0.21 0.22

0.66

Tea Infusion

Peak Area

%

121661 ± 35014 5069 ± 1459 32986 ± 4076 7737 ± 956 181064 ± 31543 11938 ± 3110 186717 ± 44499 121539 ± 11912 16817 ± 2494 57815 ± 10786 – 966616 ± 93466 11125 ± 2620 117726 ± 47158 259656 ± 32782 32166 ± 4279 7102 ± 2007 96345 ± 30271 110831 ± 12236 13698 ± 1512 6496 ± 286 – 91079 ± 26379 – 158639 ± 48276 7229 ± 3228 6895 ± 432 – – – 225298 ± 34854 – 7824 ± 3867 – Trace 337526 ± 23674

0.61 ± 0.03 ± 0.16 ± 0.04 ± 0.91 ± 0.06 ± 0.93 ± 0.61 ± 0.08 ± 0.29 ± – 4.83 ± 0.06 ± 0.59 ± 1.30 ± 0.16 ± 0.04 ± 0.48 ± 0.55 ± 0.07 ± 0.03 ± – 0.46 ± – 0.79 ± 0.04 ± 0.03 ± – – – 1.13 ± – 0.04 ± – Trace 1.69 ±

0.18 0.01 0.02 0.00 0.16 0.02 0.22 0.06 0.01 0.05 0.47 0.01 0.24 0.16 0.02 0.01 0.15 0.06 0.01 0.00 0.13 0.24 0.02 0.00

0.17 0.02

0.12

Concentration (ng/mL)

%

– – 18.01 ± 4.53 – 124.56 ± 37.7 33.85 ± 11.39 36.84 ± 10.63 270.14 ± 77.98 6.90 ± 1.78 21.84 ± 5.65 2.85 ± 0.54 484.46 ± 128.95 466.48 ± 126.96 23.18 ± 6.00 96.13 ± 29.18 94.33 ± 9.80 158.53 ± 179.99 191.09 ± 80.14 68.15 ± 10.48 43.07 ± 12.65 1.36 ± 0.57 4.54 ± 0.73 20.68 ± 5.91 13.96 ± 4.25 81.54 ± 24.08 2.44 ± 0.44 16.33 ± 2.92 9.97 ± 2.82 5.12 ± 1.37 61.99 ± 43.00 116.69 ± 30.51 185.29 ± 52.69 479.27 ± 114.68 49.41 ± 15.49 2.45 ± 0.65 126.23 ± 44.43

– – 0.15 – 1.01 0.27 0.30 2.19 0.06 0.18 0.02 3.92 3.78 0.19 0.78 0.78 1.21 1.62 0.56 0.35 0.01 0.04 0.17 0.11 0.66 0.02 0.13 0.08 0.04 0.49 0.95 1.50 3.86 0.40 0.02 1.01

± 0.04 ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.28 0.08 0.08 0.61 0.01 0.04 0.00 0.99 0.99 0.05 0.23 0.19 1.29 0.89 0.17 0.09 0.01 0.00 0.05 0.03 0.20 0.00 0.01 0.02 0.01 0.31 0.29 0.41 0.79 0.11 0.01 0.27

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