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Article

Determination of Five Phthalate Esters in Tea and Their Dynamic Characteristics during Black Tea Processing

by
Yanyan Tang
†,
Mengxin Wang
†,
Cheng Pan
,
Shuishan Mi
and
Baoyu Han
*
Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Foods 2022, 11(9), 1266; https://doi.org/10.3390/foods11091266
Submission received: 4 April 2022 / Revised: 22 April 2022 / Accepted: 25 April 2022 / Published: 27 April 2022
(This article belongs to the Section Food Analytical Methods)
Browse Figures
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Abstract

:
A highly specific and high extraction-rate method for the analysis of dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), diisobutyl phthalate (DiBP), and di-(2-ethyl) hexyl phthalate (DEHP) in tea samples was developed. Based on three-factor Box–Behnken response surface design, solid-phase extraction (SPE) of five phthalate ester (PAE) residues in tea was optimized. Optimal extraction conditions were found for extraction temperature (40 °C), extraction time (12 h), and ratio of tea to n-hexane (1:20). The dynamic distribution of PAEs at each stage of black tea processing was also analyzed, and it was found that the baking process was the main stage of PAE emission, indicating that traditional processing of black tea significantly degrades PAEs. Further, principal component analysis of the physicochemical properties and processing factors of the five PAEs identified the main processing stages affecting the release of PAEs, and it was found that the degradation of PAEs during black tea processing is also related to its own physicochemical properties, especially the octanol–water partition coefficient. These results can provide important references for the detection, determination of processing losses, and control of maximum residue limits (MRLs) of PAEs to ensure the quality and safety of black tea.

Graphical Abstract

1. Introduction

Phthalate esters (PAEs) are a type of additives used to enhance the flexibility of materials; they are widely used in plastic products and account for 80% of the total plasticizers [1,2]. PAEs are not chemically bonded to the polymer matrix, and therefore, they are easily released from the plastic and enter the environment, where they are difficult to degrade [3,4]. It is well known that PAEs can interfere with the human endocrine system and have teratogenic, carcinogenic, and mutagenic potential [5,6,7,8]. The United States Environmental Protection Agency has listed six PAEs, including dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), butyl benzyl phthalate (BBP), di-(2-ethyl) hexyl phthalate (DEHP), and di-n-octyl phthalate (DnOP), as toxic pollutants for priority control [9]. China has also issued a number of relevant standards and regulations to regulate PAEs, especially to control the contamination of food by PAEs. At this point, PAEs have become widespread environmental pollutants, and there are a lot of reports of PAEs in food [10,11] and materials in contact with food [12,13], with a focus on sample pretreatment and detection methods. Pretreatment methods mainly include solid-phase extraction (SPE) [14], solid-phase microextraction (SPME) [15], liquid–liquid extraction (LLE) [16], dispersive liquid–liquid microextraction (DLLME) [17], gas–liquid micro-extraction (GLME) [18], microwave-assisted extraction (MAE) [8,19], and isotope dilution [20]. The methods to detect PAEs mainly include supercritical fluid chromatography [21], gas chromatography–mass spectrometry (GC–MS) [22], gas chromatography tandem mass spectrometry (GC–MS/MS) [10,23], high performance liquid chromatography (HPLC) [24], high-performance liquid chromatography–electrospray ionization-mass spectrometry (HPLC–ESI-MS) [25], and liquid chromatography tandem mass spectrometry (LC-MS/MS) [26,27]. It can be seen that many scholars have been paying attention to and studying PAEs pollutants, however, there are few studies on the content and pollution characteristics of PAEs in teas.
In the 1970s to 1980s, domestic researchers in China occasionally detected residual PAEs from green tea and black tea. In the past 20 years, more and more studies have reported the detection of PAEs in various types of tea. Now, the probability of detecting PAEs in fresh tea leaves, tea during processing, and finished tea is 100%, which indicates all aspects of tea production are likely contaminated by PAEs. PAEs include more than 20 compounds, of which DBP, di-isobutyl phthalate (DiBP), DEP, DEHP, and DMP are the most commonly detected in tea [28,29]. Several methods of detecting PAEs in tea and tea infusions have been established [25,26,28,29,30], and the total loss rate of PAEs during green tea processing has also been investigated; for example, the loss rate of PAEs caused by the drying process accounts for 61.3–73.7% of the total loss rate [29].
Black tea makes up the highest proportion of tea production and sales in the world, accounting for approximately 70% of the total tea products globally. Black tea originated from China hundreds of years ago and gradually evolved into three types: congou black tea, souchong black tea, and broken black tea. Usually, countries other than China only produce broken black tea. Frequently, the detection of PAEs in black tea has aroused the concern of the tea industry. However, the dynamic characteristics of PAE residues in black tea processing, methods to prevent PAEs from contaminating black tea, and means of removing a portion of PAEs effectively by processing remain unclear.
Congou black tea is mainly produced in China and is the major type of black tea. It is processed from fresh leaves, usually through four processes: withering, rolling, fermentation, and drying (primary drying and baking). In this study, we developed a detection method to enrich, purify, and extract the PAEs in tea using solid-phase extraction technology. GC–MS was used for the qualitative and quantitative analysis of the extracted PAEs. Later, we used the established method to detect the content and changes of DMP, DEP, DiBP, DBP, and DEHP in each stage of black tea production, and evaluated their dynamic characteristics and possible causes. We expect to develop an environmentally friendly and highly efficient method for the extraction and accurate quantification of PAEs in tea, and to use the method to determine and evaluate the residual dynamics, variation, and pollution levels of PAEs during black tea processing. This method can provide a reference for the prevention and suppression of the pollution of black tea by PAEs.

2. Materials and Methods

2.1. Reagents and Standards for PAEs

Five PAE analytical standards (≥99.0%) of DMP, DEP, DiBP, DBP, and DEHP were purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany). Optima GC–MS grade toluene, acetonitrile, and n-hexane were purchased from Tedia Co., Inc. (Fairfield, OH, USA). Analytical grade sodium chloride and anhydrous ethanol were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Solid-phase extraction glass columns (CARB/NH2, 1000 mg/6 mL) were purchased from Dikma Technologies Inc. (Beijing, China).
To remove possible cross-contamination of PAEs, all glassware and chinaware used in the study were immersed in methanol overnight, rinsed with hexane, and dried at 140 °C for at least 4 h. Organic solvents were redistilled before being used. Sodium chloride was heated at 450 °C for 4 h in a muffle furnace and kept in sealed glass vials after cooling. For PAE analysis, a procedural blank and solvent blank were run with every batch of samples for quality assurance and quality control.

2.2. Tea Sampling

In April 2021, fresh and tender tea shoots were plucked and processed to black tea using the following process in an organic tea garden in Zhejiang Gengxiang Organic Tea Development Co., Ltd., Wuyi County, Zhejiang, China. The tea variety Jiukeng, aged more than 6 years, was chosen for the present study. The standard for fresh tea shoots is one bud and two leaves. One bud and two leaves were transported to the tea processing workshop, spread to dry for 0.5 h at 25 °C, withered for 6 h at 32 °C, rolled for 1.5 h at 25–28 °C, fermented for 3 h at 35 °C, primary dried for 8 min at 110 °C, and far-infrared aroma-enhanced dried (far-infrared aroma- enhanced machine model: DXCWS-05, Jiangsu, China) for 14 min at 100 °C before storage in glass bottles for tea sampling.
The sampling process proceeded according to national standard GB/T 8302-2013 [31]. In short, sampling was conducted at six stages during tea processing: plucking of fresh leaves, end of withering (withered sample), end of rolling (rolled sample), end of fermentation (fermented sample), end of initial drying (first drying sample), and end of far-infrared aroma-enhanced baking sample (finished tea sample). Samples were immediately stabilized in liquid nitrogen and stored in a −80 °C ultra-low temperature freezer for later usage.

2.3. Construction of Standard Curves of PAEs

Mixed standard stock solution was prepared. Briefly, equal amounts of DMP, DEP, DiBP, DBP, and DEHP were pipetted into a 100 mL volumetric flask and accurately diluted with n-hexane to a final concentration of 1 μg/mL mixed standard stock solution. Mixed standard stock solutions were stored at −20 °C until further usage.
Matrix-matched standard working solution was prepared. Briefly, the above mixed standard stock solution was serially diluted with the blank sample. The matrix-matched standard working solution was made fresh with concentrations of 0 μg/L, 1 μg/L, 5 μg/L, 10 μg/L, 20 μg/L, 50 μg/L, 100 μg/L, 200 μg/L, 500 μg/L, and 1000 μg/L; these were used to make the standard working curve (Table S1).

2.4. Extraction of PAEs in Tea

The method used to determine PAEs in tea was optimized and modified from the national standard GB 5009.271-2016 [32]. In short, 2 g of crushed and mixed tea samples were accurately weighed and put into a 40 mL glass centrifuge tube. Then, 2 g of sodium chloride and 20 mL of n-hexane were added. The samples were then mixed using a vortex shaker for 1 min. Samples were placed in a 40 °C water bath for 12 h, then were centrifuged at 3000 r min−1 for 2 min at 10 °C (Eppendorf, Mississauga, ON, Canada) for collection of the supernatant. Another 20 mL n-hexane was added to the precipitate, which was then shaken and centrifuged at 3000 r/min for 2 min at 10 °C. The supernatants were collected and combined with the previous supernatant. The supernatants were distilled to near dry by rotary evaporation in a 40 °C water bath (Rikakikai Co., LTD, Tokyo, Japan). Then, 8 mL of acetonitrile–toluene (3:1, v/v) mixture was added to dissolve the dried supernatant, which was then transferred into a glass SPE column, and the effluent was collected. The glass SPE column was activated with 10 mL of acetonitrile–toluene (3:1, v/v) mixture, and the effluent was discarded before use. Another 22 mL of acetonitrile–toluene (3:1, v/v) mixture was added to the column. The second eluate was collected and combined with the previous one. The eluates were distilled by rotary evaporation in a 40 °C water bath to dry. The final extracts were cooled and reconstituted with 1 mL n-hexane, vortexed, and filtered (0.45 μm cellulose acetate syring filters) for GC–MS analysis.

2.5. Optimization of PAE Extractions in Tea Using Response Surface Methodology

The response surface method is a method to optimize processing workflows and experimental conditions and is suitable for solving nonlinear data processing problems [33]. Three factors, including solid to liquid ratios (1:10, 1:15, 1:20, 1:25, 1:30), extraction time (3 h, 6 h, 9 h, 12 h, 18 h, 24 h), and extraction temperature (20 °C, 30 °C, 40 °C, 50 °C, 60 °C), were set up and tuned to optimize the above extraction conditions by using the response surface method. Single-factor experiments were performed first, and each experiment was conducted in triplicate.
Later, based on the results from the single-factor test, the solid-to-liquid ratio (A), extraction temperature (B), and extraction time (C) were used as the independent variables of the response surface test. The amount of extracted PAEs in tea (Y) was used as the response value, and the process was optimized by Box–Behnken analysis. Variance analysis and response contour map analysis were carried out to optimize the extraction conditions of PAEs in tea. The optimal conditions were used to predict the response in other experiments.

2.6. GC–MS Analysis

Samples were analyzed by gas chromatography–mass spectrometry (GC–MS) using an Agilent 6890A GC coupled to an MSD 6975 (Agilent Technologies, Wilmington, DE, USA) with an HP-5MS quartz capillary column (30.0 m × 250 μm × 0.25 μm). The injector volume was 1 μL in splitless mode, and the inlet temperature was set to 300 °C. The flowrate of the carrier gas (99.999% high-purity helium) was 1.0 mL min−1. The temperature was programmed as follows: the initial temperature of 80 °C was held for 1 min; the temperature was raised to 140 °C at 5 °C/min and held for 2 min; the temperature was raised to 170 °C at 3 °C/min and held for 2 min; then the temperature was increased to 280 °C at 5 °C/min and held at 280 °C for 1 min. The solvent delay was 5 min. The mass spectrometry was set up as follows: EI source temperature, 230 °C; ionization energy, 70 eV; and quadrupole temperature, 150 °C. Full scan mode was used for the qualitative analysis, with a mass range of 30–400 m/z.

2.7. Method Validation

The accuracy of the developed extraction method was validated by evaluating the linearity, accuracy, precision, limit of quantification, standard recovery, and matrix effect. The matrix effect (ME) was evaluated by analyzing the ratio of the slope of the matrix-matched standard curve to the slope of the solvent standard curve [34]. If the ME is higher than 1, the matrix has an enhancing effect on the result. On the other hand, an ME < 1 indicates an inhibitory effect. According to the linear range of the five PAEs and the dilution ratio of the sample pretreatment, the mixed standard solutions with three concentration gradients (100 μg/mL, 500 μg/mL, and 1000 μg/mL) were added to the blank tea samples. Each gradient contained three parallel samples. PAE extraction was carried out under the optimum extraction conditions according to the method described. The recoveries and the relative standard deviation of five PAEs were also calculated.

2.8. Statistical Data Analysis

One-way analysis of variance (ANOVA) was performed using SPSS 22.0, and multiple comparison analysis was performed using Duncan’s new multiple range test. Design-Expert V8.0.6.1 (Stat-Ease, Inc., Minneapolis, MN, USA) was used for the experimental design of Box–Behnken central combined experiment and data processing [35].
The processing factor (PF) proposed by the United States Environmental Protection Agency (EPA) was used to evaluate the effect of processing technology on the content of PAEs in tea during processing. PF > 1 indicates a processing enrichment effect, and PF < 1 suggested a processing dilution effect [36]. PF was calculated as follows:
PF = M2/M1
where M1 is the level of PAE residues in fresh tea (μg/kg), and M2 is the level of PAE residues after processing (μg/kg).

3. Results

3.1. Effects of Single Factors on Extraction of PAEs from Tea

Single-factor experiments were carried out with different extraction temperatures as the single variable. The extraction conditions were as follows: fresh leaves of Jiukeng cultivar 2 g, solid to liquid ratio 1:20, extraction time 12 h, and different temperatures of 20 °C, 30 °C, 40 °C, 50 °C, and 60 °C. As the extraction temperature increased, the amount of extracted PAEs from tea first increased and then decreased, reaching peak extraction at a temperature of 40 °C (Figure 1a). Among the five PAEs detected, DBP accounted for the largest proportion (57.40–87.85%), DEHP accounted for the smallest proportion (2.25–9.29%), and DMP, DEP, and DiBP showed little difference.
Single-factor experiments were carried out with different extraction times as the single variable. The extraction conditions were as follows: fresh leaves of Jiukeng cultivar 2 g, solid–liquid ratio 1:20, extraction temperature 40 °C, and different extraction times were set as 3 h, 6 h, 9 h, 12 h, 18 h, and 24 h. It was found that with the increase of extraction time, the amount of extracted PAEs in tea also first increased and then decreased, and the extraction amount was the highest when the extraction time was 12 h (Figure 1b). Similarly, DBP accounted for the highest proportion (31.45–87.24%) of the five PAEs extracted at the different extraction times, and the amount of extracted DBP changed most significantly with the extension of extraction time. The extraction amount of the other four PAEs did not change significantly within the different extraction times.
Single-factor experiments were carried out with different solid–liquid ratios as the single variable. The extraction conditions were as follows: fresh leaves of Jiukeng cultivar 2 g, extraction temperature 40 °C, extraction time 12 h, and different solid–liquid ratios of 1:10, 1:15, 1:20, 1:25, and 1:30. The results suggest that the amount of PAEs extracted from tea was the highest with a solid-to-liquid ratio of 1:20. The amount of DBP accounted for the largest proportion (56.17–66.97%) of the total content of PAEs, and DEHP content was the least (4.45–6.27%) (Figure 1c). No significant differences were found among the amount of DMP, DEP, and DIBP.

3.2. Response Surface Optimization Experiment

Based on the results from single-factor experiments and the principle of central combination design of the Box–Behnken response surface method [33], a three-factor and three-level response surface experiment was designed. This experiment focused on identifying the effect of each factor on the extraction of PAEs in tea and the interaction between the factors. The solid–liquid ratio (A), extraction temperature (B), and extraction time (C) were chosen as three independent variables, and the amount of PAEs extracted from tea was used as the dependent variable (Y, response value). All other conditions were the same. The detailed experimental design and results of the response surface experiment are shown in Table 1, including the experimental values and those predicted by the model. The following multiple regression equation, obtained by Design-Expert V8.0.6.1 software, using multiple regression fitting of the data in Table 1 is shown: Y = 567.92 − 17.28A + 28.44B + 107.34C − 10.93AB − 8.77AC + 4.24BC − 158.79A2 − 137.54B2 − 140.13 C2.
The experimental data were analyzed by ANOVA, and the significance of the coefficients of the regression was evaluated by their corresponding p-values. As Table 2 indicates, the p-value of the model (p < 0.01) indicates that the model is significant. The lack-of-fit p-value of 0.4980 implies that it was not significant (no lack-of-fit factor observed). These values indicate that the regression equation can be used to analyze the experimental results. The adjusted coefficient of determination of the model (R2adj = 0.9202) was very high and indicated that the model had only 7.98% of the variation that can be explained by the model. The following parameters in the equation indicate that the model is significant, the degree of fit was high, the error of experimental prediction was small, and the data were reproducible: correlation coefficient R2 = 0.9651, predicted R2 = 0.7364, the difference between R2 and R2adj < 0.1, the difference between R2adj and predicted R2 < 0.2, Adeq Precision = 11.872 > 4. These results suggest the equation has good performance and reflects the effect of three factors on the extraction of PAEs from tea. Factors C, A2, B2, and C2 all showed a highly significant effect (p < 0.05). The order of the influence of the three factors on the extraction of PAEs was as follows: C > B > A.
The 3D response surface map of the interaction of solid–liquid ratio, extraction time, and extraction temperature on the extraction of tea PAEs is shown in Figure 2. The response surface map is a three-dimensional surface map formed by the extracted amount of PAEs from tea and various influencing factors, and reflects the interaction between the optimal extraction points and different parameters. If the curve is steeper, the effect of this factor on the extraction of PAEs from tea is greater. Extraction time has the greatest influence on the extraction of PAEs, followed by extraction temperature, and the solid-to-liquid ratio has the least influence (Figure 2). The interaction between the solid-to-liquid ratio and extraction temperature is the largest, followed by the solid-to-liquid ratio and extraction time, and the extraction temperature and extraction time shows the least obvious interaction.
According to the results of response surface analysis, the optimal conditions for the extraction of PAEs from tea are: solid-to-liquid ratio 1:20, extraction temperature 40 °C, and extraction time 12 h. Under these conditions, the theoretical prediction of PAE content is 585.85 μg/kg. For validation of the optimal extraction conditions, three groups of parallel experiments were performed. The average measured and the relative error were 574.50 μg/kg and 1.98%, respectively, which suggests that the prediction of the regression model is accurate, reliable, and reproducible.

3.3. Validation of the Developed Method

A matrix-matched working standard solution with a concentration in the range of 1–1000 μg/L was prepared. The standards were measured under the predetermined GC–MS conditions, and a calibration curve was established. The total ion chromatograms of the five PAEs and n-hexane solution are shown in Figure 3, and their mass spectrometry characteristics are shown in Table 3. The five compounds all had good discrimination and flat baseline, and the noise in the chromatogram can be ignored. These results suggest that the detection of PAEs using GC–MS is reliable.
The linearity, accuracy, precision, the limit of detection (LOD), and limit of quantification (LOQ) of PAEs were performed (Table 4). Linearity was obtained at r2 > 0.99 for PAEs ranging from 1 to 1000 μg/L (except for 500 μg/L for DBP). LOD and LOQ were calculated according to the method of GB/T 27417-2017 [37] by the detection of actual samples and low-concentration spiked samples. Using 3- and 10-fold signal-to-noise ratios (S/N), the LODs of the five PAEs were 0.2–0.6 μg/kg, and the LOQs were 0.7–2.0 μg/kg.
The accuracy of the method was verified by measuring the recovery of spiked PAEs with standard solutions at three levels: 100, 500, and 1000 μg/L for tea. Three parallel samples were prepared for each gradient, and the results are shown in Table 4. The recoveries of the five PAEs ranged from 80.70% to 98.68%, and the relative standard deviations (n = 6) of the five PAEs were from 2.7% to 8.1% (all less than 10%). The matrix effects of the five PAEs in the blank matrix were investigated at five different levels: 20, 50, 100, 200, and 500 μg/L. The results show that the matrix effects of the five PAEs compounds are 0.4–1.1, which suggests the interference of the matrix on the compounds was small.

3.4. Dynamic Changes of PAEs during Black Tea Processing

In this study, a total of six batches of samples at different stages during black tea processing were tested three times using the same apparatus. After the samples from each processing stage were extracted and analyzed according to the above method, the content of five PAEs in the samples was quantified using external standards (Table 5). In order to compare and analyze the change of PAE levels during black tea processing, the content of PAEs at each stage was converted into dry matter.
As shown in Figure 4, five PAEs (DMP, DEP, DiBP, DBP, and DEHP) were all detected during black tea processing, among which the content of DBP was the highest (81.5–95.30% of the total PAEs) and DMP was the lowest. Consistent with the trend of DEHP, the amount of DBP showed a trend of increasing first and then decreasing during the whole process. During the whole process, the content of DBP and DEHP increased significantly in withering, rolling, fermentation, and initial drying, while their content decreased sharply after far-infrared baking, with a significant loss rate of 70.49% and 58.60%, respectively. The contents of DMP, DEP, and DiBP were all significantly reduced in each stage of black tea processing. Compared with fresh leaves, the loss rates of DMP and DEP after far-infrared baking were 8.53% and 63.50%, respectively.
In each stage of black tea processing except for the finished tea sample, the total content of PAEs was generally higher than that in fresh leaves, especially in the withered sample (up to 1507.21 μg/kg), followed by the initial drying sample with a content of PAEs of 1387.61 μg/kg. However, after far-infrared baking, the content of PAEs dropped sharply, with the loss rate up to 66.79%. In addition to far-infrared baking, the content of PAEs during rolling and fermentation also decreased to a certain extent, with loss rates of 17.67% and 22.39%, respectively.
The processing factor (PF) was used to evaluate the change of PAEs during tea processing and can effectively indicate the main factors causing PAE degradation. The PFs during withering, rolling, fermentation, initial drying, and far-infrared baking were 2.86, 2.35, 1.82, 2.63, and 0.87, respectively, which suggests far-infrared baking is the main cause of the degradation of PAEs during black tea processing. In each stage of black tea processing, the effects of physicochemical properties of five PAEs on the PFs were analyzed. The physicochemical properties of five PAEs are shown in Table 6. Figure 5 shows an increasing trend with the increase of the octanol–water partition coefficient (Log Kow) and boiling point (Bp). Specifically, when Log Kow was less than 4 and Bp was less than 300 °C, the PFs were less than 1, which indicates low residue levels of PAEs. On the contrary, the PFs showed an overall decreasing trend with the increase of vapor pressure (Vp) and water solubility (Sw). Specifically, the residual level of PAEs was the highest when Vp was greater than 10−5 mmHg and Sw was less than 12 mg/L.
Except for the far-infrared baking stage, the PFs of DBP and DEHP in all the other four stages during processing were higher than 1. A possible reason could be the relatively high Log Kow and Bp, and the relatively low Vp of DBP and DEHP. As a result, DBP and DEHP in the tea samples were less likely to be emitted into the air, and DBP and DEHP in the air and contact substances were adsorbed into the surface of the tea leaves and migrated into the tea leaves more easily. Owing to the extremely low melting point (Mp) of five PAEs, their degradation and dissipation may be due to prolonged high-temperature treatment, and the PF in the finished tea sample was less than 1.
Principal component analysis (PCA) of PFs and the physicochemical properties of five PAEs was conducted to determine correlations. As shown in Figure 6, PC1 and PC2 represented 99.50% in the samples, indicating that PCA analysis can reflect the comprehensive information of the samples. The loading values indicate that the levels of five PAE residues during black tea processing mainly depend on the pKow, followed by pSw and pVp. Results indicate that the value of pPF was positively correlated with pKow and pBP, but negatively correlated with pSw and pVp.

4. Discussion

In this study, solid-phase extraction was used to enrich and purify PAEs in tea, and then GC–MS was used to qualitatively and quantitatively detect the PAEs in tea. A method was developed to analyze five PAEs in tea, and the extraction conditions were optimized by response surface methodology. In terms of the selection of extraction solvents, n-hexane organic solvent was used because of its weak polarity and strong solubility for PAEs. In addition, the matrix solution extracted with n-hexane has fewer interfering substances compared with other organic solvents [38]. Due to the acid–base instability of PAE structures, sodium chloride was addicted during the pretreatment process to enhance the stability of anthocyanins during the extraction process [39]. Using the optimized conditions, the PAEs in tea can be better extracted, with a high extraction efficiency, high resolution of target chromatographic peaks, and a low LOD of the method. Especially, the method of analyzing five PAEs in tea showed good specificity, reliability, and reproducibility with certain applicability. Compared with the QuEChERS method and the simultaneous distillation extraction method adopted by Yin et al. [23] and Du et al. [28], respectively, this development method extracts PAEs with higher specificity and with a higher extraction rate than the QuEChERS method, and it also avoids the cross-contamination caused by the simultaneous distillation extraction method.
Black tea is a fully fermented tea and is the most-sold tea in the world. Moreover, in the past ten years, China’s black tea series product has developed rapidly, and their output and sales have surged. It is of great practical significance to discuss the inhibitory effect of black tea processing technology on PAEs. The results show that all five PAEs can be detected in each stage of black tea processing, among which DBP accounts for the highest proportion, consisting of 81.5–95.30% of the total amount of PAEs. Except for the finished tea sample, the content of DBP and DEHP in each stage of black tea processing was higher than that in the fresh leaves, which may be because the tea samples were exposed to the air for a long time and contacted equipment and other objects (such as loading machines, conveyors, tea twisting machine, tea drying machinery, and so on), causing PAEs to adhere to the surface of the tea leaves and migrate into the tea. By analyzing their physicochemical properties, we found that the Log Kow and Bp of DBP and DEHP are high, while the Vp and Sw are low, which further explains the enrichment of two PAEs in tea. Some researchers found that the contamination level of polycyclic aromatic hydrocarbons (PAHs) in tea showed an increasing trend during withering and rolling of black tea, which may be caused by environmental factors [40,41], but spreading and drying reduced PAH concentrations [42]. During the far-infrared baking stage, the levels of five PAEs were significantly reduced, indicating that the thermochemical reaction at high temperature may be the main reason for the degradation of PAEs. Liu et al. [29] found that PAEs were significantly reduced during green-tea processing, and considered the drying stage as the key factor for the loss of PAEs.
The PF can effectively indicate the main cause for PAE degradation. The PF value of PAEs after far-infrared baking was less than one during black tea processing, which indicates that the level of PAE residues in dried tea samples is lower than that in fresh leaves. Therefore, the baking stage is the main factor for PAE degradation, and the main reason may be the emission or degradation of PAEs due to prolonged high temperatures. Drying of the tea leaves was carried out in two stages (primary drying and far-infrared baking), and the temperature was high and the time long during the whole process. In addition, the far-infrared mode was adopted in this study; the possibility of thermal volatilization is very high during the high-temperature mode for a long time. Sood et al. [43] also found that water molecules in plant tissue can enter the interior of pesticide molecules, which can promote the volatilization and degradation of pesticides during heating. The PF of PAEs was the highest during the withering process, and then gradually decreased during rolling and fermentation, which may be because of the release of the fresh leaf juice caused by rolling and the enzymes during fermentation. Wang et al. [36] found that the loss of anthraquinone was also associated with rolling and fermentation in the study of the effect of black tea processing on the degradation of anthraquinone. PCA found that the residual level of PAEs in tea was closely related to its Log Kow: the levels of residual PAEs were positively correlated with Log Kow and BP, but negatively correlated with Sw and Vp.

5. Conclusions

In summary, our study successfully established a method for the analysis of five phthalate esters in tea using solid-phase extraction coupled with GC–MS. The extraction conditions of five PAE residues in tea were optimized by Box–Behnken response surface design. The final conditions were determined as follows: solid-to-liquid ratio of 1:20, extraction temperature of 40 °C, and extraction time of 12 h. The linearity obtained at r2 > 0.99 for PAEs ranged from 1 to 1000 μg/L (except for 500 μg/L for DBP). The LODs and LOQs of this method were in the range of 0.2–0.6 μg/kg and 0.7–2.0 μg/kg, respectively. The recoveries of the five PAEs ranged from 80.70% to 98.68%, with RSD 2.7–8.1%. The results showed that the residues of PAEs in each stage of black tea processing mainly depended on Log Kow, followed by Sw and Vp. Prolonged high temperature has a significant effect on the degradation of PAEs. This study quantified the level of PAE residues and investigated the characteristics of PAE residues during black tea processing. The PFs of PAEs during black tea processing can assess the health risk of the residues and evaluate whether it is safe for consumers. This work may serve as a guide for the detection, processing-loss determination, and control of PAE MRLs in tea.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods11091266/s1, Table S1: Equations for five PAE compounds.

Author Contributions

Conceptualization, Y.T., M.W. and B.H.; methodology, Y.T., M.W., C.P. and B.H.; software, Y.T., M.W. and C.P.; validation, Y.T., M.W. and B.H.; formal analysis, Y.T., M.W. and S.M.; writing—original draft preparation, Y.T. and M.W.; writing—review and editing, M.W. and B.H.; project administration, M.W. and B.H.; funding acquisition, M.W. and B.H. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2018YFC1604402), the National Natural Science Foundation of China (32072626, 32001910), the Zhejiang Provincial Key Research and Development Program of China (2020C02026), the Zhejiang Provincial Fundamental and Public Welfare of China (LGN20C140005), the Fundamental Research Funds for the Provincial Universities of Zhejiang (2021YW41), Science and Technology Project of State Administration for Market Regulation (S2021MK0009), Team Scientific Special Commissioner Project of Zhejiang Provincial Department of Science and Technology (2020.1–2024.12, SY-1), and a special program of scientific and technological innovation for students of China Jiliang University (2019YW18).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data sharing not applicable.

Acknowledgments

The authors thank Zhejiang Gengxiang Organic Tea Development Co., Ltd., Wuyi County, Zhejiang Province for providing access to tea plantations and tea processing.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Zia, A.I.; Syaifudin, A.R.M.; Mukhopadhyay, S.C.; Yu, P.L.; Al-Bahadly, I.H.; Gooneratne, C.P.; Kosel, J.; Liao, T.-S. Electrochemical impedance spectroscopy based MEMS sensors for phthalates detection in water and juices. J. Phys. Conf. Ser. 2013, 439, 012026. [Google Scholar] [CrossRef]
  2. Yang, J.; Li, Y.; Wang, Y.; Ruan, J.; Zhang, J.; Sun, C. Recent advances in analysis of phthalate esters in foods. TrAC Trends Anal. Chem. 2015, 72, 10–26. [Google Scholar] [CrossRef]
  3. Ramzi, A.; Gireeshkumar, T.R.; Habeeb Rahman, K.H.; Manu, M.; Balachandran, K.K.; Chacko, J.; Chandramohanakumar, N. Distribution and contamination status of phthalic acid esters in the sediments of a tropical monsoonal estuary, Cochin—India. Chemosphere 2018, 210, 232–238. [Google Scholar] [CrossRef] [PubMed]
  4. Salazar-Beltrán, D.; Hinojosa-Reyes, L.; Palomino-Cabello, C.; Turnes-Palomino, G.; Hernández-Ramírez, A.; Guzmán-Mar, J.L. Determination of phthalate acid esters plasticizers in polyethylene terephthalate bottles and its correlation with some physicochemical properties. Polym. Test. 2018, 68, 87–94. [Google Scholar] [CrossRef]
  5. Keresztes, S.; Tatár, E.; Czégény, Z.; Záray, G.; Mihucz, V.G. Study on the leaching of phthalates from polyethylene terephthalate bottles into mineral water. Sci. Total Environ. 2013, 458–460, 451–458. [Google Scholar] [CrossRef] [Green Version]
  6. Net, S.; Delmont, A.; Sempéré, R.; Paluselli, A.; Ouddane, B. Reliable quantification of phthalates in environmental matrices (air, water, sludge, sediment and soil): A review. Sci. Total Environ. 2015, 515–516, 162–180. [Google Scholar] [CrossRef]
  7. Zhao, H.-M.; Du, H.; Xiang, L.; Chen, Y.-L.; Lu, L.-A.; Li, Y.-W.; Li, H.; Cai, Q.-Y.; Mo, C.-H. Variations in phthalate ester (PAE) accumulation and their formation mechanism in Chinese flowering cabbage (Brassica parachinensis L.) cultivars grown on PAE-contaminated soils. Environ. Pollut. 2015, 206, 95–103. [Google Scholar] [CrossRef]
  8. Salazar-Beltrán, D.; Hinojosa-Reyes, L.; Ruiz-Ruiz, E.; Hernández-Ramírez, A.; Guzmán-Mar, J.L. Phthalates in Beverages and Plastic Bottles: Sample Preparation and Determination. Food Anal. Methods 2018, 11, 48–61. [Google Scholar] [CrossRef]
  9. Tan, W.; Yu, H.; Huang, C.; Li, D.; Zhang, H.; Zhao, X.; Li, R.; Wang, G.; Zhang, Y.; He, X.; et al. Intercropping wheat and maize increases the uptake of phthalic acid esters by plant roots from soils. J. Hazard. Mater. 2018, 359, 9–18. [Google Scholar] [CrossRef]
  10. Wang, J.C.; Wang, X.R. Simultaneous determination of 22 phthalate esters in milk powder by GC-MS/MS. J. Sci. Technol. Food Ind. 2022, 43, 280–285. [Google Scholar]
  11. Ji, J.; Liu, Y.; Wang, D. Comparison of de-skin pretreatment and oil extraction on aflatoxins, phthalate esters, and polycyclic aromatic hydrocarbons in peanut oil. Food Control 2020, 118, 107365. [Google Scholar] [CrossRef]
  12. Perestrelo, R.; Silva, C.; Algarra, M.; Câmara, J. Evaluation of the Occurrence of Phthalates in Plastic Materials Used in Food Packaging. Appl. Sci. 2021, 11, 2130. [Google Scholar] [CrossRef]
  13. Fang, Y.; Sha, W.Z. Research progress of detection methods for phthalate esters in food and food packing materials. J. Crim. Technol. 2016, 1, 20–24. [Google Scholar] [CrossRef]
  14. Ma, Y.; Gao, X.; Ruan, Y.; Cui, H.; Zhang, L.; Zhang, W.; Wang, S. Determination of Phthalate Esters in Beverages and Water Samples by Solid Phase Extraction with Resin Based COFs as Filler. Water 2021, 13, 3338. [Google Scholar] [CrossRef]
  15. Huang, Z.; Tu, C.; Liu, H.; Wang, L.; Zhu, Z.; Watanabe, I. Hollow fiber-solid phase microextraction of phthalate esters from bottled water followed by flash evaporation gas chromatography-flame ionization detection. J. Chromatogr. A 2020, 1619, 460953. [Google Scholar] [CrossRef]
  16. Zhou, J.; Qi, Y.; Wu, H.; Diao, Q.; Tian, F.; Li, Y. Simultaneous determination of trace migration of phthalate esters in honey and royal jelly by GC-MS. J. Sep. Sci. 2014, 37, 650–657. [Google Scholar] [CrossRef]
  17. Notardonato, I.; Passarella, S.; Iannone, A.; Di Fiore, C.; Russo, M.V.; Protano, C.; Vitali, M.; Avino, P. Comparison of Two Extraction Procedures, SPE and DLLME, for Determining Plasticizer Residues in Hot Drinks at Vending Machines. Processes 2021, 9, 1588. [Google Scholar] [CrossRef]
  18. Jin, X.; Kaw, H.Y.; Wang, Z.; Zou, Y.; Li, W.; Guo, Z.; Sun, H.; Zhao, J.; Li, D. One-step extraction method of phthalate esters in vegetable oils. Chin. J. Chromatogr. 2018, 36, 173–178. [Google Scholar] [CrossRef] [Green Version]
  19. Sinha, P.; Anshu, A.K.; Tiwari, M.; Ahmad, Y. Determination of PAEs in soil of municipal wards of Patna, India by microwave assisted extraction and LC-MS/MS. Soil Sediment Contam. Int. J. 2019, 28, 162–170. [Google Scholar] [CrossRef]
  20. Li, H.; Tian, F.; Ren, X.; Wang, X. Determination of phthalic acid esters in soil by gas chromatography-tandem mass spectrometry. Chin. J. Chromatogr. 2011, 29, 563–566. [Google Scholar] [CrossRef]
  21. Lou, C.; Guo, D.; Zhang, K.; Wu, C.; Zhang, P.; Zhu, Y. Simultaneous determination of 11 phthalate esters in bottled beverages by graphene oxide coated hollow fiber membrane extraction coupled with supercritical fluid chromatography. Anal. Chim. Acta 2018, 1007, 71–79. [Google Scholar] [CrossRef] [PubMed]
  22. Li, X.; Liu, W.; Zhang, C.; Song, P.; Wang, J. Fate of Phthalic Acid Esters (PAEs) in Typical Greenhouse Soils of Different Cultivation Ages. Bull. Environ. Contam. Toxicol. 2020, 104, 301–306. [Google Scholar] [CrossRef] [PubMed]
  23. Yin, P.; Liu, X.; Chen, H.; Pan, R.; Ma, G. Determination of 16 phthalate esters in tea samples using a modified QuEChERS sample preparation method combined with GC-MS/MS. Food Addit. Contam. Part A 2014, 31, 1406–1413. [Google Scholar] [CrossRef] [PubMed]
  24. Wang, Z.; He, M.; Chen, B.; Hu, B. Triazine covalent organic polymer coated stir bar sorptive extraction coupled with high performance liquid chromatography for the analysis of trace phthalate esters in mineral water and liquor samples. J. Chromatogr. A 2021, 1660, 462665. [Google Scholar] [CrossRef] [PubMed]
  25. Alnaimat, A.S.; Barciela-Alonso, M.C.; Bermejo-Barrera, P. Development of a sensitive method for the analysis of four phthalates in tea samples: Tea bag contribution to the total amount in tea infusion. Food Addit. Contam. Part A 2020, 37, 1719–1729. [Google Scholar] [CrossRef] [PubMed]
  26. Yadav, S.; Rai, S.; Srivastava, A.K.; Panchal, S.; Patel, D.; Sharma, V.; Jain, S.; Srivastava, L. Determination of pesticide and phthalate residues in tea by QuEChERS method and their fate in processing. Environ. Sci. Pollut. Res. 2017, 24, 3074–3083. [Google Scholar] [CrossRef] [PubMed]
  27. Tsochatzis, E.; Karayannakidis, P.; Kalogiannis, S. Determination of selected dichloroanilines and phthalates in lyophilised mussels samples with ultra-high performance liquid chromatography-tandem mass spectrometry after QuEChERS clean-up. Food Addit. Contam. Part A 2019, 36, 1253–1260. [Google Scholar] [CrossRef]
  28. Du, L.; Ma, L.; Qiao, Y.; Lu, Y.; Xiao, D. Determination of phthalate esters in teas and tea infusions by gas chromatography–mass spectrometry. Food Chem. 2016, 197, 1200–1206. [Google Scholar] [CrossRef]
  29. Liu, P.; Chen, H.; Gao, G.; Hao, Z.; Wang, C.; Ma, G.; Chai, Y.; Zhang, L.; Liu, X. Occurrence and Residue Pattern of Phthalate Esters in Fresh Tea Leaves and during Tea Manufacturing and Brewing. J. Agric. Food Chem. 2016, 64, 8909–8917. [Google Scholar] [CrossRef]
  30. Pang, Y.-H.; Yue, Q.; Huang, Y.-Y.; Yang, C.; Shen, X.-F. Facile magnetization of covalent organic framework for solid-phase extraction of 15 phthalate esters in beverage samples. Talanta 2020, 206, 120194. [Google Scholar] [CrossRef]
  31. GB/T 8302; Tea Sampling. [NSPRC] National Standards of the People’s Republic of China: Beijing, China, 2013.
  32. GB 5009.271; Determination of Phthalate Esters in Foods. [NSPRC] National Standards of the People’s Republic of China: Beijing, China, 2016.
  33. Draper, N.R. Introduction to Box and Wilson (1951) On the Experimental Attainment of Optimum Conditions. In Breakthroughs in Statistics. Springer Series in Statistics (Perspectives in Statistics); Kotz, S., Johnson, N.L., Eds.; Springer: Berlin/Heidelberg, Germany, 1992; pp. 267–269. [Google Scholar] [CrossRef]
  34. Zhang, J.; Li, M.; Kong, Z.; Bai, T.; Quan, R.; Gao, T.; Duan, L.; Liu, Y.; Fan, B.; Wang, F. Model prediction of herbicide residues in soybean oil: Relationship between physicochemical properties and processing factors. Food Chem. 2022, 370, 131363. [Google Scholar] [CrossRef] [PubMed]
  35. Feki, F.; Klisurova, D.; Masmoudi, M.A.; Choura, S.; Denev, P.; Trendafilova, A.; Chamkha, M.; Sayadi, S. Optimization of microwave assisted extraction of simmondsins and polyphenols from Jojoba (Simmondsia chinensis) seed cake using Box-Behnken statistical design. Food Chem. 2021, 356, 129670. [Google Scholar] [CrossRef] [PubMed]
  36. Wang, X.; Zhou, L.; Luo, F.; Zhang, X.; Sun, H.; Yang, M.; Lou, Z.; Chen, Z. 9,10-Anthraquinone deposit in tea plantation might be one of the reasons for contamination in tea. Food Chem. 2018, 244, 254–259. [Google Scholar] [CrossRef] [PubMed]
  37. GB/T 27417; Comformity Assessment—Guidance on Validation and Verification of Chemical Analytical Methods. [NSPRC] National Standards of the People’s Republic of China: Beijing, China, 2017.
  38. Liu, P.X.; Chen, H.P.; Zhang, M.L.; Gao, J.W.; Yin, P.; Liu, X. Progress on pollution level and detection technology of phthalate in tea leaves. J. Zhejiang Agric. Sci. 2015, 56, 1796–1804. [Google Scholar] [CrossRef]
  39. Fei, X.Y.; Lin, Z.; Liang, M.Z.; Wang, L.B.; Chen, J.W.; Lv, H.P.; Tan, J.F.; Guo, L. Study on anthocyanins extraction process in tea by response surface method. Tea Sci. 2012, 32, 197–202. [Google Scholar] [CrossRef]
  40. Lin, D.; Zhu, L. Polycyclic Aromatic Hydrocarbons: Pollution and Source Analysis of a Black Tea. J. Agric. Food Chem. 2004, 52, 8268–8271. [Google Scholar] [CrossRef]
  41. Grover, I.S.; Singh, S.; Pal, B. Priority PAHs in orthodox black tea during manufacturing process. Environ. Monit. Assess. 2013, 185, 6291–6294. [Google Scholar] [CrossRef]
  42. Gao, G.; Chen, H.; Liu, P.; Hao, Z.; Ma, G.; Chai, Y.; Wang, C.; Lu, C. Residue pattern of polycyclic aromatic hydrocarbons during green tea manufacturing and their transfer rates during tea brewing. Food Addit. Contam. Part A 2017, 34, 990–999. [Google Scholar] [CrossRef]
  43. Sood, C.; Jaggi, S.; Kumar, V.; Ravindranath, S.; Shanker, A. How manufacturing processes affect the level of pesticide residues in tea. J. Sci. Food Agric. 2004, 84, 2123–2127. [Google Scholar] [CrossRef]
Foods 11 01266 g001 550
Figure 1. Effect of extraction temperature (a), extraction time (b), and solid–liquid ratio (c) on the extraction of PAEs from tea.
Figure 1. Effect of extraction temperature (a), extraction time (b), and solid–liquid ratio (c) on the extraction of PAEs from tea.
Foods 11 01266 g001
Foods 11 01266 g002 550
Figure 2. Response surface map for interaction of various factors.
Figure 2. Response surface map for interaction of various factors.
Foods 11 01266 g002
Foods 11 01266 g003 550
Figure 3. Total ion chromatogram of five PAEs; standard (a) and n-hexane solution (b).
Figure 3. Total ion chromatogram of five PAEs; standard (a) and n-hexane solution (b).
Foods 11 01266 g003
Foods 11 01266 g004 550
Figure 4. PAE content (±SD (μg/kg)) at each stage of black tea processing.
Figure 4. PAE content (±SD (μg/kg)) at each stage of black tea processing.
Foods 11 01266 g004
Foods 11 01266 g005a 550Foods 11 01266 g005b 550
Figure 5. Effects of physicochemical properties of five PAEs on processing factors during black tea processing.
Figure 5. Effects of physicochemical properties of five PAEs on processing factors during black tea processing.
Foods 11 01266 g005aFoods 11 01266 g005b
Foods 11 01266 g006 550
Figure 6. Principal component analysis of processing factors and physicochemical parameters of five PAEs during black tea processing.
Figure 6. Principal component analysis of processing factors and physicochemical parameters of five PAEs during black tea processing.
Foods 11 01266 g006
Table
Table 1. Design and results of response surface test.
Table 1. Design and results of response surface test.
Test NumberFactorExperimental Content
(μg/kg)		Predicted Content
(μg/kg)
Solid–Liquid Ratio
(A)		Extraction Temperature
(B)		Extraction Time
(C)
11:204012546.14567.92
21:204012557.63576.48
31:105012348.29328.23
41:204012647.50585.85
51:204012559.27577.11
61:204012529.08533.45
71:104018416.98402.39
81:303012216.75236.81
91:20306193.37158.72
101:205018395.63430.28
111:103012219.02249.49
121:10406166.01170.17
131:305012302.30207.11
141:30406138.57153.16
151:203018380.81364.92
161:304018354.47350.30
171:20506191.22207.11
Table
Table 2. Variance analysis of regression model of PAE extraction from tea.
Table 2. Variance analysis of regression model of PAE extraction from tea.
Source of VarianceDegrees of FreedomSum of SquareMean SquareF-Valuep-ValueDistinctiveness
A-Solid–liquid ratio12387.402387.401.150.3190
B-Extraction temperature16468.966468.963.120.1208
C-Extraction time192,177.1592,177.1544.420.0003**
AB1477.86477.860.230.6459
AC1307.65307.650.150.7116
BC172.0072.000.0350.8575
A211.062 × 1051.062 × 10551.160.0002**
B2179,652.4579,652.4538.390.0004**
C2182,674.6482,674.6439.840.0004**
Model94.018 × 10544,642.8721.510.0003**
Residual714,525.522075.07
Lack-of-fit36028.922009.640.950.4980
Pure error48496.602124.15
Cor total 164.163 × 105
Notes: **, p < 0.01 means that the difference is very significant.
Table
Table 3. Mass spectrometric information of five PAEs.
Table 3. Mass spectrometric information of five PAEs.
NumberCompoundRetention Time (min)Qualitativeion (m/z)Quantitative Ion (m/z)
1DMP12.98163,77,194,133163
2DEP17.38149,177,105,222149
3DiBP26.90149,223,104,167149
4DBP29.50149,223,205,104149
5DEHP39.57149,167,279,113149
Table
Table 4. Method validation of linearity, recoveries, limits of detection (LOD) and quantification (LOQ), and matrix effect for five PAEs in tea.
Table 4. Method validation of linearity, recoveries, limits of detection (LOD) and quantification (LOQ), and matrix effect for five PAEs in tea.
PAEsLinear Range
(μg/L)		r2LOD
(μg/kg)		LOQ
(μg/kg)		Recoveries, % (RSD, %)Matrix Effect
100 μg/L500 μg/L1000 μg/L
DMP1.00–1000.000.99100.401.3381.71 (4.32)95.00 (7.55)97.07 (5.70)1.13
DEP1.00–1000.000.99140.612.0380.70 (5.60)94.28 (6.52)93.88 (4.56)1.02
DIBP1.00–1000.000.99500.421.4082.69 (8.14)94.22 (4.03)91.57 (3.31)0.63
DBP1.00–500.000.99610.501.6689.30 (6.67)90.37 (8.69)98.28 (4.58)0.50
DEHP1.00–1000.000.99630.210.7184.37 (6.39)93.99 (3.94)98.68 (2.72)0.40
Table
Table 5. Content of PAEs (±SD (μg/kg)) in different stages of black tea processing (n = 3).
Table 5. Content of PAEs (±SD (μg/kg)) in different stages of black tea processing (n = 3).
SampleDMPDEPDIBPDBPDEHPSum
Fresh leaves sample12.31 ± 0.3935.13 ± 0.1733.15 ± 0.56430.41 ± 15.0816.89 ± 1.64527.90 ± 31.38
Withered sample11.36 ± 0.3513.01 ± 0.2221.73 ± 0.371436.37 ± 17.3224.73 ± 2.291507.21 ± 139.04
Rolled sample11.28 ± 0.8712.97 ± 0.5122.68 ± 1.341166.90 ± 18.8326.86 ± 3.991240.86 ± 109.02
Fermented sample11.44 ± 0.3912.87 ± 0.5419.13 ± 1.88895.98 ± 9.1623.56 ± 1.69962.97 ± 100.84
First drying sample11.67 ± 0.4012.99 ± 0.3320.77 ± 1.371313.84 ± 9.3128.33 ± 1.521387.61 ± 128.37
Finished tea sample11.26 ± 1.4712.82 ± 2.6837.08 ± 3.87387.69 ± 4.0911.73 ± 1.72460.85 ± 4.33
Table
Table 6. CAS number, molecular weight (Mw), octanol–water partition coefficient (Log Kow), water solubility (Sw), vapor pressure (Vp), melting point (Mp), boiling point (Bp), and structural formula of five phthalates.
Table 6. CAS number, molecular weight (Mw), octanol–water partition coefficient (Log Kow), water solubility (Sw), vapor pressure (Vp), melting point (Mp), boiling point (Bp), and structural formula of five phthalates.
PAEsCAS NumberMwLog KowSw (mg/L, 25 °C) Vp (mm Hg, 25 °C) Mp (°C) Bp (°C) Structural Formula
DMP131-11-3194.191.604000.003.08 × 10−35.50282.68 Foods 11 01266 i001
DEP84-66-2222.242.421080.002.10 × 10−3−40.50294.00 Foods 11 01266 i002
DiBP84-69-5278.354.116.204.76 × 10−5−50.00327.00 Foods 11 01266 i003
DBP84-74-2278.354.5011.202.01 × 10−5−35.00337.00 Foods 11 01266 i004
DEHP117-81-7390.577.600.271.42 × 10−7−50.00384.90 Foods 11 01266 i005
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Tang, Y.; Wang, M.; Pan, C.; Mi, S.; Han, B. Determination of Five Phthalate Esters in Tea and Their Dynamic Characteristics during Black Tea Processing. Foods 2022, 11, 1266. https://doi.org/10.3390/foods11091266

AMA Style

Tang Y, Wang M, Pan C, Mi S, Han B. Determination of Five Phthalate Esters in Tea and Their Dynamic Characteristics during Black Tea Processing. Foods. 2022; 11(9):1266. https://doi.org/10.3390/foods11091266

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Tang, Yanyan, Mengxin Wang, Cheng Pan, Shuishan Mi, and Baoyu Han. 2022. "Determination of Five Phthalate Esters in Tea and Their Dynamic Characteristics during Black Tea Processing" Foods 11, no. 9: 1266. https://doi.org/10.3390/foods11091266

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