Impact of Six Typical Processing Methods on the ... - ACS Publications

Nov 7, 2018 - catechin components included amino acids and γ-aminobutyric acid, which increased in white tea, and dihydroxyphenylalanine, valine, bet...
0 downloads 0 Views 2MB Size
Subscriber access provided by UNIV OF LOUISIANA

Omics Technologies Applied to Agriculture and Food

The impact of six typical processing methods on the chemical composition of tea leaves using a single Camellia sinensis cultivar, Longjing 43 Yijun Wang, Zhipeng Kan, Henry J. Thompson, Tie-Jun Ling, Chi-Tang Ho, Daxiang Li, and Xiaochun Wan J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b05140 • Publication Date (Web): 07 Nov 2018 Downloaded from http://pubs.acs.org on November 7, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 38

Journal of Agricultural and Food Chemistry

The impact of six typical processing methods on the chemical composition of tea leaves using a single Camellia sinensis cultivar, Longjing 43 Yijun Wang†,‡#, Zhipeng Kan†,‡#, Henry J. Thompson‡, §, Tiejun Ling†,‡, Chi-Tang Ho‡,≠, Daxiang Li†,‡* and Xiaochun Wan†,‡* †

State Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food

Science & Technology, Anhui Agricultural University, Hefei, Anhui 230036, PRC. ‡

International Joint Laboratory on Tea Chemistry and Health Effects, Anhui

Agricultural University, Hefei, Anhui 230036, PRC. §

Cancer Prevention Laboratory, Colorado State University, Fort Collins, CO 80523, USA. ≠

Department of Food Science, Rutgers University, New Brunswick, NJ 08901, USA

#

These authors contribute equally.

*

Corresponding author: Dr. Daxiang Li ([email protected]) and Dr. Xiaochun Wan

([email protected]), Tel/Fax: +86 551 6578 6765.

1

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 2 of 38

1

ABSTRACT

2

While Camellia sinensis cultivar and processing method are key factors that affect tea

3

flavor and aroma, the chemical changes in nonvolatile components associated with tea

4

processing method using a single cultivar of C. sinensis has not been reported. Fresh

5

leaves from C. sinensis, Longjing 43 were subjected to six tea processing methods and

6

evaluated by targeted and untargeted chromatographic procedures. Based on targeted

7

assessment of total catechin content, three clusters were identified: yellow-green,

8

oolong-white-dark, and black. However, principal component analysis of the total tea

9

metabolome identified four chemical phenotypes: green-yellow, oolong, black-white,

10

and dark. Differences in the non-catechin components included amino acids and

11

gamma

12

dihydroxyphenylalanine, valine, betaine, theophylline which increased in dark tea.

13

Overall, this study identified a wide range of chemicals that are affected by commonly

14

used tea processing methods and that potentially affect the bioactivity of various tea

15

types.

16

Key words: C. sinensis, tea, bioactives, post-harvest processing, chemical

17

composition

aminobutyric

acid

which

were

increased

2

ACS Paragon Plus Environment

in

white

tea

and

Page 3 of 38

Journal of Agricultural and Food Chemistry

18

INTRODUCTION

19

Tea is a popular beverage, second only to water in terms of per capita consumption.1

20

There are many types of tea that differ in aroma and flavor. They are produced via

21

variations in the way harvested leaves are processed. In China, there are six postharvest

22

processes to which leaves of Camellia sinensis are commonly subjected (Figure 1).

23

Processing results in leaves that are used to produce: green, yellow, oolong, black,

24

white, and dark tea. These processing techniques were developed over a span of

25

thousands of years in different parts of China. When comparative analyses have been

26

done, the six tea types are generally classified into five categories, the first four of

27

which are clustered by the degree of endogenous enzymatic reaction: 1) non-fermented

28

teas: green tea; 2) lightly fermented tea: yellow tea and white tea; 3) partially fermented

29

tea: oolong tea; 4) fully-fermented tea: black tea; and 5) post-fermented tea: dark tea in

30

which the exogenous microbial fermentation plays a vital role in processing.2,3

31

The beverage referred to as tea is the hot water infusion of the leaves of C. sinensis that

32

are subjected to a specific post-harvest processing technique. The aroma and taste

33

characteristics of each tea type are based on the metabolite changes induced in the tea

34

leaf, primarily the nonvolatile components, retained in the leaf until it is infused. As

35

such, the tea science field has focused on processing-induced changes in the types of

36

catechins present in the leaf since they compromise over 20% its dry weight.4 The tea

37

catechins include: catechin (C), gallocatechin (GC), epicatechin (EC), epicatechin

38

gallate (ECG), epigallocatechin (EGC), and epigallocatechin gallate (EGCG), the

39

most abundant secondary metabolites in the fresh leaves of C. sinenesis. In most of tea 3

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

40

research, the chemical changes induced by all six typical processing methods are

41

viewed through the lens of how those processes either prevent or allow catechins to be

42

oxidized by endogenous polyphenol oxidases.5-7 Although many other chemicals, e.g.,

43

theanine and caffeine were successively discovered in tea leaves in the past decades,8,9

44

the comprehensive chemical profiling of teas is still limited. Despite the fact that the

45

fresh picked leaves of the large number of commercially important cultivars of differ

46

significantly in phytochemical content,10,11 and that specific cultivars are generally used

47

to make specific tea types,12 most work has ignored the potential contributions of the

48

cultivar used to make a tea type in comparing the chemical differences that exist among

49

tea types.

50

Mass-based metabolomics is the use of high throughput analysis platforms to

51

chromatographically separate complex mixtures of small molecules with their

52

subsequent identification via mass spectrometry. When this approach is applied to a

53

biological material such as the tea leaf, it enables the detection of hundreds of

54

endogenous metabolites simultaneously, providing an ―unbiased‖ view of the global

55

metabolome.13 Several recent studies applied either targeted or untargeted

56

metabolomics approaches to investigate the seasonal, geographical or genetic impact

57

on chemical composition of the tea plant leaf. Using this approach (LC-MS) coupled

58

with multivariate statistical analysis, the complexity and variability of a broad range of

59

metabolites in tea leaves has been unveiled.14-16

60

As discussed above, the post-harvest processing method is a key factor that governs the

61

chemical composition of the leaf which is ultimately extracted via hot water to make tea. 4

ACS Paragon Plus Environment

Page 4 of 38

Page 5 of 38

Journal of Agricultural and Food Chemistry

62

Although several analytical studies have been done to investigate certain major

63

metabolites in commercial teas or in intermediate steps during post-harvest processing,

64

a comprehensive investigation using metabolomics approaches has yet to be

65

conducted.17 In the work that has been reported, commercial teas were made from

66

diverse tea plant sources, which is a limitation to developing an in-depth understanding

67

of how specific processing techniques affect chemical composition, without

68

confounding due to chemical differences in fresh picked leaves from different C.

69

sinensis cultivars. Besides genetic factors, the environmental factors, plucking time and

70

criteria might play a role as well. Longjing 43 is one of the most widely cultivated

71

varieties in China, with the characteristics of strong drought resistance and high

72

budding rate. The Xihulongjing tea (green tea), made from Longjing 43, is one of the

73

top famous teas in China.18 In order to eliminate those confusing issue, the study

74

reported herein used fresh plucked leaves from a single popular tea plant cultivar

75

Longjing 43, followed by typical processing methods to make six tea types. The fresh

76

leaves and six types of processed leaves were analyzed and compared by targeted

77

methods using HPLC and global metabolomics approaches with validation of candidate

78

compounds using authentic standards and/or advanced in silico procedures.

79

MATERIALS AND METHODS

80

Chemicals

81

Deionized water was produced by a Milli-Q water purification system (Millipore,

82

Billerica, MA, USA). Methanol and acetonitrile of LC–MS grade was purchased from

83

Thermo Fisher (Thermo Scientific, Waltham, MA, USA). C, GC, EC, ECG, EGC, 5

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

84

EGCG, gallic acid, caffeine, theophylline, theobromine and theanine were obtained

85

from Yuanye Bio-Technology Co., Ltd. (Shanghai, China). DL-4-Chlorophenylalanine

86

was obtained from MedChemExpress (Shanghai, China).

87

Sample Preparation

88

Fresh leaves of C. sinensis L., Longjing 43 were plucked from NO. 916 tea garden in

89

Shucheng, Anhui, China. All the fresh leaves were divided into seven equal portions,

90

six of them were processed into six types of teas by using typical manufacturing

91

approaches (Figure 1). Briefly, three portions of the fresh leaves were first fixed at

92

220 ℃ to terminate the endogenous enzymatic reaction then rolled for 30 min, then

93

one of the three was directly dried into green tea. The second portion was yellowed at

94

room temperature and 70% humidity till the color of the leaves turned yellow (~6-8

95

hours), then dried into yellow tea. The third portion was post fermented at room

96

temperature and 70% humidity for 48 h and then dried into dark tea. To make black tea

97

and oolong tea, two portions of fresh leaves were withered at room temperature and 70%

98

humidity for 5h, one of them was rolled for 30min, applied heat-moisture treatment at

99

room temperature and 90% humidity for 3h and immediately dried into black tea. The

100

other portion was shaken and bruised four times, after fixed at 220 ℃ and rolling for

101

30 minutes, the leaves were dried into oolong tea. The sixth portion of fresh leaves

102

was subjected to ventilation withering at room temperature for 48h before dried into

103

white tea. The last portion of fresh leaves was lyophilized and all samples were stored

104

at -80 ℃ prior until analysis.

105

Sensory Evaluation 6

ACS Paragon Plus Environment

Page 6 of 38

Page 7 of 38

Journal of Agricultural and Food Chemistry

106

Tea types were evaluated by eight professional tea taster from the State Key Laboratory

107

of Tea Plant Biology and Utilization in accordance with Chinese National Standard

108

methods. The samples were blind-coded with random numbers. Three g of tea leaves

109

were infused with 150 mL of boiled purified water in separated white porcelain cups

110

and maintained for 5 min. Then, the tea infusion was poured into a white porcelain bowl

111

to evaluate the color, aroma, taste, and the residue (Figure 2). Post-infusion, extracted

112

leaves were transferred to white porcelain plates to observe their integrity and

113

appearance. Dried tea samples were also evaluated for color, shape, cleanliness and

114

uniformity. The panel provided a report of their sensory evaluation.

115

Sample Extraction

116

HPLC

117

Post-harvest processed leaves were ground into a powder. Then 2.5 mL of a 70%

118

methanol solution (v/v) was added to 0.1 g of tea powder at 70 °C for 10 min to extract

119

metabolites. The supernatants were collected after centrifuging at 3000 g for 10 min.

120

The sediments were re-extracted twice using the same method. After treatment, all the

121

extracts were brought to a constant volume (5 mL) and then filtered using a 0.22 μm

122

filter for HPLC analysis.

123

LC-MS

124

The freeze-dried fresh leaves and the six tea products were ground into powder. 50mg

125

sample and 0.8mL methanol were mixed with 60 Hz ultrasonication at 25 ℃ for 20

126

min. The supernatants were collected after centrifuging at 12000 g, 4 ℃. The internal

127

standard DL-4-chlorophenylalanine was added with final concentration of 5mg/L. Six 7

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 8 of 38

128

replicates were prepared and stored at -80 ℃ until they were analyzed.

129

HPLC Analysis of Major Secondary Metabolites

130

The high performance liquid chromatography (HPLC) system consisted of a Waters

131

2695 controller and a Waters 2489 UV Detector and a reverse phase C18 column

132

(250×4.60 mm, granule diameter, 5 m, Phenomenex Inc., Torrance, CA, USA). Mobile

133

phase A: water with 0.17% (v/v) acetic acid. Mobile phase B: 100% acetonitrile. Linear

134

elution was as follows: B from 6% from 0 to 4 min, to 14% at 16 min, to 15% at 22 min,

135

to 18% at 32 min, to 29% at 37 min, to 45% at 45 min, to 45% at 50 min, to 6% at 51

136

min and to 6% at 60 min.19 Samples (10 μL) were eluted at 1 mL/min, the column

137

heater was kept at 25 ℃. The detection wavelength was 278nm.The amounts of

138

polyphenol compounds in tea samples were measured by comparing the peak area of

139

each catechin in the tea samples with those of standards. Empower

140

used for data collection, integration, and analysis.

141

LC-MS Analysis

142

UPLC (Ultimate 3000, Dionex, Sunnyvale, CA, USA) coupled with Orbitrap Elite™

143

Hybrid Ion Trap-Orbitrap Mass Spectrometer (Thermo Fisher Scientific, USA) was

144

employed. The separation of all samples was performed on an Ultimate 3000 with

145

Hyper Gold column (1.9 μm, 2.1x100 mm). Water with 0.1% (v/v) formic acid and

146

acetonitrile were used as mobile phase A and B, respectively, for chromatographic

147

elution: from 0 to 7 min, phase B was linearly increased from 5 to 80%, then linearly

148

increased to 95% at 11 min, and maintained for 4 min; phase B was adjusted to 8% at

149

15.5 min for re-equilibration and maintained for 4 min. The total elapsed time required 8

ACS Paragon Plus Environment

TM

3 software was

Page 9 of 38

Journal of Agricultural and Food Chemistry

150

for a given chromatographic analysis was thus 20 min. The flow rate was set at 0.30

151

mL/min. The injection volume was 4 μL. The mass spectrometer was operated in both

152

positive and negative modes with HESI spray voltage of 3.8 kV and 3.2 kV respectively,

153

sheath gas pressure of 35 arb, auxiliary gas pressure of 10 arb, capillary temperature of

154

350 ℃, and full scan MS mode with resolution 60,000 and scan range 50-1000 (m/z).

155

Data Processing

156

The raw data acquired from the LC-MS was initially processed by the Thermo SIEVE

157

2.1 Qualitative Analysis Software (Thermo Scientific, USA) to generate a peak table

158

that included information on retention time, mass-to-charge ratio (m/z), and MS

159

intensity of the features. The retention time tolerance and mass tolerance for the peak

160

alignment was set to 0.2 min and 0.01 Da, respectively. In this table, the variables

161

presenting in at least 80% of either group were extracted and the variables with less

162

than 30% relative standard deviation (RSD) in quality control samples were then

163

retained for further multivariate data analysis because they were considered stable

164

enough for prolonged LC-Orbitrap- MS analysis. For each chromatogram, the intensity

165

of each ion was normalized to the internal standard intensity, in order to partially

166

compensate for the concentration bias of features between samples and to obtain the

167

relative intensity of features.20 The acquired data set was subjected to statistical

168

analyses.

169

Candidate ions annotations

170

Candidate chromatographic features accounting for separation among tea types were

171

identified by orthogonal projections to latent structures discriminant analysis 9

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 10 of 38

172

(OPLS-DA) modeling. The features of interest had variable importance project (VIP) >

173

than 1.5. The tandem mass spectrometry (MS/MS) of these features were collected by

174

Data Depend MS/MS model and subjected to in silico analysis that combined

175

manually matching with MS2 fragments against online databases (Metlin, HMDB,

176

Mass Bank, Mzcloud).21-24 The screened features were further filtered by database

177

TMDB (http://pcsb.ahau.edu.cn:8080/TCDB/f),25 a specific tea database enrolled all

178

the phytochemicals in tea that previously reported in literature, and the features were

179

finally annotated. Authentic standards of C, GC, EC, ECG, EGC, EGCG, gallic acid,

180

caffeine, theophylline, theobromine and theanine were used as validation.

181

Statistical analyses

182

Data were evaluated using: principal component analysis (PCA), OPLS-DA,

183

hierarchical cluster analysis (HCA) using Simca-P 14.1 software (Umetrics AB, Umeå,

184

Sweden) after Pare scaling to investigate the overall tea metabolome variations caused

185

by

186

(http://www.informationisbeautiful.net/2012/7-way-venn). Heatmap analysis was

187

performed with Multi Experiment Viewer software (version 4.8.1). The significance

188

level of the metabolite differences between groups was calculated by Analysis of

189

Variance (ANOVA) with pairwise post hoc comparisons by the method of Bonferroni

190

using the SPSS 21 software.

191

RESULTS AND DISCUSSION

192

Sensory evaluation of the teas

193

The tea products from each tea type were evaluated for color, taste, fragrance and shape.

the

process.

Venn

plots

were

drawn

10

ACS Paragon Plus Environment

using

the

website

Page 11 of 38

Journal of Agricultural and Food Chemistry

194

The results showed all samples had the expected sensory characteristics associated with

195

each tea types (Figure 2 and Table S1). This indicates that the six tea types were

196

successfully prepared from the same batch of fresh leaf. To our knowledge, this is the

197

first attempt to make all six tea types from the leaves of a single C. sinensis cultivar

198

when the leaves were harvested and processed at the same time. This required the

199

experience of a ―skilled tea processing master‖ who had the ability to thoroughly

200

manipulate all steps involved in the six typical processing methods.

201

HPLC analysis of catechins and caffeine concentrations among teas types

202

Processing methods could alter the content of catechins, which are considered the

203

major phytochemical component in tea. As shown in Table 1, total catechin levels

204

from high to low were green tea, yellow tea, oolong tea, white tea, dark tea and black

205

tea, respectively. While this result is consistent with the endogenous enzymatic

206

oxidative degradation of catechins attributed to polyphenol oxidase that is expected

207

during processing, the results of statistical analysis support the existence of three

208

distinct categories of catechin content: minimally affected (yellow or green which were

209

equivalent to unprocessed leaves), moderately affected (oolong, white, and dark), and

210

maximally affected (black). Of interest is the observation that gallic acid increased in

211

white tea, black tea and dark tea; this likely due to the ―crack reaction‖ products

212

which accumulate during fermentation and post-fermentation processing.26,27

213

Meanwhile, due to its stable chemical characteristics, the concentration of caffeine

214

was unaffected by all post-harvest processing methods.

215

Our findings are also of interest to the field of tea bioactives. Considerable attention 11

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

216

has been given to the role of tea catechins in accounting for the bioactivity of tea

217

infusions. These data support the notion that higher biological activity would be

218

expected using green or yellow activity if it were catechin dependent. On the other

219

hand, black tea would represent a useful negative control relative to the testing of

220

catechin specific mediation of biological effects in a matrix background of the other

221

chemistry present in tea leaves. Reciprocally, these data argue that bioactivity of black

222

tea is not catechin dependent, if it were made from the same C. sinensis cultivar as

223

green or yellow tea. Thus the comparative evaluation of green, yellow and black tea

224

prepared from the same C. sinensis cultivar could provide a gateway into uncharted

225

chemistry that are important to human health. Another observation of interest is that

226

previous reports have suggested that white tea would be classified into the minimal

227

effect catechin category. Our findings are inconsistent with that expectation. This

228

discrepancy is likely due to difference in chemistry of the fresh leaves attributable to

229

C. sinensis cultivar, highlighting the value of the approach reported herein in efforts to

230

better understand the chemistry of fermentation and the origins of the bioactivity of

231

various types of tea.

232

Global analysis of the metabolome by tea type

233

Metabolomics analysis was used to provide a global profile of chemical differences

234

among tea types prepared from a single C sinensis cultivar in recognition of one of the

235

guiding principles in the application of metabolomics to a new problem, i.e., ―we don’t

236

know what we don’t know‖. Accordingly, the chemical profile of the tea types was

237

analyzed using an untargeted approach. A typical total ion current chromatogram for 12

ACS Paragon Plus Environment

Page 12 of 38

Page 13 of 38

Journal of Agricultural and Food Chemistry

238

each tea type is shown in Figure 3A. A total of 2489 ion features were detected after

239

peak alignment. A Venn plot was constructed using these data and indicated that 2059

240

out of 2489 ion features were detected in all samples. Of the remaining 430 ion features,

241

no feature was specific to only one type of tea (Figure 3B). This indicates that the

242

chemical changes occurring during post-harvest processing (Figure 1) are primarily

243

quantitative in nature. Nonetheless, it should be noted that because of the strong signal

244

intensity due to catechins, signal suppression of ions present in smaller amounts is

245

known to occur. For those ions, newer deep analysis metabolomics procedures are

246

required and have been recently introduced into metabolomics data acquisition and

247

analysis work flows. Thus the analyses reported herein, while exceedingly useful for

248

the tea science field, are limited by this constraint, which may be of value in

249

understanding changes in sensory characteristics of tea cultivars and tea types,

250

especially those associated with degradation of quality over time following leaf

251

processing. Moreover, for the field of tea bioactives, there is growing recognition that

252

small molecules with striking biological activities exert meaningful effects at

253

nanomolar exposure concentrations.28 Thus, our approach can be of great value as the

254

tea field advances into the arena of deep analysis of the metabolome using tools such

255

as Metabox.29

256

Multivariate analyses

257

The mass spectra data set and the HPLC catechins data in Table 1 were analyzed by

258

PCA separately (Figure 4A and B). The chemical phenotypes of the six tea types were

259

well discriminated, all replicates from each tea type clustered together and were 13

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

260

separated from other types as shown in Figure 4A (PC1 = 38.2% and PC2 = 24.3%).

261

Figure 4B shows similar grouping except white tea and black tea are more distant. In

262

addition, the HCA analysis of these same data (Figure 4C and D) provided further

263

insight, displaying the interrelationships among tea types based on the entire profile of

264

catechins assessed, clear separation between tea types, and the order of closeness of tea

265

types were generally similar. While the position of the fresh leaves changed in the two

266

sets of HCA, the black tea and white tea reversed their positions, indicating that

267

non-catechin components play a role in distinguishing among tea types.

268

Feature annotation and Heatmap analysis of the relative variation among tea

269

types

270

OPLS-DA identified ions that distinguished among tea types. The nature of these

271

differences was summarized using several tools given the wide range of differences that

272

were observed. A total of 168 features overlapped among tea types and were excluded.

273

Compared with fresh leaves, the candidate features (VIP>1.5) that distinguished green

274

tea (43), yellow tea (48), black tea (49), dark tea (54), oolong tea (43) and white tea (51)

275

were subjected to vigorous in silico analysis. Overall 111 features were annotated and

276

98 of them were identified based on authentic standards or tandem mass spectrometry

277

(Table 2).

278

Heatmap analysis was applied to visualize the relative variation of the annotated

279

chemicals in all six tea types (Figure 5), and the relative fold change of annotated

280

features were listed in Table 3. Color coding was graded from green to red with the

281

relative intensity shift from low to high, respectively. All annotated compounds were 14

ACS Paragon Plus Environment

Page 14 of 38

Page 15 of 38

Journal of Agricultural and Food Chemistry

282

classified into six categories including amino acids, catechins, flavonoids and flavone

283

glycosides, phenolic acids, alkaloids, and others. As reflected in the heatmap,

284

manufacturing procedures either significantly decreased or increased certain

285

distinctive chemicals in a given tea type. The following sections identify several

286

notable changes in each chemical category.

287

Amino acids

288

Dark tea

289

significantly increased, 231.9- and 10.4-folds increase, respectively, after dark tea

290

processing. This finding is consistent with the possibility that these amino acids are

291

microbial formation products derived from tyrosine and aspartic acid.30

292

White tea

293

aminobutyric acid were significantly increased 4.9, 2.4,3.6,8.2,2.0,6.1 and 2.0 fold,

294

respectively, after white tea processing. This finding is consistent with previous reports

295

that proteolysis and transformation among amino acids occurs during withering and

296

that these amino acid alterations contribute to the ―umami taste‖ of white tea.17,31

297

Flavanols

298

Black tea Flavan-3-ol and polymeric catechin content changed marked during the

299

fermentation process resulting in black tea. EGCG, EGC, EC dramatically decreased

300

by 21% to 68% with concomitant increases in polymeric catechins such as theaflavin,

301

theaflavin-3-gallate, theacitrin A, theasinensin A and theasinensin B ranging from 1.6

302

to 29.6 times. This finding is consistent with other reports.32-34

303

White tea

Amino acids, such as dihydroxyphenylalanine and valine were found to be

Alanine, tyrosine, phenylalanine, proline, tryptophan, leucine and gamma

White tea is classified as a slightly fermented tea type since the 15

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

304

processing method was considered very gentle and preserved most characteristics

305

including the catechins composition of the fresh leaves.35,36 However, our result

306

showed marked decreases in catechins (19% to 75%) with a concomitant increase in

307

the polymeric catechin theasinensin B (2.3 fold). Although there was no hygrothermal

308

action in white tea processing, catechins are known to be slowly oxidized with the

309

withering. Thus it appears that the conditions of room temperature, 70% humidity, and

310

48 hours withering time was sufficient to allow the endogenous polyphenol oxidase to

311

significantly decrease catechin content.

312

Dark tea

313

times after dark tea processing compared with the other tea types. Meanwhile, the

314

catechins were also significantly decreased during dark tea processing, which may be

315

due to microbial degradation during the post fermentation step.37

316

Other notable changes

317

by processing methods. Compared with other tea types, herbacetin, malvidin and

318

quercetin 3-O-glucoside were higher levels after black tea processing (6.4, 4.5 and 3.2

319

folds higher compared with the fresh leaves, respectively). On the other hand,

320

eriodictyol, myricetin, naringenin, tiliroside and myricetin 3-glucoside were markedly

321

decreased in black tea (89%, 82%, 59 %, 94% and 36%, respectively). The same type

322

of phenomenon was observed after white tea processing. Kaempferol-3-glucoside was

323

8.9 times higher than fresh leaves. The noted changes in black and white tea are

324

consistent with the possibility that flavonoids with hydroxyls in B ring are altered

325

during the fermentation step in black tea processing or the withering step in white tea

Theaflagallin and epiafzelechin significantly increased by 27.7 and 1.5

Other flavonoids and flavonoid glycosides were also altered

16

ACS Paragon Plus Environment

Page 16 of 38

Page 17 of 38

Journal of Agricultural and Food Chemistry

326

processing.

327

Phenolic acids

328

contribute to the color and taste of a tea infusion.14,38

329

Black tea

330

by black tea processing: caffeic acid was undetectable39,40 and chlorogenic acid and

331

salicylic acid were decreased by 80.0% and 83.0%, respectively.

332

Dark tea Gallic acid and 2,5-dihydroxyphenylacetic acid sharply increased (10.3 and

333

3.8 times, respectively) due to dark tea processing compared with other teas. Whereas

334

the dark tea processing also led to marked decrease of shikimic acid, quinic acid and

335

malic acid (56%, 92% and 94%, respectively).

336

Alkaloids

337

the dry weight of the leaf.41 After processing, the caffeine level remained relatively

338

stable among the six types of tea while theophylline and theobromine markedly

339

increased to 69.4 and 1.5 times, respectively, after dark tea processing, perhaps due to

340

microbial fermentation. Aspergillus niger van Tieghem have been reported to produce

341

theobromine and theophylline.3,42,43

342

Synthesis

343

Endogenous enzymes play a very important role in tea processing methods. A

344

dominant feature of black tea processing was the formation of catechin polymers such

345

as theaflavins while the monomers of catechins and other flavonoids decreased

346

sharply. This also occurred during oolong tea except the magnitude of the changes

347

was smaller than observed after black tea processing; however, this is controversial in

Phenolic acids are another important chemical group in tea that

Caffeic acid, chlorogenic acid and salicylic acid were markedly reduced

Caffeine is the dominant alkaloid in tea and it can constitute 1.2-5.1% of

17

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

348

the tea quality arena, possibly because most studies to not consider potential

349

contributions of difference in tea variety, which was control in our study. To this point,

350

oolong tea had few distinguishing characteristic in our heatmap. We speculate that this

351

is due to our focus on nonvolatile chemical constituents; whereas, oolong tea’s most

352

distinctive characteristic is its flower aroma. We suspect oolong tea is more likely to

353

be different in its volatile components relative to other tea types. As noted above,

354

white tea processing is considered a very gentle method which results in no obvious

355

chemical changes. However, in this study we demonstrated the chemical reaction was

356

indeed comparatively strong during the long withering step, and that the chemical

357

profiling was dramatically changed compared to the fresh leaves, including an

358

increase in several amino acids, with concomitant decreases in catechins monomers

359

and phenolic acids. Such changes are likely to account for the umami or sweet but less

360

astringent taste characteristics of white tea. Dark tea was distinguished by large shifts

361

in amino acid content with concomitant increases phenolic acids, alkaloids, and some

362

pigments. Green tea and yellow tea look alike in the heatmap; this is consistent with

363

the fact that the only difference in processing is the yellowing step which apparently

364

has little effect on the chemical profiles that were detected. Nonetheless, given the

365

sensory evaluation results, distinct chemistries must underlie the sensory differences

366

that are detected and this topic merits further investigations. Finally, green tea is

367

generally considered synonymous with fresh leaves within the tea science field.

368

However, our comparison of processed green tea leaves with lyophilized fresh leaves

369

of the same Camellia cultivar showed they are not equal. Some amino acids 18

ACS Paragon Plus Environment

Page 18 of 38

Page 19 of 38

Journal of Agricultural and Food Chemistry

370

significantly increased and this may enhance the umami taste and some lipids

371

decreased which may impact aroma since they are transformed into aroma compounds.

372

This serves as an important reminder that leaf withering begins when they are plucked

373

from the plant, and that enzymatic reaction occurs even during the short time from the

374

field to the factory. The drying method of heating might also contribute to the flavor

375

and aroma of the green tea compared with the fresh leaves.

376

In summary, by using only one Camellia cultivar to exclude confounding factors due to

377

difference in chemical composition that exist among tea varieties, distinct changes in

378

chemical composition were found to be associated with each tea processing method

379

that extend beyond those traditionally associated with each process. Our findings

380

contribute new insights to the chemotaxonomy of teas and the identification of the

381

effects of processing specific techniques on tea chemistry. This work has the potential

382

to provide a foundation for continuing efforts to improve tea quality via the

383

optimization of processing methods. There exists the potential to develop new niche

384

markets through chemistry directed tailoring of processing methods to take advantage

385

of unique composition of newly identified and developed varieties of Camellia and

386

other family members of the family Theaceae.

387

ACKNOWLEDGMENT

388

We thank Shihui Fang and Jingming Ning for their technical support on the

389

processing of six tea types.

390

SUPPORTING INFORMATION

391

The result of sensory evaluation (Table S1) 19

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 20 of 38

REFERENCES 1.

Lin, Y. L.; Juan, I. M.; Chen, Y. L.; Liang, Y. C.; Lin, J. K. Composition of polyphenols in fresh

tea leaves and associations of their oxygen-radical-absorbing capacity with antiproliferative actions in fibroblast cells. J. Agric. Food Chem. 1996, 44, 1387-1394. 2.

Wu, C.; Xu, H.; Heritier, J.; Andlauer, W. Determination of catechins and flavonol glycosides in

Chinese tea varieties. Food Chem. 2012, 132, 144-149. 3.

Lv, H. P.; Zhang, Y.-J.; Lin, Z.; Liang, Y.-R, Processing and chemical constituents of Pu-erh tea: A

review. Food Res. Internat. 2013, 53, 608-618. 4.

Del, R. D.; Stewart, A. W.; Burns, J.; Lean, M. E.; Brighenti, F.; Crozier, A. HPLC-MSn analysis

of phenolic compounds and purine alkaloids in green and black tea. J. Agric. Food Chem. 2004, 52, 2807-2815. 5.

Toschi, T. G.; Bordoni, A.; Hrelia, S.; Bendini, A.; Lercker, G.; Biagi, P. L. The protective role of

different green tea extracts after oxidative damage is related to their catechin composition. J. Agric. Food Chem. 2000, 48, 3973-3978. 6.

Friedman, M.; Levin, C. E.; Sukhyun, C.; Seungun, L.; Kozukue, N. Changes in the composition

of raw tea leaves from the Korean yabukida plant during high-temperature processing to pan-fried Kamairi-cha green tea. J. Food Sci. 2009, 74, C406-412. 7.

Sakakibara, H.; Honda, Y.; Nakagawa, S.; Ashida, H.; Kanazawa, K. Simultaneous determination

of all polyphenols in vegetables, fruits, and teas. J. Agric.& Food Chem. 2003, 51, 571-581. 8.

Ogawa, N.; Ueki, H. Clinical importance of caffeine dependence and abuse. Psychiatry Clin.

Neurosci. 2007, 61, 263-268. 9.

Saeed, M.; Naveed, M.; Arif, M.; Kakar, M. U.; Manzoor, R.; Abd El-Hack, M. E.; Alagawany,

M.; Tiwari, R.; Khandia, R.; Munjal, A., Green tea (Camellia sinensis) and L-theanine: Medicinal values

and

beneficial

applications

in

humans-A comprehensive

review.

Biomedicine

&

Pharmacotherapy . 2017, 95, 1260-1275. 10. Li, P.; Dai, W.; Lu, M.; Xie, D.; Tan, J.; Yang, C.; Zhu, Y.; Lv, H.; Peng, Q.; Zhang, Y. Metabolomic analysis reveals the composition differences in 13 Chinese tea cultivars of different manufacturing suitabilities. J. Sci. Food Agric. 2018, 98, 1153-1161. 11. Tu, Y.; Bian, M.; Wan, Y.; Fei, T. Tea cultivar classification and biochemical parameter estimation from hyperspectral imagery obtained by UAV. Peer J. 2018, 6, e4858. 12. Fraser, K.; Lane, G. A.; Otter, D. E.; Harrison, S. J.; Quek, S. Y.; Hemar, Y.; Rasmussen, S. Non-targeted analysis by LC-MS of major metabolite changes during the oolong tea manufacturing in New Zealand. Food Chem. 2014, 151, 394-403. 13. Daglia, M.; Antiochia, R.; Sobolev, A. P.; Mannina, L. Untargeted and targeted methodologies in the study of tea ( Camellia sinensis L.). Food Res. Internat. 2014, 63, 275-289. 14. Dai, W.; Qi, D.; Yang, T.; Lv, H.; Guo, L.; Zhang, Y.; Zhu, Y.; Peng, Q.; Xie, D.; Tan, J., Nontargeted Analysis Using Ultraperformance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry Uncovers the Effects of Harvest Season on the Metabolites and Taste Quality of Tea (Camellia sinensis L.). J. Agric. Food Chem. 2015, 63, 9869-9878. 15. Lee, J. E.; Lee, B. J.; Chung, J. O.; Kim, H. N.; Kim, E. H.; Jung, S.; Lee, H.; Lee, S. J.; Hong, Y. S., Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography. Food Chem. 2015, 174, 452-459. 16. Chen, S.; Li, M.; Zheng, G.; Wang, T.; Lin, J.; Wang, S.; Wang, X.; Chao, Q.; Cao, S.; Yang, Z., 20

ACS Paragon Plus Environment

Page 21 of 38

Journal of Agricultural and Food Chemistry

Metabolite Profiling of 14 Wuyi Rock Tea Cultivars Using UPLC-QTOF MS and UPLC-QqQ MS Combined with Chemometrics. Molecules 2018, 81, 321. 17. Dai, W.; Xie, D.; Lu, M.; Li, P.; Lv, H.; Yang, C.; Peng, Q.; Zhu, Y.; Guo, L.; Zhang, Y., Characterization of white tea metabolome: Comparison against green and black tea by a nontargeted metabolomics approach. Food Res. Internat. 2017, 40-45. 18. Wei, K.; Zhang, Y.; Wu, L.; Li, H.; Li, R.; Bai, P.; Zhang, C.; Zhang, F.; Xu, L.; Wang, L., Gene expression analysis of bud and leaf color in tea. Plant Physiol Biochem. 2016, 107, 310-318. 19. Tai, Y.; Wei, C.; Yang, H.; Zhang, L.; Chen, Q.; Deng, W.; Wei, S.; Zhang, J.; Fang, C.; Ho, C. Transcriptomic and phytochemical analysis of the biosynthesis of characteristic constituents in tea (Camellia sinensis) compared with oil tea (Camellia oleifera). BMC Plant Biol. 2015, 15, 190. 20. Wu, Y.; Li, L. Sample normalization methods in quantitative metabolomics. J. Chromatogr. A 2016, 1430, 80-95. 21. Tautenhahn, R.; Cho, K.; Uritboonthai, W.; Zhu, Z.; Patti, G. J.; Siuzdak, G. An accelerated workflow for untargeted metabolomics using the METLIN database. Nature Biotechnol. 2012, 30, 826-828. 22. Wishart, D. S.; Jewison, T.; Guo, A. C.; Wilson, M.; Knox, C.; Liu, Y.; Djoumbou, Y.; Mandal, R.; Aziat, F.; Dong, E. HMDB 3.0—The Human Metabolome Database in 2013. Nucleic Acids Res. 2013, 41, D801. 23. Horai, H.; Arita, M.; Kanaya, S.; Nihei, Y.; Ikeda, T.; Suwa, K.; Ojima, Y.; Tanaka, K.; Tanaka, S.; Aoshima, K. MassBank: a public repository for sharing mass spectral data for life sciences. J. Mass Spectr. 2010, 45, 703-714. 24. Wang, J.; Peake, D. A.; Mistrik, R.; Huang, Y.; Inc, T. F. S.; Jose, S.; Bratislava, A. Platform to Identify Endogenous Metabolites Using a Novel High Performance Orbitrap MS and the mzCloud Library. Thermo Scientific. 25. Yue, Y.; Chu, G. X.; Liu, X. S.; Tang, X.; Wang, W.; Liu, G. J.; Yang, T.; Ling, T. J.; Wang, X. G.; Zhang, Z. Z., Xia, T.; Wan, X. C.; Bao, G. H. TMDB: A literature-curated database for small molecular compounds found from tea. BMC Plant Biol. 2014, 14, 243-251. 26. Lin, J. K.; Lin, C. L.; Liang, Y. C.; Lin-Shiau, S. Y.; .; Juan, I. M. Survey of catechins, gallic Acid, and methylxanthines in green, oolong, pu-erh, and black teas. J. Agric. Food Chem.1998, 46, 3635-3642. 27. Lee, V. S.; Dou, J.; Chen, R. J.; Lin, R. S.; Lee, M. R.; Tzen, J. T. Massive accumulation of gallic acid and unique occurrence of myricetin, quercetin, and kaempferol in preparing old oolong tea. J. Agric. Food Chem. 2008, 56, 7950-7956. 28. Gray, A. I.; Igoli, J. O.; Edrada-Ebel, R., Natural products isolation in modern drug discovery programs. Methods Mol Biol. 2012, 864, 515-534. 29. Wanichthanarak, K.; Fan, S.; Grapov, D.; Barupal, D. K.; Fiehn, O. Metabox: A toolbox for metabolomic data analysis, interpretation and integrative exploration. PloS One 2017, 12, e0171046. 30. Zhu, Y.; Luo, Y.; Wang, P.; Zhao, M.; Li, L.; Hu, X.; Chen, F. Simultaneous determination of free amino acids in Pu-erh tea and their changes during fermentation. Food Chem. 2016, 194, 643-649. 31. Unachukwu, U. J.; Ahmed, S.; Kavalier, A.; Lyles, J. T.; Kennelly, E. J. White and green teas (Camellia sinensis var. sinensis): variation in phenolic, methylxanthine, and antioxidant profiles. J. Food Sci. 2010, 75, C541–C548. 32. Wan, X.; Nursten, H. E.; Cai, Y.; Davis, A. L.; Wilkins, J. P. G.; Davies, A. P. A New Type of tea pigment—From the chemical oxidation of epicatechin gallate and isolated from tea. J. Sci. Food Agric. 21

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 22 of 38

2015, 74, 401-408. 33. Wang, Y.; Ho, C.-T. Functional Contribution of Polyphenols in Black Tea, In ACS Symp. Ser., 1036, 2010; p 45-59. 34. Stodt, U. W.; Blauth, N.; Niemann, S.; Stark, J.; Pawar, V.; Jayaraman, S.; Koek, J.; Engelhardt, U. H. Investigation of processes in black tea manufacture through model fermentation (oxidation) experiments. J. Agric. Food Chem. 2014, 62, 7854-7861. 35. Tan, J.; Engelhardt, U. H.; Lin, Z.; Kaiser, N.; Maiwald, B. Flavonoids, phenolic acids, alkaloids and theanine in different types of authentic Chinese white tea samples. J. Food Comp. Anal. 2016, 57, 8-15 36. Mao, J. T. Chapter 3 - White Tea: The Plants, Processing, Manufacturing, and Potential Health Benefits. Elsevier Inc.: 2013; p 33-40. 37. Zeng, L.; Tian, X.; Luo, L.; Guan, X.; Gao, L. Characteristic components of aqueous extracts of raw Pu-erh tea with different storage times. Food Sci. 2017, 38, 198-205. 38. Liu, Q.; Wu, L.; Pu, H.; Li, C.; Hu, Q. Profile and distribution of soluble and insoluble phenolics in Chinese rapeseed (Brassica napus). Food Chem. 2012, 135, 616-622. 39. Dufresne, C. J.; Farnworth, E. R. A review of latest research findings on the health promotion properties of tea. J. Nutr. Biochem. 2001, 12, 404-421. 40. Naveed, M.; Bibi, J.; Kamboh, A. A.; Suheryani, I.; Kakar, I.; Fazlani, S. A.; Fangfang, X.; Kalhoro, S. A.; Yunjuan, L.; Kakar, M. U. Pharmacological values and therapeutic properties of black tea (Camellia sinensis): A comprehensive overview. Biomed. Pharmacother. 2018, 100, 521-531. 41. Obuchowicz, J.; Engelhardt, U. H.; Donnelly, K. Flavanol database for green and black teas utilising ISO 14502-1 and ISO 14502-2 as analytical tools. J. Food Comp. Anal. 2011, 24, 411-417. 42. Wang, X.; Wan, X.; Hu, S.; Pan, C. Study on the increase mechanism of the caffeine content during the fermentation of tea with microorganisms. Food Chem. 2008, 107, 1086-1091. 43. Wang, Z.; Tan, H.; Ling, S. Dynamics of major nitrogenous compounds during the primary processing of dark green tea. J.Tea Sci. 1991, 11, 29-33.

FUNDING This study was supported by the Key research and development projects of Anhui province (1804b06020367), the Earmarked Fund for Anhui Featured Agricultural Development Project (Anhui Provincial Agriculture Commission, 2016-188), the Earmarked fund for China Agriculture Research System (CARS-19), Funds of Anhui Provincial Science and Technology Department (1408085MKL39), the High-End Foreign

Experts

Recruitment

Program

(GDT20143400024),

Anhui

Major

Demonstration Project for Leading Talent Team on Tea Chemistry and Health (1306c083018). 22

ACS Paragon Plus Environment

Page 23 of 38

Journal of Agricultural and Food Chemistry

FIGURE CAPTIONS Figure 1. Flow diagram depicting the manufacture processes used to produce the six tea types investigated. Figure 2. The pictures of processed six tea types that used for sensory evaluation (upper: dry leaves, lower: tea infusion). (A) Green tea (B) Yellow tea (C) White tea (D) Oolong tea (E) Black tea (F) Dark tea Figure 3. LC-Orbitrap-MS analysis of six tea types (A) Typical total ion current (TIC) chromatogram (B) Venn plot. Numbers represent the detected features in relative teas. Figure 4. Multivariate statistical analysis of six tea types. (A and B) The PCA score plot of the LC-MS data set and the HPLC data set, respectively. (C and D) the HCA plot of the LC-MS data set and the HPLC data set, respectively. Figure 5. The heatmap analysis of annotated chemicals in fresh leaves and six tea types by chemical categories. The compounds were identified either by MS2 spectra* or by authentic standards#.

23

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 24 of 38

TABLES Table 1 The Absolute Content of Catechins and Caffeine in Six Tea Types (mean±sem, n=3, mg/g) Fresh leaves

Green tea

Yellow tea

Oolong tea

d

c

0.38±0.004

C

0.97±0.07a

0.98±0.11a

GC

2.15±0.03b

EGC CAF

29.80±0.15

EC

7.12±0.17b

8.41±0.05a

7.94±0.30ab

5.03±0.05c

EGCG

69.53±0.63a

75.04±0.94a

71.65±2.57a

GCG

2.12±0.05a

2.69±0.06a

ECG

13.67±0.37ab 114.9±1.80b

Catechins

0.23±0.02

d

GA

Total

a-e

d

0.33±0.01

White tea

Black tea

cd

Dark tea b

4.54±0.25a

0.98±0.02

0.82±0.15

1.94±0.09

0.90±0.02a

0.76±0.02ab

0.51±0.03b

0.23±0.04b

0.82±0.04a

2.78±0.04ab

2.67±0.13ab

1.69±0.03b

0.94±0.07c

0.55±0.01c

3.20±0.32a

19.37±0.55b

25.92±1.34a

23.25±0.60ab

13.09±0.52c

6.37±0.06d

0.88±0.09e

22.14±0.56b

b

ab

ab

ab

ab

33.71±0.53a

3.40±0.07d

Not detected

7.64±0.24ab

42.98±0.21c

49.05±0.68b

5.46±0.43e

21.47±0.06d

2.85±0.69a

1.41±0.08a

2.84±0.12a

2.04±0.62a

3.07±0.38a

14.98±0.27a

14.55±0.65a

8.55±0.05c

12.13±0.38b

2.68±0.17e

6.00±0.15d

130.8±2.51a

123.8±3.98ab

73.50±0.9c

75.24±0.81c

11.84±0.57d

64.32±0.61c

30.96±0.31

31.51±1.33

30.74±0.17

33.43±0.42

a

31.16±0.75

: Values in the same row that are labeled with different superscript letters differ significantly (P < 0.05). Statistical analysis was

ANOVA with pairwise post hoc comparisons by the method of Bonferroni.

24

ACS Paragon Plus Environment

Page 25 of 38

Journal of Agricultural and Food Chemistry

Table 2 Tentative Features Annotation through Tandem Mass Spectrometry and /or Authentic Standards Order 1

Accurate MZ 307.0801

Theoretical MZ 307.0812

Delta ppm 3

Adduct ion

RT

Formula

Name

Fragments

[M+H]

+

2.11

C15H14O7

Gallocatechin*

+

#

139

169

289

137

2

443.0965

443.0973

1

[M+H]

2.44

C22H18O10

Catechin gallate*

123

139

153

291

3

611.1384

611.1395

1

[M+H]+

2.46

C30H26O14

Theasinensin C*

139

611

593

307

247

2

[M+H]

+

3.14

C30H26O13

Epigallocatechin-(4beta->8)-catechin

[M+H]

+

3.24

C15H14O7

Epigallocatechin*#

127

169

141

139

181

[M+H]

+

3.25

C37H30O18

Theasinensin B*

593

611

425

443

[M+H]

+

139

121

247

273

261

[M+H]

+

3.49

C15H14O6

Epicatechin*

139

123

147

207

179

[M+H]

+

3.59

C37H30O17

Epicatechin-(4beta->8)-epigallocatechin 3-O-gallate

[M+H]

+

3.62

C22H18O11

Epigallocatechin Gallate*#

289

127

307

139

151

[M+H]

+

3.66

C22H18O11

Gallocatechin 3-O-gallate*

138

153

307

289

+

4 5 6 7 8 9 10 11

595.1429 307.0804 763.1491 291.0855 291.0854 747.1553 459.091 459.091

595.1446 307.0812 763.1505 291.0863 291.0863 747.1556 459.0922 459.0922

2 1 2 2 0 2 2

3.46

#

C15H14O6

Catechin*

#

12

275.0904

275.0914

3

[M+H]

3.79

C15H14O5

Epiafzelechin*

139

137

257

121

13

443.096

443.0973

2

[M+H]+

3.84

C22H18O10

Epicatechin 3-O-gallate*#

139

153

123

425

291

3

[M+H]

+

4.05

C22H18O9

Epiafzelechin 3-O-gallate*

139

153

107

121

409

[M+H]

+

4.06

C29H24O12

Theaflavin*

427

139

259

163

271

[M+H]

+

4.1

C36H28O16

Theaflavin-3-gallate*

139

397

699

127

-

4.14

C36H28O16

Theaflavin Monogallates*

577

407

169

241

+

4.18

C43H32O20

Theaflavin Digallate*

731

333

561

277

[M-H]

-

3.38

C37H28O18

Theacitrin A*

741

169

137

151

[M-H]

-

3.73

C44H34O22

Theasinensin A*

761

743

283

423

[M-H]

-

3.8

C23H20O11

Epigallocatechin 3-(3-methylgallate)*

125

161

307

183

-

14 15 16 17 18 19 20 21

427.1010 565.1323 717.1431 715.1305 869.1545 759.1207 913.1473 471.0938

427.1024 565.1341 717.145 715.1306 869.156 759.1203 913.1469 471.0933

3 2 1 1 0 0 0

[M-H]

[M+H]

621

22

609.0886

609.0886

0

[M-H]

3.89

C29H22O15

Epigallocatechin 3,5,-di-O-gallate

23

399.0729

399.0722

1

[M-H]-

3.97

C20H16O9

Theaflagallin*

137

261

339

381

219

24

911.1318

911.1313

0

[M-H]-

4.02

C44H32O22

Theacitrin C*

169

455

855

125

773

25

ACS Paragon Plus Environment

273

455

607

Journal of Agricultural and Food Chemistry

25 26

551.0839 699.1362

551.0831 699.1355

Page 26 of 38

1

[M-H]-

4.07

C27H20O13

Epitheaflagallin 3-O-gallate*

169

125

413

491

533

381

0

[M-H]

-

4.12

C36H28O15

Theaflavate B*

137

427

561

681

383

289

-

169

289

535

125

27

851.1470

851.1465

0

[M-H]

4.2

C43H32O19

Theaflavate A*

713

579

28

90.05455

90.05496

4

[M+H]+

0.88

C3H7NO2

Alanine*

90

72

29

116.0702

116.0706

3

[M+H]+

0.9

C5H9NO2

Proline*

70

68

5

[M+H]

+

0.91

C5H11NO2

Valine*

72

55

57

[M+H]

+

0.92

C11H20N2O3

Pro-Leucine*

114

166

86

[M+H]

+

0.92

C5H9NO4

Glutamate*

84

102

56

[M+H]

+

0.94

C6H13NO2

Leucine*

86

69

[M+H]

+

1.23

C13H24N2O8

1-deoxy-1-L-theanino-D-fructopyranose*

158

208

253

[M+H]

+

0.96

C7H14N2O3

Theanine*

158

129

84

[M+H]

+

1.23

C6H13N3O3

Argininic acid*

158

60

71

140

+

30 31 32 33 34 35 36

118.0856 229.1540 148.0601 132.1014 337.1605 175.1071 176.1045

118.0863 229.1547 148.0604 132.1019 337.1598 175.1077 176.103

3 2 4 2 3 5

#

183

301

114

37

182.0805

182.0812

3

[M+H]

1.24

C9H11NO3

Tyrosine*

165

136

91

119

38

198.0754

198.0761

3

[M+H]+

1.41

C9H11NO4

Dihydroxyphenylalanine*

152

107

135

139

3

[M+H]

+

2.03

C9H11NO2

Phenylalanine*

120

103

93

[M+H]

+

3.44

C11H12N2O2

Tryptophan*

118

146

188

159

-

0.86

C4H7NO4

Aspartic Acid*

72

104

[M+H]

+

0.91

C4H9NO2

γ-Aminobutryic acid*

87

69

[M+H]

+

3.26

C15H12O6

Eriodictyol*

271

289

137

153

261

121

[M+H]

+

3.36

C30H26O13

Tiliroside*

287

577

147

105

269

431

[M+H]

+

3.5

C27H30O15

Vicenin Ⅱ*

577

559

445

427

[M+H]

+

3.55

C30H26O12

Procyanidin B2*

127

409

291

427

301

287

+

147

329

39 40 41 42 43 44 45 46

166.0857 205.0964 132.0309 104.0703 289.0700 595.1437 595.1642 579.1476

166.0863 205.0972 132.0302 104.0706 289.0707 595.1446 595.1658 579.1497

3 5 2 2 1 2 3

[M-H]

47

595.1641

595.1658

2

[M+H]

3.57

C27H30O15

Kaempferol 3-rungioside

48

433.1109

433.1129

4

[M+H]+

3.6

C21H20O10

Kaempferol 3-rhamnoside*

287

269

257

147

4

[M+H]

+

3.6

C27H30O14

Kaempferitrin*

287

285

415

433

[M+H]

+

3.63

C26H28O14

Kaempferol 3-rhamnoside-7-arabionopyranoside

49 50

579.1683 565.1539

579.1708 565.1552

2

26

ACS Paragon Plus Environment

163

Page 27 of 38

Journal of Agricultural and Food Chemistry

51 52

433.1118 433.1107

433.1129 433.1129

2

[M+H]+

3.48

C21H20O10

Isovitexin*

283

281

339

415

313

403

2

[M+H]

+

3.69

C21H20O10

Vitexin*

415

397

283

367

337

323

+

153

165

273

290

274

53

319.0437

319.0448

3

[M+H]

3.7

C15H10O8

Myricetin*

54

449.1061

449.1078

3

[M+H]+

3.72

C21H20O11

Quercetin 3-O-rhamnoside

55

611.1596

611.1607

1

[M+H]+

3.74

C27H30O16

Rutin*

303

465

129

3

[M+H]

+

3.74

C15H10O6

Cyanidin*

137

213

109

241

[M+H]

+

3.78

C15H10O7

Delphinidin*

229

257

201

125

[M+H]

+

3.8

C15H10O7

Quercetin*

153

137

229

257

285

[M+H]

+

3.84

C15H10O7

Morin*

153

219

205

137

165

[M+H]

+

3.84

C15H12O5

Naringenin*

153

147

119

[M+H]

+

4.7

C15H10O6

Kaempferol*

258

153

121

165

213

[M+H]

+

3.88

C20H18O11

Quercetin 3-arabinopyranoside

+

274

56 57 58 59 60 61 62

287.0541 303.0487 303.0489 303.0487 273.075 287.0539 435.0909

287.055 303.0499 303.0499 303.0499 273.0758 287.055 435.0922

4 3 4 2 4 2

63

579.1486

579.1497

1

[M+H]

4.21

C30H26O12

Procyanidin B5

64

303.0485

303.0499

4

[M+H]+

4.35

C15H10O7

Herbacetin*

169

121

181

2

[M+H]

+

4.66

C17H14O7

Malvidin*

242

287

213

[M+H]

+

3.87

C15H10O6

Luteolin*

153

135

241

[M+H]

+

5.96

C21H20O11

Kamepferol 3-glucoside*

287

259

153

[M-H]

-

1.76

C30H26O14

Prodelphinidin B

[M-H]

-

3.44

C28H24O17

Myricetin 3-(6''-galloylglucoside)

[M-H]

-

3.49

C22H22O11

Kaempferide 3-glucoside*

301

283

427

163

445

[M-H]

-

3.71

C21H20O13

Myricetin 3-glucoside*

316

317

287

271

178

[M-H]

-

3.75

C33H40O20

Kaempferol 3-rutinoside-7-galactoside

-

153

301

65 66 67 68 69 70 71 72

331.0804 287.0538 449.1061 609.1256 631.0949 461.1097 479.0838 755.2038

331.0812 287.055 449.1078 609.125 631.0941 461.1089 479.0831 755.204

4 3 0 1 1 1 0

73

463.0891

463.0882

1

[M-H]

3.8

C21H20O12

Quercetin 3-O-glucoside*

300

137

229

74

154.0494

154.0499

3

[M+H]+

1.22

C7H7NO3

4-Aminosalicylic acid*

108

107

78

75

139.0385

139.039

3

[M+H]+

2.1

C7H6O3

2,5-Dihydroxybenzaldehyde*

111

93

3

-

3.35

C8H8O4

2,5-Dihydroxyphenylacetic acid*

149

123

76

167.0356

167.035

[M-H]

27

ACS Paragon Plus Environment

161

Journal of Agricultural and Food Chemistry

77 78

139.0385 165.0541

139.039 165.0546

Page 28 of 38

3

[M+H]+

3.23

C7H6O3

4-Hydroxybenzoic acid*

95

121

109

3

[M+H]

+

4.84

C9H8O3

4-Hydroxycinnamic acid*

119

105

147

+

79

163.0386

163.039

2

[M+H]

3.16

C9H6O3

4-Hydroxycoumarin*

121

91

80

175.0255

175.0248

4

[M-H]-

1.25

C6H8O6

Ascorbic acid*

87

115

127

71

1

+

2.17

C9H8O4

Caffeic acid*

135

117

145

163

[M-H]

-

2.61

C22H18O12

Chicoric acid*

179

161

291

311

427

[M-H]

-

2.84

C16H18O9

Chlorogenic acid*

191

161

[M-H]

-

3.41

C9H8O2

Cinnamic acid*

129

103

[M+H]

+

3.6

C9H8O3

Coumaric acid*

91

119

147

[M+H]

+

3.52

C9H6O2

Coumarin*

91

103

77

-

3.47

C14H10O9

Digallate*

125

293

151

169

107

153

127

125

109

69

113

81 82 83 84 85 86 87 88

181.0492 473.0737 353.0886 147.0458 165.054 147.0435 321.026 171.0283

181.0495 473.0726 353.0878 147.0452 165.0546 147.0441 321.0252 171.0288

2 2 4 3 3 2 2

[M+H]

[M-H]

+

1.38

C7H6O5

Gallic acid*

-

[M+H]

#

89

131.0356

131.035

4

[M-H]

2.33

C5H8O4

Glutaric acid*

87

90

118.0647

118.0651

3

[M+H]+

3.36

C8H7N

Indole*

91

91

188.0701

188.0706

2

[M+H]+

3.36

C11H9NO2

Indoleacrylic acid*

170

142

115

6

-

1.05

C4H6O5

Malic acid*

115

71

89

[M+H]

+

2.17

C9H17NO5

Pantothenic acid*

90

184

202

[M+H]

+

1.32

C10H16O

Piperitone*

135

111

109

-

1.04

C7H12O6

Quinic acid*

85

93

127

[M+H]

+

3.79

C7H6O2

Salicylaldehyde*

77

95

[M+H]

+

3.84

C7H6O3

Salicylic acid*

121

95

[M-H]

-

3.57

C7H10O5

Shikimic acid*

93

67

59

137

-

92 93 94 95 96 97 98

133.0151 220.1172 153.1274 191.0566 123.0436 139.0384 173.0461

133.0143 220.118 153.1274 191.0561 123.0441 139.039 173.0456

3 0 2 4 4 2

[M-H]

[M-H]

57

99

427.0682

427.0671

2

[M-H]

3.99

C21H16O10

Theaflavic acid*

137

289

383

409

100

345.0808

345.0816

2

[M+H]+

1.42

C14H16O10

Theogallin*

193

299

153

237

3

-

1.24

C13H16O10

β-Glucogallin*

169

125

179

313

+

0.93

C5H13NO

Choline*

60

58

101 102

331.0681 104.1064

331.0671 104.107

5

[M-H]

[M+H]

28

ACS Paragon Plus Environment

141

Page 29 of 38

Journal of Agricultural and Food Chemistry

103 104

118.0857 181.0717

118.0863 181.072

4

[M+H]+

1

[M+H]

+ +

1.14

C5H11NO2

1.93

Betain*

C7H8N4O2

58

59

#

138

153

#

Theobromin*

110

105

181.0714

181.072

1

[M+H]

3.3

C7H8N4O2

Theophylline*

124

96

106

195.0864

195.0877

5

[M+H]+

3.6

C8H10N4O2

Caffeine*#

138

110

123

4

[M+H]

+

7.6

C26H50NO7P

PC(18:2/0:0)*

263

221

337

417

[M+H]

+

8.1

C24H50NO7P

PC(16:0/0:0)*

184

104

[M+H]

+

8.88

C35H34N4O6

Phaeophorbide B*

589

561

571

547

[M+H]

+

10.13

C35H36N4O5

Pheophorbide A

[M+H]

+

10.54

C33H34N4O3

Pyropheophorbide A

107 108 109 110 111

520.3375 496.3373 607.2528 593.2724 535.2675

520.3398 496.3398

5

607.2551

3

593.2759

5

535.2704

5 2

*

#

The compounds were identified either by MS spectra or by authentic standards .

29

ACS Paragon Plus Environment

88

Journal of Agricultural and Food Chemistry

Page 30 of 38

Table 3 Relative Fold Change of Annotated Chemicals in Six Tea Types Fold change (Tea vs. Fresh leaves) ID

Name

#

Fresh

Green

Yellow

Oolong

White

Black

Dark

leaves

tea

tea

tea

tea

tea

tea

a

a

b

0.5

d

0.25

e

0.72c

1

Gallocatechin*

1.00

0.96

0.87

2

Catechin gallate*

1.00a

0.86b

0.84b

0.58d

0.81bc

0.01e

0.73c

3

Theasinensin C*

1.00a

0.84b

0.79b

0.56d

0.68c

0.02f

0.47e

4

EGC-(4β-8)-C

1.00b

0.89c

0.88c

0.64d

0.53e

0.02f

1.15a

5

Epigallocatechin*#

1.00a

1.01a

1.05a

0.75b

0.38c

0.05d

0.70b

6

Theasinensin B*

1.00d

0.82e

0.82e

1.60c

2.29b

3.28a

0.57f

7

Catechin*#

1.00c

1.11b

1.18a

0.85d

0.31e

0.11f

1.00c

8

Epicatechin*#

1.00c

1.12b

1.19a

0.86d

0.32e

0.11f

0.98c

a

a

a

b

b

c

0.47c

9

EC-(4β-8)-EGCG

1.00

1.06

1.09

0.77

10

Epigallocatechin Gallate*#

1.00b

1.19a

1.28a

0.98b

0.79c

0.18e

0.61d

11

Gallocatechin 3-O-gallate*

1.00b

1.21a

1.31a

1.01b

0.81c

0.19e

0.63d

12

Epiafzelechin*

1.00bc

1.03b

0.98c

0.78d

0.39e

0.78d

1.53a

13

Epicatechin 3-O-gallate*#

1.00c

1.24b

1.38a

1.03c

0.81d

0.37f

0.70e

14

Epiafzelechin 3-O-gallate*

1.00b

0.83d

0.88c

1.08a

0.70e

1.11a

0.23f

15

Theaflavin*

1.00c

0.12f

0.12f

1.24b

0.70d

1.56a

0.24e

16

Theaflavin 3-gallate*

1.00c

0.21e

0.2e

4.15b

0.87d

7.31a

0.13e

17

Theaflavin Monogallates*

1.00c

0.21e

0.2e

4.13b

0.87d

7.20a

0.13e

18

Theaflavin Digallate*

1.00c

0.27d

0.17d

17.05b

1.40c

30.74a

0.06d

bc

c

c

b

a

1.00c

1.00

Theacitrin A*

1.00

20

Theasinensin A*

1.00d

1.49d

1.62d

5.49c

7.36b

29.57a

1.39d

21

EGC-3-(3-methylgallate)*

1.00c

1.11bc

1.12b

1.25a

1.14b

0.79d

1.03c

22

Epigallocatechin 3,5,-di-O-gallate

1.00b

0.91c

0.91c

0.80d

1.10a

0.81d

0.30e

23

Theaflagallin*

1.00e

0.31f

0.59ef

7.50c

2.91d

16.15b

27.67a

24

Theacitrin C*

1.00d

0.39d

0.45d

10.07b

3.39c

38.84a

0.24d

25

Epitheaflagallin 3-O-gallate

1.00e

0.53e

0.54e

29.2b

8.54c

97.18a

6.90d

26

Theaflavate B*

1.00d

0.003e

0.003e

4.95c

4.01c

34.27a

6.49b

27

Theaflavate A*

1.00c

1.00c

1.00c

5421.64b

1094.21c

50085.89a

1.00c

28

Alanine*

1.00d

1.11c

1.04cd

1.07cd

4.97a

2.20b

0.27e

29

Proline*

1.00

e

d

d

c

a

b

0.39f

30

Valine*

1.00f

1.58de

1.54e

31

Pro-Leucine*

1.00f

2.27c

32

Glutamate*

1.00d

33

Leucine*

34

1-deoxy-1-L-theanino-

1.64

1.11

2.24

1.83

0.45

19

1.75

1.00

b

0.82

0.03

f

25.26

8.15

3.91

1.72d

4.55b

2.61c

10.44a

2.40b

1.46e

1.42e

1.88d

3.43a

2.54b

2.73a

1.08d

1.46c

2.62ab

0.82e

1.00e

1.67cd

1.22de

1.77c

6.08a

3.00b

0.85e

1.00c

1.36b

1.02c

1.01c

0.93c

1.59a

0.72d

D-fructopyranose * 35

Theanine*#

1.00a

0.95b

0.97ab

0.84c

0.63d

0.82c

0.20e

36

Argininic acid*

1.00a

0.96b

0.97ab

0.84c

0.62d

0.83c

0.20e

37

Tyrosine*

1.00c

0.73d

0.72d

1.35b

2.45a

1.38b

0.39e

b

b

b

b

b

1.39

b

3.56a

2.6b

38

Dihydroxyphenylalanine*

1.00

39

Phenylalanine*

1.00e

0.98

1.06

2.21c

1.96d

1.12

2.26c

30

ACS Paragon Plus Environment

1.17

231.91a 0.43f

Page 31 of 38

Journal of Agricultural and Food Chemistry

40

Tryptophan*

1.00d

0.99d

0.88e

1.08c

2.08a

1.55b

0.26f

41

Aspartic Acid*

1.00d

2.08b

2.07b

1.86c

1.82c

2.55a

0.17e

42

γ-Aminobutryic acid*

1.00b

0.43d

0.32e

1.01b

2.03a

0.95c

0.09f

43

Eriodictyol*

1.00a

1.02a

1.05a

0.77b

0.54c

0.11d

0.6c

44

Tiliroside*

1.00b

0.89c

0.88c

0.63d

0.6d

0.06e

1.17a

45

Vicenin Ⅱ*

1.00c

1.24a

1.08b

0.94d

1.10b

1.02c

0.85e

46

Procyanidin B2*

1.00b

1.06b

1.22a

0.96b

0.53c

0.12d

0.60c

47

Kaempferol 3-rungioside

1.00cd

1.20a

1.05bc

0.92e

1.09b

0.98d

0.79f

48

Kaempferol 3-rhamnoside*

1.00d

1.33b

1.19c

0.86e

0.87e

0.72f

2.11a

c

a

a

b

b

c

1.03c

49

Kaempferitrin*

1.00

1.32

1.28

1.09

50

Kaempferol-3-rha-7-ara

51

1.00d

1.17b

0.98d

1.09c

1.08c

1.27a

0.97d

Isovitexin*

1.00d

1.21b

1.06c

0.81e

0.84e

0.67f

1.63a

52

Vitexin*

1.00d

1.32b

1.18c

0.85e

0.87e

0.72f

2.07a

53

Myricetin*

1.00a

0.97a

0.99a

0.75b

0.97a

0.18d

0.61c

54

Quercetin 3-O-rhamnoside

1.00b

1.05a

1.06a

0.67e

0.91c

0.90c

0.77d

55

Rutin*

1.00c

1.20b

1.28a

0.95c

1.15b

1.31a

1.17b

56

Cyanidin*

1.00c

1.00c

1.02c

0.90d

1.08b

1.34a

0.71e

57

Delphinidin*

1.00a

0.95b

0.94b

0.70c

1.03a

1.03a

0.56d

58

Quercetin*

1.00b

0.95c

0.94c

0.70d

1.03ab

1.04a

0.56e

59

Morin*

1.00a

0.96b

0.94b

0.70c

1.03a

1.03a

0.56d

c

b

a

d

e

g

0.67f

60

Naringenin*

1.00

61

Kaempferol*

1.00d

62

Quercetin 3-arabinopyranoside

63

1.18

1.12

1.28

0.93

1.06bc

1.06b

0.81e

1.02cd

1.10a

0.70f

1.00bc

0.97cd

0.94d

0.83e

1.03ab

1.08a

0.73f

Procyanidin B5

1.00c

1.24a

1.06b

0.97cd

0.96d

0.80e

1.00c

64

Herbacetin*

1.00g

3.07e

3.38d

4.04c

1.51f

6.38b

7.99a

65

Malvidin*

1.00e

1.05e

0.84f

2.59c

1.83d

4.52a

2.97b

66

Luteolin*

1.00g

2.29f

3.33d

3.82c

2.69e

6.80b

7.50a

67

Kamepferol 3-glucoside*

1.00e

0.56f

0.28g

3.22d

8.94a

3.66c

4.13b

68

Prodelphinidin B

1.00ab

0.74c

0.72c

0.75c

0.93b

0.47d

1.03a

69

Myricetin 3-(6''-galloylglucoside)

1.00f

1.40e

3.21c

4.28b

5.93a

1.93d

0.09g

cd

bc

d

b

b

a

1.96

0.07e

1.11

Kaempferide 3-glucoside*

1.00

71

Myricetin 3-glucoside*

1.00d

1.15b

1.10bc

1.06cd

1.35a

0.64f

0.88e

72

Kaempferol-3-rut-7-gal

1.00d

1.44bc

1.43bc

1.52b

1.35c

3.79a

0.78e

73

Quercetin 3-O-glucoside*

1.00e

1.51b

1.56b

1.34c

1.11d

3.16a

1.24c

74

4-Aminosalicylic acid*

1.00b

6.40b

7.06b

3.43b

10.38b

6.13b

569.12a

75

2,5-Dihydroxybenzaldehyde*

1.00a

0.92b

0.82c

0.49e

0.27f

0.04g

0.74d

76

2,5-Dihydroxyphenylacetic acid*

1.00b

1.06b

1.01b

0.88c

0.72d

0.44e

3.45a

77

4-Hydroxybenzoic acid*

1.00b

1.01ab

1.03a

0.74d

0.45e

0.08f

0.86c

78

4-Hydroxycinnamic acid*

1.00a

0.98ab

0.98ab

0.68d

0.88c

0.7d

0.95b

79

4-Hydroxycoumarin*

1.00a

1.00a

0.98a

0.58c

0.97a

0.18d

0.76b

c

d

d

cd

19.15

a

3.46

1.28

1.07

1.30

0.41

70

d

0.83

0.79

1.05

Ascorbic acid*

1.00

81

Caffeic acid*

1.00ab

1.14a

0.89b

0.43c

0.26d

-e

0.92b

82

Chicoric acid*

1.00a

0.35c

0.32d

0.18e

0.58b

0.10f

0.17e

83

Chlorogenic acid*

1.00a

0.98a

0.97a

0.59b

0.99a

0.20d

0.33c

31

ACS Paragon Plus Environment

1.11

1.52

15.89b

80

Journal of Agricultural and Food Chemistry

Page 32 of 38

84

Cinnamic acid*

1.00b

1.12a

1.09a

0.94b

0.56c

0.17d

1.14a

85

Coumaric acid*

1.00b

0.89c

0.93c

0.78d

1.05b

1.17a

0.62e

86

Coumarin*

1.00cd

1.32b

1.36b

1.06c

0.99cd

1.68a

0.91d

87

Digallate*

1.00c

1.02bc

1.00c

0.94d

1.51a

1.07b

0.05e

88

Gallic acid*#

1.00d

0.96d

1.21c

1.35c

0.87d

2.93b

10.32a

89

Glutaric acid*

1.00e

0.92e

1.00e

1.26d

1.50c

2.99b

3.81a

90

Indole*

1.00c

1.00c

0.91d

1.02c

1.77a

1.27b

0.42e

91

Indoleacrylic acid*

1.00d

0.96d

0.86e

1.05c

2.03a

1.39b

0.26f

92

Malic acid*

1.00c

1.02c

1.08b

0.95d

0.69e

1.35a

0.06f

b

c

d

e

c

e

1.12a

93

Pantothenic acid*

1.00

94

Piperitone*

1.00b

1.02b

1.35a

0.75c

0.56d

0.33e

0.58d

95

Quinic acid*

1.00b

0.84e

0.90d

0.95c

0.81f

1.18a

0.08g

96

Salicylaldehyde*

1.00c

1.15b

1.22a

0.89d

0.75e

0.29f

0.71e

97

Salicylic acid*

1.00d

1.07c

1.12b

0.83e

0.53f

0.17g

1.35a

98

Shikimic acid*

1.00b

0.83cd

0.86c

0.80d

0.63e

1.77a

0.44f

99

Theaflavic acid*

1.00d

0.39e

0.37e

4.09c

3.92c

20.65a

5.75b

100

Theogallin*

1.00b

1.05b

1.45a

0.79c

0.52d

0.30e

0.50d

101

β-Glucogallin*

1.00a

0.97b

0.87c

0.68e

0.83d

0.46f

0.23g

102

Choline*

1.00a

0.44e

0.46e

0.68d

0.89b

0.78c

0.23f

103

Betain*

1.00f

1.63d

1.58e

1.81d

5.10b

2.81c

11.98a

b

c

c

e

f

d

#

0.82

0.60

0.77

0.60

0.66

0.47

0.85

0.35

0.67

0.52

1.54a

104

Theobromin*

1.00

105

Theophylline*#

1.00b

0.76b

0.93b

0.94b

0.88b

1.87b

69.38a

106

Caffeine*#

1.00d

0.96e

0.97e

0.96e

1.03c

1.13b

1.20a

107

PC(18:2/0:0)*

1.00b

0.59e

0.57e

0.87c

0.50f

0.69d

1.65a

108

PC(16:0/0:0)*

1.00a

0.25f

0.19g

0.76b

0.58d

0.66c

0.49e

109

Pheophorbide B*

1.00c

21.93b

22.81b

50.77a

9.19c

21.93b

48.28a

110

Pheophorbide A

1.00g

3.35e

4.3d

6.73b

2.37f

5.12c

11.62a

111

Pyropheophorbide A

1.00d

107.43c

102.79c

192.93b

7.32d

117.76c

1134.77a

The compounds were identified either by MS2 spectra* or by authentic standards#. a-g

: Values in the same row that are labeled with different superscript letters differ significantly (P < 0.05). Statistical analysis was

ANOVA with pairwise post hoc comparisons by the method of Bonferroni. rha: rhamnoside. ara: arabionopyranoside. rut: rutinoside. gal: galactoside

32

ACS Paragon Plus Environment

Page 33 of 38

Journal of Agricultural and Food Chemistry

FIGURE GRAPHICS Figure 1

33

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Figure 2

34

ACS Paragon Plus Environment

Page 34 of 38

Page 35 of 38

Journal of Agricultural and Food Chemistry

Figure 3

35

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Figure 4

36

ACS Paragon Plus Environment

Page 36 of 38

Page 37 of 38

Journal of Agricultural and Food Chemistry

Figure 5

37

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

GRAPHIC FOR TABLE OF CONTENTS

38

ACS Paragon Plus Environment

Page 38 of 38