Profile of the Polyphenols in a European Diet

Profile of the Polyphenols in a European Diet

by

Farnoosh Dairpoosh

A thesis submitted in partial fulfillment of the

requirements for the degree of

Doctor of Philosophy

in chemistry

Approved, Thesis Committee:

Professor Dr. Nikolai Kuhnert School of engineering and science- Jacobs University Bremen

-----------------------------------------------------------------------------

Dr. Adam Le-Gresley School of pharmacy and chemistry- Kingston University London

-----------------------------------------------------------------------------

Professor Dr. Roland Benz School of engineering and science- Jacobs University Bremen

Date of defense: 30th

May, 2011

School of Engineering and Science

ii

Abstract

Dietary phenolic compounds are secondary metabolites, widely distributed in the plant

kingdom and consumed in large amounts in the human diet. Studies have shown a

positive correlation between an increased consumption of polyphenols and a reduced risk

of cardiovascular disease, neurodegenerative diseases and certain types of cancer,

suggesting that these compounds are beneficial for human health. Besides the strong

antioxidant capacities, dietary polyphenols have been shown to posses other properties by

which cell activities are regulated. An accurate assessment on the nature and distribution

of these compounds in diet enables epidemiological analysis to realize the relation

between the intake of these substances and the risk of development of several diseases.

Such an assessment requires a polyphenol intake database to support clinical and

epidemiological studies. The present research studies the main contributors to human

polyphenol intake in a typical European diet by profiling the polyphenol content of a

number of selected fruits and vegetables contributing most to an average European daily

polyphenol intake. A total of 42 methanolic extractions from the fleshes and peels of 20

different fruits and vegetables were prepared and subjected to chemical characterisation

using HPLC interfacing of an ESI-Ion Trap mass spectrometer or an ESI-TOF mass

spectrometer. The peaks in tandem MS chromatograms were assigned based on the

structural information of the most commonly occurring food polyphenols reported in the

literature. The presence of more than 60 different compounds was confirmed using this

method. For most fruits and vegetables the number of qualitatively observed polyphenols

was considerably lower than reported in the literature. However, around 20 compounds

not previously described in the literature could be identified. Storage of the samples was

investigated and it was observed that after 12 months refrigeration, the majority of

phenolic constituents had decomposed. A new approach, Van Krevelen analysis, was

applied for identification of further unassigned peaks in the mass spectra. Findings on

polyphenolic contents of the samples, compared and confirmed with the literature and the

polyphenolic compounds which have not been reported in a specific fruit or vegetable so

far, reported for each sample individually.

iii

Acknowledgement

Completing a Ph.D is truly a marathon event, and I would not have been able to complete

this journey without the aid and support of countless people over the past five years.

First and foremost, I express my sincerest gratitude to my supervisor, Professor Dr.

Nikolai Kuhnert, for the unique opportunity of joining his research group and to

accomplish my studies under his supervision. I am very grateful for his full support

throughout my thesis with his patience, attention and knowledge. Without him this thesis,

would not have been completed or written. One simply could not wish for a better or

friendlier supervisor.

I would like to thank Professor Dr. Roland Benz and Dr. Adam Le-Gresley for their

attention and valuable time spent for carefully reading this Ph.D thesis.

I would like to thank Anja Müller, our laboratory assistant, for helping in running the

instruments and analysis of the samples and providing me with the materials needed.

I wish to thank Peter Tsvetkov and all my friends for their supports, specially Dr. Nora

Hanelt , who advised me, spent many office hours with me and guided me in preparing

my Ph.D proposal.

I would like to thank the graduate students Abhinandan Shrestha and Dileep Dakhal

whom I have worked with.

I would like to acknowledge Jacobs University for scholarship during my Ph.D studies

and I would like to thank Prof. Dr. Bernhard Kramer for his support and making the

financial aid available.

Finally, my parents receive my deepest gratitude and love for their dedication and many

years of support during my undergraduate studies and instilling in me confidence and a

drive for pursuing my Ph.D as well as supporting me throughout my studies at Jacobs

University.

iv

List of the contents Page

number

1- Introduction 2

1.1- Phenolic compounds and polyphenols 2

1.2- General types of phenolic compounds 3

1.2.1- Flavonoids 3

1.2.2- Isoflavonoids 6

1.2.3- Neoflavonoids 7

1.2.4- Minorflavonoids 8

1.2.5- Anthocyanidins 8

1.2.6- Anthraquinones 10

1.2.7- Phenolic acids 10

1.2.8- Stilbenes 11

1.3- Distribution of polyphenols and phenolic acids in dietary plants 12

1.3.1- Phenolic acids 12

1.3.2- Flavonols 13

1.3.3- Flavones 13

1.3.4- Flavanones 14

1.3.5- Isoflavones (flavans) 14

1.3.6- Flavanols (flavan-3-ols) 14

1.3.7- Tannins 15

1.3.8- Anthocyanidins 16

1.3.9- Lignans 17

1.4- Variability of polyphenol content of foods 17

1.5- General overview on a typical diet (How much do we eat of what) 20

1.6- Bioactivities of the dietary polyphenols 23

1.6.1- Oxidative stress 23

1.6.2- Antioxidant and free radical scavenging properties of polyphenols 24

1.6.3- The ways polyphenols exhibit their antioxidant activity 24

1.6.4- Potential mode of action of phenolic compounds 25

1.6.5- Biological activities of flavonoids 27

1.6.6- Biological activities of isoflavones 27

1.6.7- Biological activities of anthocyanidins 27

1.6.8- Biological activities of tannins 28

1.6.9- Anti-atherosclerosis and cardioprotection effects 28

1.6.10 Neuroprotective effects of dietary polyphenols 29

1.6.11-Anti-inflammatory properties of dietary polyphenols 29

1.6.12-Antimutagenic/Anticarcinogenic properties of dietary polyphenols 30

1.6.13-Protective effect on immune cell functions 30

1.6.14-Antiallergic activity 30

1.6.15-Antidiabetic effects 31

1.6.16-Regulation of cell cycle progression 31

1.6.17-Modulation of hormonal effects 31

1.6.18-Other bioactive effects 31

1.7- Bioavailability and metabolism of polyphenols 32

1.8- Biosynthesis of polyphenols 33

v

1.9- Liquid chromatography Mass spectrometry (LC-MS) of polyphenols 36

1.9.1- Chromatographic conditions 36

1.9.2- Detection 36

1.9.3- LC-MS 38

2- Aim of the project 40

3- Materials and methods 41

3.1- Materials and equipments 41

3.1.1- Chemicals and consumables 41

3.1.2- Biological samples 42

3.1.3- Equipments 42

3.2- Methodology 43

3.2.1- Preparation of the samples 43

3.2.2- Methanolic extraction 45

3.2.3- Samples preparation for liquid chromatography mass spectrometry 45

3.2.4- Methodology for liquid chromatography mass spectrometry 45

3.2.4.1- LC-MS using tandem mass spectrometer (LC-MSn) 46

3.2.4.2- LC-MS using high resolution TOF mass spectrometer 46

3.2.5- Assignment of the compounds 46

3.2.6- Confirmation of the assigned compounds 46

4- Results and discussion 48

4.1- Consumption of polyphenols 48

4.2- Methodology 48

4.2.1- Criteria for the selection of the samples 48

4.2.2- Method of extraction 50

4.2.3- Method for LC-MS 51

4.2.4- Polyphenols previously identified in fruits and vegetables 52

4.3- General considerations in natural product analysis 66

4.3.1- Identification of known compounds 69

4.3.2- Identification of unknown compounds 70

4.3.3- Quality of HR-MS measurment 71

4.3.4- Calculation of molecular formulas 74

4.3.5- Choice of correct molecular formula 75

4.3.6- Tandem MS data interpretation for unknown compounds 76

4.4- Investigated polyphenols in the samples 80

4.4.1- Polyphenols in Apple (Malus domestica) 81

4.4.1.1- Findings on investigated polyphenols in Apple samples 102

4.4.2- Polyphenols in Asparagus (Asparagus officinalis) 92

4.4.2.1- Findings on investigated polyphenols in Asparagus samples 92

4.4.3- Polyphenols in Carrot (Daucus carota) 93

4.4.3.1- Findings on investigated polyphenols in Carrot samples 93

4.4.4- Polyphenols in Pear (Pyrus communis) 95

4.4.4.1- Findings on investigated polyphenols in Pear samples 102

4.4.5- Polyphenols in Lettuce (Lactuca sativa) 104

4.4.5.1- Findings on investigated polyphenols in Lettuce samples 105

4.4.6- Polyphenols in Banana (Musa paradisiaca) 106

4.4.6.1- Findings on investigated polyphenols in Banana samples 106

vi

4.4.7- Polyphenols in Onion (Allium cepa) 107

4.4.7.1- Findings on investigated polyphenols in Onion samples 107

4.4.8- Polyphenols in Orange (Citrus sinensis) 108

4.4.8.1- Findings on investigated polyphenols in Orange samples 111

4.4.9- Polyphenols in Nectarine (Prunus persica var. nucipersica) 113

4.4.9.1- Findings on investigated polyphenols in Nectarine samples 113

4.4.10- Polyphenols in Melon (Cucumis melo) 115

4.4.10.1- Findings on investigated polyphenols in Melon samples 115

4.4.11- Polyphenols in Courgette (Cucurbita spp.) 116

4.4.11.1- Findings on investigated polyphenols in Courgette samples 117

4.4.12- Polyphenols in Cauliflower (Brassica oleracea) 118

4.4.12.1- Findings on investigated polyphenols in Cauliflower samples 118

4.4.13- Polyphenols in Strawberry (Fragaria x ananassa) 119

4.4.13.1- Findings on investigated polyphenols in Strawberry samples 122

4.4.14- Polyphenols in Leek (Allium ampeloprasum) 123

4.5- Results for confirmed compounds in high resolution mass chromatograms 124

4.6- Results for the assigned compounds on tandem MS chromatograms 138

4.7- Summary of the findings 138

4.8- Changes in the polyphenolic content of vegetable and fruit extracts in long 156

term freezing conditions

4.8.1- Investigation of the specific polyphenols in the chromatograms of 156

the stored samples

4.8.2- Results and discussion 157

4.9- New strategy for identification of the unknown compounds 163

4.9.1- Neutral loss 163

4.9.2- Van Krevelen analysis 167

5- Conclusion 180

6- References 183

7- Appendix

Supplementary information (Tandem MS data of the samples and related tandem

MS chromatograms)

CD

vii

List of figures Page

number

Figure 1 Benzopyran (chromene) 4

Figure 2 The structure of flavonoids, isoflavonoids and neoflavonoids 4

Figure 3 Different groups and examples of flavonoids 5

Figure 4 Different structures of isoflavonoids 7

Figure 5 Different structures of neoflavonoids 8

Figure 6 Different structures of minor flavonoids 8

Figure 7 Structural classification of common anthocyanidin species 9

Figure 8 Anthraquinone 10

Figure 9 Chemical structures of some phenolic acids 11

Figure 10 Resveratrol 11

Figure11 5-caffeoylquinic acid 13

Figure 12 Structures of some tannins 16

Figure 13 Chemical structure of lignan and coniferyl alcohol 17

Figure 14

Chart showing the phenolic content of selected beverages,

vegetables and Chocolate in milligrams per serving

21

Figure 15

A chart showing the phenolic content of selected fruits in

milligrams per serving

22

Figure 16 Radical scavenging mechanism of polyphenols 25

Figure 17 ß-estradiol 27

Figure 18 Bioactivities of dietary polyphenols 28

Figure 19

Schematic diagram of the main pathways and key enzymes

involved in the biosynthesis of hydrolysable tannins,

hydroxycinnamates and 5-O-caffeoylquinic acid

34

Figure 20

Schematic diagram of the stilbene and flavonoid biosynthetic

pathways

35

Figure 21

UV-VIS spectra of the anthocyanidin delphinidin, epicatechin,

the flavanone hesperetin, the flavone luteolin, the flavonol

quercetin and the isoflavone genistein

38

Figure 22

Base peak chromatogram for the mixture of standard

compounds in negative ion mode

52

Figure 23 5- caffeoylquinic acid 83

Figure 24

Total ion chromatogram in the negative ion mode of sample

3, UV-VIS spectrum, MS, MS2 and MS

3 spectra of compound

5-caffeoylquinic acid

83

Figure 25

Structures of the compounds quercetin-3-O-glucoside and

myricetin-3-O-rhamnoside

85

Figure 26


3,UV-VIS spectrum, MS, MS2 and MS


quercetin-3-O-glucoside

85

Figure 27 Structure of compounds morin, quercetin and robinetin 87

Figure 28



3 spectra of cmpound

morin , quercetin and robinetin

87

Figure 29 Compound (+)-catechin 88

viii

Figure 30

Total ion chromatogram in the negative ion mode of sample 3,

UV-VIS spectrum, MS, MS2 and MS

3 spectra of compound (-)-

picatechin

88

Figure 31

Structures of compounds (-)-gallocatechin and (-)-epillocatechin 97

Figure 32

Total ion chromatogram in the positive ion mode of sample


3 spectra of compounds

(-)-gallocatechin, (-)-epigallocatechin

97

Figure 33 Quercetin-3-O-rutinoside (rutin) 99

Figure 34




quercetin-3-O-rutinoside

99

Figure 35

Structure of the compound 5,7-dihydroxy-3',4',5'-

trimethoxyflavone

101

Figure 36

Total ion chromatogram in the positive ion mode of sample 33,


3 spectra of compound 5,7-

dihydroxy-3',4',5'-trimethoxyflavone

101

Figure 37 Structure of delphinidin 105

Figure 38 Hesperetin-7-O-rutinoside (hesperidin) 110

Figure 39





110

Figure 40 Ellagic acid 121

Figure 41




ellagic acid

121

Figure 42

Different classes of dietary phenolic compounds and number of

the compounds belonging to each class, found to be present in

the Apple samples

139

Figure 43



the Asparagus samples

140

Figure 44



the Carrot samples

141

Figure 45

Different classes of dietary phenolic compounds and number

of the compounds belonging to each class, found to be present

in the Pear samples

142

Figure 46



the Lettuce samples

143

Figure 47



the Banana samples

144

Figure 48

Different classes of dietary phenolic compounds and number

of the compounds belonging to each class, found to be present in

145

ix

the Onion samples

Figure 49



the Orange samples

146

Figure 50



the Nectarine samples

147

Figure 51



the Melon samples

148

Figure 52



the Courgette samples

149

Figure 53



the Cauliflower samples

150

Figure 54



the Strawberry samples

151

Figure 55

A comparison between the tandem mass spectra of the samples

at the beginning of the storage and the mass spectra of the

samples after 12 months storage.

157

Figure 56

Constant neutral loss chromatogram for the mass of 162

(C6H10O5) corresponding to a hexose in sample 1 (Apple peel

from New Zealand )

165

Figure 57 Constant neutral loss chromatogram for the mass of 132

(C5H8O4) corresponding to a pentose in sample 4 (Apple peel

from Argentina)

166

Figure 58

Example of Van Krevelen representation, showing the

positioning of various classes of molecules according to their

H/C and O/C ratios

168

Figure 59 Van Krevelen representation with density ellipse for polyphenols 169

Figure 60 Van Krevelen representation with density ellipse for terpenes 169

Figure 61 Density ellipse for the phenolic and polyphenolic compounds 170

Figure 62

The improved Van Krevelen representation for all classes of

compounds including polyphenols and terpenes

170

Figure 63

Van Krevelen plot of the H/C versus O/C ratio for unknown

compounds in Apple peel samples

177

Figure 64

Van Krevelen representation combined with the Scatter plot of

the H/C versus O/C ratio of the unknown compounds in Apple

peel samples

177

Figure 65

Van Krevelen plot of the H/C versus O/C ratio for unknown

compounds in Apple flesh samples

179

Figure 66

Van Krevelen representation combined with the Scatter plot of

the H/C versus O/C ratio of the un known compounds in Apple

flesh samples

179

x

List of tables Content Page number

Table 1 The classification and sources of some dietary

polyphenols and their contents in some food

subjects.

18

Table 2 List of the samples 44

Table 3 Estimated total polyphenol content (TPC) and

polyphenol intake (PI) of fresh fruit and vegetables

49

Table 4 List of the most commonly occurring dietary

phenolic compounds including the molecular

formulas, theoretical masses and m/z values in

positive and negative ion modes of the compounds

53

Table 5 The structural information of the most commonly

occurring food polyphenols

55

Table 6 Assigned compounds in Apple samples 90

Table 7 Assigned compounds in Asparagus samples 93

Table 8 Assigned compounds in Carrot samples 94

Table 9 Assigned compounds in Pear samples 102

Table 10 Assigned compounds in Lettuce samples 106

Table 11 Assigned compounds in Banana samples 107

Table 12 Assigned compounds in Onion samples 107

Table 13 Assigned compounds in Orange samples 112

Table 14 Assigned compounds in Nectarine samples 114

Table 15 Assigned compounds in Melon samples 116

Table 16 Assigned compounds in Courgette samples 117

Table 17 Assigned compounds in Cauliflower sample 118

Table 18 Assigned compounds in Strawberry sample 122

Table 19 High resolution MS data for confirmed compounds

in Apple peels (Samples: 1, 3, 4, 5, 7)

125-127


in Apple fleshes (Samples: 2, 6, 8, 9, 12)

128


in Asparaguses (Samples: 10,11, 40)

129


in Carrots (Samples: 13, 15, 16)

129


in Pear peels (Samples: 17, 33, 36)

130-131


in Pear fleshes (Samples: 14, 36)

131


in Onions (Samples: 19, 24, 30)

132


in Oranges (Samples: 21, 34, 39)

133-134

xi


in Nectarine Peel (Sample 25 )

135


in Nectarine fleshes (Sample 32, 41)

135


in Cauliflower (Sample 37)

136


in Strawberry (Sample 42)

136-137

Table 31 The phenolic compounds and polyphenols found in

the samples

153-155

Table 32 List of phenolic compounds present or absent in

fruit and vegetable samples after 12 months storage

at -12º C (compounds assigned from LC-ESI-MS-

TOF runs in positive and negative ion modes);

sample numbers on pages 42 and 43

158-159

Table 33 List of compounds present and absent in tandem

MS chromatograms of the samples after 12 months

storage (these phenolic compounds were present in

the tandem MS chromatograms of the fresh

samples)

160-161

Table 34 High resolution mass spectrometric data,

suggestions and comparison

162

Table 35 Results with the unknown compounds in Apple

peels

175-176

Table 36 Suggested molecular formulas for the unknown

compounds for Apple flesh samples

178

CD document

for tandem MS

data

page numbers

Table 37 Tandem MS data of assigned compounds for Apple

peel (Samples: 1, 3, 4, 5, 7)

2-14

Table 38 Tandem MS data of assigned compounds for Apple

Flesh (Samples: 2,6,8,9,12)

15-18

Table 39 Tandem MS data of assigned compounds for

Asparagus (Samples: 10, 11, 40)

19-26

Table 40 Tandem MS data of assigned compounds for carrot

(Samples:13)

27-29

Table 41 Tandem MS data of assigned compounds for pear

peel (Samples: 17,33)

30-36

Table 42 Tandem MS data of assigned compounds for pear

flesh (Samples: 14,36)

37


Lettuce (Samples: 18,22)

38

xii

Table 44 Tandem MS data of assigned compounds for Onion

(Samples: 19,24,30)

39-41


Banana (Samples: 20,29 and 38)

42-43


Orange (Samples: 21, 34 , 39)

44-52

Table 47 Tandem MS data of assigned compounds for Melon

(Samples: 23,31, 35)

53-54


Nectarine Peel (Sample 25)

55-57


Nectarine flesh (Sample 32,41)

58-59


Courgette flesh (Sample 26)

60-61


Courgette peel (Sample 27)

61-65


Cauliflower (Sample 37)

66-67


Strawberry (Sample 42)

68-71

xiii

Abrreviations

AP-1 activator protein-1

[M+H] positive ion mode

[M-H] negative ion mode

µL microliter

µM micromol

ACoAC acetylCoA carboxylase

ANR anthocyanidin reductase

ANS anthocyanidin synthase

APCI atmospheric pressure chemical ionization

C4H caffeic/5-hydroxyferulic acid O-methyltransferase

CHI chalcone isomerase

CHR chalcone reductase

CHS chalcone synthase

CI chemical ionization

DAD diode-array detector

DFR dihydroflavonol 4-reductase

DNA deoxynucleic acid

DPPH 1,1-diphenyl-2-picrylhydrazyl

EI electrostatic ionization

EIC extracted ion chromatogram

ER α estradiol receptor alpha

ERK extracellular signal-regulated kinase

ESI electrospray ionization

EU extension units

Exp. experimental value

F30H flavonoid 30-hydroxylase

F3H flavanone 3-hydroxylase

F5H ferulate 5-hydroxylase

FDB flavonoid database

FEP fresh edible portion

FLS flavonol synthase

fmol femtomole

FNS flavone synthase

FTIRC-MS

fourier transform ion cyclotron resonance mass

measurements

GAE gallic acid equivalent

GT galloyl transferase

HDL high density lipoprotein

HPLC high performance liquid chromatography

IC50 antiradical dose required to cause a 50% inhibition

xiv

IFS isoflavone synthase

JNK c-Jun NH2-terminal kinase

Kg kilogram

LAR leucoanthocyanidin 4-reductase

LC-MS liquid chromatography mass spectrometery

LC-MSn liquid chromatography tandem mass spectrometery

MALDI matrix-assisted laser desorption/ionization

MAP mitogen-activated protein

MeOH methanol

mg milligram

min minute

ml milliliter

mm millimeter

MS mass specterometery

MSn tandem mass

NDL nutrient data laboratory

NF-κB transcription factor nuclear factor-kappa B

nm nano meter

NMR nuclear magnetic resonance

PAL phenylalanine ammonia-lyase

PDB proanthocyanidin database

pH potent hydrogen

PI polyphenol intake

PI3K ultraviolet B-activated phosphatidylinositol 3-kinase

PON-1 paraoxonase 1

ppm parts per million

RBL rat basophilic leukemia

ROS reactive oxygen species

RP reversed-phase

SS stilbene synthase

TIC total ion chromatogram

TPC total polyphenol content

tR retention time

TU terminal unit

USDA U.S. department of agriculture

UV ultraviolet

VIS visible

vol volume

wt weight

1

2

1- Introduction

1.1- Phenolic compounds and polyphenols

Polyphenols are a class of compounds found in plants which contain more than one

phenol unit per molecule. Several thousand molecules have been identified in higher

plants and several hundred are found in dietary plants which can be classified as

polyphenols. These phenolic compounds are secondary metabolites, widely distributed in

the plant kingdom and have been found to possess a variety of bioactivities with potential

human health benefits (1, 2).

Phenolic compounds may be classified into different groups as a function of the number

of phenolic rings that they contain and the structural elements that bind these rings to one

another. These classifications include phenolic acids, flavonoids, flavones, flavonols,

flavanones, flavanes, flavanols, anthocyanidins, tannins, chalcones, hydroxycinnamates

and others (2).

Dietary phenolic compounds and polyphenols, present in a variety of plants, are

consumed as main components in human food stuffs such as barley, dry beans, peas and

other legumes; fruits such as Apples, Blackberries, Cranberries, Grapes, Peaches, Pears,

Plums, Raspberries and Strawberries; vegetables such as Cabbage, Celery, Onion and

Parsley. Phenolic compounds are also present in tea, Coffee, Chocolate and wine (3).

Dietary phenolic compounds and polyphenols have attracted great interest since 1990s

owing to a large number of epidemiological studies and observations that showed the

protective effects of dietary polyphenols against a variety of chronic diseases particularly

cardiovascular disease and cancers. Studies have suggested that polyphenols play a

protective role by a wide range of biochemical mechanisms and pharmacological effects

through antioxidative action and modulation of protein function such as blocking and

deactivating enzymes, which are effective in developing diseases such as cancer. The

interest in pharmacological effects of dietary polyphenols was stimulated mainly by

3

epidemiological studies indicating an inverse association between consumption of foods

rich in these compounds and the incidence of cardiovascular diseases, diabetes and

cancer. Potter (1997) reviewed 200 epidemiological studies, the majority of which

showed a protective effect of increased fruit and vegetable intake. Potter concluded that

the high content of polyphenol antioxidants in fruits and vegetables is probably the main

factor responsible for these effects (3, 4).

The presence of polyphenols in the edible plants is largely influenced by the factors and

conditions such as genetic, environmental variations, degree of ripening, variety,

processing and storage (3).

The large number of phenolic compounds, their structural diversity, numerous dietary

sources, variation in concentration and the diversity of analytical methods present a

challenge to develop a comprehensive database. Consequently, determining the amounts

and structures of the polyphenols present in vegetables, fruits and teas represents a topic of

wide interest (5).

1.2- General types of phenolic compounds

Polyphenols can be classified as polycyclic types such as flavonoids, anthraquinones,

anthocyanidins and others. The chemical structures of some of these classes are described

in this chapter:

1.2.1- Flavonoids

The term ‗flavonoid‘ is generally used to describe a broad collection of structurally

similar natural products that include a C6-C3-C6 carbon framework. Depending on the

position of the linkage of the aromatic ring to the benzopyran (Figure 1) moiety, this

group of natural products may be divided into three classes: flavonoids 1, isoflavonoids 2

and neoflavonoids 3 (Figure 2). Numerous structures of flavonoids are theoretically

possible, based on the assumption that ten carbons of the flavonoid skeleton can be

4

substituted by a range of different substituents, among which are hydroxyl, methoxyl,

methyl, isoprenyl and benzyl substituents. Furthermore, each hydroxyl group and some

carbons can be substituted by one or more of a range of different carbohydrates and in

turn, each sugar can be acylated with a variety of different phenolic or aliphatic acids (6).

O

Figure 1- benzopyran (chromene) (6)

O

3

4

2

5

6

7

8

2'3'

4'

5'6'

A C

B

1

flavonoides

O

A C

B

2

isoflavonoides

O

4A C

B

3

neoflavonoides

Figure 2- The structure of flavonoids, isoflavonoids and neoflavonoids (6)

Based on the degree of oxidation and saturation present in the C-ring, the flavonoids may

be divided into the following groups (Figure 3):

5

O

flavans

O

O

HO

HO

R1

R2

R3

flavanones

R1=H; R

2=OH: naringenin

R1=R

2=OH: eriodictyol

R1=OH; R

2=OCH

3: hesperetin

O

O

R1

R2

R3

OH

HO

flavones

R1=H; R

2=OH: apigenin

R1=R

2=OH: luteolin

O

O

OH

HO

OH

R1

R2

R3

flavonols

R1=OH; R

2=R

3=H: kaempferol

R1=R

2=OH; R

3=H: quercetin

R1=R

2=R

3=OH: myricetin

OH

O

HO OH

OH

OOH

HO

O

HO

OH

OH

theaflavin

O

OH

HO

OH

R1

R2

R3

flavan-3-ol or flavanols

R1=R

2=OH; R

3=H: catechins

R1=R

2=R

3=OH: gallocatechin

O

OH

flavan-4-ol

OH

OH

HO O

OH

OH

(-)-epicatechin

O

OH

OH

flavan-3,4-diol

Figure 3- Different groups and examples of flavonoids (4, 6)

6

Within the classes of flavonoids, various differentiations occur based on the number and

the nature of substituents attached to the rings (7). Flavonoids are responsible for the

coloration of flowers, fruits and sometimes leaves. More than 4000 flavonoids have been

reported in nature and new flavonoids are constantly added to the list (8). Flavonoids,

along with other secondary metabolites are belived to be biosynthesized for protection

against UV light, pathogens and herbivores. In plants the dominant form of flavonoids is

a flavonoid glycoside. In all flavonoid glycosides, a glycosidic moiety is attached via

either an O (-O-) atom or a skeletal C atom (-C-) to the skeletal C15 (9). Flavonoids exist

everywhere in the nature; they are found in petals, leaves and are widely distributed in the

edible parts of plants (10). The flavonoid subclasses and patterns of glycosylation are

strongly correlated with plant taxonomy and give rise to a wide range of chemical

properties (1).

1.2.2- Isoflavonoids

Isoflavonoids are a distinctive subclass of the flavonoids. Isoflavonoids have limited

distribution in the plant kingdom but their structural variations are considerably diverse.

Isoflavonoids are subdivided into the following groups (6) (Figure 4).

7

O 2

8

2'

4

isoflavan

O

OOH

HO

R1

isoflavone

R1= H: daidzein

R1=OH: genistein

O

O

isoflavanone

O

isoflav-3-ene

O

OH

isoflavanol

OO

1

4

2

3

5678

9

10

11 12

rotenoid

O

O

O

12

34 5

6a7

8

91011

11a

coumestane

O O

3-arylcoumarin

O O

coumaronochromene

O O

O

coumaronochromone

O

O

6a

11a

pterocarpan

Figure 4- Different structures of isoflavonoids (6)

1.2.3- Neoflavonoids

The neoflavonoids are structurally related to the flavonoids and the isoflavonoids (figure

5).

8

O O

arylcomarin

O O

3,4-dihydro-4-arylcoumarin

O

neoflavene

Figure 5- Different structures of neoflavonoids (6)

1.2.4- Minor flavonoids

Natural products such as chalcones and aurones also contain a C6-C3-C6 backbone and

are considered to be minor flavonoids (6) (Figure 6).

OH

O

2’-OH-chalcone

OH

O

2’-OH-dihydrochalcone

O

OH

2’-OH-retro-chalcone

O

O

O

O

OH

aurone auronols

Figure 6- Different structures of minor flavonoids (6)

1.2.5- Anthocyanidins

Anthocyanidins are the largest group of water-soluble pigments in the plant kingdom.

They are dissolved in the vacuoles of epidermal tissues of flowers and fruits which

exhibit different colors. They belong to the family of compounds known as flavonoids

and they are distinguished from other flavonoids as a separate class by virtue of their

ability to exist in the flavylium ion form. Highly red, blue and purple colored vegetables,

9

flowers and fruits such as Blueberries, Cherries, Raspberries, Strawberries, Black

Currants and Purple Grapes tend to be the major source for anthocyanidins (11).

Color differentiations among anthocyanidins are caused by the different substitution

patterns of the B-ring of the glycone, the pattern of glycosylation, the degree and nature

of esterification of the sugars with aliphatic or aromatic acids and by the pH, temperature,

type of solvent and the presence of co-pigments (11). The six anthocyanidins commonly

found in plants are pelargonidin, cyanidin (the most commonly occurring anthocyanidin

in nature), delphinidin, peonidin, petunidin and malvidin (Figure 7). Anthocyanins,

glycosylated derivative of anthocyanidins, are present in colourful flowers and fruits.

These are responsible for the pink-red colors of most flower petals, of most red fruits

(like Apples) and almost all red leaves during the autumn. (12).

O+

2

345

6

7

8 1'

2' 3'

4'

5'6'

OH

R2HO

OH

R3

1

R1

A C

B

Figure 7- Structural classification of common anthocyanidin species (11)

R1 R

2 R

3

delphinidin OH OH OH

cyanidin OH H OH

petunidin OCH3 OH OH

peonidin OCH3 H OH

malvidin OCH3 OCH3 OH

pelargonidin H H OH

10

1.2.6- Anthraquinones

Anthraquinones are mostly present in the plants as glycosides. Anthraquinones were not

detected in any vegetables or fruits, but they are known to be contained in some

medicinal plants such as Aloe, Cascara Sagrada and Senna. Usually anthraquinones are

found in the form of aglycone with one or more substituent molecules. Anthraquinone

(Figure 8), a polycyclic aromatic hydrocarbon containing two opposite carbonyl groups

(C=O) at 9, 10 position (3).

5

6

7

8O

O

12

3

4

Figure 8- anthraquinone (3)

1.2.7- Phenolic acids

The main non-flavonoids dietary phenolic compounds are the C6–C1, C6-C3 and C6-C5

phenolic acids and their derivatives. Two classes of phenolic acids can be recognized: (a)

derivatives of benzoic acid and (b) derivatives of cinnamic acid. The common

hydroxycinnamates are ρ-coumaric acid, caffeic acid, ferulic acid and sinapic acid

conjugates. Gallic acid is the most common phenolic acid usually conjugated with

carbohydrates. Figure 9 shows the structure of some phenolic acids in the plants (2,4,12).

11

OH

HOOC

p- coumaric acid

OH

OH

HOOC

caffeic acid

OH

OCH3

HOOC

ferulic acid

OH

OHHO

COOH

gallic acid

O

OH

cinnamic acid

OH

OH

O

O

OH

HO

O

O

ellagic acid

HOOC

phenylvaleric acid

HOOC

phenylpropionic acid

OCH3

OH

OCH3

HOOC

sinapic acid

Figure 9- Chemical structures of some phenolic acids (4)

1.2.8- Stilbenes

Stilbenes have a C6–C2–C6 structure and they are produced by plants in response to

disease, injury and stress. These compounds are found only in low quantities in dietary

plants. An example of the stilbenes is resveratrol (a major compound in red wine) which

has been well studied in medicinal plants (figure 10) (2, 4).

HO

OH

OH

Figure 10- resveratrol (2)

12

1.3- Distribution of polyphenols and phenolic acids in dietary plants

Dietary polyphenols, the most abundant antioxidants in human diets, occur in fruits,

vegetables, wine, Tea, Olive oil, Chocolate and cereals. Most of the dietary phenolic

compounds are derivatives of flavonoids (about two third of the total intake) and phenolic

acids (about one third of the total intake). Most of dietary phenolic compounds are

discussed in the following section. Table 1 summarises the occurrence of the most

common pholyphenols and phenolic acids in diatary plants (2, 12).

1.3.1- Phenolic acids

The phenolic acids mostly occur in glycosylated derivatives or esters of quinic acid,

shikimic acid and tartaric acid (2).

Caffeic acid is present in both free and esterified form represents between 75%-100% of

the total hydroxycinnamic acid content of most fruits (2).

5-caffeoylquinic acid is another important phenolic acid occurs in foods, which is an ester

of caffeic acid and quinic acid which is abundant in many fruits with high concentration

in Coffee (70-350 mg /cup), (Figure 11) (2, 12).

Ferulic acid is the most common phenolic acid found in cereal grains, representing about

90% of the total polyphenols in wheat grain (63 mg/kg) and the content in maize flour is

about three times as high (2).

Hydroxybenzoic acid is another example of phenolic acids. The amount of

hydroxybenzoic acids in edible plants is low, with the exception of some red fruits such

as black radish and Onions which may contain several tens of milligrams per kilogram

fresh weight. Hydroxybenzoic acids are also found in Mangoes, Strawberries and

Raspberies. Gallic acid is abundant in Tea. Tea leaves may contain up to 4.5 g/kg fresh

weight (2).

13

OHOH

OH

O

O

HO

O

OHHO

Figure11- 5-caffeoylquinic acid (2)

1.3.2- Flavonols

Flavonols such as quercetin, kaempferol, myricetin and isorhamnetin are the most

ubiquitous flavonoids in food which are found in vegetables such as Capers, Chives,

Onions (the richest source; up to 1.2 g/kg fresh weight) and the leaves such as Lettuce,

Celery and Broccoli. The glycoside concentration in the green outer leaves is about10

times higher than in the inner light colored leaves. In cereals such as Buckwheat, Beans

and in fruits such as Apples, Apricots, Grapes, Plums, Bilberries, Blackberries,

Blueberries, Cranberries, Olive, Elderberries, Currants and Cherries contain between five

to ten different flavonol glycosides. Flavonols are also found in spices and herbs such as

Dill Weed. Other dietary sources for flavonols are red wine, Tea (green, black), Tea

(black beverage), Cocoa powder, Turnip (green), Endive and Leek (2, 12).

1.3.3- Flavones

Flavones are not distributed widely. The most important examples are glycosides of

apigenin and luteolin (Figure 3). Flavones are mostly found in Celery, Parsley and some

herbs (2, 12).

14

1.3.4- Flavanones

Flavanones are found mostly in tomatoes and certain aromatic plants such as Mint, but in

high concentrations only in citrus fruits. The main aglycones are naringenin in Grapefruit,

hesperetin in Oranges (200-600 mg/l) and eriodctyol in Lemons. The solid parts of citrus

fruits (the white spongy portion) and the membranous portions are high in flavanones

compared to the pulb, therefore the whole fruit may contain up to five times as much as a

glass of Orange juice. Apigenin and luteolin are mostly found in fruits such as Olives, in

vegetables such as hot Peppers, fresh Parsley, spices and herbs such as Oregano ,

Rosemary, dry Parsley and Thyme ( table 1) (2,12) .

1.3.5- Isoflavones (flavans)

Isoflavones including ginestein and daidzein (figure 4) are found in fruits such as Grapes,

the seed and skin and in leguminous plants. Soya is the main source of isoflavones in the

humandiet (see table 1). They contain three main molecules: genistein, daidzein and

glycitein. The isoflavones are found as aglycones and glycosylated derivatives of the

aglycones (2, 12).

1.3.6- Flavanols (flavan-3-ols)

Flavanols exist in monomeric form (catechins) and the oligomeric form

(proanthocyanidins), are found in many fruits such as Apples, Apricots, Grapes, Peaches,

Nectarines, Pears, Raisins, Raspberries, Cherries, Blackberries, Blueberries and

Cranberries. Other sources of flavanols are red Wine, Tea, Chocolate, Wine and Cocoa.

An infusion of green Tea contains up to 200 mg catechins. Black Tea contains fewer

monomer flavanols, which are oxidized during fermentation of Tea leaves to more

complex condensed polyphenols known as theaflavins and thearubigins (2, 12).

15

1.3.7- Tannins

Tannins are a group of water-soluble polyphenols having molecular weights from 500 to

3,000 which are subdivided into condensed and hydrolizable tannins and commonly

found in complex with alkaloids, polysaccharides and proteins, particularly the latter

(12).

Tannins are responsible for the astringent taste of fruits. The level of astringency changes

over maturation and often disappears when the fruit reaches ripeness. Polymerization of

the tannins with acetaldehyde is an explanation for the reduction in the amount of tannins

observed during ripening of many types of fruits. Proanthocyanidins also known as

condensed tannins, have a wide range of structures and molecular weights which make it

difficult to estimate their amounts in plants (2, 12) .Tannins are found in fruits and

vegetables such as Grape, Strawberry, Raspberry, Pomegranate, Walnut, Peach,

Blackberry, Olive, Plum, Chick pea and Lentil. Other sources of tannins are Haricot

Bean, red wine, Cocoa, Chocolate, Tea, cider, Coffee and immature fruits. Table 1 shows

the content of tannins in some dietary sources (12). The structures of some tannins are

illustrated in Figure 12.

16

Condensed tannins

ellagitannins

casuarictin

tannic acid

Figure 12- Structure of some tannins

1.3.8- Anthocyanidins

As mentioned earlier in section 1.2.5, anthocyanidins are pigments dissolved in the

vacuoles of epidermal tissues of flowers and fruits which exhibit different colors in the

ranges of pink to purple. Cyanidin is the most frequent anthocyanidin in dietary plants

such as Blackberries, Blueberries, Black Grape, Elderberries, Strawberries, Cherries,

Plums, Cranberry and some other fruits (2,12).

17

1.3.9- Lignans

The highest amount of lignans (figure 13), which are considered as dimers of coniferyl

alcohol, can be found in linseed (up to 3.7 g/kg dry wt). Other cereals, grains, fruit and

certain vegetables also contain traces of lignans, but concentrations in linseed are

about1000 times as high as concentrations in the other food sources (2).

HO

OCH3

OH

coniferyl alcohol OCH3

OH

HO

H3CO CH2OH

CH2OH

lignan

Figure 13- Chemical structure of lignan and coniferyl alcohol (2)

1.4- Variability of polyphenol content of foods

Certain polyphenols such as quercetin are found in most of the fruits and vegetables,

cereals, leguminous plants, Tea, etc, while others are found in particular foods (flavones

in citrus fruits, isoflavones in soya and phloridzin in Apple). Foods contain mixtures of

polyphenols which are poorly characterized. Apples are one of the rare types of food for

which fairly precise data on polyphenolic contents are available. The information on the

polyphenol profile of all varieties of Apples is identical, but concentrations may range

from 0.1 to 5g total polyphenols/kg fresh weight and may reach up to 10 mg/kg in some

varieties of cider Apple.

Polyphenolic content in many plant products is unknown and the data is often limited to

one or few varieties. Moreover, factors other than variety may affect the polyphenolic

content of plants such as ripness at the time of harvest, environmental factors, processing

and storage conditions (2). Table 1 represents the classification and sources of some

dietary polyphenols and their contents in some food subjects (12).

18

Table1- Classification and sources of some dietary polyphenols and their contents

Classes of the compounds

Source (serving size)

Polyphenol content

By wt or vol By serving

mg/kg fresh wt (or mg/l) mg/serving References

Hydroxybenzoic acids Blackberry (100 g) 80–270 8–27 2,13,14

protocatechuic acid Raspberry (100 g) 60–100 6–10

gallic acid, ellagic acid Black currant (100 g) 40–130 4–13

p-hydroxybenzoic acid Strawberry (200 g) 20–90 4–18

Hydroxycinnamic acids Blueberry (100 g), Cherry (100 g) 2000–2200 200–220 2, 15

caffeic acid Kiwi (100 g) 600–1000 60–100

5-caffeoylquinic acid Peach (200 g) 180–1150 36–230

p- coumaric acid Plum (200 g) 140–1150 28–230

ferulic acid Aubergine (200 g) 600–660 120–132

sinapic acid Orange (200 ml) 50–600 10–120

Pear (200 g), Apple (200 g) 15–600 3–120

Chicory (200 g) 200–500 40–100

Artichoke (100 g) 450 45

Potato (200 g) 100–190 20–38

Corn flour (75 g) 310 23

Flour: wheat, rice, oat (75 g) 70–90 5–7

Cider (200 ml) 10–500 2–100

Coffee (200 ml) 350–1750 70–350

Anthocyanins Aubergine (200 g) 7500 1500 2 , 16, 17

cyanidin Blackberry (100 g), Elderberry (100 g) 1000–4000 100–400 18, 19

pelargonidin Black currant (100 g) 1300–4000 130–400

peonidin Blueberry (100 g) 250–5000 25–500

delphinidin Black Grape (200 g) 300–7500 60–1500

malvidin Cherry (200 g) 350–4500 70–900

Rhubarb (100 g) 2000 200

Strawberry (200 g) 150–750 30–150

Red wine (100 ml) 200–350 20–35

Plum (200 g) 20–250 4–50

Pomgranate (200 g) 250 50

Flavonols Yellow Onion (100 g) 350–1200 35–120 2, 17, 20, 21

quercetin Curly kale (200 g) 300–600 60–120

kaempferol Leek (200 g) 30–225 6–45

myricetin Cherry tomato (200 g) 15–200 3–40

19

isorhamnetin Broccoli (200 g) 40–100 8–20

Blueberry (100 g) 30–160 3–16

Black currant (100 g) 30–70 3–7

Apricot (200 g) 25–50 5–10

Apple (200 g) 20–40 4–8

Beans, green or white (200 g) 10–50 2–10

Black Grape (200 g) 15–40 3–8

Tomato (200 g) 2–15 0.4–3.0

Black tea infusion (200 ml) 30–45 6–9

Green tea infusion (200 ml) 20–35 4–7

Red wine (100 ml) 2–30 0.2–3

Flavones Parsley (5 g) 240–1850 1.2–9.2 17, 22

apigenin Celery (200 g) 20–140 4–28

luteolin Capsicum pepper (100 g) 5–10 0.5–1

Flavanones Orange juice (200 ml) 215–685 40–140 2, 23, 24, 25

hesperetin Grapefruit juice (200 ml) 100–650 20–130

naringenin Lemon juice (200 ml) 50–300 10–60

eriodictyol peppermint

Isoflavones (Flavans) Soy flour (75 g) 800–1800 60–135 2, 24

daidzein Soybeans, boiled (200 g) 200–900 40–180

genistein Miso (100 g) 250–900 25–90

Tofu (100 g) 80–700 8–70

Tempeh (100 g) 430–530 43–53

Soy milk (200 ml) 30–175 6–35

Flavanols Chocolate (50 g) 460–610 23–30 2, 26, 27

catechin Beans (200 g) 350–550 70–110

epicatechin Apricot (200 g) 100–250 20–50

epicatechin -3-gallate Cherry (200 g) 50–220 10–44

morin Grape (200 g) 30–175 6–35

epigallocatechin Peach (200 g) 50–140 10–28

epigallocatechin-3-gallate Cranberries,Blackberries, Blueberries

Raspberries (100 g)

130 13

gallocatechin Apple (200 g) 20–120 4–24

Green tea (200 ml) 100–800 20–160

Black tea (200 ml) 60–500 12–100

Red wine (100 ml) 80–300 8–30

20

Class of

compounds

Source (serving

size)

mg/kg fresh wt (or mg/l) mg/serving

References

Flavonoid

glycoside

Lemon (200 ml) 50–300 40–140 28

rutin Orange (200 ml) 215–685 40–140

hesperidin Grapefruit (200 ml) 100-550 20-130

naringenin

Tannins Apple (200 g) 19-37 5-10 29

proanthocyanidi

ns

Pear (200 g) 2-19 5

casuarictin Pomegranate (200

g)

40-117 10-30

tannic acids Peach (200 g) 9- 48 2-12

ellagitannins Red wine (100 ml) 20-100 2-10

sanguine H6 Green Tea (200 ml) 18- 48 4.5-12

Coffee (200 ml) 35-50 8-12.5

1.5- General overview on a typical diet (How much do we eat of what?)

As mentioned above, dietary phenolic acids and polyphenols are aboundant in Tea (black

and green), fruits, vegetables, Olive oil, red and white wines as well as Chocolate and the

amount of them varies from a few micro grams to hundreds of milligrams or even grams

per serving for the mentioned foods (figure 13, 14), although the concentration of these

compounds always vary for each type of food. People with diets rich in fruits and

vegetables, may consume about five to ten grams of polyphenols per day.

The structural diversity of polyphenols makes the estimation of their content in food

difficult (30). The average content in some food serving is compared in the following

charts (Figures 14, 15) (31).

21

Figure 14- chart showing the phenolic content of selected beverages, vegetables and

Chocolate in milligrams per serving. Serving size is based on a typical beverage size (240

ml), piece of Chocolate (40 g), or serving of vegetables (31)

22

Figure 15- A chart showing the phenolic content of selected fruits in milligrams per

serving. Serving size is based on a typical serving of fruit (31)

23

1.6- Bioactivities of the dietary polyphenols

Polyphenols and phenolic compounds are a large part of human diet and therefore it is

highly desirable to understand their biological functions and modes of activity (31, 32).

Epidemiologic studies have shown a correlation between an increased consumption of

phenolic antioxidants and a reduced risk of cardiovascular disease, neurodegenerative

diseases and certain types of cancers (33, 34, 35, 36). The chemical structure of

polyphenols affects their biological properties such as bioavailability, antioxidant

activity, specific interactions with cell receptors and enzymes and other properties (17,

37).

Polyphenols have been often evaluated for their biological activities in vitro on pure

enzymes, cultured cells, or isolated tissues by using polyphenol aglycones or some

glycosylated polyphenols available in dietary plants. Information about the biological

properties of conjugated derivatives of polyphenols present in plasma or tissues is very

scarce because of lack of precise identification and availability of commercial standards

(2, 38, 39, 40).

1.6.1- Oxidative stress

Reactive oxygen species (ROS), such as hydroxyl radical (OH∙), hydrogen peroxide

(H2O2) and superoxide anion radical (O2∙ -

) are responsible for oxidative damage in cells

such as damaging proteins, lipids and DNA (41, 42, 43, 44). The free radical theory of

aging was proposed by Denham Harman more than 50 years ago and the phenomenon

has been termed ―oxidative stress‖ by Helmut Sies in 1985 (45). Oxidative damage of

DNA is a cause of cancer, aging, neurodegenerative diseases such as Alzheimer and

Parkinson, cardiovascular diseases such as arteriosclerosis (42, 43, 44, 46, 47).

Prevention of oxidative stress caused by ROS is important for the prevention and

treatment of such diseases (48, 49, 50, 51).

24

1.6.2- Antioxidant and free radical scavenging properties of polyphenols

Antioxidants are reducing agents that are capable of delaying or inhibiting the oxidation

of other molecules. In oxidation reactions, free radicals can be produced, which start

chain reactions that damage cells (52, 53). Antioxidants such as polyphenols terminate

these chain reactions trough their radical scavenging property and inhibit other oxidation

reactions by being oxidized themselves (e.g., oxidation by H2O2, Fe3+

and Cu2+

) (52, 54,

55). Cells and tissues are threatened by the damage caused by free radicals which is

produced during metabolism or induced by exogenous damage. One of the most

important reasons why free radicals interfere with cellular functions seems to be due to

lipid peroxidation which causes cellular membrane damage leading to a shift in the net

charge of the cell thus changing the osmotic pressure of within the cell, resulting in

swelling and cell death (56, 57, 58, 59).

1.6.3- The ways polyphenols exhibit their antioxidant activity:

Flavonoids and other polyphenols exhibit their antioxidant activity in several ways:

Radical scavenging activity toward reactive species (e.g., ROS) or toward lipid

peroxidizing radicals such as R∙, RO∙ and ROO∙. Radical scavenging action generally

occurs through hydrogen atom transfer or electron donation (figure 16).

Prevention of the transition metal –catalyzed production of reactive species.

Interaction with other antioxidants (such as cooperative actions), localization and

mobility of the antioxidant at the microenvironment (52).

http://www.search.com/reference/Chain_reaction

http://www.search.com/reference/Cell_%28biology%29

25

RO

O

H

H

RO

O

HR

O

O

H-O

H-O

- H2O-H2O

Figure 16- Radical scavenging mechanism of polyphenols

Polyphenols exhibit a wide range of biological effects as a consequence of their

antioxidant properties (3, 60, 61). The radical scavenging properties of polyphenols are

important for preventing diseases associated with oxidative damage of membranes,

proteins, lipids and DNA (62). As mentioned earlier, studies suggest that consumption of

dietary polyphenols is associated with reduced risk of various cancers, prevention of

neurodegenerative and heart diseases as well as prevention and minimizing the

menopausal symptoms (63, 64 and 65).

1.6.4- Potential mode of action of phenolic compounds

Besides the strong antioxidant capacities, dietary polyphenols have been largely studied

for other properties by which cell activities are regulated (12, 66).

They might interfere through several mechanisms that lead to development of tumors,

inactivating carcinogens, inhibiting the expression of mutant genes and enzymes involved

in the activation of procarcinogens (3, 67, 68). Studies have shown that polyphenols,

particularly flavonoids, inhibit the initiation, promotion and progression of tumors,

possibly by different mechanism other than their antioxidant protective effects on DNA

and gene expression (3, 69, 70, 71).

Flavonoides and their metabolites exert modulatory actions through the activation of

different protein kinases such as mitogen-activated protein kinase (MAP kinase) (72).

There are several types of MAP kinase such as Extracellular signal-Regulated Kinase

(ERK), c-Jun NH2-terminal Kinase (JNK) and P38 and each of them is responsible for

different functions for example apoptosis. These MAP kinases phosphorylate different

26

transcription factors such as NF-κB and Activator protein-1(AP-1). For example the NF-

κB regulates the expression of cytokines, growth factors and inhibitors of apoptosis.

MAP kinase is a protein kinase which can be activated by different mitogenes (signals

that come to the cell). Once MAP kinase is activated then it changes the spectrum of

transcription in a cell as a response to stimuli (4, 73, 74).

There are many examples of polyphenols that play role in inhibition or activation of

enzymes by which cell activities are regulated. The research for understanding the

mechanism of actions observed for health benefits has recently intensified. As an

illustration, the inhibitory effect of (-)-epigallocatechin-3-gallate on Ultraviolet B-

activated phosphatidylinositol 3-kinase (PI3K) in mouse epidermal JB6 Cl 41 cells was

shown in a study. The researchers suggest that because PI3K is an important factor in

carcinogenesis, the inhibitory effect of these polyphenols on activation of PI3K and its

downstream effects may further explain the anti-tumor promotion action of the Tea

polyphenols (75). In another study, results provide the first evidence that 5-caffeoylquinic

acid could protect against environmental carcinogen-induced carcinogenesis and suggest

that the chemopreventive effects of 5-caffeoylquinic acid may be through its up-

regulation of cellular antioxidant enzymes and suppression of ROS-mediated NF-κB, AP-

1 and MAPK activation (76).

27

1.6.5- Biological activities of flavonoids

Flavonoids are considered as the major bioactive components of many medicinal plants.

Besides the antioxidant activity, they show biological activities and clinical effects such

as anti-atherrosclerotic effects, anti-tumor, anti-mutagenic, anti-thrombotic, anti-

inflammatory, anti-osteoporotic, anti-alergic and anti-viral activity (8, 9, 77, 78,79). For

example, hesperetin was found to inhibit the replication of herpes simplex virus type 1,

poliovirus type 1 and parainfluenzavirus type 3. Hesperidin and naringin have inhibitory

activity on rotavirus infection (80, 81).

1.6.6- Biological activities of isoflavones

Isoflavones are particularly abundant in plants belonging to Fabaceae family, especially

in soybeans. Due to their structural similarity to mammalian ß-estradiol (figure 17),

isoflavones are known to possess estrogenic activties. Hypotheses on their benefits for

human health such as anti-carcinogenic activity, protection against cardiovascular

diseases, protection in osteoporosis and menopausal symptoms, have been suggested by

several authors. Clinical trials are necessary to address these important issues (7, 82).

OH

HO

A

H3C

Figure 17- ß-estradiol

1.6.7- Biological activities of anthocyanidins

Anthocyanidins may enhance anti-inflammatory and neuroprotective effects. They can

inhibit lipid peroxidation and enzymes associated with tumour formation and reduce the

risk of coronary heart diseases (11, 83).

28

1.6.8- Biological activities of tannins

Tannins are reported to possess biologically multifunctional properties including anti

oxidant, anti-bacterial, anti-viral, anti-inflammatory, anti-tumor activities and inhibitory

effects on various enzymes (84).

Various examples of biological activities of dietary polyphenols and their health effects

are illustrated in the following (Figure 18).

Figure 18- Bioactivities of dietary polyphenols (12)

1.6.9- Anti-atherosclerosis and cardioprotection effects of dietary polyphenols

Studies have demonstrated that some dietary polyphenols show anti-atherosclerosis and

cardioprotection effects, such as quercetin which inhibited lipid peroxidation, upregulated

the expression of serum high density lipoprotein (HDL)-associated paraoxonase 1(PON-

29

1) in HUH7 human hepatoma cell line (12). Some other polyphenols which exert anti-

atherosclerosis in vitro level are listed below:

1- resveratrol (85, 86, 87, 88, 89)

2- (-)-epicatechin (90)

3- caffeic acid (91)

4- quercettin (92)

5- kaempferol and apigenin (93,94)

6- epigallocatechin gallate and epicatechin gallate (95)

7- genestein (96)

9- proanthocyanidin in vitro and in vivo levels (97, 98)

1.6.10- Neuroprotective effects of dietary polyphenols

There has been a considerable interest in the neuroprotective effects of some dietary

polyphenols and the mechanism of actions of these effects. Such polyphenols had been

considred as therapeutic agents for altering brain aging processes and as possible

neuroprotective agents in progressive neurodegenerative disorders such as Parkinson‘s

and Alzheimer‘s diseases (12). Some dietary polyphenols which show neuroprotective

effects are listed below:

1- resveratrol in vitro and in vivo levels (99,100).

2- epigallocatechin gallate and epicatechin gallate in vivo and in vitro levels (101, 102).

3- catechin, quercetin, genestein, naringenin in vivo levels (103)

4- epicatechin and kaempferol in vitro level (104)

1.6.11- Anti-inflammatory properties of dietary polyphenols

Oxidative stress induced inflammation is mediated by the activation of NF-кB and AP-1.

It affects a wide variety of cellular signaling processes leading to generation of

inflammatory mediators (12). Some dietary polyphenols which exhibit anti-inflammatory

effects are listed below:

1- epigallocatechin gallate and epicatechin gallate in vitro level (105, 106)

30

2- resveratrol in vitro level (107, 108, 109)

3- apigenin, luteolin and quercetin in vitro level (110, 111, 112)

4- anthocyanidins (113)

1.6.12- Anti-mutagenic /anti-carcinogenic properties of dietary polyphenols

Dietary polyphenols could modulate diverse biochemical processes involved in

carcinogenesis. Cellular signaling cascades mediated by NF-кB or AP-1 acted as a

centerplay in regulating many of aforementioned biochemical processes (12). Some

dietary polyphenols which exhibit anti-mutagenic /anti-carcinogenic effects are listed

below:

1- resveratrol in vitro and in vivo levels (114, 115, 116)

2- 5- caffeoyl quinic acid in vitro level (117)

3- quercetin, luteolin, myricetin, apigenin and kaempferol in vitro level (28,118)

4- hesperetin and daidzein in vitro level (119)

5- epigallocatechin gallate in vitro and in vivo levels (120)

1.6.13- Protective effect on immune cell functions

Dietary polyphenols appear to have a protective effect on immune cell functions. One

study showed that leukocyte functions were improved in prematurely aging mice after

five weeks of diet supplementation with polyphenol-rich cereals (121). They could

increase the immune cell functions such as phagocytosis, chemotaxis and microbicidal

activity (12).

1.6.14- Anti-allergic activity

The tannins from Apple could inhibit the release of histamine from rat basophilic

leukemia (RBL-2H3) cells stimulated by the antigen-stimulation and from rat peritoneal

mast cells stimulated by compound. They also inhibited hyaluronidase activity and

31

increase in intracellular free calcium concentration in RBL-2H3 cells stimulated with the

antigen (122)

1.6.15-Anti-diabetic effects

Some dietary polyphenols which exhibit anti-diabetic effects are listed below:

1- epigallocatechin gallate and (-)-epigallocatechin in vitro levels (123,124)

2- quercetin in vitro levels (125)

3- tannins in vitro levels (126)

1.6.16- Regulation of cell cycle progression

It was demonstrated that some polyphenols such as resveratrol regulate cell cycle

progression in vitro levels (127).

1.6.17- Modulation of hormonal effects and contraceptive activity

Studies have shown that some dietary polyphenols could modulate the level of sexual

hormone. The phytoestrogens can act like estrogen at low doses but block estrogen at

high doses (128). For example, resveratrol acts as a mixed agonist/antagonist for estrogen

receptors alpha and beta (129,130).

It was shown that both genistein and quercetin are full agonist of estradiol receptor alpha

(ER α). At low concentrations (≤1µM) they both stimulate the proliferation of breast

cancer lines that are dependent on ER α. On the other hand at higher concentrations (≥10

µM) both phytoestrogens become cytotoxic (131).

1.6.18- Other bioactive effects

It has been demonstrated that dietary polyphenols have other biological effects such as

anti-bacterial activity (132,133), anti-HIV activity (134) and hepatoprotective activity

(135,136,137).

32

1.7- Bioavailability and metabolism of polyphenols

Polyphenol metabolites that are detected in blood result from digestive or hepatic activity

and the form that reach cells and tissues are chemically distinct from the dietary form (4).

The difference between the chemical structure of the consumed phenolics and the

chemical structure of the produced metabolites affects their bioactivity. Very small

amount of the absorbed polyphenols retain their original structure found in the plant and

the rest of the dietary phenolics and polyphenols are modified during absorption. (4,138).

Metabolism of polyphenols follows a common pathway (30). The absorption of

aglycones occurs in the small intestine. Polyphenols which are present in the forms of

esters, glycosides or polymers cannot be absorbed in their original forms. Therefore they

are subjected to hydrolysis by intestinal enzymes or colonic microflora before absorption.

Polyphenols that are not absorbed in the small intestine reach the colon. Microflora

hydrolyzes glycosides into aglycones and extensively metabolizes and degrades the

released aglycones and produces various aromatic acids. Therefore the efficacy of

absorption is reduced by microflora (2). The polyphenols undergo a conjugation process

including sulfation and glucuronidation in the small intestine and liver. Similar to

detoxication of xenobiotics, the potential toxic effects are restricted. The increased

hydrophilicity also facilitates their biliary and urinary elimination (2).The aglycones are

generally absent in blood or present in low concentrations after consumption. Therefore

conjugation mechanisms must be highly effective. Later, conjugated derivatives of

polyphenols are circulated in the body (2).

Data on bioavailability of polyphenol metabolites are still very scarce in animals and

human (4, 20). Like other substrates, each single dietary phenol or polyphenol generates

several metabolites. The metabolites vary with the individual‘s genetic profile and the

composition and competence of that individual‘s intestinal microflora (4).

33

The biological effect(s) of a metabolite will be a function of the concentration of the

metabolite at the relevant site and the susceptibility of the organelle (receptor, enzyme,

transporter, etc.) that might vary with the individual‘s genetic profile (4).

To understand the role of dietary phenolics in disease prevention, their bioavailability

must be established and it must be clear which of the flavonoids and phenolic compounds

and their related metabolites gain access to appropriate cellular sites within the body to

exert their biological effects (2).

In a study with rats, methyl and glucuronide metabolites in the brain of rats were detected

after acute ingestion of a high does of (-)-epicatechin (139). In another study,

anthocyanidins in rat brains after supplimentation with berry and grape extracts were

detected (139). Extremely low concentrations of anthocyanidins were also detected in rat

brains after the consumption of a blackberry extract for 15 days (139). In the only study

to date with humans, glucorono-, sulfo- and methylated flavan-3-ol metabolites were

identified in plasma, but they were not present in cerebrospinal fluid three hours after the

ingestion of 300 ml of green Tea (139).

1.8- Biosynthesis of polyphenols

The biosynthesis of flavonoides, stilbenes, hydroxycinamates and phenolic acids

principally stand with the shikimic acid pathway, leading to phenylalanine and finally p-

coumaric acid (Figure 19, 20). Much of the recent information on these pathways, the

enzymes involved and the encoding genes has come from molecular biology-based

studies with Arabidopsis thaliana. This knowledge has opened up the possibility of using

genetic engineering to produce fruits and vegetables containing elevated levels of key

phenolic and polyphenolic compounds that may enhance protection of human health (4).

34

Figure 19- Schematic diagram of the main pathways and key enzymes involved in the biosynthesis of

hydrolysable tannins, hydroxycinnamates and 5-O caffeoylquinic acid . Enzyme abbreviations: PAL,

phenylalanine ammonia-lyase; C4H, cinnamate 4-hydroxylase; COMT-1, caffeic/5-hydroxyferulic acid O-

methyltransferase; 4CL, p-coumarate: CoA ligase; F5H, ferulate 5-hydroxylase; GT, galloyltransferase;

ACoAC, acetylCoA carboxylase (4).

35

Figure 20- Schematic diagram of the stilbene and flavonoid biosynthetic pathways. Enzyme abbreviations:

SS, stilbene synthase; CHS, chalcone synthase; CHR, chalcone reductase; CHI, chalcone isomerase; IFS,

isoflavone synthase; FNS, flavone synthase; F3H, flavanone 3-hydroxylase; FLS, flavonol synthase; F30H,

flavonoid 30-hydroxylase; DFR, dihydroflavonol 4-reductase; LAR, leucoanthocyanidin 4-reductase; ANS,

anthocyanidin synthase; ANR, anthocyanidin reductase; EU, extension units; TU, terminal unit (4).

36

1.9- Liquid chromatography mass spectrometery (LC-MS) of polyphenols

A large number of different methods, papers and reviews have been published for

identifying and quantifying analysis of flavonoids in plants (140). High performance

liquid chromatography (HPLC) was first used for the determination of flavonoids in 1976

by Fisher and Wheaton (79). Ever since, HPLC combined with various detection

methods, has remained the method of choice for the analysis of polyphenols in dietary

material and plasma.

1.9.1- Chromatographic conditions

Liquid chromatography analysis of flavonoids is usually carried out in the reversed-phase

(RP) mode, on C18– or C8-bonded silica columns ranging from 100 to 250 mm in length

and usually with an internal diameter of 3.9 to 4.6 mm (140). Elution systems are usually

binary, with an aqueous acidified polar solvent such as aqueous acetic acid, phosphoric

acid or formic acid (solvent A) and a polar organic solvent such as methanol or

acetonitrile (solvent B). Runs are generally an hour maximum. To avoid peak

broadening, flow rates in analytical runs are usually 1.0 or 1.5 ml/min.Thermostatically

controlled columns are normally kept at ambient or slightly above ambient temperatures.

Injections generally range from 1 to 100 µl (140,141).

1.9.2- Detection

All phenolic compounds contain at least one aromatic ring and therefore absorb UV light.

Two absorption bands are characteristic of flavonoids.The first maximum, which is in the

240–285 nm range, is belived to arise from the A-ring or B-ring. The second maximum,

which is in the 300–550 nm range, to the substitution pattern and conjugation of the C-

ring (79).

Simple substituents such as methyl and methoxy groups generally effect only minor

changes in the position of the absorption maxima. Already several decades ago, UV

spectrophotometry was still a popular technique to detect and quantify flavonoid

aglycones. More recently, diode-array detectors (DAD) give much more information

37

about the full spectra of these compounds if coupled to HPLC, which may be a great help

in their identification. Usually the spectra, collected in the range 200-400 nm, are

compared with the spectra of reference compounds by evaluating the degree of identity.

Today, UV detection become the preferred tool in LC-based analyses and, LC with DAD

is a fully satisfactory tool in studies dealing with, e.g. screening, quantification of the

main aglycones and/or a provisional sub-group classification (140).

Band II, with a maximum in the 240-285 nm range, is believed to arise from the A-ring.

Band I, with a maximum in the 300-550 nm range, presumably arises from the B-ring.

Anthocyanidins show band II and band I absorption maxima in the 265-275 nm and 465-

560 nm regions, respectively. Because there is little or no conjugation between the A- and

B-rings, UV spectra of flavanones and isoflavones usually have an intense band II peak

but a small band I peak . This lack of conjugation also results in small band I peaks for

the catechins (Figure 21). UV spectra of flavones and flavonols have a band II peak at

around 240-280 nm and a band I peak around 300-380 nm (79).

Detection of (iso) flavonoids in food analysis is usually by UV-VIS with diode array

detection (DAD). Typical wavelengths for analysis and quantification of anthocyanidins

are 502 nm, 510 nm, 520 nm and 525 nm. Catechins are generally quantified at 210 nm,

278 nm and 280 nm. Flavanones and their glycosides are generally detected at 280 nm

and 290 nm. Flavones, flavonols and flavonol glycosides are usually detected at

wavelengths such as 270 nm, 365 nm and 370 nm, although detection at 280 and 350 nm

was used. Isoflavones were generally detected at 236 nm, 260 nm, 262 nm and 280 nm

(79).

38

Figure 21- UV-VIS spectra of the anthocyanidin delphinidin, epicatechin, the flavanone

hesperetin, the flavone luteolin, the flavonol quercetin and the isoflavone genistein (79)

1.9.3- LC-MS

An HPLC can be connected to a mass spectrometer, as was done in the analysis of fruits,

vegetables and beverages by Justesen et al. in 1998 (79).The introduction of liquid

chromatography mass spectrometery (LC-MS) for crude plant extract analysis has

revolutionized compounds analysis and is most frequently used for the on-line

identification of natural compounds such as polyphenols (7). UV-VIS absorption is used

39

primarily for quantification, but can be used for identification of flavonoid subclasses.

Tandem MS with electrospray ionization (ESI) or atmospheric pressure chemical

ionization (APCI), are soft ionization techniques, usually used for identification and

structural characterization (8), which generate mainly molecular ions for relatively small

plant metabolites such as flavonoids. Molecular weight information alone is however not

sufficient for the on-line structure determination of natural products and fragment

information is necessary for partial on-line identification of known constituents (7).

Electrospray ionization (ESI) in negative ion mode MS for polyphenol analysis ESI is the

method of choice for polyphenol structural elucidation, due to the polar nature of

polyphenols and the presence of acidic functional groups. ESI provides usually the parent

ion without fragmentation. Several MS detectors can be used to obtain structural

information on polyphenolic compound. Detectors include high resolution instrument

such as Fourier transform ion cyclotron resonance (FTICR) or Time of Flight (TOF)

detectors, whose accurate mass measurements provide direct reliable information on

molecular formulas. Furthermore, tandem MS (triple quadrupole, Quadrupole-TOF (Q-

TOF) and ion trap techniques can be used to study fragmentation to increase information

on structure (8).

40

2- Aim of the project

During the last decade, research has been intensified investigating the potential health

benefits of dietary polyphenols. This recent surge in interest in the health effects of these

ubiquitous plant secondary metabolites was sparked by epidemiology with the Zutphen

Elderly Study (142) revealing for the first time an inverse association between the

mortality from cardiovascular disease and the intake of flavanoids. Much subsequent

work in epidemiology has substantiated these initial observations, providing

overwhelming evidence that dietary polyphenols play an important role in the prevention

of various diseases such as cancer, cardiovascular and neurodegenerative diseases

(2,143). However, cause and effect relationships still need to be studied in detail.

For most diets, epidemiology has established a causal link between the type of diet and its

health benefits. The chemical compounds being responsible for these effects and the

biological targets targeted by these compounds leading to a mechanism of action

rationalizing the observed health benefits are still unclear. Therefore as a first step to

accomplish an understanding between the diet and health effects, a thorough investigation

of various plant secondary metabolites, in this work polyphenols, present in an average

diet, needs to be established and these findings will be further linked to epidemiological

data. Once certain dietary varieties have been identified to share a common health

benefit, a comprehensive database containing compounds present in these varieties will

allow for a more efficient screening of dietary compounds against putative biological

targets linked to the diseases in question.

Several reviews have been published on dietary sources of polyphenols which briefly

illustrate the existence of some polyphenols in several food sources (2, 144, 145) and few

special databases have been released on polyphenols and their origins such as the

flavonoid database (FDB) and proanthocyanidin database (PDB) stablisted by Nutrient

Data Laboratory (NDL) at U.S. Department of Agriculture (146) and phenol Explorer

(147). Although these reviews and databases are well recognized and provide useful

41

information, they do not provide comprehensive information on the dietary polyphenols

and their origins, generally because the data from each source were for a limited number

of compounds and in the lack of comprehensive data on glycosylated polyphenols exist in

the mentioned databases. Furthermore, these reviews and databases are not updated and

many polyphenolic compounds in food sources have remained unknown and to be

structurally elucidated using modern analytical tools.

The present research, studies the main contributors to human polyphenol intake in a

typical European diet, in order to establish a basis for further in vitro and in vivo assay

and human intervention studies, such as finding evidence for the effects of polyphenol

consumption on health and to identify which of the hundreds of existing polyphenols are

likely to provide the greatest protection in the context of preventive nutrition.

From statistical data available, the most commonly consumed fruits and vegetables in a

typical European diet have been identified and the aim of this work is to screen these

qualitatively, using LC-MS methods for the identification of polyphenolic secondary

metabolites present.

3- Materials and methods

3.1- Materials and instruments

3.1.1-Chemicals and reagents

HPLC-grade acetonitrile, methanol and formic acid, sodium formate was purchased from

Sigma Aldrich. Standards, including epicatechin, kaempferol, luteolin, rutin, apigenin,

epigallocatechin gallate, quercetin and gallic acid were purchased from Sigma Aldrich.

42

3.1.2- Biological Samples:

A wide range of fruits and vegetables of different varieties and origins were purchased

including Apple (Malus domestica), Pear (Pyrus communis), Carrot (Daucus carota),

Leek (Allium ampeloprasum), Cauliflower (Brassica oleracea), Strawberry (Fragaria x

anassa), Nectarine (Prunus persica var. nucipersica), Banana (Musa paradisiaca), Onion

(Allium cepa), Courgette (Cucurbita spp.), Melon (Cucumis melo), Asparagus (Asparagus

officinalis), Lettuce (Lactuca sativa) and Orange (Lactuca sativa) at local grocery stores

such as Plus, Penny, Marktkauf, Aldi, Lidl and Karstadt in Bremen, Germany.

3.1.3- Equipments:

A normal kitchen knife, a homogenizer, a rotary-evaporator (Labrota, Heidolph 4000),

balance (Sartorius, CP225D), sonicator (Sonorex, Bandelin, Berlin, Germany) were used.

For Liquid Chromatography Mass Spectrometery (LC-MS) the following equipments

were used:

High Performance Liquid chromatography (HPLC): HPLC equipment (Agilent 1100

series, Karlsuhe, Germany) comprised a binary pump, an autosampler with a 100 μL loop

and a diode array detector (DAD) with a light-pipe flow cell (recording at 320 and 254

nm and scanning from 200 to 600 nm). Separation was achieved on a 150 x 3 mm i.d.

column containing diphenyl 5 μm with a 4 x 3 mm i.d. guard column of the same

material (Varian, Darmstadt, Germany).

Tandem mass spectrometer: An ion-trap mass spectrometer fitted with an ESI source

(Bruker Daltonics HCT Ultra, Bremen, Germany) was used.

High resolution mass spectrometer: A MicrOTOF Focus mass spectrometer (Bruker

Daltonics) fitted with an ESI source was used.

43

3.2- Methodology

3.2.1- Preparation of the samples:

The peels of Apples, Pears, Nectarines were kept. Oranges, Bananas, Onions, Melons

were roughly peeled. Peel and flesh were analysed separately unless stated otherwise.

Seeds were discarded for all the fruits except strawberry. In stone fruit, the stone was

removed. A total of 42 samples were prepared by methanolic extractions of fleshes and

peels of the fruits and vegetables listed in table 2.

44

Table 2- List of the samples

Sample

No

sample Origin Sample

No

sample Origin

1 Apple peel New Zealand 23 Galia Melon Italy

2 Apple flesh Argentina 24 White Onion Germany

3 Apple peel Germany 25 Nectarine peel Italy

4 Apple peel Argentina 26 Zucchini flesh Germany

5 Apple peel China 27 Zucchini peel Germany

6 Apple flesh New Zealand 28 Leek Germany

7 Apple peel Italy 29 Banana Colombia

8 Apple flesh Germany 30 White Onion Spain

9 Apple flesh China 31 Galia Melon Brazil

10 Green Asparagus Germany 32 Nectarine flesh Italy

11 White Asparagus Germany 33 Pear peel Spain

12 Apple flesh Italy 34 Valencia Orange Souht

Africa

13 Carrot Italy 35 Honey Melon Spain

14 Pear flesh Argentina 36 Pear flesh Spain

15 Carrot Israel 37 Cauliflower Germany

16 Carrot Holand 38 Banana Ecuador

17 Pear peel Argentina 39 Navel Orange South

Africa

18 Lettuce Iceberg Germany 40 White Asparagus Peru

19 Red Onion Egypt 41 Nectarine flesh Spain

20 Banana Dominica

republic

42 Strawberry Germany

21 Orange Argentina

22 Lettuce Romana Germany

45

3.2.2- Methanolic Extraction:

Fifty grams of each fruit and vegetable sample was cut and chopped into small pieces and

frozen with liquid nitrogen in a flask. 100 ml methanol was added to the frozen particles

and stirred with the homogenizer. The solution was allowed to stand in an ultra-sonic

bath (Sonorex, Bandelin, Berlin, Germany) for 30 minutes in a closed vessel. The mixture

was filtered using filter papers at least twice to remove the tissue particles and cell debris.

The liquid was concentrated in a vacuum rotary evaporator at 40 º C. The flasks

containing dry extract were stored at -18 º C.

3.2.3- Sample preparation for liquid chromatography mass spectrometry:

In order to subject the samples to Liquid chromatography mass spectrometery (LC-MS),

50 mg of each dried sample were dissolved into 5 ml methanol, sonicated, filtered using

filter membrane and placed into a HPLC vial. The solution was diluted with methanol to

30:1 for LC-MS using ESI-TOF mass spectrometer.

3.2.4- Methodology for liquid chromatography mass spectrometry (LC-MS):

Methanolic vegetable and fruit extracts from 42 samples were analysed by LC-MS. For

liquid chromatography using the mentioned HPLC instrument, a solvent system was

developed using solvent (A) and (B), in which (A) was water/formic acid (1000:0.05 v/v)

and solvent (B) was acetonitrile. Solvents were delivered at a total flow rate of 500

μl/min. The concentration ratios for (A):(B) varied linearly from 85:15 at 0 min, to 75:25

at 10 min, to 55:45 at 20 min, to 35:65 at 30 min, to 25:75 at 40 min, to 25:75 at 45 min

followed by 10 min isocratic and a return to 15% B at 55 min. The HPLC was used

interfacing an ESI-ion trap mass spectrometer or interfacing an ESI-TOF mass

spectrometer.

46

3.2.4.1- LC-MS using tandem mass spectrometer (LC-MSn)

The HPLC was equipped with the ESI-tandem mass spectrometer operating in Auto-MSn

mode (smart fragmentation) using a ramping of the collision energy. Maximum

fragmentation amplitude was set to 1 V, starting at 30% and ending at 200%. Tandem

MSn measurments were carried out in alternative ion mode. The MS method was

optimized using 5-caffeoylquinic acid.

3.2.4.2- LC-MS using high resolution TOF mass spectrometer

The HPLC was equipped with the ESI-high resolution TOF mass spectrometer. All MS

measurments were carried out both in negative and positive ion mode. External

calibration was achieved with 10ml of 0.1M sodium formate solution injected through a

six-port valve prior to each chromatographic run. Calibration was carried out using the

enhanced quadratic calibration mode.

3.2.5- Assignment of the compounds

Tandem MS spectra of the samples were investigated for the assignment of the

compounds based on the m/z values of the peaks and fragmentation pattern of the most

commonly occurring dietary phenolic compounds and polyphenols reported by

Sakakibara (148). Mass spectral data was processed with Data Analysis 4.0 Bruker

Daltonics.

3.2.6- Confirmation of the assigned compounds

The m/z values of the assigned peaks in the tandem MS spectra of the samples were

reinvestigated and the presence of the compounds confirmed in the extracted ion

chromatograms (EIC) of high resolution mass spectra of the samples within 10 ppm

tolerance. Smartformula Manually lists the generated formulas for the given m/z value.

For each formula, a set of data including various error values, rankings and statistical

47

values is calculated. The data were recorded includes: Mol. Formula (Sum formula), m/z

(Calculated m/z of the formula), |err| [ppm] (Absolute value of relative deviation

between measured mass and theoretical mass of the selected peak (monoisotopic peak) in

[ppm]) and mSigma (Sigma value which combines the standard deviation of the masses

and intensities for isotopic peaks of a single compound. The value is given in

[milliSigma]).

48

4- Results and Discussion

4.1- Consumption of polyphenols

The United States Department of Agriculture (USDA) has published a database that

serves as a reference for the determination of intake of polyphenols (146). However, like

all nutrients, there is variation with cultivar, year, growing conditions, etc. The average

amount of daily intake of polyphenols differs for individuals and populations based on

the region and dietary habits. An individual who consumes fruits and vegetables several

times on a daily basis along with consumption of Cocoa, Tea or Coffee could easily reach

an amount of total polyphenol intake of hundreds of milligrams per day (2,149). It must

be quoted that substantial loss in polyphenolic content of ingredients could occur during

cooking (150). In comparison with the raw ingredients, procesed food may contain

different amounts of polyphenols. It should not be assumed that a food containing e.g.

two Apples will contain the same amount of polyphenols as two Apples eaten raw.

4.2- Methodology

4.2.1- Criteria for the selection of the samples

A total of 34 different fruits and vegetables were purchased at local supermarkets in fresh

form. The samples were purchased in Bremen, Germany. The samples were bought from

different varieties and country of origins, representing the market patterns in Europe.

The primary criteria for the selection of a fruit or a vegetable included (a) fruits and

vegetables that are highly consumed in Europe according to the patterns reported in

France, Spain, Finland, US and England (150,151,32,152,153,154); (b) the items with the

highest total polyphenol content (TPC) (150).

49

Total polyphenol contents are measured by a variety of methods, most commonly the

Folin-Ciocalteu assay and DPPH (1,1-diphenyl-2-picrylhydrazyl) assay (150, 155). The

TPC of the samples are determined and expressed with respect to a reference compound,

normally gallic acid and it is expressed as gallic acid equivalent (GAE). Gallic acid

response represents the mean response of all the major polyphenol compounds in fruit

and vegetables as aglycones and conjugates (quercetin, quercitrin, catechin, procyanidin

mixture, caffeic and 5-caffeoylquinic acid) (150). Table 3 presents data on TPC of fruit

and vegetables considered for this project. The values are mean TPC for 3 samples each,

presented as mg of GAE /100 g of fresh edible portion (FEP) (150).

To obtain the amount of polyphenol intake, the amount of fruit or vegetable consumed in

grams/d is multiplied by the total polyphenol content in the fruit or vegetable. Table 3

present data on polyphenol intake estimated from fruit and vegetables most commonly

purchased in France.

Table 3- Estimated total polyphenol content (TPC) and polyphenol intake (PI)

of fresh fruit and vegetables (150)

Common

name

Mean

TPC

(mg of

GAE/100

g FEP)

Consumption

FEP g/d

PI

mg

GAE/d

Common

name

Mean

TPC

(mg of

GAE/100

g FEP)

Consumption

FEP g/d

PI

mg

GAE/d

Strawberry 263.8 6.9 18.2 Onion 76.1 8.8 6.7

Apple 179.1 52.8 94.5 Asparagus 14.5 1.3 0.2

Pear 69.2 12.3 8.5 Lettuce 35.6 15.8 8

Nectarine 72.7 15.9 9.4 Leek 32.7 4.9 1.6

Banana 51.5 16.9 8.7 Courgette 18.8 10.8 2

Orange 31.0 21.2 6.6 Cauliflower 12.5 4.0 0.5

Melon 7.8 9.5 0.7 Carrot 10.1 23.1 2.3

FEP: Fresh edible portion

d: day

50

These fruits and vegetables have been selected from a list, reporting and ranking the TPC

of 24 fruits and 29 vegetables consumed in France (150). The fruits and vegetables

selected for this project were repeatedly reported to be consumed in different quantities in

Europe as well as in US (150, 151, 32, 152, 153). The rest of the items, which were not

considered for this project have been already investigated in our research group. Potato

and tomato, although consumed in considerable quantities and reported to contain high

leveles of polyphenols, were omitted from this study, since they have recently been

investigated (156). Chocolate, Coffee, red wine and black Teas have been well-studied

within the Kuhnert group.

4.2.2- Method of extraction

Different method papers and reviews have been published for extraction and

identification of polyphenols (79,157,158,159,160,161,162,163). In general they were

used either to determine a single class of polyphenols from a variety of foods or to

determine all of the phenolic compounds in a single food (1,164). Sakakibara et al.

describe a method for the determination of ―all‖ flavonoids in vegetables, fruits and Teas.

They also identified isoflavones, anthraquinones, chalcones and theaflavins (148). In

general, the methods are similar, using methanol for extraction and separation by liquid

chromatography with diode array detector (DAD) and/or mass spectrometric (MS)

detection.

The principal factors that contribute to the efficiency of extraction are: type of solvent,

pH, temperature, number of steps and volume of solvent and particle size in the sample

(165). Different solvent systems have been used for extraction of polyphenols from plant

materials (166). Extraction yield is dependent on the solvent and method of extraction

(167). The extraction method must enable complete extraction of the compounds of

interest and must avoid their chemical modification (168). Water, aqueous mixtures of

ethanol, methanol and acetone are commonly used (169).

51

This research applied methanol as a polar solvent for extraction of polyphenols to

minimize the co-extraction of non-polyphenolic water soluble compounds such as

proteins and carbohydrates. Using liquid nitrogen allows destruction of plant cells and

inactivation of polyphenol oxidase prior to extraction. All samples were immersed in

liquid nitrogen prior to extraction (temperature is -196°C).

4.2.3- Method of LC-MS

As mentioned earlier, a large number of chromatographic methods have been reported for

the determination of polyphenols. This research utilized an optimized methodology,

which has been developed for satisfactory separation of different classes of polyphenols

covering a whole range of retention times (170). As stationary phase a diphenyl column

was chosen with an optimised gradient system comprising water and acetonitrile as the

mobile phase. The concentration of acetonitrile changed from 15% to 75% over 45

minutes. Solvent (A) was water/formic acid (1000:0.05 v/v) and solvent (B) was

acetonitrile. Solvents were delivered at a total flow rate of 500 μl/min. The concentration

ratios for (A) : (B) varied linearly from 85:15 at 0 min, to 75:25 at 10 min, to 55:45 at 20

min, to 35:65 at 30 min, to 25:75 at 40 min, to 25:75 at 45 min followed by 10min

isocratic and a return to 15% B at 55 min. The efficacy of the LC-MS method was

validated using a mixture of standard compounds (200 mg/l) including 5-caffeoylquinic

acid, luteolin, rutin, kaempferol, quercetin, epicatechin, epigallocatechin gallate, cynarin,

apigenin, gallocatechin and epigallocatechin (the two later compounds are the hydrolysis

products of epigallocatechin gallate). The compounds were well separated over 45

minutes chromatographic run and identified in MS spectra which indicated that the LC-

MS method is efficient for the separation of low polar to high polar polyphenols in low

concentrations (figure 22).

52

Figure 22- Base peak chromatogram for the mixture of standard compounds in negative

ion mode, representing the separation of the compounds over 45 minutes.

4.2.4- Polyphenols previously identified in fruits and vegetables

The peaks of the MS spectra were assigned according to their m/z values and

fragmentation patterns in tandem MS and compared with the structural information of the

most commonly occurring food polyphenols as reported by Sakakibara et al.(148) (Table

4). The assigned compounds were confirmed with high resolution MS spectra. Structural

formulas are given in table 4 and 5 along with numbering.

53

Table 4– List of the most commonly occurring dietary phenolic compounds including the

molecuar formulas, theoretical masses and m/z values in positive and negative ion modes

of the compounds (148)

compound

No. Compound Name Molecular formula M [M+H] [M-H]

1 o-hydroxybenzoic acid C7H6O3 138.031 139.038 137.023

2 m-hydroxybenzoic acid C7H6O3 138.031 139.038 137.023

3 P-hydroxybenzoic acid C7H6O3 138.031 139.038 137.023

4 sesamol C7H6O3 138.031 139.038 137.023

5 ß-resorcylic acid C7H6O4 154.026 155.033 153.019

6 protocatechuic acid C7H6O4 154.026 155.033 153.019

7 o-coumaric acid C9H8O3 164.047 165.054 163.039

8 m-coumaric acid C9H8O3 164.047 165.054 163.039

9 p-coumaric acid C9H8O3 164.047 165.054 163.039

10 vanillic acid C8H8O4 168.039 169.046 167.032

11 gallic acid C7H6O5 170.021 171.028 169.013

12 caffeic acid C9H8O4 180.042 181.049 179.035

13 ferulic acid C10H10O4 194.057 195.064 193.049

14 isoferulic acid C10H10O4 194.057 195.064 193.049

15 caffeine C8H10N4O2 194.079 195.086 193.072

16 anthraquinone C14H8O2 208.052 209.059 207.045

17 chalcone C15H12O 208.088 209.095 207.081

18 flavone C15H10O2 222.068 223.075 221.061

19 isoflavone C15H10O2 222.068 223.075 221.061

20 flavol or flavonol C15H10O3 238.063 239.069 237.056

21 alizarin C14H8O4 240.042 241.049 239.035

22 7,4'-dihydroxyflavone C15H10O4 254.057 255.065 253.049

23 chrysin C15H10O4 254.057 255.065 253.049

24 daidzein C15H10O4 254.057 255.065 253.049

25 purpurin C14H8O5 256.037 257.044 255.029

26 isoliquiritigenin C15H12O4 256.073 257.081 255.066

27 formononetin C16H12O4 268.074 269.081 267.067

28 7,3',4'-trihydroxyflavone C15H10O5 270.052 271.059 269.045

29 baicalein C15H10O5 270.052 271.059 269.045

30 apigenin C15H10O5 270.052 271.059 269.045

31 emodin C15H10O5 270.052 271.059 269.045

32 galangin C15H10O5 270.053 271.061 269.046

33 genistein C15H10O5 270.053 271.061 269.046

34 pelargonidin C15H11O5+ 271.059 272.066 270.052

35 naringenin C15H12O5 272.068 273.075 271.061

36 butein C15H12O5 272.068 273.075 271.061

37 phloretin C15H14O5 274.084 275.091 273.077

38 rhein C15H8O6 284.032 285.039 283.025

39 genkwanin C16H12O5 284.068 285.075 283.061

54

40 biochanin A C16H12O5 284.068 285.075 283.061

41 luteolin C15H10O6 286.047 287.054 285.040

42 datiscetin C15H10O6 286.047 287.054 285.040

43 kaempferol C15H10O6 286.047 287.054 285.040

44 cyanidin C15H11O6+ 287.055 288.062 286.048

45 eriodictyol C15H12O6 288.063 289.070 287.056

46 (+)-catechin C15H14O6 290.079 291.086 289.072

47 (-)-epicatechin C15H14O6 290.079 291.086 289.072

48 diosmetin C16H12O6 300.063 301.070 299.056

49 chrysoeriol C16H12O6 300.063 301.070 299.056

50 ellagic acid C14H6O8 302.006 303.013 300.999

51 morin C15H10O7 302.042 303.049 301.035

52 quercetin C15H10O7 302.042 303.049 301.035

53 robinetin C15H10O7 302.042 303.049 301.035

54 hesperetin C16H14O6 302.079 303.086 301.072

55 delphinidin C15H11O7+ 303.049 304.056 302.042

56 (+)-taxifolin C15H12O7 304.058 305.065 303.051

57 (-)-gallocatechin C15H14O7 306.073 307.080 305.066

58 (-)-epigallocatechin C15H14O7 306.073 307.080 305.066

59 isorhamnetin C16H12O7 316.058 317.065 315.051

60 tamarixetin C16H12O7 316.058 317.065 315.051

61 quercetagetin C15H10O8 318.037 319.044 317.030

62 myricetin C15H10O8 318.037 319.044 317.030

63 5,7-dihydroxy-3',4',5'-trimethoxyflavone C18H16O7 344.089 345.096 343.082

64 5-caffeoylquinic acid C16H18O9 354.095 355.102 353.088

65 tangeretin C20H20O7 372.120 373.127 371.113

66 sinensetin C20H20O7 372.120 373.127 371.113

67

daidzein-7-O-glucoside

(daidzin) C21H20O9 416.110 417.117 415.103

68 daidzein-8-C-glucoside (puerarin) C21H20O9 416.111 417.118 415.104

69 gardenin A C21H22O9 418.126 419.133 417.119

70 apigenin-6-C-glucoside C21H20O10 432.105 433.112 431.098

71 apigenin-8-C-glucoside (vitexin) C21H20O10 432.106 433.113 431.099

72 apigenin-7-O-glucoside C21H20O10 432.106 433.113 431.099

73 vitexin-2''-O-rhamnoside C21H20O10 432.106 433.113 431.099

74 genistein-7-O-glucoside C21H20O10 432.106 433.113 431.099

75 (-)-epicatechin gallate C22H18O10 442.090 443.097 441.083

76 (-)-catechin gallate C22H18O10 442.090 443.097 441.083

77 baicalein-7-O-glucuronide (baicalin) C21H18O11 446.084 447.091 445.077

78 luteolin-8-C-glucoside C21H20O11 448.100 449.107 447.093

79 luteolin-6-C-glucoside C21H20O11 448.101 449.108 447.094

80 luteolin-7-O-glucoside C21H20O11 448.101 449.108 447.094

81 luteolin-4'-O-glucoside C21H20O11 448.101 449.108 447.094

82 kaempferol-3-O-glucoside C21H20O11 448.101 449.108 447.094

55

(astragalin)

83 quercetin-3-O-rhamnoside (quercitrin) C21H20O11 448.101 449.108 447.094

84 (-)-epigallocatechin gallate C22H18O11 458.085 459.092 457.078

85 (-)-gallocatechin gallate C22H18O11 458.085 459.092 457.078

86 quercetin-3-O-glucoside (isoquercetin) C21H20O12 464.095 465.102 463.088

87 myricetin-3-O-rhamnoside(Myricitin) C21H20O12 464.095 465.102 463.088

88 theaflavin C29H24O12 564.127 565.134 563.120

89 naringenin-7-O-rutinoside (naringin) C27H32O14 580.179 581.186 579.172

90 kaempferol-3-O-rutinoside C27H30O15 594.158 595.165 593.151

91 kaempferol-7-O-neohesperidoside C27H30O15 594.158 595.165 593.151

92 cyaniding- 3-O-rutinoside C27H31O15 595.166 596.173 594.159

93 diosmetin-7-O-rhamnoside (diosmin) C28H32O15 608.174 609.181 607.167

94 luteolin-3',7-di-O-glucoside C27H30O16 610.153 611.160 609.146

95 quercetin-3-O-rutinoside (rutin) C27H30O16 610.153 611.160 609.146

96 hesperetin-7-O-rutinoside (hesperidin) C28H34O15 610.189 611.196 609.182

97 theaflavin-3-gallate C36H28O16 716.138 717.145 715.131

98 theaflavin-3'-gallate C36H28O16 716.138 717.145 715.131

99 theaflavin-3,3'-digallate C43H32O20 868.149 869.156 867.142

Table 5- The structural information of the most commonly occurring food polyphenols

(148)

(1)- o-hydroxybenzoic acid

(2)- m-hydroxybenzoic acid

(3)- p-hydroxybenzoic acid

(4)- sesamol

(5)- ß-resorcylic acid

(6)- protocatechuic acid

56

(7)- o-coumaric acid

(8)- m-coumaric acid

(9)- p-coumaric acid

(10)- vanillic acid

(11)- gallic acid

(12)- caffeic acid

(13)- ferulic acid

(14)- isoferulic acid

(15)- caffeine

(16)- anthraquinone

(17)- chalcone

(18)- flavone

(19)- isoflavone

(20)- flavonol

57

(21)- alizarin

(22)- 7,4’-dihydroxyflavone

(23)- chrysin

(24)- daidzein

(25)- purpurin

(26)- isoliquiritigenin

(27)-formononetin

(28)- 7,3’,4’-trihydroxyflavone

(29)- baicalein

(30)- apigenin

(31)- emodin

(32)- galangin

58

(33)- genistein

(34)- pelargonidin

(35)- naringenin

(36)- butein

(37)- phloretin

(38)- rhein

(39)-genkwanin

O

OO

CH3

HO

OH

(40)- biochanin A

(41)- luteolin

(42)- datiscetin

59

(43)- kaempferol

(44)- cyanidin

(45)- eriodictyol

(46)- (+)-catechin

(47)- (-)-epicatechin

(48)- diosmetin

(49)- chrysoeriol

(50)- ellagic acid

60

(51)- morin

(52)- quercetin

(53)- robinetin

(54)- hesperetin

(55)- delphinidin

(56)- (+)-taxifolin

(57)- (-)-gallocatechin

(58)- (-)-epigallocatechin

(59)- isorhamnetin

(60)- tamarixetin

61

(61)- quercetagetin

(62)- myricetin

(63)- 5,7-dihydroxy-3’,4’,5’-trimethoxyflavone

(64)- 5-caffeoylquinic acid

(65)- tangeretin

(66)- sinensetin

(67)- daidzein-7-O-glucoside (daidzin)

(68)- daidzein-8-C-glucoside (puerarin)

62

(69)- gardenin A

(70)- apigenin-6-C-glucoside

(71)- apigenin-8-C-glucoside (vitexin)

(72)- apigenin-7-O-glucoside

(73)- vitexin-2”-O-rhamnoside

(74)- genistein-7-O-glucoside

(75)- (-)-epicatechin gallate

(76)- (-)-catechin gallate

63

(77)- baicalein-7-O-glucuronide (baicalin)

(78)- luteolin-8-C-glucoside

(79)- luteolin-6-C-glucoside

(80)- luteolin-7-O-glucoside

(81)- luteolin-4’-O-glucoside

(82)- kaempferol-3-O-glucoside

(83)- quercetin-3-O-rhamnoside (quercetrin)

(84)-(-)-epigallocatechin gallate

64

(85)- (-)-gallocatechin gallate

(86)- quercetin-3-O-glucoside (isoquercetin)

(87)- myricetin-3-O-rhamnoside (myricitin)

(88)- theaflavin

(89)- naringenin-7-O-rutinoside

(90)- kaempferol-3-O-rutinoside

(91)- kaempferol-7-O-neohesperidoside

(92)- cyanidin-3-O-rutinoside

65

(93)- diosmetin-7-O-rhamnoside(diosmin)

(94)- luteolin-3’,7-di-O-glucoside

(95)- quercetin-3-O-rutinoside (rutin)

(96)- hesperetin-7-O-rutinoside (hesperidin)

(97)- theaflavin-3-gallate

(99)- theaflavin-3,3’-digallate

66

(98)- theaflavin-3’-gallate

4.3- General considerations in natural product analysis

The aim of natural product analysis is to identify naturally occurring compounds from

natural sources and unambigiously elucidate their chemical structre. Traditionally, natural

product chemists have used isolation and purification strategies followed by a full

spectroscopic analysis of the purified material including NMR-, IR-, UV-VIS-

spectroscopy, mass spectrometry, elemental analysis and other techniques such as X-ray

single crystal diffractometry or chirooptical methods. Such a full spectroscopic

characterization results in an unambiguous assignment of a chemical structure and must

be considered as the gold standard of natural product elucidation.

However, this approach suffers from a series of the following disadvantages:

1. The method requires large amounts of material (in the mg range for NMR analysis)

and is therefore limited to major secondary metabolites.

2. Analysis of mixtures is difficult and frequently not possible due to problems in

spectroscopic signal assignments.

3. The method is very labour and cost intensive.

4. Only a small sample throughput is possible.

5. Natural sources frequently produce hundreds or even thousands of different

compounds, which cannot be separated by conventional purification methods. Hence no

purification and subsequent structure elucidation is possible.

67

6. Intensive purification and work-up procedure frequently lead to decomposition of

sensitive materials (171).

In order to circumvent these problems, liquid chromatography coupled to mass

spectrometry (LC-MS) has evolved as a viable alternative method to traditional natural

product chemistry. Within the last two decades, mass spectrometry has developed into

one of the most powerful techniques in chemical analysis (172). While until the 1990s

mass spectrometry was limited to the analysis of volatile compounds with low molecular

weight that were easy to ionize by electron ionization (EI) or chemical ionization (CI)

methods and exclusively yielded spectra dominated by fragment ions, the development of

soft ionization techniques by Fenn and Tanaka has dramatically changed the picture

(173,174). With soft ionization techniques, it is possible to ionize almost any analyte

irrespective of its volatility and molecular weight using either Matrix-assisted laser

desorption/ionization (MALDI) or electrospray ionization (ESI). In both methods almost

exclusively intact molecular ions are produced resulting from protonation or

deprotonation of the analyte that facilitate spectra interpretation. Furthermore, following

the introduction of soft ionization techniques, a dramatic surge in the development of

novel mass detectors has occurred in the last ten years. All aspects of performance of

mass detectors have been dramatically improved including mass resolution, mass

accuracy or the ability to produce fragment spectra (174). Finally, MS detectors can be

routinely coupled to chromatographic equipment and other detector systems, therefore

providing multi dimensional information in a single chromatographic run (175).

In applying these developments to natural product analysis, LC-MS techniques offer the

following advantages over traditional natural product analysis (176, 177):

1. Small sample amounts are required (typically sensitivity of modern mass

detectors is routinely in the fmol region).

2. Minor as well as major components can be analysed jointly due to a large

dynamic range of MS detectors.

68

3. Complex mixtures with hundreds of compounds (typical for food material) can be

analysed.

4. The method can be automated and a large sample throughput is possible.

5. The method is not very labour intensive and, apart from investment costs into

instrumentation cost efficient.

6. No to little sample purification is required to obtain data on crude extracts

containing even sensitive material.

However, a few disadvantages of the method must be highlighted as well, which include

1. While sample preparation and measurement is fast and efficient and not labour

intensive, data interpretation still is.

2. No comprehensive understanding of structure assignment based solely on MS

data exists. Only for selected classes of compounds definite rules for

fragmentation exist, that allow an unambiguous structure elucidation, providing a

confidence level comparable to NMR analysis. This limitation is of course due to

the novelty of the methods and future work will show whether MS can be

developed into a competitive structure elucidation tool.

3. No standardized MS techniques exist, which make direct comparison of spectral

data or the use of databases often difficult. For example, tandem MS data can be

obtained from ion trap or triple quadrupol instruments yielding significantly

different fragment spectra.

4. For LC-MS data no comprehensive databases exist.

Due to their overwhelming advantages, LC-MS based methods form a perfect tool for

the investigation of natural products in particular in food. Its use can be broadly

classified into two areas. Firstly, the identification of compounds already described in

the literature and secondly, the screening and subsequent structure elucidation of

novel compounds not yet described (178). Both aspects require a more in depth

discussion.

69

4.3.1- Identification of known compounds

Typically the standard used by any chemist to positively identify a known compound

already described in the chemical literature, involves the application of two to three

independent spectroscopic methods. If the spectral data measured are identical to those

reported in the literature or to an authentic reference material, confirmation is possible.

Ideally, the methods used are ―rich in information‖ and provide a unique fingerprint of

the compound analysed. E.g. NMR spectra contain more unique information if compared

to a melting point or a UV-VIS spectrum. In LC-MS experiments carried out here, the

HPLC instrument is coupled to a UV-VIS detector, a high resolution mass spectrometer

(HR-MS) providing molecular formula information and an ion trap mass spectrometer

providing fragmentation data (tandem-MS). Hence for each compounds within a crude

mixture retention times, UV-VIS spectra, HR-MS and tandem MS data are obtained. This

comprises a total of at least four independent techniques and allows for unambiguous

structure confirmation for known compounds.

HR-MS data measured should adhere to the standards of the chemical literature

(177,178). Here most scientific journals require that the experimental mass and

theoretical mass should not be separated by an error larger than 5 ppm.

Define error

Error is defined by the equation below:

Error [ppm] = [ (Experimental m/z – theoretical m/z) / theoretical m/z] * 106

For identification of known compounds the following flow chart of steps was employed

in this work:

1. A list of likely structures to be present was prepared based on previous literature on

the plant under investigation.

70

2. A list of molecular formulas and literature on tandem MS data, retention times and

UV-VIS data was prepared.

3. The LC-MS chromatogram was searched for the molecular formulas suggested by

creating extracted ion chromatograms (EICs) for the m/z value of the compound

under investigation. The EIC provides chromatographic peaks corresponding to the

mass sought.

4. All peaks in the EICs are investigated and the HR-MS m/z value determined. This

value is subsequently compared to molecular formula suggestions generated by the

software. If a molecular formula suggestion below an error of 5 ppm agrees with the

structure believed to be present the next step 5 is carried out.

5. Experimental retention times and UV-VIS data are compared to literature values or

values for authentic reference compounds. If agreement is there move to step 6. It

should be noted that the UV-VIS detector is by an order of magnitude of 100 less

sensitive if compared to the MS detector, so that at times good MS data are not

accompanied and supported by good quality UV-VIS data. Furthermore MS data

show always good resolution for co-eluting species, whereas this resolution is not

observed in UV-VIS data, where co-eluting analytes are jointly detected. These two

points have been accommodated in the data interpretation.

6. Tandem MS data are inspected. If the tandem MS data are in agreement with

literature data or with data from authentic reference compounds the structure is finally

confirmed. Since tandem MS data published are, however, relatively rare and at times

difficult to compare due to differences in instrumentation, a structure was confirmed

if the majority of intense fragments observed are in line with structure proposed.

4.3.2- Identification of unknown compounds

While the identification of known compounds using direct spectral comparison is usually

quite straightforward, identification of unknown compounds by LC-MS must be

considered a scientific challenge and a non-routine exercise.

71

Again in an LC-MS experiments carried out here, the HPLC instrument is coupled to a

UV-VIS detector, a high resolution mass spectrometer (HR-MS) providing molecular

formula information and an ion trap mass spectrometer providing fragmentation data

(tandem-MS). Based on these data, structure elucidation must be carried out and the

individual steps are discussed in detail.

HR-MS

For known compounds HR-MS provides a relatively straightforward confirmation of

molecular formulas. From the experimental mass determined a software routine

calculates a list of all possible molecular formula within a specified error range. If the

expected molecular formula is present ideally with an error below 5 ppm molecular

formula confirmation has been successfully achieved.

For unknown compounds the situation is dramatically more complex with three levels of

complex problem solving and critical evaluation involved. The first level is defined by

the quality of the measurement, the second by the limitation and restriction of the

software used for molecular formula calculation and the third by prioritization and choice

of the correct molecular formula. These are discussed in the following:

4.3.3- Quality of HR-MS measurement

In order to obtain a reliable molecular formula from HR-MS measurements, one must

assume a high quality experiment and a reliable experimental m/z value on which to base

all further considerations. The instrument used in these experiments is a microTOF Focus

instrument with a specified mass resolution of 17000 at m/z 300 and specified mass error

of 4 ppm. That means that ideally 99 % of experimentally determined m/z values provide

an error below 4 ppm.

However, this is an ideal scenario and in reality, a series of parameters influence the

quality of the measurement. These can be roughly divided into several groups including

72

external parameters, measurement parameters and software interpretation parameters.

The following parameters, given in order of their importance, can negatively influence a

HR-MS measurement and must be critically evaluated before embarking on a molecular

formula assignment.

1. Quality of the calibration: The instrument itself is regularly calibrated (once a

day, to ensure performance within specified 4 ppm range) and prior to each

chromatographic run using a calibration solution. The calibrant used here is

composed from 0.1 M aqueous sodium formate producing a series of 10-15

formate cluster ions used for calibration in a mass range from m/z 100-1200.

Firstly each experimental mass converted into a molecular formula must always

lie within the calibrant points. Using the calibrant data points a calibration curve

is produced and applied to the complete LC-MS data set. For TOF data, typically

enhanced quadratic calibration is employed since time of flight and m/z are not

strictly linear over the full mass range with deviations from linearity observed in

the low mass range (m/z 100-250). Therefore, alternative calibration modes e.g.

HPC is recommended for low molecular weight compounds. Within the

calibration process, typically an enhanced quadratic calibration curve is fitted to

all data points and a standard deviation calculated indicating the error limit for 99

% of all measured m/z values. This error limit should be as low as possible and in

order to achieve a reduction of this value calibrant points displaying a larger error

are typically removed from the calibration curve to increase its quality. For the

quality of the measurements and thus a reliable molecular formula assignment it

matters which points are removed here. E.g. if an ion at m/z 700 is measured

removal of calibrant data points close to this value will have a negative impact on

the mass accuracy, whereas removal of calibrant data points far away from this

mass at the high or low mass range will have little impact. Hence careful

calibration is required to achieve reliable results.

2. External temperature: Our TOF instrument measures the time of flight of an ion

through a 3 m long flight tube. An accurate knowledge on the precise length of

the tube is paramount in order to obtain a HR-MS value based on the time of

73

flight measurement. This flight tube is subject to thermal expansion and

contraction with changing external temperature. Although the instrument is

housed in an air conditioned environment a stable temperature is a prerequisite for

high quality HR-MS measurements. Any one person entering the instrument room

causes due to body heat an increase of temperature of 0.5°C within 20 minutes,

any two persons 1°C. Such a temperature change results ij a thermal expansion of

the flight tube of around 2µm, which equates to a mass error of 5 ppm rendering

the measurement irrelevant. Consequently HR-MS measurements should be

carried out in a stable temperature ideally overnight in the absence of interfering

personnel.

3. Concentration of analyte: If a HR-MS measurement of an analyte is carried at

high concentrations the MS detector will become saturated similar to a UV-VIS

photomultiplier, typically above an absolute intensity of 106. This saturation

results in a failure of the instrument to accurately measure the apex of the ion

signal. However, the software will calculate the apex from the existing data

resulting in significant mass errors. Therefore manual inspection of signal

intensity is required for intense peaks. The problem can in general be

circumvented in LC-MS runs by carrying out HR-MS measurements in the flanks

of a chromatographic peak, where lower concentrations are present, rather that at

its centre.

4. Overlapping isobaric ions: In natural product analysis frequently hundreds or

thousands of analytes are present frequently displaying similar masses (isobaric

ions). If these ions co-elute chromatographically unsymmetric mass signals result.

HR-MS software includes all data points as specified by the user in this

unsymmetrical signal to calculate the apex of the peak again resulting in an

increased mass error. Therefore visual inspection of the shape of the signal is

required to ascertain that a symmetrical peak shape exists. For samples with

frequently occurring isobaric ions a reduction of data points per signal results in

an improved result.

5. Averaging of spectra: Experimental HR-MS values can be obtained from single

point spectra or averaged spectra. Typically 50 spectra are acquired per second.

74

Varying spectra averaging can result in mass error variation of around +/- 2 ppm,

which should be taken into account when computing molecular formulas.

4.3.4- Calculation of molecular formulas

From an experimental m/z value determined in a HR-MS measurement molecular

formulas are calculated using dedicated software routines. Firstly it is worth pointing out

that most webbased software programmes are inadequate and erroneous, necessitating in

the use of reliable instrument manufacturer software packages.

Within such molecular formula computations a series of parameters are fed into the

programme to carry out the task, based on specialized algorithms.

As a first step, the charge state of the ion must be defined by determination of the spacing

between the molecular ion and its mono-isotopic ions.

From the experimental m/z value a list of possible molecular formulas within a specified

error limit are generated and the user needs to choose one of the suggested molecular

formulas. The error limit is specified by the instrument performance, the journal

requirements and the considerations noted above. Typically a first search will involve a 5

ppm error limit and if no suitable molecular formula is found this is extended to 10 ppm.

The most important parameter is the elements present. Typically with increasing numbers

of elements present the number of molecular formula suggestions increases

exponentially. Therefore a detailed knowledge of the sample and its likely components is

highly useful. For polyphenol analysis CHO only is sufficient as elemental compositions.

Elemental analysis data often provide useful suggestions with respect to elements that

need inclusion. If no suitable molecular formulas are suggested inclusion of additional

elements is required.

Next to the elements included a series of parameters allow the exclusion of chemical

nonsensical molecular formulas. While chemists have a good knowledge of the rules of

75

valency and the chemistry of the samples computers do not. For a chemist, identification

of non-sensical formulas is straightforward, whereas defining these in a software routine

is more difficult. Some of these parameters are highly useful. For example a minimum

and maximum H/C ratio should be defined. To illustrate this as an example an ion with

m/z 28 can result from sensical CO, C2H4 or N2 fragments but not from CH16 with a

nonsensical H/C ratio. Furthermore double bond equivalents (DBEs) can be restricted

with organic compounds displaying a maximum of four DBEs per six carbons (in an

aromatic ring). Furthermore from the m/z value a range for sensical carbon numbers in an

organic natural product can be identified and all nonsensical carbon numbers excluded

(e.g.C3H6N34O51). Similar elemental composition ratio restrictions apply to any

combination of elements e.g. N, O, P, S etc.

4.3.5- Choice of correct molecular formula

Taking all these considerations above into account a list of molecular formulas result,

which require prioritsation and choice of the likely correct molecular formula. The

process has been summarized and formalized by Fiehn et al. providing rules for choice of

molecular formulas known as ―The seven Golden Rules‖. These can be summarized as

follows (179):

1. Apply heuristic restrictions of number of elements during molecular formula

generation (see arguments above).

2. Perform Lewis and Senior check. Chemical valencies are defined by Lewis and

Senior rules and any molecular formula suggested must adhere to these rules

(179). A computational check of these rules is commonly not included in

molecular formula software and must be performed manually by the chemist

interpreting the data or can be performed using specialized software such as

MOLGEN .

3. Perform isotope pattern filter. For any compound a mass spectrum can be

simulated with a theoretical isotope pattern generated. Each molecular formula

76

calculated will contain a set number of elements with a known distribution of

naturally occurring isotopes (e.g. 13

C, 2H,

14N etc) and hence will lead to a defined

ratio of molecular ion and mono-isotopic ions.. The experimental spectrum can

be compared to the theoretical spectrum and the similarity expressed as a

numerical parameter. This parameter is termed mΣ and calculated automatically

for each molecular formula. As a rule of thumb it can be assumed that the lower

mΣ the better (ideally below 15).

4. Perform H/C ratio check (see argument above).

5. Perform NOPS ratio check.

6. Perform heuristic HONPS probability check: A high number of heteroatoms will

pass the tests above, however such a high ration is not probable. Statistic numbers

exist defining probabilities to find a certain heteroatom ratio in a synthetic or

naturally occurring compound.

7. Rule seven only applies to GC-MS measurements of derivatives.

Fiehn´s rules (179) define a good framework for molecular formula generation and

selection. In the last section of this thesis novel approaches to interpreting HR-MS

data from natural products are suggested, implemented and discussed based on

petrolomics style data interpretation strategies in particular van Krevelen analysis.

4.3.6- Tandem MS data interpretation for unknown compounds

Before embarking on a discussion on spectra and data interpretation a short overview

on the physical basis of tandem MS is given. In tandem MS intact molecular ions

generated by ESI or other ionization methods are accelerated by application of an

electric potential in a collision cell in the presence of a neutral inert gas, most

commonly helium. The accelerated ions collide with the gas and the kinetic energy

from the collision is transferred to the molecular ion and redistributed into the normal

modes of vibration of the molecule (180,181,182). Energy accumulates in these

normal modes of vibration unequally along the molecule until one mode contains

77

sufficient energy that bond dissociation occurs. Experimental evidence supporting

this process is given for example by the observation that more collision energy is

required to fragment larger molecules with increased number of normal modes of

vibration. The process is known as collision induced dissociation (CID) and best

described by the Rice Rampsberger Kassel Marcus (RRKM) theory of unimolecular

gas phase reactions (182, 183). Currently there exists no suitable theoretical

framework to predict the normal modes of vibration, into which energy is transferred

and hence no reliable predictive model to forecast fragmentations.

Using different instruments the nature of the energy is transfer is quite different. In an

ion trap instrument the collision energy or acceleration voltage employed is usually

ramped starting with a low value until full fragmentation is observed. This leads to a

mild scission of bonds with only few fragments observed. Further fragment ions can

be obtained by repetition of the process in higher order MSn spectra. In contrast in a

triple quadrupole collision cell a high voltage is applied leading to excess energy

transferred and multiple fragment ions generated (184). This can be compared to

cutting window glass with a glass cutter or a sledge hammer.

Despite the challenge existing in understanding and predicting fragmentation

reactions there are certain rules and considerations, which always apply formulated

here :

1. Any fragmentation reaction is an exothermic process. Following the Hammond

postulate this means, that any fragmentation reaction possesses a late transition

state and the transition state is product like.

2. Following from point 1 the energetics and the structure of the products of

fragmentation resemble the transition state. Hence it can be concluded that the

most stable products will be formed. In any fragmentation reaction the products

are one or several charged ions and one or several neutral fragments.

3. The gas phase chemistry of ESI tandem MS is based on even electron species

(unlike odd electron chemistry in EI or CI ionization). From solution chemistry

the stability of such even electron charged and neutral species is well established

78

and all rules of solution state stability can be critically applied, if assuming the

absence of a stabilizing solvent, to rationalize fragmentation reactions.

4. Since electronegative heteroatoms with free electron pairs are able to stabilize

positive or negative charges, fragmentation will usually occur at these sites (e.g.

ester, amide bonds, ether bonds etc).

5. In any fragmentation reaction a charged fragment ion and a neutral fragment

species are generated. In all cases one of those is better able to stabilize a charge

and will hence carry the charge (either positive or negative). Chemical intuition

allows prediction of this moiety.

6. Fragmentation of single single bonds is preferred over fragmentations of several

single bonds or multiple bonds.

7. Fragmentations producing unstable species (in solution chemistry these equate to

reaction intermediates) are unlikely. For example the breakage of an aromatic C-

O bond is unlikely since it would produce an aryl cation.

8. In tandem MS experiments the fragmentation chemistry of identical ions is

always identical. For example an ion generated from 5-caffeoylquinic acid in MS

has the same structure (is identical) to an ion generated from 3,5-dicaffeoylquinic

acid in MS2 with the 3-substituent lost first. Hence structural elements and

moieties can be readily identified by comparing higher order MSn spectra of more

complex structures to lower order MSn spectra of reference compounds. This is a

unique advantages of MS not found for any other spectroscopic technique.

9. For selected families of compounds reliable information on fragmentation

preferences exist. A prime example is the work of Clifford and Kuhnert on

chlorogenic acids (185). Here tandem-MS has reached a level of reliability and

sophistication, at which it is superior to NMR spectroscopy in structure

elucidation. Other examples where predictive and reliable knowledge of

fragmentation preferences exist include the fragmentation of glycosides or

peptides. For example O- and C-glycosides can be readily distinguished using

tandem MS. For O-glycosides the anomeric O-C bond is always cleaved resulting

in a neutral carbohydrate loss, whereas for C-glycosides ring fission within the

carbohydrate ring occurs with neutral losses of multiples of 30 (CH2O). In the

79

context of this work it is worth noting that fragmentation preferences for

flavanoid compounds do not exist. Fragmentation patterns reported in the

literature must be considered random and unsystematic.

10. All major fragment ions observed in a tandem mass spectrum must comply with

the proposed structure. This means that all major fragments generated must be

explained within the framework of mechanistic chemistry in order to confirm a

structure. If this is not possible the proposed structure is wrong.

Using a knowledge based approach

The task of interpreting tandem MS data should ideally lead to the suggestion of a

chemical structure. Such structure assignment starts with HR-MS data from which one or

several molecular formula suggestions are obtained that require further probing.

For this purpose one or several structures must be proposed from a molecular formula.

For natural product chemistry knowledge about structures made by nature allows this

process with molecular formulas suggesting according to their elemental ratio a class of

compound.

A good starting point for such an investigation uses a combined knowledge of likely

structures present combined with knowledge on typical fragmentation mechanisms. For

example ester bonds or glycosidic bonds are readily cleaved in tandem MS. Hence data

can be searched for fragment ions or neutral losses of commonly encountered ester

groups or carbohydrates. Extracted ion chromatograms in all MSn mode or neutral loss

chromatograms allow the identification of such moieties e.g. m/z 162 (hexose or caffeic

acid), 152 (gallate), 92 (succinic acid), 146 (deoxyhexose) or 132 (pentose).

Identification of such moieties already allows structure assignment of at least one half of

the molecule under investigation. Further targeted MSn experiments on the remaining

moiety allows accumulation of further investigation. These spectra can be compared to

reference spectra of known compounds and fragments facilitating structure elucidation.

80

A second approach involves the comparison of MSn spectra with reference compounds.

As argued above if an ion of a certain m/z value is observed in a fragment spectra it is

worth comparing its fragment spectra to those of reference compounds with the same m/z

value. Identical spectra here mean identical chemical moieties.

For unusual fragment ions observed it is worth accumulating HR-MS data for the

fragments. In our laboratory this can be achieved by in source dissociation experiments

(ISCID), where ions are accelerated prior to entry of the flight tube.

If fragments observed can be rationalized within the framework of the structure

suggested a tentative suggestion of a chemical structure can be made. If fragmentation

patterns for a class of compounds are understood in detail this structure suggestion

provides a reliable structure that can be proposed with confidence. In other cases further

spectroscopic analysis or the analysis of reference material is required for complete

structure elucidation.

4.4- Investigated polyphenols in the samples

The polyphenols assigned according to the m/z values observed in tandem MS

chromatograms and comparison with the fragmentation patterns. All the investigated and

assigned polyphenols in samples based on the information obtained from tandem MS

chromatograms have been compared and confirmed by high resolution MS

chromatograms and smart molecular formula suggestions. The results are discussed in the

following, arranged by the type of fruits and vegetables investigated.

For selected compounds, a detailed discussion on structure assignment is provided to

illustrate the style of structure assignment. All other compounds were identified using the

same approach.

81

4.4.1- Polyphenols in Apple (Malus domestica)

A total of 10 Apple samples from fleshes and peels were investigated including:

sample (1)- Apple peel New Zealand ; Sample (2)- Apple flesh Argentina; sample (3)-

Apple peel Germany; sample (4)- Apple peel Argentina; sample (5)- Apple peel China;

sample (6)- Apple flesh New Zealand; sample (7)- Apple peel Italy; sample (8)- Apple

flesh Germany; sample (9)- Apple flesh China; sample (12)- Apple flesh Italy

Findings on Apple polyphenols are discussed in details in section 4.4.1.1. A few

examples for compound assignments are illustrated in the following (examples 1-4):

Example 1 (5-caffeoylquinic acid 64)

In the tandem MS spectrum of sample 3 (Apple peel from Germany), a peak was

observed at a retention time of 5.2 min. The high resolution mass spectrometrical data

gave an experimental value of the parent ion at m/z 353.0884 in the negative ion mode at

a retention time of 2.3 min. A molecular formula search suggested a molecular formula of

C16H18O9 with an error of 1.6 ppm and a mΣ value of 11.9. The UV-VIS data of this

chromatographic peak revealed a maximum of absorbance at 330 nm. This value is

characteristic for a cinnamate chromophore.

Tandem MS data in the negative ion mode revealed the following fragmentation. In the

MS2 spectrum, a base peak at m/z 190.6 corresponding to a neutral loss of m/z 162 is

observed, which was assigned to a loss of caffeic acid (C9H6O3). MS3 data of the

transition 353 to191 showed a base peak at m/z 108.9 with a further strong fragment at

m/z 172.6. This fragmentation behavior is consistent with the presence of a quinic acid

moiety (see figure 23) and related tandem MS chromatogram (figure 24).

The full set of data is therefore in line with the presence of a mono-caffeoylquinic acid

derivative. Comparison to literature data, in particular to the hierarchial key for

82

regioisomer assignment for 5-caffeoylquinic acid using tandem MS data, allowed

unambiguous identification of this compound as 5-caffeoylquinic acid 64 (figure 23)

(185).

83

Figure 24- (a) Total ion chromatogram in the negative ion mode of sample 3, (b) UV-VIS

spectrum, (c) MS, (d) MS2 and (e) MS

3 spectra of compound 5-caffeoylquinic acid 64

OO

OH

OH

OH

OHHO

HOOC

Mass: 191

Figure 23- 5- caffeoylquinic

acid (C16H18O9, Theoretical

mass : 354.095) ;

Exp. m/z [M-H] : 353.0884

a

b

c

d

e

84

Example 2 (quercetin-3-O-glucoside 86)

In the tandem MS chromatogram of sample 3 (Apple peel from Germany) a peak was


gave an experimental value of the parent ion at m/z 463.0899 in the negative ion mode. A

molecular formula search suggested a molecular formula of C21H19O12 with an error of

3.6 ppm and mΣ value of 17 at a retention time of 9.5 min. The UV-VIS data of this

chromatographic peak revealed a maximum of absorbance at 230 nm. This value is

characteristic for a flavonoid chromophore.

These data suggested tentatively the presence of either quercetin-3-O-glucoside 86 or its

isomer myrecitin-3-O-rhamnoside 87. A close inspection of the characteristic tandem MS

data allows distinction between the two alternative structures.


MS2 spectrum, a base peak at m/z 299.7 corresponding to a neutral loss of m/z 163, which

was assigned to a loss of hexose moiety (C6H10O5) thereby excluding compound

myrecitin-3-O-rhamnoside 87 (figure 25). Further fragments at m/z 378.6, 216.6, 178.7

and 150.7 were observed (see figure 26). The later fragment ion can be rationalized in

terms of a retro Diels-Alder fragmentation, in which two bonds within the C-ring of

quercetin-3-O-glucoside 86 are cleaved.

MS3

data of the transition 463 to 299 showed a base peak at m/z 270.7 with further

fragments at m/z 216.5, 178.6 and 150.7. This fragmentation behavior is consistent with

the presence of a quercetin aglycon.

Hence this compound was tentatively assigned as quercetin-3-O-glucoside 86 with

further supporting evidence from the literature confirming its presence in Apple (186,

187).

85

Figure 26- (a)Total ion chromatogram in the negative ion mode of sample 3,(b) UV-VIS


3 spectra of compound quercetin-3-O-glucoside 86

Figure 25- Structures of the compounds

number quercetin-3-O-glucoside 86,

myricetin-3-O-rhamnoside 87

(C21H20O12,Theoretical mass: 464.095)

Exp. m/z [M-H] : 463.0899

a

b

c

O

OH

OH

O

OH

HO

OH

O OH

OH

OH

H3C

O

OH

HO

OH

O

HO

O

HOH2C

OH

OH

OH

86- quercetin-3-O-glucoside (isoquercetin)

Mass: 163

Mass:312

87- myricetin-3-O-rhamnoside (myricitin)

O

O

c

d

e

86

Example 3 (quercetin 52)



gave an experimental value of the parent ion at m/z 301.0349 in the negative ion mode in

a retention time of 11.4 min. A molecular formula search suggested a molecular formula

of C15H9O7 with an error of 1.5 ppm and a mΣ value of 12.5.

The UV-VIS data of this chromatographic peak revealed a maximum of absorbance at

230 nm. This value is characteristic for a flavonoid chromophore (148).


MS2 spectrum, the base peak at m/z 164.7 is observed which was assigned to a loss of

C7H4O3 (mass: 165) in compounds morin 51 and quercetin 52. Also in MS

2 spectrum, a

further fragment at m/z 137 could be assigned to a loss of C7H5O3 in compound robinetin

53 (figure 27).

MS3 data of the transition 300.8 to 164.7 did not show any base peak or other

fragmentations (figure 28).

Comparison to the literature data allowed the possible identification of the compound as

quercetin 52 (2, 12, 188).

87



3 spectra of compound morin 51, quercetin 52 and

robinetin 53

O

OOH

HO

HO OH

OH

MS2, Mass: 165

Compound 51- morin (C15H10O7 ,

Theoretical mass: 302.042)

O

OOH

HO

OH

OH

OH

MS2, Mass: 165

Compound 52- quercetin (C15H10O7

, Theoretical mass: 302.042)

O

O

HO

OH

OH

OH

OHMS2, Mass: 137

Compound 53- robinetin (C15H10O7

,Theoretical mass: 302.042

Exp. m/z [M-H]: 301.0349

Figure 27-structure of compounds

morin 51, quercetin 52 and robinetin 53

a

b

c

d

e

87

Example 4 ((+)-catechin 46 and (-)-epicatechin 47)



gave an experimental value of the parent ion at m/z 289.0713 in negative ion mode at a

retention time of 5.4 minutes. A molecular formula search suggested a molecular formula

of C15H13O6 with an error of 1.5 ppm and mΣ value of 3.8.

Due to the reduced sensitivity of the UV detector if compared to LC-MS detector, no

reliable UV-VIS data could be obtained for this peak.


MS2 spectrum, a base peak at m/z 244.7 corresponding to a neutral loss of m/z 44 is

observed, which was assigned to a loss of C2H4O. Further fragments at m/z 205, 270.7

and 125 were observed.

MS3 data of the transition 289 to 244.7 showed a base peak at m/z 202.7 with further

fragments at m/z 160.7, 174.7, 226.7 and 186.7. The fragmentation at m/z 186.7 is

corresponding for the neutral loss of m/z 58 which could be assigned to a loss of C2(OH)2

(see figure 29, related tandem MS chromatogram (figure 30)).

According to the literature data, the pair of diastereoisomers (+)-catechin 46 and (-)-

epicatechin 47 cannot be distinguished on the basis of their fragmentation pattern.

However (+)-catechin 46 and (-)-epicatechin 47 show very distinct retention times with

(+)-catechin 46 eluting earlier on reverse phase packing (189). Comparison to the

literature data allowed identification of this compound as either (+)-catechin 46 or (-)-

epicatechin 47 (189). Refering to the base peak chromatogram of the mixture of standard

compounds (figure 22), the compound was assigned as (-)-epicatechin 47 due to the

retention time of the peak at 8 minutes.

88

Error!

88



3 spectra of compound (-)-epicatechin 47

O

OH

H

HO

OH

HO

OHMS3, Mass: 58

MS2, Mass: 44

Figure 29- compound (+)-catechin 46

(C15H14O6, Theoretical mass : 290.079)

Exp. m/z [M-H]: 289.0713

a

b

c

d

e

89

4.4.1.1-Findings on investigated polyphenols in Apple samples:

In Apple samples the following compounds listed in table 6, were identified according to

the m/z values observed in tandem MS chromatograms and comparison with the

fragmentation patterns of the most commonly occuring dietary polyphenols as reported

by Sakakibara (148) .

90

Table 6– Assigned compounds in Apple samples

Compound

number

Compound Name

Peel

Samples

Flesh

Samples

Sample number

26 isoliquiritigenin 3, 7 6

35 naringenin 1

37 phloretin 2

39 genkwanin 3 6

46 (+)-catechin 4, 5 8

47 (-)-epicatechin 3

48 diosmetin 3, 7, 1, 4, 5 8, 6, 2

49 chrysoeriol 3, 7, 1, 4, 5 8, 6, 2

52 quercetin 3

53 robinetin 3

55 delphinidin 3, 7, 4, 5,1 8, 2

64 5-caffeoylquinic acid 3, 7, 4 8, 12, 2

66 sinensetin 3

69 gardenin A 5

70 apigenin-6-C-glucoside 4

71 apigenin-8-C-glucoside (vitexin) 4

72 apigenin-7-O-glucoside 4

73 vitexin-2''-O-rhamnoside 4

74 genistein-7-O-glucoside 4

80 luteolin-7-O-glucoside 5, 7 12, 9

81 luteolin-4'-O-glucoside 5, 7 12, 9

82

kaempferol-3-O-glucoside

(astragalin) 5, 7 12, 9

83

quercetin-3-O-rhamnoside

(quercitrin) 4, 5, 7 12, 9

86


(isoquercetin) 3, 7, 4, 5

95 quercetin-3-O-rutinoside (rutin) 3, 4, 5

Samples: (1) - Apple peel from New Zealand; (2) - Apple flesh from Argentina;

(3)- Apple peel from Germany; (4) - Apple peel from Argentina; (5) - Apple peel

from China; (6)- Apple flesh from New Zealand; (7)- Apple peel from Italy;

(8)- Apple flesh from Germany; (9) - Apple flesh from China; (12) - Apple flesh

from Italy

91

1- As observed in the LC-MS data, a total of 25 polyphenols were found to be present in

the Apple samples based on tandem MS data and comparison with fragmentation

patterns of the most commonly occuring dietary polyphenols (148).

2- Most of the polyphenols in terms of numbers (24 polyphenols) investigated in the

Apple samples, were found in the Apple peels (96 % of total) in which, 12 of them

were found to be present only in peel samples. A total of 12 polyphenols were found

to be present in the flesh samples (48% of total) in which, phloretin was found to be

present only in flesh samples.

3- The presence of the compounds phloretin 37 (190, 191), (+)-catechin 46 (192), (-)-

epicatechin 47 (192), quercetin 52 (192), 5-caffeoylquinic acid 64 (192), sinensetin 66

(193), quercetin-3-O-glucoside 86 (193), quercetin-3-O-rutinoside 95 (194),

quercetin-3-O-rhamnoside 83 (195), luteolin-7-O-glucoside 80 (196), kaempferol-3-

O-glucoside 82 (197) in Apple samples were as well reported in the literature as

Apple secondary metabolites.

4- Among the polyphenols were found to be present in the Apple samples, compounds

robinetin 53 and luteolin-4'-O-glucoside 81 have not been reported in the literature as


Other phenolic compounds, which have been reported in Apples in the literature but, not

found in the Apple samples analysed here, include:

cyanidin-3-O-galactoside (192), cyanidin-3-O-xyloside (192), 3-hydroxyphloretin-2'-O-

glucoside (192), phloridzin (192), procyanidin dimer B1 (192), procyanidin dimer B2

(192), quercetin 3-O-arabinoside (198), quercetin 3-O-galactoside (192), quercetin 3-O-

xyloside (192), gentisic acid (199), syringic acid (199), 4-caffeoylquinic acid (200), 5-

caffeoylquinic acid (192), caffeic acid (201), ferulic acid (199), p-coumaric acid (192).

92

4.4.2- Polyphenols in Asparagus (Asparagus officinalis)

A total of three Asparagus samples were investigated including:

sample (10)- Green Asparagus from Germany; sample (11)- White Asparagus from

Germany; (40)- White Asparagus from Peru.

4.4.2.1- Findings on investigated polyphenols in Asparagus samples:

In Asparagus samples the following compounds listed in table 7 were identified

according to the m/z values observed in tandem MS chromatograms and comparison with

the fragmentation patterns of the most commonly occuring dietary polyphenols reported

by Sakakibara (148) .

Table 7- Assigned compounds in Asparagus samples

compound

number Compound Name

Sample

number

13 ferulic acid 40

14 isoferulic acid 40

26 isoliquiritigenin 40

27 formononetin 40

42 datiscetin 11

43 kaempferol 11

44 cyanidin 11

45 eriodictyol 11

48 diosmetin 11, 40

49 chrysoeriol 11, 40

55 delphinidin 40

57 (-)-gallocatechin 11, 40

59 isorhamnetin 40

60 tamarixetin 40

62 myricetin 40

64 5-caffeoylquinic acid 10

Samples: (10)-Green Asparagus from Germany ;

(11)-White Asparagus from Germany

(40)-White Asparagus from Peru

93

1- As observed in the LC-MS data, a total of 16 polyphenols were found to be present

in the Asparagus samples based on tandem MS data and comparison with

fragmentation patterns of the most commonly occuring dietary polyphenols (148).

2- The presence of the compounds 5-caffeoylquinic acid 64 (202), kaempferol 43

(203), cyanidin 44 (204), ferulic acid 13 (205), isoferulic acid 14 (205),

isorhamnetin 59 (203), myricetin 62 (206) and formononetin 27 (207)

in Asparagus samples were as well reported in the literature as Asparagus

secondary metabolites.

Other phenolic compounds, which have been reported in Asparagus in the literature but,

not found in the Asparagus samples analysed here, include: quercetin-3-O-rutinoside

(208), daidzein (207), genistein (207), glycitein (207), biochanin A (207),

secoisolariciresinol (207), matairesinol (207), quercetin (146), rutin (209), quercetin-3-O-

rhamnoside (210).

4.4.3- Polyphenols in Carrot (Daucus carota)

A total of three Carrot samples were investigated including:

sample (13)- Carrot from Italy; sample (15)- Carrot from Israel; (16)- Carrot from Holand

4.4.3.1- Findings on investigated polyphenols in Carrot samples

In Carrot samples the following compounds listed in table 8 were identified according to


fragmentation patterns of the most commonly occuring dietary polyphenols reported by

Sakakibara (148).

94

Table 8- Assigned compounds in Carrot samples

compound

number Compound Name Sample number

39 genkwanin 13

48 diosmetin 13, 15, 16

49 chrysoeriol 13, 15, 16

55 delphinidin 13, 16

56 (+)-taxifolin 16

59 isorhamnetin 15

60 tamarixetin 15


72 apigenin-7-O-glucoside 15, 16

73 vitexin-2''-O-rhamnoside 15, 16

74 genistein-7-O-glucoside 15, 16

Samples: (13) - Carrot from Italy; (15) - Carrot from Israel

(16)- Carrot from Holland

1- As observed in the LC-MS data, a total of 11 polyphenols were found to be

present in the Carrot samples based on tandem MS data and comparison with the

fragmentation patterns of the most commonly occuring dietary polyphenols (

148).

2- The presence of the compound 5-caffeoylquinic acid 64 (211), chrysoeriol 49

(212), isorhamnetin 59 (213), delphinidin 55 (145) and apigenin-7-O-glucoside 72

(146) in Carrot samples as well reported in the literature as Carrot secondary

metabolites.

Other phenolic compounds, which have been reported in Carrots in the literature but, not

found in the Carrot samples analysed here, include:

4-hydroxybenzoic acid (200), 3,4-dicaffeoylquinic acid (214), 3,5-dicaffeoylquinic acid

(214), 3-caffeoylquinic acid (214), 3-feruloylquinic acid (214), 4-caffeoylquinic acid

(200), 4-feruloylquinic acid (214), 5-caffeoylquinic acid (214), 5-feruloylquinic acid

(214), caffeic acid (200), cyanidin (146) , malvidin (146), pelargonidin (146), peonidin

(146), petunidin (146), (-)-epicatechin (146), (-)-epicatechin-3-gallate (146), (-)-

epigallocatechin (146) , (-)-epigallocatechin-3-gallate (146) , (+)-catechin (146) , (+)-

95

gallocatechin (146) , hesperetin (146), naringenin (146), apigenin (146), luteolin (146),

myricetin (146) and quercetin (146).

4.4.4- Polyphenols in Pear (Pyrus communis)

A total of 4 Pear samples from fleshes and peels were investigated including:

sample (14)- Pear flesh Argentina; Sample (17)- Pear peel Argentina; sample (33)-Pear

peel spain; sample (36)- Pear flesh spain

Findings on Pear polyphenols are discussed in details in section 4.4.4.1. A few examples

for compound assignments are illustrated in the following (examples 5-7):

Example 5 ((-)-gallocatechin 57 or (-)-epigallocatechin 58):

In the tandem MS chromatogram of sample 17 (Pear peel from Argentina) a peak was


gave an experimental value of the parent ion at m/z 307.0792 in the positive ion mode at a

retention time of 5.8 min. A molecular formula search suggested a molecular formula of

C15H15O7 with an error of 6.6 ppm and a mΣ value of 15.3.

Due to the reduced sensitivity of the UV detector if compared to the LC-MS detector, no


Tandem MS data in the positive ion mode revealed the following fragmentation. In the

MS2 spectrum, the base peak at m/z 184.8 corresponding to a neutral loss of m/z 121.9 is

observed, which was assigned to a loss of C7H6O2. Further fragmentation at m/z 145 was

also observed.

MS3 data of the transition 306.9 to 184.8 didn‘t show any fragmentation (see figure 31

and related tandem MS chromatogram in figure 32). Comparison to the literature data

96

allowed identification of this compound as (-)-gallocatechin 57 (146). The presence of

epigallocatechin 58 has not been reported in the literature as Pear secondary metabolite.

97

Figure 32- (a) Total ion chromatogram in the positive ion mode of sample 17, (b) UV-VIS spectrum,

(c) MS, (d) MS2 and (e) MS

3 spectra of compounds (-)-gallocatechin 57, (-)-epigallocatechin 58

O

OH

HO

OH

HO

OH

OHMass: 122

57- (-)-gallocatechin

O

OH

HO

OH

HO

OH

OHMass: 122

58- (-)-epigallocatechin

Figure 31- Structures of

compound (-)-gallocatechin

57 and (-)-epigallocatechin 58

(C15H14O7, Theoretical Mass:

306.073)

Exp. m/z [M+H]: 307.0792

a

b

c

d

e

98

Example 6 (quercetin-3-O-rutinoside 95)

In the tandem MS chromatogram of sample 17 (Pear peel from Argentina) a peak was





Due to the reduced sensitivity of the UV detector if compared to the LC-MS detector, no



MS2 spectrum, the base peak at m/z 299.9 corresponding to a neutral loss of m/z 308 is

observed, which was assigned to a loss of C12H21O9 (rutinoside). Further fragments at m/z

343, 300, 271 and 179 were observed.

MS3 data of the transition 609 to 300.9 showed a base peak at m/z 151 with further

fragments at m/z 254.7, 270.8, 271.8, 272.9 and 179 were observed. The fragment at m/z

179 is corresponding to a neutral loss of m/z 121, which could be assigned to a loss of

C7H5O2.

Please see figure 33 and related tandem MS chromatogram (figure 34).

Comparison to the literature data allowed identification of this compound as quercetin-3-

O-rutinoside 95 (215).

99

Figure 34- (a) Total ion chromatogram in the negative ion mode of sample 17,

(b) UV-VIS spectrum, (c) MS, (d) MS2 and (e) MS


quercetin-3-O-rutinoside 95

OHO

OH O

OH

OH

O

O

HOO

OCH3

HO

HO

OH

HO

OH

MS2, Mass : 309

MS3, Mass:121

Figure 33- quercetin-3-O-

rutinoside (rutin) , (C27H30O16 ,

Theoretical Mass: 610.153)

Exp. m/z [M-H]: 609.1491

a

b

c

d

e

100

Example 7 (5,7-dihydroxy-3',4',5'-trimethoxyflavone 63)

In the tandem MS chromatogram of sample 33 (pear peel from Spain) a peak was


gave an experimental value of the parent ion at m/z 345.0993 in the positive ion mode at a

retention time of 2.5 min. A molecular formula search suggested a molecular formula of

C18H17O7 with an error of 7.1 ppm and a mΣ value of 18.

UV-VIS data of this chromatographic peak revealed a maximum of absorbance around

200 nm. Therefore a flavone can be assigned (148).

Tandem MS data in the positive ion mode revealed the following fragmentation. In the

MS2 spectrum, the base peak at m/z 262.7 and further fragments at m/z 303,187 and 105

were observed. The fragment at m/z 303 corresponding to a neutral loss of m/z 42 is

observed, which was assigned to a loss of C2HO (Mass: 41)

MS3 data of the transition 345.9 to 262.7 showed a base peak at m/z 105.1 with further

fragment at m/z 180.7. Please see figure 35 and related tandem MS chromatogram (figure

36).

Comparison to the literature data allowed identification of this compound as 5,7-

dihydroxy-3',4',5'-trimethoxyflavone 63 as a new compound which its presence has not

been reported in Pear in the literature as Pear secondary metabolite.

101

Figure 36- (a) Total ion chromatogram in the positive io mode of sample 33,


3 spectra of compound 5,7-dihydroxy-3',4',5'-

trimethoxyflavone 63

Figure 35- Structure of the

compound 5,7-dihydroxy-

3',4',5'-trimethoxyflavone 63

(C18H17O7, Exact Mass:

344.090);

Exp. m/z [M+H] : 345.0993

a

OHO

OH

OCH3

OCH3

OCH3

Mass:41

O

a

b

c

d

e

b

102

4.4.4.1-Findings on investigated polyphenols in Pear samples

In Pear samples the following compounds listed in table 9 were identified according to



Sakakibara (148).

Table 9- Assigned compounds in Pear samples

Compound No.

Compound Name

Peel Samples

Flesh Samples

Sample No

12 caffeic acid 17

36 butein 17

39 genkwanin 36

46 (+)-catechin 17, 33

48 diosmetin 17, 33 14

49 chrysoeriol 17, 33 14

57 (-)-gallocatechin 17, 33

58 (-)-epigallocatechin 17, 33

63 5,7-dihydroxy-3',4',5'-trimethoxyflavone 33

64 5-caffeoylquinic acid 17, 33 36, 14

66 sinensetin 33

80 luteolin-7-O-glucoside 17, 33

81 luteolin-4'-O-glucoside 17, 33

82 kaempferol-3-O-glucoside (astragalin) 17, 33

83 quercetin-3-O-rhamnoside (quercitrin) 17, 33

86 quercetin-3-O-glucoside (isoquercetin) 17, 33

90 kaempferol-3-O-rutinoside 33

91 kaempferol-7-O-neohesperidoside 33

95 quercetin-3-O-rutinoside (rutin) 17, 33

Samples: (17)- Pear peel from Argentina; (33)- Pear peel from Spain; (14)- Pear

flesh from Argentina; (36)- Pear flesh from Spain

103


present in the Pear samples based on tandem MS data.

2- Most of the polyphenols in terms of numbers (18 polyphenols) investigated in the

Pear samples were found in the Pear peels (94.7% of total). Among the

polyphenols investigated in Pear samples, 79% of them only present in the pear

peel samples.

3- The presence of the compounds (+)-catechin 46 (146), quercetin-3-O-rutinoside

95 (215), (-)-gallocatechin 57 (146), kaempferol-3-O-rutinoside 90 (216),

quercetin-3-O-glucoside 86 (215), chrysoeriol 49 (216), luteolin-7-O-glucoside

80 (216), luteolin-4'-O-glucoside 81 (216), kaempferol-3-O-glucoside 82 (216),

quercetin-3-O-rhamnoside 83 (217), 5-caffeoylquinic acid 64 (218) and caffeic

acid 12 (219) in Pear samples, were as well reported in the literature as Pear


4- Among the polyphenols were found to be present in the Pear samples, compounds

5,7-dihydroxy-3',4',5'-trimethoxyflavone 63, sinensetin 66, (-)-epigallocatechin 58

and kaempferol-7-O-neohesperidoside 91 have not been reported in the literature

as Pear secondary metabolites.

Other phenolic compounds, which have been reported in Pears in the literature but,

not found in the Pear samples analysed here, include:

isorhamnetin-3-O-glucoside (215), quercetin-3-O-galactoside (215), gentisic acid (199),

5-caffeoylquinic acid (199), arbutin (215), procyanidin dimer B1 (220), procyanidin

dimer B2 (220), procyanidin dimer B3 (220), procyanidin dimer B5 (220), procyanidin

dimer B7 (220), procyanidin trimer C1 (220), procyanidin trimer EEC (220), p-coumaric

acid (221), cyanidin (146), delphinidin (146), malvidin (146), pelargonidin (146),

peonidin (146), petunidin (146), hesperetin (146), naringenin (146), apigenin (146),

luteolin (146), isorhamnetin (146), kaempferol (146), myricetin (146), quercetin (146)

and (-)-epicatechin (220).

104

4.4.5- Polyphenols in Lettuce (Lactuca sativa)

A total of two Lettuce samples were investigated including:

sample(18)-Lettuce Iceberg from Germany ; and sample (22)-Lettuce Romana from

Germany;

Findings on Lettuce polyphenols are discussed in details in section 4.4.5.1. An example

for compound assignment is illustrated in the following (example 8):

Example 8 (delphinidin 55)

In the tandem MS chromatogram for delphinidin 55 in sample 22 (Lettuce Romana) the

parent ion at m/z 304.1 was observed in the positive ion mode at a retention time of 37.5

min. The MS2 spectrum for this parent ion show a base peak at m/z 244.7 corresponding

to the neutral loss of m/z 59 was observed which could be assigned for a loss of C2H2O2

(Mass: 58) and therefore the assignment of the compound delphinidin 55 (figure 37)

(please see graph number 112 for tandem MS results in the supplementary information).

O

OH

OH

HO

OH

OH

OH

Mass: 58

Figure 37- Structure of delphinidin 55

(C15H11O7+, Theoretical mass: 303.049)

105

4.4.5.1-Findings on Lettuce polyphenols

In Lettuce samples the following compounds listed in table 10 were identified according

to the m/z values observed in tandem MS chromatograms and comparison with the


Sakakibara (148).

Table 10- Assigned compounds in Lettuce samples

compound number

Compound Name

Sample number

39 genkwanin 18

55 delphinidin 22


71

apigenin-8-C-glucoside

(vitexin) 18

Samples: (18)- Lettuce Iceberg from Germany;

(22)- Lettuce Romana from Germany


in the Lettuce samples based on tandem MS data.

2- The presence of the compound delphinidin 55 (146) in Lettuce samples, was as

well reported in the literature as Lettuce secondary metabolite.

Other phenolic compounds, which have been reported in Lettuce in the literature

but, not found in the Lettuce samples analysed here, include:

cyanidin-3-O-(6''-malonyl-glucoside) (222), cyanidin-3-O-glucoside (222), luteolin-7-O-

glucuronide (222), quercetin-3-O-(6"-malonyl-glucoside) (222), quercetin-3-O-(6"-

malonyl-glucoside) 7-O-glucoside (222), quercetin-3-O-galactoside (222), quercetin-3-O-

glucoside (222), quercetin-3-O-glucuronide (222), quercetin-3-O-rhamnoside (222),

quercetin-3-O-rutinoside (222), cyanidin (146), malvidin (146), pelargonidin (146),

peonidin (146), petunidin (146), (-)-epicatechin (146), (-)-epicatechin-3-gallate (146), (-)-

epigallocatechin (146), (+)-catechin (146), (+)-gallocatechin (146), hesperetin (146),

106

naringenin (146), apigenin (146), luteolin (146), kaempferol (146), myricetin (146),

quercetin (146) and 5-caffeoylquinic acid (223).

4.4.6- Polyphenols in Banana (Musa paradisiaca)

A total of three Banana samples were investigated including:

sample (20)- Banana Dominica republic; sample (29)- Banana Colombia; sample (38)-

Banana Ecuador .

4.4.6.1- Findings on investigated polyphenols in Banana samples

In Banana samples the following compounds listed in table 11 were identified according



Sakakibara (148).

Table 11- Assigned compounds in Banana samples

Compound Number

Compound Name

Sample No

48 diosmetin 20, 29, 38

49 chrysoeriol 20, 29, 38

55 delphinidin 20, 29, 38

Samples: (20)- Banana from Dominica republic;

(29)- Banana from Colombia; (38)- Banana from Ecuador

1- As observed in the LC-MS data, a total of three polyphenols were found to be

present in the Banana samples based on tandem MS data and comparison with


2- The presence of the compounds delphinidin 55 (146) in Banana samples were as

well reported in the literature as Banana secondary metabolites.

Other phenolic compounds, which have been reported in Banana in the literature

107

but, not found in the Banana samples analysed here, include:

(+)-catechin (224), (-)-epicatechin (225), (-)-epigallocatechin (220), prodelphinidin dimer

B3 (220), cyanidin (146), malvidin (146), pelargonidin (146), peonidin (146), petunidin

(146), (+)-gallocatechin (146), hesperetin (146), naringenin (146), apigenin (146),

luteolin (146), kaempferol (146) and gallic acid (224).

4.4.7- Polyphenols in Onion (Allium cepa)

A total of three Onion samples were investigated including:

sample (19)- Red Onion from Egypt; sample (24)- White Onion from Germany; sample

(30)-Onion from Spain

4.4.7.1- Findings on investigated polyphenols in Onion samples

In Onion samples the following compounds listed in table 12 were identified according to



Sakakibara (148).

Table 12- Assigned compounds in Onion samples

Compound number

Compound Name

Sample number

48 diosmetin 30

49 chrysoeriol 30

55 delphinidin 24

59 isorhamnetin 30, 24

60 tamarixetin 30, 24

86


(isoquercetin) 19, 30, 24

Samples: (19)- Red Onion from Egypt; (30)- Onion from Spain;

(24)- White Onion from Germany

108

1- As observed in the LC-MS data, a total of six polyphenolic compounds were

found to be present in the Onion samples based on tandem MS data and

comparison with fragmentation patterns of the most commonly occuring dietary

polyphenols (148).

2- The presence of the compounds quercetin-3-O-glucoside 86 (226), isorhamnetin

59 (146) and tamarixetin 60 (227) which were found to be present in the Onion

samples, were as well reported in the literature as Onion secondary metabolites.

Other phenolic compounds, which have been reported in Onions in the literature

but, not found in the Onion samples analysed here, include:

cyanidin-3-O-(6''-malonyl-3''-glucosyl-glucoside) (228), cyanidin-3-O-(6''-malonyl-

glucoside) (228), delphinidin-3-O-glucosyl-glucoside (228), isorhamnetin-4'-O-glucoside

(229), quercetin (230), quercetin-3,4'-O-diglucoside (230), quercetin-3-O-rutinoside

(230), quercetin-4'-O-glucoside (229), quercetin-7,4'-O-diglucoside (226), kaempferol

(146), (-)-epicatechin (146), (-)-epigallocatechin (146), (+)-catechin (146), (+)-

gallocatechin (146), apigenin (146), luteolin (146), myricetin (146), cyanidin (146),

delphinidin (146), pelargonidin (146), peonidin (146), apigenin (146), malvidin (146),

petunidin (146), hesperetin (146), naringenin (146) and protocatechuic acid (226).

4.4.8- Polyphenols in Orange (Citrus sinensis)

A total of three Orange samples were investigated including:

sample (21)- Orange from Argentina; sample (34)- Orange Valencia from sought Africa;

sample (39)-Orange Navel from sought Africa

Findings on Lettuce polyphenols are discussed in details in section 4.4.8.1. A few

examples for compound assignment are illustrated in the following (examples 9,10):

109

Example 9 (hesperidin-7-O-rutinoside 96)

In the tandem MS chromatogram of sample 21 (Orange from Argentina) a peak was



a retention time of 13.0 min. A molecular formula search suggested a molecular formula

of C28H33O15 (related to compound hesperetin-7-O-rutinoside 96) with an error of 7.2

ppm and a mΣ value of 6.1.

The UV-VIS data of this chromatographic peak revealed a maximum of absorbance at

230 nm and 280 nm. This value is characteristic for hesperetin-7-O-rutinoside 96 (148).


MS2 spectrum, the base peak is at m/z 300.9. Corresponding to a neutral loss of m/z 308 is

observed, which was assigned to a loss of C12H21O9

in compounds quercetin-3-O-

rutinoside 95 and hesperetin-7-O-rutinoside 96.

MS3 data of the transition 609.2 to 300.9 shows fragments at m/z 226.9, 238.9, 239.9,

241.9, 256.9, 125, 173.9, 198.9, 200.8, 214.8 and 163.9. The fragment at m/z 163.9 could

be responsible for the loss of C6H11O5 (Mass: 163). Please see figure 38, related tandem

MS chromatogram (figure 39).

This compound was tentatively assigned as hesperidin-7-O-rutinoside 96. Both the low

resolution mass molecular ion and fragmentation pattern in MS2

spectrum are identical to

compounds quercetin-3-O-rutinoside 95 and hesperetin-7-O-rutinoside 96. However high

resolution MS and MS3 data allow distinction between two common polyphenol

glycosides.

Supporting evidence from the literature, confirms the presence of the compound

hesperetin-7-O-rutinoside 96 in Orange (231, 232).

110


spectrum, (c)MS, (d) MS2 and (e) MS

3 spectra of compound quercetin-3-O-rutinoside 95

O

OOH

OO

OH

HO

H2C

O

O

MS2, Mass: 309MS3, Mass:163

CH3

OH

OH

OCH3

HO

HO

OH

Figure 38- hesperetin-7-O-rutinoside

95 (hesperidin)

(C28H34O15, Theoretical Mass: 610.190

; Exp. m/z [M-H]: 609.1869 )

a

b

c

d

e

111

Example 10

In the tandem MS chromatogram for compounds luteolin-4'-O-glucoside 81, kaempferol-

3-O-glucoside 82, quercetin-3-O-rhamnoside 83 in Oranges (samples 34) the parent ion

at m/z 449.1 was observed in the positive ion mode at a retention time of 10.1 min. The

MS2 spectrum for this parent ion shows a base peak at m/z 286.9 corresponding to the

neutral loss of m/z 162 that could be assigned for a loss of a hexose (C6H11O5) or a loss of

O-rhamnoside (Mass:163) (please see graph number 131 for tandem MS data in the

spplementary information).

4.4.8.1-Findings on Orange polyphenols:

In Orange samples the following compounds listed in table 13 were identified according



Sakakibara (148).

112

Table 13- Assigned compounds in Orange samples

Compound number

Compound Name

Sample number

36 butein 34

46 (+)-catechin 39

55 delphinidin 34

59 isorhamnetin 39

60 tamarixetin 39

61 quercetagetin 39

67 daidzein-7-O-glucoside 21

80 luteolin-7-O-glucoside 21, 34, 39

81 luteolin-4'-O-glucoside 21, 34, 39

82


(astragalin) 21, 34, 39

83


(quercitrin) 21, 34, 39

86


(isoquercetin) 34

89

naringenin-7-O-rutinoside

(naringin) 21


91

kaempferol-7-O-

neohesperidoside 21, 34, 39

95


(rutin) 39

96

hesperetin-7-O-rutinoside

(hesperidin) 21, 34, 39

Samples: (21)- Orange from Argentina; (34)- Orange Valencia

from south Africa (39)- Orange Navel from south Africa


present in the Orange samples based on tandem MS data and comparison with the


2- The presence of the compounds naringenin-7-O-rutinoside 89 (233), hesperetin-7-

O-rutinoside 96 (234), quercetin-3-O-rutinoside 95 (139), delphinidin 55 (146),

(+)-catechin 46 (146) and quercetagetin 61 (235) in Orange samples were as well

reported in the literature as Orange secondary metabolites.

113

3- Among the polyphenols were found to be present in the Orange samples,

compounds kaempferol-3-O-rutinoside 90 and kaempferol-7-O-neohesperidoside

91 have not been reported in the literature.

Other phenolic compounds, which have been reported in Oranges in the literature but, not

found in the Orange samples analysed here, include:

hesperetin (236), apigenin (146), (+)-gallocatechin (146), (-)-epicatechin (146), cyanidin

(146), myricetin (146), malvidin (146), quercetin (146), pelargonidin (146), peonidin

(146), petunidin (146), eriodictyol (146), (-)-epigallocatechin (146) and kaempferol

(236).

4.4.9- Polyphenols in Nectarine (Prunus persica var. nucipersica)

A total of three Nectarine samples from fleshes and peels were investigated including:

sample (25)- Nectarine peel from Italy ; Sample (32)- Nectarine flesh from Italy ; sample

(41)- Nectarine flesh sweed lady from Spain

4.4.9.1- Findings on investigated polyphenols in Nectarine samples

In Nectarine samples the following compounds listed in table 14 were identified



by Sakakibara (148).

114

Table 14- Assigned compounds in Nectarine samples

Compound

number

Compound Name

Peel

Samples

Flesh Samples

Sample Number

46 (+)-catechin 25 32, 41

48 diosmetin 32

49 chrysoeriol 32

55 delphinidin 32

57 (-)-gallocatechin 25

58 (-)-epigallocatechin 25


66 sinensetin 41




76 (-)-catechin gallate 41

80 luteolin-7-O-glucoside 25

81 luteolin-4'-O-glucoside 25

82


(astragalin) 25

83


(quercitrin) 25

86


(isoquercetin) 25

Samples: (25)- Nectarine peel from Italy; (32)- Nectarine flesh from Italy;

(41)- Nectarine Sweed Lady flesh from Spain


present in the Nectarine samples based on tandem MS data and comparison with

the fragmentation patterns of the most commonly occuring dietary polyphenols

(148).

2- Among the 17 polyphenols investigated in the Nectarine samples, 12 polyphenols

were found in the Nectarine peels (70.5 % of total) and ten of them (83.3.8%)

were found to be present only in peel samples.

2- The presence of the compounds (+)-catechin 46 (146), 5-caffeoylquinic acid 64(

147), quercetin-3-O-glucoside 86 (147), (-)-gallocatechin 57 (146), (-)-

epigallocatechin 58 (146), diosmetin 48 (146), delphinidin 55 (146), sinensetin 66

115

(146), (-)-catechin gallate 76 (225) in Nectarine samples were as well reported in

the literature as Nectarine secondary metabolites.

3- Among the polyphenols were found to be present in the Nectarine samples,

compounds luteolin-7-O-glucoside 80, luteolin-4'-O-glucoside 81, kaempferol-3-

O-glucoside 82 and quercetin-3-O-rhamnoside 83 have not been reported in the

literature.

Other phenolic compounds, which have been reported in Nectarines in the literature but,

not found in the Nectarine samples analysed here, include:

cyanidin-3-O-glucoside (237), procyanidin dimer B1 (237), quercetin-3-O-galactoside

(237), 3-caffeoylquinic acid (237), malvidin-3,5-O-diglucoside (238), malvidin (146),

pelargonidin (146), peonidin (146), petunidin (146), (-)-epicatechin (146), (+)-

gallocatechin (146), hesperetin (146), naringenin (146), apigenin (146), luteolin (146),

myricetin (146), quercetin (146), cyanidin (146) and quercetin-3-O-rutinoside (238).

4.4.10- Polyphenols in Melon (Cucumis melo)

A total of three Melon samples were investigated including:

sample (23)- Galia Melon from Italy; Sample (31)- Galia Melon from Brazil; sample

(35)- Honey Melon from Spain

4.4.10.1- Findings on investigated polyphenols in Melon samples

In Melon samples the following compounds listed in table 15 were identified according



Sakakibara (148).

116

Table 15- Assigned compounds in Melon samples

Compound

number

Compound Name

Sample number

26 isoliquiritigenin 31

48 diosmetin 31

49 chrysoeriol 31

55 delphinidin 23, 31

59 isorhamnetin 31, 35

60 tamarixetin 31, 35




Samples:(23)- Galia Melon from Italy; Sample (31)- Galia Melon

from Brazil; sample (35)-Honey Melon from Spain

1- As observed in the LC-MS data, a total of nine polyphenols were found to be

present in the Melon samples based on tandem MS data and comparison with


2- The presence of the compounds delphinidin 55 (146) in Melon samples were as

well reported in the literature as Melon secondary metabolites.

Other phenolic compounds, which have been reported in Melons in the literature but, not

found in the Melon samples analysed here, include:

cyanidin (146), malvidin (146), pelargonidin (146), peonidin (146), petunidin (146),

epicatechin (146), epicatechin-3-gallate (146), epigallocatechin-3-gallate (146), catechin

(146), hesperetin (146), naringenin (146), apigenin (146), luteolin (146), kaempferol

(146), myricetin (146), quercetin (146), peonidin (146) and petunidin (146).

4.4.11- Polyphenols in Courgette (Cucurbita spp.)

Two Courgette samples from flesh and peel were investigated including:

Sample (26)-Courgette flesh from Germany; sample (27)-Courgette peel from Germany

117

4.4.11.1- Findings on investigated polyphenols in Courgette samples

In Courgette samples the following compounds listed in table 16 were identified




Table 16- Assigned compounds in Courgette samples

Compound number

Compound Name

Peel sample Flesh sample

Sample No

48 diosmetin 27

49 chrysoeriol 27

55 delphinidin 26

67 daidzein-7-O-glucoside 27


71


(vitexin) 27


77

baicalein-7-O-glucuronide

(baicalin) 27

86


(isoquercetin) 27


91

kaempferol-7-O-

neohesperidoside 27

95


(rutin) 27

96


(hesperidin) 27

sample (26)-Courgette flesh from Germany;

sample (27)-Courgette peel from Germany


present in the Courgette samples based on tandem MS data and comparison with


2- The presence of the compounds quercetin-3-O-rutinoside 95 (239) in Courgette

sample was as well reported in the literature as Courgette secondary metabolite.

118

Other phenolic compounds, which have been reported in Courgette in the literature but,

not found in the courgette samples analysed here, include:

quercetin (146), (-)-epicatechin (146), (-)-epicatechin 3-gallate (146), (-)-epigallocatechin

(146), (-)-epigallocatechin 3-gallate (146), (+)-catechin (146) and (+)-gallocatechin (146).

4.4.12- Polyphenols in Cauliflower (Brassica oleracea)

One Cauliflower sample was investigated including: sample (37) - Cauliflower from

Germany.

4.4.12.1- Findings on investigated polyphenols in Cauliflower samples

In Cauliflower sample, the following compounds listed in table 17 were identified




Table 17- Assigned compounds in Cauliflower sample

Compound number

Compound Name

Sample number

48 diosmetin 37

49 chrysoeriol 37

59 isorhamnetin 37

60 tamarixetin 37

66 sinensetin 37


71


(vitexin) 37



82


(astragalin) 37

83


(quercitrin) 37

Sample (37)- Cauliflower from Germany

119


in the Cauliflower sample based on tandem MS data and comparison with the


2- The presence of the compounds isorhamnetin 59 (240) and vitexin 71 (240) in

Cauliflower sample, were as well reported in the literature as Cauliflower


3- Among the polyphenols were found to be present in the Cauliflower samples,

compound sinensetin 66 has not been reported in the literature.

Other phenolic compounds, which have been reported in Cauliflower in the literature but,

not found in the Cauliflower samples analysed here, include:

gallic acid (199), protocatechuic acid (199), syringic acid (199), 5-caffeoylquinic acid

(199), caffeic acid (199), ferulic acid (199), kaempferol (146), quercetin (146), (-)-

epicatechin (146), (-)-epicatechin-3-gallate (146), (-)-epigallocatechin (146) and sinapic

acid (199).

4.4.13- Polyphenols in Strawberry (Fragaria x ananassa)

One Strawberry sample was investigated including: sample (42)-Strawberry from

Germany

Findings on strawberry polyphenols are discussed in details in section 4.4.13.1. An

example for compound assignment is illustrated in the following (example 11):

Example 11 (ellagic acid 50)

In the tandem MS chromatogram of sample 42 (Strawberry from Germany) a peak was





120

Tandem MS data in the negative ion mode revealed the following fragmentation. The

MS2 spectrum shows a base peak at m/z 167.8, which could be assigned to a loss of

C7H3O5 (Mass: 167) and further fragment at m/z 216.7 corresponding to a loss of m/z 84

that could be assigned to a loss of C4H3O2 (Mass: 83).

MS3 data of the transition 301 to 167.8 shows a base peak at m/z 114.3 and further

fragment at m/z 149.9. Please see Figure 40 and related tandem MS chromatogram in

Figure 41.

Comparison to the literature data allowed identification of this compound as ellagic acid

50 (200, 241, 242).

121

Figure 41 - (a) Total ion chromatogram in the negative ion mode of sample 42,


3 spectra of compound ellagic acid 50

OH

HO O O

OO OH

OH

Mass: 83

Mass :167

Figure 40- ellagic acid (C14H6O8,

Theoretical Mass: 302.006)

Exp. m/z [M-H]: 300.9994

a

b

c

d

e

e

122

4.4.13.1- Findings on investigated polyphenols in Strawberry sample:

In Strawberry sample the following compounds listed in table 18 were identified

according to the m/z values observed in tandem MS chromatograms and comparison

with the fragmentation patterns of the most commonly occuring dietary polyphenols

reported by Sakakibara (148).

Table 18- Assigned compounds in Strawberry sample

Compound number

Compound Name

Sample number

39 genkwanin 42

46 (+)-catechin 42

50 ellagic acid 42






82


(astragalin) 42

83


(quercitrin) 42

86


(isoquercetin) 42

Sample (42) - Strawberry from Germany


present in the Strawberry sample based on tandem MS data and comparison

with fragmentation patterns of the most commonly occuring dietary

polyphenols (148).

2- The presence of the compounds (+)-catechin 46 (146), ellagic acid 50 (220),

kaempferol-3-O-glucoside 82 (243) and quercetin-3-O-glucoside 86 (244) in

Strawberry sample were as well reported in the literature as Strawberry


3- Among the polyphenols were found to be present in the Strawberry sample,

compounds genkwanin 39, apigenin-7-O-glucoside 72, vitexin-2''-O-

rhamnoside 73, genistein-7-O-glucoside 74, luteolin-7-O-glucoside 80,

luteolin-4'-O-glucoside 81, quercetin-3-O-rhamnoside 83 have not been

reported in the literature.

123

Other phenolic compounds, which have been reported in strawberry in the literature

but, not found in the strawberry sample analysed here include:

cyanidin (245, 246), cyanidin-3-O-(6''-succinyl-glucoside) (247), cyanidin-3-O-

glucoside (248), pelargonidin (248), pelargonidin-3-O-(6''-malonyl-glucoside) (246),

pelargonidin-3-O-(6''-succinyl-glucoside) (247), pelargonidin-3-O-arabinoside (248),

pelargonidin-3-O-glucoside (248), pelargonidin-3-O-rutinoside (247), (+)-

gallocatechin (220), (-)-epicatechin-3-O-gallate (220), (-)-epigallocatechin (220),

procyanidin dimer B1 (220), procyanidin dimer B2 (220), procyanidin dimer B3

(220), procyanidin dimer B4 (220), procyanidin trimer EEC (220), morin (249),

quercetin 3-O-glucuronide (246), 4-hydroxybenzoic acid 4-O-glucoside (250), 5-O-

galloylquinic acid (250), ellagic acid glucoside (247), 5-caffeoylquinic acid (200),

caffeoyl glucose (250), cinnamic acid (249), feruloyl glucose (250), p-coumaric acid

(249), p-coumaric acid 4-O-glucoside (250), p-coumaroyl glucose (250), kaempferol

(146), quercetin (146), eriodictyol (146), hesperetin (146), naringenin (146), (-)-

epicatechin (146) and resveratrol (249).

4.4.14- Polyphenols in Leek (Allium ampeloprasum)

One Leek sample was investigated including: sample (28)-Leek from Germany

There was no phenolic compound identified according to the m/z values observed in

tandem MS chromatogram of the Leek sample and comparison with the fragmentation

patterns of the most commonly occuring dietary polyphenols reported by Sakakibara

(148).

Other phenolic compounds, which have been reported in Leek in the literature but, not

found in the Leek sample analysed here include:

(-)-epicatechin (146), (-)-epicatechin-3-gallate (146), (-)-epigallocatechin (146), (-)-

epigallocatechin-3-gallate (146), (+)-catechin (146), (+)-gallocatechin (146), apigenin

(146), luteolin (146), kaempferol (146), myricetin (146) and quercetin (146).

124

4.5- Results for the confirmed compounds in the HR-MS chromatograms:

The following phenolic and polyphenolic compounds have been assigned in tandem

MS chromatograms of the samples according to their m/z values, their fragmentation

patterns and they were confirmed by investigations in the HR-MS chromatograms of

the related samples within 10 ppm tolerance (see tables 19-30).

125

Table 19- High resolution MS data for confirmed compounds in Apple peels (Samples: 1, 3, 4, 5, 7) (see table 2 on page 44)

Compound name Compound

number

Molecular Theoretical Experimental Error

(ppm) m∑ Ion

mode

Sample tR

formula m/z m/z (min)

5-caffeoylquinic acid 64 C16H17O9 353.0878 353.0884 1.6 11.9 - 3 2.3

(-)-epicatechin 47 C15H13O6 289.0717 289.0713 1.5

3.8 - 3 5.4

sinensetin 66 C20H19O7 371.1136 371.1134 0.6

64.6 - 3 2.3

quercetin-3-O-rutinoside 95 C27H29O16 609.1461 609.1458 0.5 30.3 - 3 1.5

quercetin-3-O-glucoside 86 C21H19O12 463.0882 463.0899 3.6 17.0 - 3 10.4

robinetin 52 C15H9O7 301.0353 301.0349 1.5

12.5 - 3 11.7

126

Table 19- High resolution MS data for confirmed compounds in Apple peels (Samples: 1, 3, 4, 5, 7) (see table 2 on page 44)

Compound name Compound

number


(ppm) m∑ Ion

mode

Sample tR



86 C21H21O12 465.1027 465.1011 3.5 - + 4 10.8


83 C21H19O11 447.0932 447. 0942 2 21.8 - 4 1.7


95 C27H29O16 609.1461 609.1478 2.9 29.9 - 4 1.4

5-caffeoylquinic acid 64 C16H17O9 353.0878 353.0882 1.1

13.8 - 4 2.3

(+)-catechin

46 C15H13O6 289.0717 289.0716 0.55 1.2 - 4 1.5

luteolin-7-O-glucoside luteolin-4'-O-glucoside kaempferol-3-O-glucoside quercetin-3-O-rhamnoside

80, 81, 82,

83

C21H21O11 449.1078 449.1070 1.8 12.2 + 5 2.9


95

C27H29O16 609.1461 609.1467 0.9 11.7 - 5 4.8

127

Table 19 - High resolution MS data for confirmed compounds in Apple peels (Samples: 1, 3, 4, 5 and 7) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR



86 C21H19O12 463.0882 463.0896 3 4.8 - 5 1.5


80, 81, 82,

83

C21H19O11 447.0932 447.0942 2 7.4 - 5 1.7

5-caffeoylquinic

acid

64 C16H17O9 353.0878 353.0871 1.9 12 - 7 1.9


86 C21H19O12 463.0882 463.0926 9.5 5.7 - 7 6.5


80, 81, 82,

83

C21H19O11 447.0933 447.0962 6.4 8.3 - 7 1.6

128

Table 20- High resolution MS data for confirmed compounds in Apple fleshes (Samples: 2, 6, 8, 9, 12) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR


5-caffeoylquinic acid 64 C16H17O9 353.0878 353.0881 0.8 1.1 - 2 2.1

5-caffeoylquinic acid 64 C16H17O9 353.0878 353.0880 0.5 3.7 - 8 2.1-

2.6 luteolin-7-O-glucoside luteolin-4'-O-glucoside

kaempferol-3-O-glucoside quercetin-3-O-rhamnoside

80, 81, 82,

83

C21H19O11 447.0932 447.0949 3.6 11.4 - 9 10.6

5-caffeoylquinic acid 64 C16H17O9 353.0878 353.0882 1.1 4.3

- 12 2.2

129

Table 21- High resolution MS data for confirmed compounds in Asparaguses (Samples: 10,11, 40) (see table 2 on page 44)

Compound

name

Compound

number


(ppm) m∑ Ion

mode

Sample tR


5-caffeoylquinic

acid

64 C16H17O9 353.0878 353.0886 2.2 15 - 10 2.3

Table 22- High resolution MS data for confirmed compounds in Carrots (Samples: 13, 15, 16) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR


5-caffeoylquinic

acid

64 C16H17O9

353.0878 353.0900 6.2 7 - 13 9.1

130

Table 23- High resolution MS data for confirmed compounds in Pear peels (Samples: 17, 33, 36) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR



86 C21H21O12 465.1027 465.1059 6.7 27 + 33 2.6


86 C21H21O12 465.1027 465.1026 0.3 14.3 + 17 2.4

5-caffeoylquinic

acid

64 C16H19O9 355.1023 355.1024 0.1 13 + 17 2.2

(-)-gallocatechin, (-)-epigallocatechin

57, 58 C15H15O7 307.0812 307.0792 6.6 15.3 + 17 5.8

(+)-catechin 46 C15H15O6 291.0863 291.0864 0.3 2.2 + 17 6.2

5,7-dihydroxy-3',4',5'-trimethoxyflavone

63 C18H17O7 345.0968 345. 0993 7 18 + 33 4.5

Sinensetin 66

C20H21O7 373.1281 373.1271 2.8 17.5 + 33 2.6


86 C21H19O12 463. 0882 463. 0925 9.2 17.3 - 33 9.5

kaempferol-3-O-rutinoside, kaempferol-7-O-neohesperidoside

90, 91 C27H29O15 593.1511 593. 1571 9.9 27.7 - 33 1.4

131

Table 23- High resolution MS data for confirmed compounds in Pear peels (Samples: 17,33,36) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR


5-caffeoylquinic

acid

64 C16H17O9 353.0878 353.0885 1.9 5 - 36 4.1

(+)-catechin

46

C15H13O6

289.0717

289.0700

6

4.5

-

17 1.7


95

C27H29O16

609.1461

609.1491

4.9

6.7

-

17 7.4

Table 24- High resolution MS data for confirmed compounds in Pear fleshes (Samples: 14, 36) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR


5-caffeoylquinic

acid

64 C16H17O9 353.0878 353. 0890 3.3 26.6 - 14 2.2

5-caffeoylquinic

acid 64 C16H17O9 353.0878 353. 0893

4.2

25

- 36 4

132

Table 25- High resolution MS data for confirmed compounds in Onions (Samples: 19, 24, 30) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR



86 C21H19O12 463. 0882 463. 0905 4.9 11.9 - 19 1.5


86 C21H19O12 463. 0882 463.0916 7.3 6.5 - 24 1.3


86 C21H19O12 463. 0877 463. 0922 8.6 1.7 - 30 1.3

133

Table 26- High resolution MS data for confirmed compounds in Oranges (Samples: 21, 34, 39) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR


kaempferol-3-O-rutinoside, kaempferol-7-O-neohesperidoside

90,91 C27H29O15 593.1519 593.1526 2.3 3.6 - 21 5.5


89 C27H31O14 579.1719 579.1750 5.3 21.8 - 21 11.8


96 C28H33O15 609.1824 609.1869 7.2 6.1 - 21 13


96 C28H35O15 611.1976 611.1972 0.2 41.3 + 21 1.6


89 C27H31O14 579.1719 579.1743 4.0 107 - 34 1.2


96 C28H33O15 609.1824 609.1861 5.9 22.3 - 34 1.2


96 C28H35O15 611.1970 611.2031 9.9 99 + 34 1.9


89 C27H31O14 579.1719 579.1719 0.0 17 - 39 11.8

134

Table 26- High resolution MS data for confirmed compounds in Oranges (Samples: 21, 34, 39) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR



96 C28H33O15 609.1824 609.1841 2.6 12.7 - 39 13.2


96 C28H35O15 611.1970 611.1965 0.9 8.6 + 39 13.2


95

C27H29O16 609.1461 609.1477 2.6

15.9 - 39

4.0

135

Table 27- High resolution MS data for confirmed compounds in Nectarine Peel (Sample 25 ) (see table 2 on page 44)

Compound

name

Compound

number


(ppm) m∑ Ion

mode

Sample tR


Luteolin-7-O-glucoside, luteolin-4'-O-glucoside, kaempferol-3-O-glucoside, quercetin-3-O-rhamnoside

80, 81, 82

83

C21H21O11 449.1078 449.1087 1.9 35.7 + 25 2.5

Table 28- High resolution MS data for confirmed compounds in Nectarine fleshes (Sample 32, 41) (see table 2 on page 44)

Compound

name

Compound

number


(ppm) m∑ Ion

mode

Sample tR


(+)-catechin,

46 C15H13O6 289.0717 289. 0714 1.25 3.3 - 41 4.6

136

Table 29- High resolution MS data for confirmed compounds in Cauliflower (Sample 37) (see table 2 on page 44)

Compound

name

Compound

number


(ppm)

m∑ Ion

mode

Sample tR


sinensetin 66 C20H19O7 371.1136 371.1157 5.6 16.5 - 37 5.6

Table 30- High resolution MS data for confirmed compounds in Strawberry (Sample 42) (see table 2 on page 44)

Compound

name

Compound

number


(ppm) m∑ Ion

mode

Sample tR


apigenin-7-O-glucoside, vitexin-2''-O-rhamnoside, genistein-7-O-glucoside

72, 73,

74

C21H19O10 431.0983 431.1022 8.9 13.2 - 42 2.9

genkwanin 39 C15H7O6 283.0248 283.0272 8.4 520 - 42 6.1

137


Compound

name

Compound

number


(ppm) m∑ Ion

mode

Sample tR


luteolin-7-O-glucoside, luteolin-4'-O-glucoside, kaempferol-3-O-glucoside, quercetin-3-O-rhamnosid

80, 81, 82,

83

C21H21O11

449.1078

449.1103

5.4

25.6

+

42

2.3


Compound

name

Compound

number


(ppm) m∑ Ion

mode

Sample tR



86 C21H19O12 463.0882 463.0898 3.4 339 - 42 3.2

ellagic acid 50 C14H5O8

300.9989 300.9994 1.3 5.5 - 42 10.2

(+)-catechin 46

C15H13O6 290.0717 289.0732 4.9 9.1 - 42 4.6

138

4.6- Results for the assigned compounds in tandem MS chromatograms:

The phenolic and polyphenolic compounds have been assigned in tandem MS

chromatograms of the samples according to their m/z values and their fragmentation

patterns. Please see the results, presented in the supplementary information.

4.7- Summary of the findings

In some occasions, the literature reports on the presence of aglycones, which were not

found in the samples, but the glycosylated derivatives, were found. It suggests that in

the published work, aglycones might have been artifacts of the analytical procedure,

rather than genuine plant metabolites e.g., kaempferol in Orange.

Most of the polyphenols identified in the samples analysied in this study were

belonging to the classes of flavones and flavonols.

In the following, a summary of findings on investigated polyphenols in the samples of

vegetables and fruits is presented, based on tandem MS data and comparison with the

fragmentation patterns of the most commonly occurring dietary polyphenols.

139

Apple:

As observed in the LC-MS data, a total of 25 polyphenols were found to be present in

the Apple samples based on tandem MS data and comparison with fragmentation


Most of the polyphenols in terms of numbers (24 polyphenols) investigated in the

Apple samples, were found in the Apple peels (96 % of total) in which, 12 of them

were found to be present only in peel samples. A total of 12 polyphenols were found

to be present in the flesh samples (48% of total) in which, phloretin was found to be

present only in flesh samples.

Figure 42 shows the summary of the findings in the Apple samples.

Among the polyphenols were found to be present in the Apple samples, compounds



Figure 42- Different classes of dietary phenolic compounds

and number of the compounds belonging to each class,

found to be present in the Apple samples .

140

Asparagus:


the Asparagus samples based on tandem MS data and comparison with the


Figure 43 shows the summary of the findings in the Asparagus samples.



found to be present in the Asparagus samples .

141

Carrot:


the Carrot samples based on tandem MS data and comparison with the fragmentation

patterns of the most commonly occuring dietary polyphenols (148). Figure 44- shows

the summary of the findings in the Carrot samples.

1

0

1 1

5

2

1

00

0

2

4

6

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Carrot samples .

142

Pear:


the Pear samples based on tandem MS data.

Most of the polyphenols in terms of numbers (18 polyphenols) investigated in the

Pear samples were found in the Pear peels (94.7% of total). Among the polyphenols

investigated in Pear samples, 79% of them only resent in the Pear peel samples.

Among the polyphenols were found to be present in the Pear samples, compounds

5,7-dihydroxy-3',4',5'-trimethoxyflavone 63, tangeretin 66, (-)-epigallocatechin 58

and kaempferol-7-O-neohesperidoside 91 have not been reported in the literature as

Pear secondary metabolites. Figure 45 shows the summary of the findings in the Pear

samples.



found to be present in the Pear samples .

143

Lettuce:

As observed in the LC-MS data, a total of four polyphenols were found to be present

in the Lettuce samples based on tandem MS data and comparison with the


Figure 46shows the summary of the findings in the Lettuce samples.

.

0 0 0 0

3

0

1

00

0

2

4

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Lettuce samples .

144

Banana:

As observed in the LC-MS data, a total of three polyphenols were found to be present

in the Banana samples based on tandem MS data and comparison with fragmentation

patterns of the most commonly occuring dietary polyphenols (148). Figure 47 shows

the summary of the findings in the Banana samples.

0 0 0 0

2

0

1

00

0

2

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Banana samples .

145

Onion:

As observed in the LC-MS data, a total of six polyphenolic compounds were found to

be present in the Onion samples based on tandem MS data and comparison with


Figure 48 shows the summary of the findings in the Onion samples.

0 0 0 0

2

3

1

00

0

2

4

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Onion samples .

146

Orange:


the Orange samples based on tandem MS data and comparison with the fragmentation


Among the polyphenols were found to be present in the Orange samples, compounds

kaempferol-3-O-rutinoside 90 and kaempferol-7-O-neohesperidoside 91 have not

been reported in the literature. Figure 49 shows the summary of the findings in the

Orange samples.

0

1

0

2 2

9

1 11

0

2

4

6

8

10

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Orange samples .

147

Nectarine:


the Nectarine samples based on tandem MS data and comparison with the


Among the 17 polyphenols investigated in the Nectarine samples, 12 polyphenols

were found in the Nectarine peels (70.5 % of total) and ten of them (83.3.8%) were

found to be present only in peel samples.

Among the polyphenols were found to be present in the Nectarine samples,

compounds luteolin-7-O-glucoside 80, luteolin-4'-O-glucoside 81, kaempferol-3-O-

glucoside 82 and quercetin-3-O-rhamnoside 83 have not been reported in the

literature. Figure 50 shows the summary of the findings in the Nectarine samples.

1

0

1

0

7

3

1

4

0

0

2

4

6

8

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Nectarine samples .

148

Melon:

As observed in the LC-MS data, a total of nine polyphenols were found to be present

in the Melon samples based on tandem MS data and comparison with fragmentation


the summary of the findings in the Melon samples.

0

1 1

0

4

2

1

00

0

2

4

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Melon samples .

149

Courgette:


the Courgette samples based on tandem MS data and comparison with fragmentation


the summary of the findings in the Courgette samples.

0 0 0

1

6

4

1

00

0

2

4

6

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Courgette samples .

150

Cauliflower:


the Cauliflower sample based on tandem MS data and comparison with the


Among the polyphenols were found to be present in the Cauliflower samples,

compound sinensetin 66 has not been reported in the Cauliflower in the literature as

Cauliflower secondary metabolite. Figure 53 shows the summary of the findings in

the Cauliflower samples.

0 0 0 0

6

4

0 00

0

2

4

6

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Cauliflower samples.

151

Strawberry:


the Strawberry sample based on tandem MS data and comparison with fragmentation


Among the polyphenols were found to be present in the Strawberry sample,

compounds genkwanin 39, apigenin-7-O-glucoside 72, vitexin-2''-O-rhamnoside 73,

genistein-7-O-glucoside 74, luteolin-7-O-glucoside 80, luteolin-4'-O-glucoside 81,

quercetin-3-O-rhamnoside 83 have not been reported in the literature as Strawberry

secondary metabolite. Figure 54 shows the summary of the findings in the Strawberry

samples.

0 0 0 0

4

3

0

3

1

0

2

4

cinnamic acids

chalcones

isoflavones

flavanones

flavones

flavonols

anthocyanidins

catechins

others



found to be present in the Strawberry samples.

152

Leek:

There was no phenolic compounds identified according to the m/z values observed in

the tandem MS chromatogram of the Leek sample.

A summary for the known compounds in all the samples is presented in table 31.

Table provides the individual compound numbers horizontally versus the individual

samples vertically. Therfore it provides information on individual compounds present

in the different vegetables and fruits. The numbersgiven in the cells x/y refer to x =

number of samples where compound were found, y = number of total samples

analysed.

153

Table 31- The phenolic compounds and polyphenols found in the samples

Samples Compound numbers

12 13 14 26 27 35 36 37 39 40 41 42 43 44 45 46 47 48 49 50 51 52

Apple peels : 1, 3,

4, 5, 7

2/5 1/5 1/5 2/5 1/5 5/5 5/5 1/5

Apple fleshes:

2, 6, 8, 9, 12

1/5 1/5 1/5 1/5 3/5 3/5

Asparagus : 10,

11, 40

1/3 1/3 1/3 1/3 1/3 1/3 1/3 1/3 2/3 2/3

Carrot: 13 ,15, 16 1/3 3/3 3/3

Pear feshes: 14, 36 1/2 1/2 1/2 1/2

Pear peels: 17, 33 1/2 1/2 2/2 2/2 2/2 2/2

Lettuce: 18 ,22 1/2

Banana: 20, 29, 38 3/3 3/3

Onion: 19, 24, 30 1/3 1/3

Orange: 21, 34, 39 1/3 1/3

Nectarine peel: 25 1/1

Nectarine

fleshes:32, 41

2/2 1/2 1/2

Cauliflower: 37 1/1 1/1

Strawberry: 42 1/1 1/1 1/1

Melon: 23, 31, 35 1/3 1/3 1/3

Courgette peel: 27 1/1 1/1

Courgette flesh:

26

Color indicators used in classification of the compounds: cinnamic acids ; chalcones ; isoflavones ; flavanones ; flavones ; flavonols; anthocyanidins; catechins ; others;

154


Samples Compound Numbers

53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 69 70 71 72 73 74 75 76 77

Apple peels :

1,3,4,5,7

1/5 5/5 3/5 1/5 1/5 1/5 1/5 1/5 1/5 1/5

Apple fleshes:

2, 6,8,9,12

2/5 3/5

Asparagus : 10,11,40 1/3 2/3 1/3 1/3 1/3 1/3

Carrot: 13, 15, 16 2/3 1/3 1/3 1/3 1/3 2/3 2/3 2/3

Pear fleshes: 14, 36 2/2

Pear peels: 17, 33 2/2 2/2 1/2 2/2 1/2

Lettuce: 18, 22 1/2 1/2 1/2

Banana: 20, 29, 38 3/3

Onion: 19, 24, 30 1/3 2/3 2/3

Orange: 21, 34, 39 1/3 1/3 1/3 1/3 1/3

Nectarine peel: 25 1/1 1/1 1/1 1/1 1/1 1/1

Nectarine fleshes: 32,

41

1/2 1/2 1/2

Cauliflower: 37 1/1 1/1 1/1 1/1 1/1

Strawberry: 42 1/1 1/1 1/1 1/1 1/1 1/1

Melon: 23, 31, 35 2/3 2/3 2/3 1/3 1/3 1/3

Courgette peel: 27 1/1 1/1 1/1 1/1

Courgette flesh:26 1/1 1/1

Color indicators used in classification of the compounds: cinnamic acids ; isoflavones ; flavanones ; flavones ; flavonols; anthocyanidins; catechins

155


Samples Compound numbers

78 79 80 81 82 83 84 85 86 87 89 90 91 95 96

Apple peels :

1,3,4,5,7

2/5 2/5 2/5 3/5 4/5 3/5

Apple fleshes:

2, 6,8,9,12

2/5 2/5 2/5 2/5

Asparagus :

10,11,40

Carrot: 13,15,16

Pear fleshes: 14, 36

Pear peels:17,33 2/2 2/2 2/2 2/2 2/2 1/2 1/2 2/2

Lettuce:18,22

Banana:20,29,38

Onion:19,24,30 3/3

Orange:21,34,39 3/3 3/3 3/3 3/3 1/3 1/3 1/3 3/3 3/3 3/3

Nectarine peel:25 1/1 1/1 1/1 1/1 1/1

Nectarine

fleshes:32,41

1/1

Cauliflower:37 1/1 1/1 1/1 1/1

Strawberry:42 1/1 1/1 1/1 1/1 1/1

Melon:23,31,35

Courgette peel:27 1/1 1/1 1/1 1/1 1/1

Courgette flesh:26 Color indicators : flavanones ; flavones ; flavonols;; Catechins

156

4.8- Changes in the polyphenolic content of vegetable and fruit extracts in long

term freezing conditions

To our knowledge little information is available on changes of polyphenolic

compounds in fruits and vegetables during postharvest storage. Since polyphenolic

compounds are one of secondary metabolites and their metabolism is greatly

dependent on a significant number of factors such as light, temperature, etc.,

polyphenolic content in fruits and vegetables could be greatly affected by postharvest

storage conditions and this probably could affect the chemical composition and

possibly the antioxidant function of these compounds (251).

Experiments have been conducted investigating the effects of storage under different

conditions such as storage at room temperature (20º C) or low temperatures (0º C to -

4º C), (251, 252, 253, 254, 255) but little is known about the effects of long term

frozen storage conditions (e.g., at -12 º C for one year) and its effects on phenolic and

polyphenolic content and composition of fruits and vegetables. Since in many

countries, vegetables and some types of fruits are kept frozen for many months at

homes or they are sold in the form of frozen packages on the supermarkets, it is

important to understand the changes of nutrients as well as the changes in

polyphenolic contents of the plant materials under long term freezing conditions. This

study reports some examples for the loss of polyphenols in the long term stored

samples at -12 º C for one year. The investigation was conducted using selected fruits

and vegetables to study the changes of polyphenol profiles prior to storage and after

storage.

4.8.1- Investigation of the specific polyphenols in the chromatograms of the

stored samples

The samples were prepared as described and stored at -12 º C for 12 months. Each

sample was dissolved in methanol (10 mg/ml) and analysed by LC-MS using an ion

trap or TOF mass spectrometer. The presence of the phenolic compounds and

polyphenols, which were already assigned in the tandem MS chromatograms of the

fresh samples were investigated in the obtained high resolution chromatograms of the

stored samples (at -12 º C for 12 months).

157

4.8.2- Results and discussion

Figure 55 shows that the mass spectra of the samples at the beginning of the storage

and the mass spectra of the samples after 12 months storage are different.

TIC of Sample 6 (negative mode, before storage)

Concentration: 10mg/ml

TIC of Sample 6 (negative mode , after storage)

Concentration: 10mg/ml

TIC of Sample 19 in (-) mode , before storage

Concentration : 10mg/ml

TIC of Sample 19 in (–) mode , after storage

Concentration : 10mg/ml

Figure 55- A comparison between the tandem mass spectra of the samples at the

beginning of the storage and the mass spectra of the samples after 12 months storage.

TIC stands for total ion chromatogram

In the chromatograms after 12 months storage at -12 º C (e.g., in the TIC of the

sample 6), a hump was observed. This hump could be the result of fermentation of the

compounds similar to chromatograms of black Tea, in which green Tea flavan 3-ols

are oxidized to complex materials named the thearubigins (256).

After analysis of the chromatograms using the ESI-TOF detector, a total of 27

polyphenols were found to be present in some samples after 12 months storage and a

total of 55 polyphenols was found to be absent in some samples after storage. The list

of the compounds either present or absent after 12 months storage is given in table 32.

5 10 15 20 25 30 35 40 Time [min]

0.5

1.0

1.5

2.0

2.5

3.0

7x10

Intens.

19: TIC -All MS

0 5 10 15 20 25 30 35 40 Time [min]

0.5

1.0

1.5

2.0

2.5

7x10

Intens.

19: TIC -All MS

5 10 15 20 25 30 35 40 Time [min]0

1

2

3

4

5

8x10

Intens.

6: TIC +All MS0 5 10 15 20 25 30 35 40 Time [min]

1

2

3

4

5

8x10

Intens.

6: TIC +All MS

158

Table 32- List of phenolic compounds present or absent in fruit and vegetable

samples after 12 months storage at -12º C (compounds assigned from LC-ESI-MS-

TOF runs in positive and negative ion modes); sample numbers on page 44

Compound No.

Compound Name

Molecular formula

Samples of Group I:

Compounds were absent in HR

chromatograms of these

samples after storage

Samples of Group II:

Compounds

were present in

HR

chromatograms

of these

samples after

storage

Sample No

12 caffeic acid C9H8O4 14,17

13 ferulic acid C10H10O4 40

14 isoferulic acid C10H10O4 40

26 isoliquiritigenin C15H12O4 3,6,40,31

27 formononetin C16H12O4 40

35 naringenin C15H12O5 1,34

36 butein C15H12O5 17,34

37 phloretin C15H14O5 2

39 genkwanin C16H12O5 3,6,13,18,36 42

40 biochanin A C16H12O5 33,36,38

41 luteolin C15H10O6 33,36,38

42 datiscetin C15H10O6 4,33,36,14,20, 38,41

43 kaempferol C15H10O6 4,11,33,36,14,20,38,41

44 cyanidin C15H11O6+ 11

45 eriodictyol C15H12O6 11,17,5

46 (+)-catechin C15H14O6 5,8, 33,39,25,32 41,42,3,4,17

47 (-)-epicatechin C15H14O6 33,39,25,32, 5,8 41,42, 3,4,17

48 diosmetin C16H12O6 3,7,1,4,5,8,6,2,11,40,13,15,16,17, 33, 14,20,29,38,32,31,27,37,30

49 chrysoeriol C16H12O6

3,7,1,4,5,8,6,2,11,40,13,15,16 17,33,14,20,29,33, 14,20,29,38,32,31,27,37,30

50 ellagic acid C14H6O8 4 42

51 morin C15H10O7 - 3,4

52 quercetin C15H10O7 - 3,4

53 robinetin C15H10O7 - 3,4

54 hesperetin C16H14O6 4

55 delphinidin C15H11O7+

3,7,4,5,8,2,40,13,16 22,20,29,38,34,32,23,31,26

56 (+)-taxifolin C15H12O7 16

57 (-)-gallocatechin C15H14O7 40,31,33,25 17

58 (-)-epigallocatechin C15H14O7 40,31,33,25 17

59 isorhamnetin C16H12O7 40,15,39,31,35,37,30,24

60 tamarixetin C16H12O7 40,15,39,31,35,37,30,24

61 quercetagetin C15H10O8 40,39

62 myricetin C15H10O8 40,39

63 5,7-dihydroxy-3',4',5'-trimethoxyflavone C18H16O7 - 33

64

5-caffeoylquinic acid

C16H18O9

25

3,7,4,8,12,2,10, 13,16, 17,14,36

159

65 tangeretin C20H20O7 37 3,37

66 sinensetin C20H20O7 15,41 3,33,37

67 daidzein-7-O-glucoside C21H20O9 21,27

69 Gardenin A C21H22O9 5,42

70 apigenin-6-C-glucoside C21H20O10 18,27,37

71 apigenin-8-C-glucoside (vitexin) C21H20O10 18,27,37

72 apigenin-7-O-glucoside C21H20O10 15,16,23,25 42

73 vitexin-2''-O-rhamnoside C21H20O10 15,16,25,23,26 42

74 genistein-7-O-glucoside C21H20O10 15,16,25,23 42

75 (-)-epicatechin gallate C22H18O10 41

76 (-)-catechin gallate C22H18O10 41

77 baicalein-7-O-glucuronide (baicalin) C21H18O11 27

78 luteolin-8-C-glucoside C21H20O11 40, 25, 42

79 luteolin-6-C-glucoside C21H20O11 40, 25, 42

80 luteolin-7-O-glucoside C21H20O11 40,17,33,21,34,39,12 9,25,42

81 luteolin-4'-O-glucoside C21H20O11 40,17,33,21,34,39,12 9,25,42

82 kaempferol-3-O-glucoside (astragalin) C21H20O11 40,17,33,21,34,39,12 9,25,42

83

quercetin-3-O-rhamnoside (quercitrin) C21H20O11 40,17,33,21,34,39 4,5,9, 25,42

84 epigallocatechin gallate C22H18O11 32

85 (-)-gallocatechin gallate C22H18O11 32

86

quercetin-3-O-glucoside (isoquercetin) C21H20O12 34,25,27

42,19,30,24, 3,4,5,7,17,33

87 myricetin-3-O-rhamnoside(Myricitin) C21H20O12 - 42

89 naringenin-7-O-rutinoside (naringin) C27H32O14 - 21,34,39

90 kaempferol-3-O-rutinoside C27H30O15 27 33,21,34,39

91 kaempferol-7-O-neohesperidoside C27H30O15 27 33,21,34,39

95 quercetin-3-O-rutinoside (rutin) C27H30O16 33,21,34,27 3,4,5,17,39

96

hesperetin-7-O-rutinoside (hesperidin) C28H34O15 3,4,5,17,33, 27 34,39,21

From the results shown, a large number of phenolic compounds (a total of 55)

previously identified, were absent in samples stored for 12 months at -12º C. At the

same time, the chemical composition of the sample was found to have changed

160

dramatically as apparent from the TICs shown in figure 57. Therefore, it was decided

to reinvestigate the samples using the ESI- ion trap detectors to identify further

compounds that might have survived the storage conditions.

For the experiments, a high sample concentration (40 mg/ml) was chosen to allow

detection of weak signals. Table 33 summaries the results, showing the compounds

absent or present in tandem LC-MS chromatograms. As can be seen from the data,

indeed some compounds previously not observed could be detected.

Table 33- List of compounds present and absent in tandem MS chromatograms of

samples after 12 months storage (these phenolic compounds were present in the

tandem MS chromatograms of the fresh samples)

Compound No.

Compound Name

Molecular formula

Samples Group I: compounds were present in tandem MS chromatograms of these samples after storage

Samples Group II:

compounds were

absent in tandem MS

chromatograms

of these samples after

storage

Sample No

12 caffeic acid C9H8O4 - 14,17

13 ferulic acid C10H10O4 - 40

14 isoferulic acid C10H10O4 - 40

26 isoliquiritigenin C15H12O4 6 3,40,31

27 formononetin C16H12O4 40 -

35 naringenin C15H12O5 - 1,34

36 butein C15H12O5 - 17,34

37 phloretin C15H14O5 - 2

39 genkwanin C16H12O5 - 3,6,13,18,36

40 biochanin A C16H12O5 - 33,36,38

41 luteolin C15H10O6 - 33,36,38

42 datiscetin C15H10O6 - 4,33,36,14,20, 38,41

43 kaempferol C15H10O6 - 4,11,33,36,14,20,38,41

44 cyanidin C15H11O6+ - 11

45 eriodictyol C15H12O6 - 11,17,5

46 (+)-catechin C15H14O6 - 5,8, 33,39,25,32

47 (-)-epicatechin C15H14O6 - 33,39,25,32, 5,8

48

diosmetin

C16H12O6

6, 8, 13, 16, 38, 40

3,7,1,4,5, ,2,11,15, 17, 33, 14,20,29,,32,31,27,37,30

49 chrysoeriol C16H12O6 6, 8, 13, 16, 38, 40

3,7,1,4,5, 2,11,15, 17,33,14,20,29 ,32,31,27,37,30

50 ellagic acid C14H6O8 - 4

54 hesperetin C16H14O6 - 4

55 delphinidin C15H11O7+ 3, 16, 40, 29

7,4,5,8,2,13, ,22,20,38,34,32,23,31,26

56 (+)-taxifolin C15H12O7 - 16

161

57 (-)-gallocatechin C15H14O7 - 40,31,33,25

58 (-)-epigallocatechin C15H14O7 40 33,25,31

59 isorhamnetin C16H12O7 31, 35, 37, 30, 24 40,15,39, 37

60 tamarixetin C16H12O7 31, 35, 37, 24, 30 40,15,39

61 quercetagetin C15H10O8 39 40

62 myricetin C15H10O8 39 40

64 5-caffeoylquinic acid C16H18O9 - 25

65 tangeretin C20H20O7 - 37

66 sinensetin C20H20O7 - 15,41

67 daidzein-7-O-glucoside C21H20O9 - 21,27

69 gardenin A C21H22O9 - 5,42

70 apigenin-6-C-glucoside C21H20O10 - 18,27,37

71 apigenin-8-C-glucoside (vitexin) C21H20O10 - 18,27,37

72 apigenin-7-O-glucoside C21H20O10 - 15,16,23,25

73 vitexin-2''-O-rhamnoside C21H20O10 - 15,16,25,23,26

74 genistein-7-O-glucoside C21H20O10 - 15,16,25,23

75 (-)-epicatechin gallate C22H18O10 - 41

76 (-)-catechin gallate C22H18O10 - 41

77 baicalein-7-O-glucuronide C21H18O11 - 27

78 luteoline-8-C-glucoside C21H20O11 - 40, 25, 42

79 luteolin-6-C-glucoside C21H20O11 - 40, 25, 42

80 luteolin-7-O-glucoside C21H20O11 34 12,40,17,33,21,39

81 luteolin-4'-O-glucoside C21H20O11 - 40,17,33,21,34,39,12

82

kaempferol-3-O-glucoside (astragalin) C21H20O11 17 12,40,33,21,34,39

83 quercetin-3-O-rhamnoside C21H20O11 34 12,40,17,33,21,39

84 epigallocatechin gallate C22H18O11 32

85 (-)-gallocatechin gallate C22H18O11 32

86 quercetin-3-O-glucoside C21H20O12 25 34,27

90 kaempferol-3-O-rutinoside C27H30O15 27

91 kaempferol-7-O-neohesperidoside C27H30O15 27

95 quercetin-3-O-rutinoside (rutin) C27H30O16 33,21,34,27

96 hesperetin-7-O-rutinoside C28H34O15 3,4,5,17,33, 27

162

The 17 samples of group I, listed in table 33, were selected. Each sample was

dissolved in methanol (40mg/ml) and prepared for a LC-MS run using TOF mass

spectrometer. The high resolution MS chromatograms were reinvestigated to confirm

the presence of the polyphenols. Only few molecular formulas obtained from the

reinvestigation of the m/z values in the high resolution chromatograms. Table 34

shows the suggested molecular formulas and the actual molecular formulas of the

expected polyphenols.

Table 34- High resolution mass spectrometric data, suggestions and comparison

Compound

number

Name of polyphenol

Sample

number and

ion mode

Experimental

Mass

Actual

(Molecular

Formula)

Suggested

Molecular

Formula

Error

(ppm)

Rt (min)

48 /49 diosmetin or chrysoeriol 40 (+) 301.0276 C16H13O6 C22H5O2 10 4.7

59/60 isorhamnetin or tamarixetin 24 (+) 317.1385 C16H13O7 C18H21O5 1 33.6

48 /49 diosmetin or chrysoeriol 40 (+) 301.1414 C16H13O6 C18H21O4 10 39.4

58 (-)-epigallocatechin 40 (+) 307.0971 C15H15O7 C19H15O4 10 2.3

As it is observed in table 34, the suggested molecular formulas are different from the

actual molecular formulas of the expected polyphenols. This means that none of the

polyphenols listed in table 33, exists in the mentioned samples.

This study concludes that the phenolic compounds, were absent in the HR-MS

chromatograms of samples after storage (listed in table 32), do not exist in the

samples after 12 months storage however, some were still present in other samples

after 12 months storage at -12º C. Most probably, the presence of oxygen or other

environmental factors could affect the chemical composition of the phenolic

compounds. Based on the results observed in this experiment, it is concluded that the

majority of the phenolic compounds and polyphenols are degrading under the

mentioned storage conditions however, a few of them survived in different samples

(see table 32). These results indicate that the polyphenol composition change, may

affect the change in antioxidant relative functions of the sample during storage.

163

4.9- New strategy for identification of unknown compounds

In the previous sections the most comonly occurring dietary phenolic compounds

already described in the literature, present in the samples under investigation, were

identified from chromatograms using HR-MS and tandem MS techniques. After close

inspection of the chromatograms it becomes evident that a total of 182 peaks remain

still unassigned including 15 peaks in the samples of Apple, 11 in Asparagus, 24 in

Pear, two in Lettuce, 22 in Onion, five in Banana, 31 in Orange, three in Melon, 18 in

Nectarine, 25 in Courgette, six in Cauliflower and four in Strawberry. In order to

identify these compounds or to obtain some minimum information on their chemical

structure, two further data interpretation approaches were followed. Firstly, the m/z

values of those peaks and related MS2 data were recorded separately and a list for

unknown compounds compiled. Related neutral losses for each fragment were also

calculated and recorded. Secondly, a new approach (Van Krevelen approach) was

performed for identification of those compounds.

In a tandem MS analysis, compounds typically fragment to give charged species

appearing in MSn fragment spectra and uncharged fragments not detectable in the

MSn spectra. Typically, one fragment is able to better stabilize a positive or negative

charge, depending on the mode of ionization chosen, whereas the second fragment

does not stabilize the charge, appearing as a neutral loss.

4.9.1- Neutral loss

MSn

spectra can be searched for specific fragment ions in all MSn extracted ion

chromatograms displaying all chromatographic peaks with a given m/z value or

alternatively for neutral losses of a specified m/z value in a so called neutral loss

chromatograms.

Since the fragmentation mechanisms of many classes of naturally occurring

compounds are well known and understood, this technique can be used to identify

classes of compounds by generating such neutral loss chromatograms. For example,

polyphenol glycosides provide in the negative ion mode a charged fragment of the

phenol moiety and a neutral loss of the glycosidic moiety after breaking of the

glycosidic bond. Hence, glycosides can be readily identified by the generation of

164

neutral loss chromatograms searching for the mass of 162 (C6H10O5) corresponding to

a hexose, 132 (C5H8O4) corresponding to a pentose or 146 (C6H10O4) corresponding

to a deoxyhexose such as rhamnose or fucose.

Other common neutral loss fragments frequently encountered in naturally occurring

samples include the gallate fragment at m/z 152 (C7H5O4) or the caffeoyl fragment at

m/z 162 and 180 or the quinic acid fragment at m/z 192.

As illustration, two selected neutral loss chromatograms are shown in figures 56 and

57. From the data a series of chromatographic peaks can be tentatively assigned as

glycosides or gallates respectively.

165

1: Constant Neutral Loss: 162.0

0

2

4

6

4x10

Intens.

0 5 10 15 20 25 30 35 40 Time [min]

UV, 4.9min #735,

134.0

-221.1159.8

-195.2

174.9

-180.2

-162.2

216.8

-138.2

234.8

-120.3

264.9

-90.2 294.8

-60.3

192.9

-162.2 -MS2(355.1), 4.9min #251

0.0

2.5

5.0

7.5

10.0

12.5

Intens.

[mAU]

0

20

40

60

80

100

Intens.

[%]

100 200 300 400 500 600 m/z

200 220 240 260 280 300 320 340 360 380 Wavelength [nm]

Figure 56- Constant neutral loss chromatogram for the mass of 162 (C6H10O5)

corresponding to a hexose in sample 1 (Apple peel from New Zealand )

166

4: Constant Neutral Loss: 132.0

0

1

2

3

4

5

6x10

Intens.

0 5 10 15 20 25 30 35 40 Time [min]

UV, 11.9min #1782,

178.8

-254.4

-132.4

300.9

-132.4 -MS2(433.2), 11.9min #608

-10

0

10

20

Intens.

[mAU]

0

20

40

60

80

100

Intens.

[%]

100 200 300 400 500 600 m/z

200 220 240 260 280 300 320 340 360 380 Wavelength [nm]

Figure 57- Constant neutral loss chromatogram for the mass of 132 (C5H8O4)

corresponding to a pentose in sample 4 (Apple peel from Argentina)

167

4.9.2- Van Krevelen analysis

Marshall and colleagues developed innovative interpretation strategies for

characterization of petroleum products and crude oils where the Fourier transform ion

cyclotron resonance mass measurements (FTIRC-MS) data, comprise many thousands

molecular ions (257). These data interpretation strategies, provide powerful

visualization and graphical display tool to further understand highly complex data.

Such graphical visualizations facilitate the identification of patterns and trends within

the data sets, leading to structural models of the underlying chemistry (257).These

methods have been applied also to humic substances (258) and have been reviwed and

discussed by Koch (259) and Marshall (260) and for wine (261) and recently by our

group to black Tea thearubigins (256, 262) as the only dietary materials investigated

by HR-MS (263). Accordingly, we here apply them for the first time to other dietary

samples.

Commonly two main interpretation strategies are followed: Firstly, the Van Krevelen

analysis and secondly, the Kendrick analysis (264).

The Van Krevelen analysis, otherwise known as elemental ratio analysis, displays

HR-MS data in a multidimentional plot, where elemental ratios are calculated from

the molecular formulas, calculated from the experimental HR-MS data. Most

commonly, the H/C and O/C ratios are calculated and both ratios are plotted in a two

dimentional graph against each other (265, 266). Thereby, each molecular formula

results in a single data point on a two dimentional Van Krevelen plot. In a third

dimentional, it is possible to add the intensity of the observed peak, corresponding to

a given molecular formula or a third elemental ratio (256). A set of elemental ratios

for a given peak is considered as characteristic for a certain class of compounds, e.g.

in a carbohydrate H/C is ~2 and O/C ~1.

Elemental ratio boundries for selected classes of natural products have been published

by the group of Schmitt-Kopplin (267) and are shown in Figure 58.

168

Figure 58 - Example of Van Krevelen representation, showing the

positioning of various classes of molecules according to their H/C

and O/C ratios (267)

For this project it was, however, required to expand on these available boundaries and

include boundary values for other common classes of natural products in particular

terpenes and polyphenols.

For this purpose, a representative selection of molecular formulas for a total of 52

terpenes (268) and 99 commonly occurring dietary phenolic compounds and

polyphenols (148) were collected. For each list, the O/C and H/C ratio were

calculated and the values were scatter plotted. The elemental ratio boundaries were

defined for terpenes and polyphenols using statistical software JMP 8.2 in order to

show the area where these class of compounds have the most intensity in a scatter plot

matrix (Figure 59, 60).

169

Figure 59- Van Krevelen representation with density ellipse for polyphenols

Figure 60- Van Krevelen representation with

density ellipse for terpenes

The software enables to draw an ellipse that contains the specified mass of points. The

density ellipsoid is a graphical indicator of the correlation between two variables and

it is computed from the bivariate normal distribution fit to the X and Y variables. The

bivariate normal density is a function of the means and standard deviations of the X

and Y variables and the correlation between them.These ellipses are both density

contours and confidence curves. As confidence curves, they show where a given

percentage of the data is expected to lie, assuming the bivariate normal distribution.

Figure 61 shows the two density ellipses developed for the polyphenols with sugar

moities and without sugar moities separately, overlap.

170

Figure 61- Density ellipse for the phenolic and polyphenolic compounds;

(a): density ellipse for the polyphenols with sugar moieties

(b): density ellipse for the polyphenols without sugar moieties

(c): (a) and (b) overlap

The obtained intervals for polyphenols and terpenes were added to the Van Krevelen

representation (see Figure 62).

Figure 62- The improved Van Krevelen representation for all

classes of compounds including polyphenols and terpenes

terpenes

a b

c

171

With sufficient elemental ratio data, boundaries for H/C and O/C ratios can be defined

for individual classes of naturally occurring compounds: while any data point that lies

within the elemental ratio boundaries defined for a certain class of compounds might

correspond to this class of compound, it does not inevitably do so. However, if a data

point falls outside the elemental ratio boundaries, it certainly does not belong to this

class of compounds (265).

The presence of a datapoint within the elemental ratio boundaries defined in the Van

Krevelen diagram, allows tentative assignment of a compound to a given class of

natural products. In principle, data analysis can be expanded to allow correct choice

of molecular formulas, if more than one molecular formula suggestion is given in the

computation routine. If a choice of data points exsists, it is suggested here that the

Van Krevelen diagram allows selection of a likely class of natural products in

particular, if one data point lies within elemental ratio boundaries and others do not.

Therefore this technique adds a welcome addition to Fiehns seven golden rules in

correct assignment of molecular formulas.

This principle is illustrated using the following examples:

Example 1:

In the tandem MS chromatogram of sample 4 (Apple peel from Argentina), a peak at

m/z 509.3 was observed at a retention time of 33.1 min in positive ion mode. Tandem

MS data revealed the following fragmentation. In the MS2 spectrum, a fragment ion at

m/z 377 corresponding to a neutral loss of m/z 132 was observed, which could be

assigned to a loss of C5H8O4 corresponding to a pentose. To obtain information about

the structure of the excluding compound, the HR-MS chromatogram of this sample

was investigated by developing extracted ion chromatogram for the m/z value of the

fragment ion and finding the related peak. The HR-MS data, gave an experimental

value of this fragment ion at m/z 377.0836 in the positive ion mode. A molecular

formula search, suggested a molecular formula of C18H17O9 with an error of 8.2 ppm

and mΣ value of 9.3 (see datapoint 24, table 35). The elemental H/C and O/C ratio for

the given molecular formula is characteristic for a polyphenol (0.7 ≤ H/C ≤ 1.5 and

0.07 ≤ O/C ≤ 0.6). The given molecular formula results in a data point in a scattered

172

plot for (H/C versus O/C). The position of this data point compared with the Van

Krevelen representation, which shows that the data point lays in the elemental ratio

boundry for polyphenols (see figure 65, 66). This comparison provided evidence,

suggesting the assignment of the given molecular formula to a polyphenol aglycon

with a formula of C13H9O5 bound to a pentose.

Example 2:

In the tandem MS chromatogram of sample 1 (Apple peel from New Zealand), a peak

at m/z 473.1 was observed at a retention time of 1.4 min in negative ion mode.

Tandem MS data revealed the following fragmentation. In the MS2 spectrum, a

fragment ion at m/z 340.9 corresponding to a neutral loss of m/z 132 was observed,

which could be assigned to a loss of C5H8O4 corresponding to a pentose. To obtain

information about the structure of the excluding compound, the HR-MS

chromatogram of this sample was investigated by developing extracted ion

chromatogram for the m/z value of the fragment ion and finding the related peak.The

HR-MS data, gave an experimental value of this fragment ion at m/z 341.1117 in the

negative ion mode. A molecular formula search, suggested a molecular formula of

C12H21O11 with an error of 8.1 ppm and mΣ value of 10.2 (see datapoint 4, table 35).

The elemental H/C and O/C ratio for the given molecular formula is characteristic for

a carbohydrate (H/C is ~2 and O/C ~1). The given molecular formula results in a data

point in a scattered plot for (H/C versus O/C). The position of this data point

compared with the Van Krevelen representation, which shows that the data point lays

in the elemental ratio boundry for carbohydrates (see Figure 63, 64). This comparison

provided evidence, suggesting the assignment of the given molecular formula to a

carbohydrate compound for a pentose and a heptose.

Example 3:

In the tandem MS chromatogram of sample 7 (Apple peel from Italy), a peak at m/z

567.1 was observed at a retention time of 14.3 min in negative ion mode. Tandem MS

data revealed the following fragmentation. In the MS2 spectrum, a fragment ion at m/z

272.9 corresponding to a neutral loss of m/z 162 was observed, which could be

assigned to a loss of C6H10O5 corresponding to a hexose. To obtain information about

the structure of the excluding compound, the HR-MS chromatogram of this sample

173

was investigated by developing extracted ion chromatogram for the m/z value of the

fragment ion and finding the related peak. The HR-MS data, gave an experimental

value of this fragment ion at m/z 273.0781 in the negative ion mode (see datapoint 7,

table 35). A molecular formula search, suggested a molecular formula of C15H13O5

with an error of 4.7 ppm and mΣ value of 15.5. The elemental H/C and O/C ratio for

the given molecular formula is characteristic for a polyphenol (0.7 ≤ H/C ≤ 1.5 and

0.07 ≤ O/C ≤ 0.6). The given molecular formula results in a data point in a scattered

plot for (H/C versus O/C). The position of this data point compared with the Van

Krevelen representation, which shows that the data point lays in the elemental ratio

boundry for polyphenols (see figure 65, 66). This comparison provided evidence,

suggesting the assignment of the given molecular formula to a polyphenol most

probably pheloretin conjugated to a hexose.

Should a selection of molecular formulas exist, of which none meets the elemental

ratio boundary selection criteria, it is suggested here that, the basic assumption on

elements present in the molecular formula determination routine is incorrect and a

recalculation of molecular formulas must be performed, assuming the presence of

different elements. A full recalculation and reinterpretation of the data was outside the

scope of this thesis.

A summary of the findings on revealing unknown compounds in Apple samples is

presented in table 35 for the Apple peel samples and in table 36 for Apple flesh

samples.

Since H/C and O/C ratio in polyphenols fall in a specific range (0.7 ≤ H/C ≤ 1.5 and

0.07 ≤ O/C ≤ 0.6), therefore among the molecular formulas suggested, three different

categories were recognized and represented in white, yellow and blue in table 35 and

36 which are described below:

1- The molecular formulas shown in white cells, are suggested molecular formulas,

that do not meet the elemental ratio boundary selection criteria for polyphenols.

2- The molecular formulas shown in yellow cells, are suggested molecular formulas

that meet the elemental ratio boundary selection criteria for polyphenols but, their

formulas do not match or do not exist in the list of the polyphenols investigated.

3- The molecular formulas shown in blue cells, are suggested molecular formulas

that meet the elemental ratio boundary selection criteria for polyphenols and their

formulas match with the polyphenols investigated.

174

The comparisons to find the position of the suggested molecular formulas with the

Van krevelen representation are presented in figure 63 and 64 for Apple peel samples

and in figure 65 and 66 for Apple flesh samples.

The term suspicious formula, in the table 35 and 36 indicates that:

1- The suggested molecular formula, lies outside the elemental ratio boundaries

defined for individual classes of naturally occurring compounds in the Van Krevelen

representation (e.g., data points 11, 15 and 17 in table 35).

2- The data point lies within an elemental ratio boundary defined for an individual

class of naturally occurring compounds but, the related formula match with the other

class of compounds e.g., in table 35 data points 9 (C22H27O3) and 18 (C23H23O2) could

be polyphenols but these data points lie in the boundry for terpenes or the data point

22 (C15H9O7) and 10 (C17H11O3) which lie within the elemental ratio boundry for the

polyphenols but, the suggested molecular formula for this data point does not meet the

elemental ratio boundry selection criteria for the polyphenols. Another example is

when the data point lies within an elemental ratio boundary defined for an individual

class of naturally occurring compounds but, the related formula does not match with

the molecular formulas of the compounds of that class of natural compounds e.g., data

point 20 (C19H37O10) in table 35 lies in the class of amino acids which is not realistic

because the molecular formula must contain N.

Therefore for the data a recalculation of the molecular formula using different

elemental compositions is recommended. For example, a set of recalculated formulas

for the data point 9 (C22H27O3) in table 35 assuming the presence of additional

nitrogens are C6H27N8O8, C7H23N12O4, C8H19N16, C10H31N2O10, C11H27N6O6 and

C12H23N10O2 which are all nonsensible. Once the presence of the element S is

considered in the recalculation for this data point then C19H32O3S is suggested in 3.1

ppm which is acceptable.

A full recalculation and reinterpretation of the data was outside the scope of this

thesis.

175

Table 35- Results with the unknown compounds in Apple peels

Data point number

Molecular

Formula

Possible

Class of

natural

compounds

Experimental

m/z value of

fragment ion

in MS2

Theoretical

m/z value

of

fragment

ion in MS2

Error

(ppm)

m∑ Ion

mode

Sample

number

3

C8H11O6 suspicious

formula

203.0533 203.0550 8.3 520 + 1

4 C12H21O11 carbohydrate 341.1117 341.1089 8.1 10.2 - 1

3

C8H11O6 suspicious

formula

203.0537 203.0550 6.4 167 + 7

4 C12H21O11 carbohydrate 341.1093 341.1089 1.2 14 - 7

5

C18H31O10 suspicious

formula

407.1944 407.1922 5.4 14.6 - 7

6 C17H33O4 fatty acid 301.2379 301.2384 1.7 51 - 7

7 C15H13O5 pheloretin 273.0781 273.0768 4.7 15.5 - 7


9

C22H27O3 suspicious

formula

339.1989 339.1965 7.1 23.8 - 7

10

C17H11O3 suspicious

formula

263.0699 263.0702 1.1 106 + 3

11

C20H15O2 suspicious

formula

287.1089 287.1066 8.0 8.5 + 3

12

C18H21O4 suspicious

formula

301.1407 301.1434 9.0 14.2 + 3

13 C24H25O6 polyphenol 409.1628 409.1645 4.2 36.8 + 3

15

C23H21O2 suspicious

formula

329.1562 329.1536 7.9 659 + 3

16

C17H23O6 suspicious

formula

323.1511 323.1489 6.8 610 + 3

17

C8H7O7 suspicious

formula

215.018 215.0186 2.8 22.3 + 4

18

C23H23O2 suspicious

formula

331.1713 331.1692 6.3 79 + 4

19

C22H21O4 suspicious

formula

349.1425 349.1434 2.6 2.6 + 4

20

C19H37O10 suspicious

formula

425.2424 425.2392 7.5 7.5 - 4

21

C7H11O6 suspicious

formula

191.0560 191.0550 5.2 5 + 4

22

C15H9O7 suspicious

formula

301.0359 301.0353 2.0 1.7 - 4

23 C19H17O5 polyphenol 325.1088 325.1070 5.5 24.6 + 4

176

Table 35- Results with the unknown compounds in Apple peels

Data point number

Molecular

Formula

Possible

Class of

natural

compounds

Experimental

m/z value of

fragment ion

in MS2

Theoretical

m/z value

of

fragment

ion in MS2

Error

(ppm)

m∑ Ion

mode

Sample

number

24 C18H17O9 polyphenol 377.0836 377.0867 8.2 9.3 + 4

25

C25H13O4 suspicious

formula

377.0812

377.0819

1.8 44

-

4

26

C20H37O2 suspicious

formula

309.2776 309.2799 7.4 16

-

4

28

C31H21O suspicious

formula

409.1617 409.1586 7.6 28.6 + 5

177

Figure 63- Van Krevelen plot of the H/C versus O/C ratio for

unknown compounds in Apple peel samples

Figure 64- Van Krevelen representation combined with the

Scatter plot of the H/C versus O/C ratio of the unknown

compounds in Apple peel samples

178

Table 36- Suggested molecular formulas for the unknown compounds for

Apple flesh samples

Data

point

number

Molecular

formula

Possible

Class

Experimental

m/z value of

fragment

ion in MS2

Theoretical

m/z value

of

fragment

ion in MS2

Error

(ppm)

m∑ Ion

mode

Sample


2 C12H7O4 suspicious

formula

215.033 215.0349 8.8 190 - 6


formula

215.033 215.0349 8.8 191 - 8


formula

409.1628 409.1645 4.2 35 + 9

5 C15H13O5 naringenin-

butein

273.0756 273.0757 0.4 83 + 12

179

Figure 65- Van Krevelen plot of the H/C versus O/C ratio

for unknown compounds in Apple flesh samples

Figure 66- Van Krevelen representation combined with the Scatter plot of the H/C

versus O/C ratio of the un known compounds in Apple flesh samples

180

5- Conclusion

In this work, 42 samples from peels and fleshes obtained from selected fruits and

vegetables purchased from local markets in Bremen, Germany were prepared by

methanolic extraction of the samples. A high-performance liquid chromatographic

(HPLC) separation method with diod array detector (DAD) and mass spectrometric

(MS) detection was developed to determine the presence of the most commonly

occurring phenolic and polyphenolic compounds in the samples (148). The HPLC was

interfacing an ion trap mass spectrometer or a high resolution mass spectrometer. The

tandem MS data were investigated for the assignment of the compounds and

comparison with the fragmentation patterns of the most commonly occuring dietary

polyphenols (148). The presence of the assigned compounds were confirmed by

investigation in the high resolution mass spectra. Identification was based on MS data,

retention time, UV and mass spectra of commercial standards where they were

available. However, UV detector had reduced sensitivity.

In this study, the compounds were identified as aglycones and glycosylated

derivatives of aglycones. As observed in the LC-MS data, a total of 25 polyphenols

were found to be present in the Apple samples, 16 in Asparagus samples, 11 in Carrot

samples, 19 in Pear samples, four in Lettuce samples, three in Banana samples, six in

Onion samples, 17 in Orange samples, 17 in Nectarine samples, nine in Melon

samples, 13 in Courgette samples, 11 in Cauliflower sample and 11 in Strawberry

sample based on tandem MS data and comparison with the fragmentation patterns of

the most commonly occuring dietary polyphenols (148).

Among the polyphenols were found to be present in the Apple samples, compounds



Among the polyphenols were found to be present in the Pear samples, compounds

5,7-dihydroxy-3',4',5'-trimethoxyflavone 63, sinensetin 66, (-)-epigallocatechin 58

and kaempferol-7-O-neohesperidoside 91 have not been reported in the literature as

Pear secondary metabolites.

181

Among the polyphenols were found to be present in the Orange samples, compounds

kaempferol-3-O-rutinoside 90 and kaempferol-7-O-neohesperidoside 91 have not

been reported in the literature as Orange secondary metabolites.

Among the polyphenols were found to be present in the Nectarine samples,

compounds luteolin-7-O-glucoside 80, luteolin-4'-O-glucoside 81, kaempferol-3-O-

glucoside 82 and quercetin-3-O-rhamnoside 83 have not been reported in the

literature as Nectarine secondary metabolites.

Among the polyphenols were found to be present in the Cauliflower samples,

compound sinensetin 66 has not been reported in the Cauliflower in the literature as

Cauliflower secondary metabolite.

Among the polyphenols were found to be present in the Strawberry sample,

compounds genkwanin 39, apigenin-7-O-glucoside 72, vitexin-2''-O-rhamnoside 73,

genistein-7-O-glucoside 74, luteolin-7-O-glucoside 80, luteolin-4'-O-glucoside 81,

quercetin-3-O-rhamnoside 83 have not been reported in the literature as Strawberry


Other phenolic compounds and polyphenols were reported to be present in the fruits

and vegetables in the literature, but not found to be present in the samples analysed in

this study, were listed as well.

More than 60 phenolic and polyphenolic compounds were found in the samples

analysed in this study. This amount of polyphenols in terms of number in much less

than what has been reported in the literature on the same fruits and vegetables

analysed. This finding makes screening based on epidemiological studies more

straight forward than expected previously, since less phenolic compounds need to be

included in screening of potential biological studies.

After close inspection of the chromatograms, a total of 182 peaks remain still

unassigned. Two further data interpretation approaches were followed. Firstly, the m/z

values of those peaks and related MS2 data were recorded separately and a list for

unknown compounds compiled. Related neutral losses for each fragment were also

calculated and recorded. Secondly, a new approach (Van Krevelen approach) was

performed for identification of those compounds.

182

A close inspection was conducted to study the polyphenolic composition changes in

fruit and vegetable samples stored at -18° C for one year. It was concluded that the

majority of the phenolic compounds and polyphenols degrade under the mentioned

storage conditions however, a few of them survived in different samples. These

results indicate that the polyphenol composition change, may affect the biological

effects of long term frozen fruit and vegetables.

183

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