The Development and Improvement of Instructions

PROCESSING TECHNIQUES AND PRODUCTION SYSTEMS ON PHYTOCHEMICAL

PROPERTIES IN FRUITS, VEGETABLES AND THEIR PROCESSED PRODUCTS

A Thesis

JUNYI WANG

Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

Chair of Committee, Bhimanagouda S. Patil Committee Members, G. K. Jayaprakasha Joseph M. Awika Head of Department, Steve Searcy

May 2019

Major Subject: Food Science and Technology

Fruits and vegetables contain substantial amounts of phytochemicals that play crucial roles in the prevention of several chronic diseases. However, there is a general lack of insight among the researchers regarding the impacts of processing techniques, diversity among varieties, and other similar such factors on the overall metabolic profiles of these fruits and vegetables. The recent use of advanced metabolomic approaches in assistance with powerful statistical tools to characterize the entire metabolic composition has been gaining significant momentum in the areas of food science. In the first study, comprehensive metabolomics was combined with chemometric approaches to evaluate the impact of processing techniques on the physiochemical attributes, phytochemical contents and antioxidant activities of 21 commonly consumed vegetables. The results suggested that the purple baby carrot blended juice had the highest total phenolics and DPPH value. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-

DA) characterized kaempferol glycosides and betaxanthins attached with amino acids, which, were significantly affected by the processing techniques. In the second study, the chemometric characterization of 30 commercial thermal and cold pressed juices were investigated. Significant variations were observed for metabolic compositions in juices with diverse ingredients. Kaempferol and quercetin glycosides, decarboxylated betalains, and quercetin derivatives were found to be the representative metabolites in classifying the samples. In the third study, the solvent extract efficiency and antioxidant activities in conventionally- and organically-grown beets (red and golden colored) were assessed by using a comprehensive range of solvents. The results demonstrated that red beet extracted with methanol with or without ascorbic acid had the highest betanins, while the water-based extracts had the lowest betanins. Golden colored beet extracted with methanol: ascorbic acid: water (18:80:2, v/v/v) had the highest vulgaxanthin I. Meanwhile, the Ultra-high-

ii performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-

MS) identified 25 phytochemicals in conventional red-, 20 in organic red-, 6 in conventional golden-, and 6 in organic golden-colored beet extracts, respectively. In summary, these results highlight the potential of metabolomic approaches in phytochemical profiling of vegetables grown under diverse production systems and their juices processed through different techniques.

iii DEDICATION

I would like to dedicate this dissertation and my entire academic experience to my family who taught me the value of education. To my father, Wenbo Wang, who always supported, encouraged, and motivated me. I owe my entire education to his advice and motivation. I know it would be impossible for me to be as selfless person as he is, but I will try my best. To my mother,

Haixia Zheng for her love, patience, and encouragement.

iv ACKNOWLEDGEMENTS

I would like to thank my committee chair, Dr. Bhimanagouda S. Patil, and my committee members, Dr. G.K. Jayprakasha, Dr. Joseph M. Awika, and Dr. Stephen Talcott for their guidance and support throughout the course of this research.

Thanks also go to my friends: Kevin, Dora, Tadesse, Cory, Abby, and colleagues: Diwas,

Varsha, Singh, Deepak, Pratibha, Rita, Drishti, Jose, Jisun and the department faculty and staff for making my time at Texas A&M University a great experience. Finally, thanks to my mother and father for their encouragement, patience, and love.

v CONTRIBUTORS AND FUNDING SOURCES

Contributors

This work was supervised by a thesis committee consisting of Professor Bhimanagouda S.

Patil and Joseph M. Awika of the Department of Nutrition and Food Science and Professor(s) G.K.

Jayaprakasha of the Department of Horticultural Sciences.

All work conducted for the thesis was completed by the student independently.

Funding source

This study was supported by the USDA-NIFA-SCRI- 2017-51181-26834 through the

National Center of Excellence for Melon at the Vegetable and Fruit Improvement Center of Texas

A&M University.

vi NOMENCLATURE

AA Ascorbic Acid

ABTS 2,2’Aazinobis (3-etylbenzothiszoline-6-sulphonic acid)

Cyclo-DOPA Cyclo-dopa 5-O-glucoside

DPPH 2,2-Diphenyl-1-(2,4,6-trinitrophenyl) Hydrazyl

FC Folin Ciocalteu

HPLC High Performance Liquid Chromatography

ICP-AES Inductively Coupled Plasma Atomic Emission Spectroscopy

L-DOPA L-3,4-dihydroxyphenylalanine

LC-MS Liquid Chromatography Mass Spectrometry

TAA Total Ascorbic Acid

TCEP Tris (2-carboxythyl) Phosphine Hydrochloride

TP Total Phenolics

PCA Principal Component Analysis

PLS-DA Partial Least Square Discriminant Analysis

VIP Variable Importance in Projection

vii TABLE OF CONTENTS

Page

ABSTRACT ...... ii

DEDICATION ...... iv

ACKNOWLEDGEMENTS ...... v

CONTRIBUTORS AND FUNDING SOURCES ...... vi

NOMENCLATURE ...... vii

TABLE OF CONTENTS ...... viii

LIST OF FIGURES ...... xii

LIST OF TABLES ...... xiii

1. INTRODUCTION ...... 1

2. REVIEW OF LITERAUTRE ...... 5

2.1. Effect of solvent types on betalain compounds ...... 5 2.2. Effect of processing techniques on phytochemical properties ...... 5 2.3. Variation of phytochemicals in fruits and vegetables ...... 8 2.4. Using UPLC-QTOF-HR-MS to identify phytochemicals ...... 10 2.5. Metabolomics combined with chemometrics in food analysis ...... 11

3. COMPREHENSIVE METABOLOMICS COMBINED CHEMOMETRICS

APPROACH TO EVALUATE THE IMPACT OF THREE PROCESSING

viii TECHNIQUES ON THE PHYTOCHEMICAL PROFILES AND ANTIOXIDANT

ACTIVITIES IN COMMONLY CONSUMED VEGETABLES ...... 14

3.1. Materials and methods ...... 17 3.1.1. Chemicals ...... 17 3.1.2. Sample preparation ...... 17 3.1.3. Instrumental color attributes ...... 18 3.1.4. Targeted phytochemicals quantification ...... 18 3.1.5. Estimation of total phenolics ...... 19 3.1.6. Antioxidant activity ...... 21 3.1.7. Data processing and chemometrics analysis ...... 22 3.2. Results and discussions ...... 22 3.2.1. Effect of household processing techniques on color attributes ...... 22 3.2.2. Variation in phytochemical concentration under three processing techniques ...... 23 3.2.3. Influence of household processing techniques on total phenolics ...... 24 3.2.4. Identification of bioactive compounds in 21 various vegetables processed by three juicing techniques by UHPLC–QTOF-MS analysis ...... 26 3.2.5. Effect of household processing techniques on DPPH and ABTS radical scavenging activities ...... 28 3.2.6. Inhibition of α-amylase enzymes ...... 30 3.2.7. Chemometrics-based analysis in discriminating phytochemicals profiles under three processing techniques ...... 30 3.3. Conclusions ...... 32

4. CHEMOMETRIC CHARACTERIZATION OF 30 COMMERCIAL

THERMAL AND COLD PROCESSED JUICES USING UPLC-QTOF-HR-MS

FINGERPRINTS ...... 41

4.1. Materials and methods ...... 44 4.1.1. Juice samples ...... 44 4.1.2. Chemicals and reagents...... 44 4.1.3. Color measurements...... 44 4.1.4. pH and soluble solid measurements ...... 45

ix 4.1.5. Determination of ascorbic acid, total ascorbic acid, and nitrate in commercial juices ...... 45 4.1.6. Sample preparation for total phenolics and antioxidant activities ...... 45 4.1.7. Identification of phenolics by UPLC-HR-ESI-QTOF-MS ...... 47 4.1.8. Statistical analysis ...... 48 4.2. Results and discussion ...... 49 4.2.1. Variation in color attributes, brix, and pH ...... 49 4.2.2. Influence of juice ingredients and processing techniques on ascorbic acid, total ascorbic acid, and nitrate ...... 50 4.2.3. Free radical scavenging activity and total phenolics ...... 51 4.2.4. Pearson correlation analysis for variables ...... 54 4.2.5. Untargeted metabolomics analysis in commercial juice samples ...... 55 4.2.6. Influence of processing techniques on phenolic compounds ...... 56 4.2.7. Influence of production system on phenolic compounds ...... 59 4.3. Conclusion ...... 60

5. UPLC-QTOF-MS FINGERPRINTING COMBINED WITH CHEMOMETRICS

TO ASSESS THE SOLVENT EXTRACTION EFFICIENCY AND ANTIOXIDANT

ACTIVITIES OF BEETROOT (BETA VULGARIS) ...... 68

5.1. Material and Methods...... 70 5.1.1. Plant materials ...... 70 5.1.2. Chemicals ...... 70 5.1.3. Sample preparation for mineral analysis...... 71 5.1.4. Extraction of betalains from beetroots ...... 71 5.1.5. Purification of betanin by flash chromatography...... 72 5.1.6. Quantification the major betalains by HPLC ...... 72 5.1.7. Total phenolics, DPPH, and ABTS radical scavenging activity ...... 73 5.1.8. Identification of phytochemicals by UHPLC-QTOF-MS ...... 73 5.1.9. Statistical and chemometric analysis ...... 75 5.2. Results and Discussion ...... 75 5.2.1. Differences in mineral contents of conventional and organic beets ...... 75 5.2.2. Identification of phytochemicals from beetroots by UHPLC-QTOF-MS ...... 76 5.2.3. Variation in betalains in conventional and organic red and golden beets measured by HPLC ...... 77

x 5.2.4. Influence of solvent combination on total phenolics and radical scavenging activities ...... 81 5.2.5. Chemometrics-based approach to identify the influence of extraction solvent on phytochemical profiles ...... 84 5.3. Conclusion ...... 87

6. SUMMARY AND CONCLUSION ...... 96

REFERENCES ...... 99

APPENDIX A TABLES FOR ADDITIONAL INFORMATION ...... 117

APPENDIX B FIGURES FOR ADDITIONAL INFORMATION ...... 126

xi LIST OF FIGURES

Page

Figure 1. The (A) total phenolics and (B) α-Amylase inhibitory activity of 21 vegetables processed by three techniques ...... 38

Figure 2. The (A) ABTS and (B) DPPH scavenging activity of 21 vegetables processed by three techniques ...... 39

Figure 3. Relative abundance of significantly changed metabolites are presented as box- and-whisker plot in (A) kale and (B) beet processed samples ...... 40

Figure 4. OPLS-DA score plot and heatmap based on LC-MS profiling of juice samples obtained from thermal and cold processed techniques ...... 66

Figure 5. PLS-DA-3D score plot shows the antioxidant activities and total phenolics present in 30 commercial juice samples from (A) kale, (B) beet and (C) melon ...... 67

Figure 6. UV and UPLC chromatograms of (A, B) red beet and (C, D) golden beet, with mass spectra of betalains of (E–H) red beet and (G–H) golden beet obtained by HR-ESI-QTOFMS analysis in positive ionization mode...... 90

Figure 7. Total phenolics, plus DPPH and ABTS radical scavenging activity of (A) conventional and (B) organic red beets extracted with twenty different solvent combinations (see Table S1)...... 91

Figure 8. Total phenolics, plus DPPH and ABTS radical scavenging activity of (A) conventionally and (B) organically grown golden beets extracted with twenty solvent combinations (see Table S1)...... 92

Figure 9. Betalain biosynthetic pathway and relative contents of main metabolites in conventionally and organically grown red and golden beet extracts...... 93

Figure 11.Chemical structures of (A) betaxanthins and (B, C) betacyanins present in conventional and organic beets. The number in parenthesis of each compound matches Table 7...... 95

xii LIST OF TABLES

Page

Table 1. Identification of bioactive compounds from 21 processed vegetables using UPLC- HR-ESI-QTPF-MS...... 33

Table 2. Levels of total ascorbic acid (TAA), and nitrate contents of processed vegetable samples...... 37

Table 3. Results* for ascorbic acid, total ascorbic acid, and nitrate content in 30 commercial juices...... 61

Table 4. Pearson’s correlation coefficients (r) of color parameters, phytochemical contents, and antioxidant activities in commercial kale, beet, and melon juices...... 62

Table 5. Characteristic marker compounds identified by UPLC-HR-MS in various juice samples...... 63

Table 6. Levels of betanin, isobetanin, vulgaxanthin I, and valine-betaxanthin in beet extracts...... 88

Table 7. Identified phytochemicals found in conventionally and organically grown red and golden beets...... 89

xiii 1. INTRODUCTION

Fruits and vegetables consist of several phytochemicals that are a vital part of human diet and nutrition. Given these health-promoting characteristics, some fruits and vegetables are even considered “functional food” by the consumers (Yahia, 2017). Although fruits and vegetables have mounting health benefits, Americans only consume 1.8 cups of fruits and vegetables per day, which is far below the recommended amount (4.5 cups) (Rekhy & McConchie, 2014). Therefore, food manufacturers created beverages with a wealth of functional ingredients to cater consumer needs for “convenient, palatable and health-beneficial” products.

Recently, the general public are more interested in consuming phytochemical compounds derived from food products due to their health-promoting potentials. The use of postharvest processing strategies in retaining and promoting the nutraceutical properties of phytochemicals in processed fruit and vegetable products have become an area of key interest for many researchers

(Tiwari & Cummins, 2013). The generally accepted hypothesis was that most of these processing techniques induce rapid enzymatic depletion of natural antioxidants as a result of cellular disruption which allows the contact between substrates and enzymes and lowers the antioxidant concentrations and activities in comparison to the raw samples. The household juicing techniques that are used to extract phytochemicals are generally categorized into blending, centrifugal juicing, and low-speed juicing, based on the type of juicer used. Blenders which are generally used for making smoothies, have blades that chop raw materials to the desired consistency and the pitch of the blades create a kind of tornadic action which circulates the chopped materials into pastes. High- speed centrifugal juicer contains a flat blade disk rotating at high speeds, above which the fruits and vegetables are grounded and filtered. Low-speed juicers employ horizontal helical screws that squeeze juice from the raw materials at low speed and high efficiency (M.-J. Kim, Kim, Kang,

1 Kwon, Jun, Choi, et al., 2015). Few researches have evaluated the effect of household juicers on quality, free radical scavenging activity, and phytochemical stability, either on a single vegetable or fruit processed products (M.-J. Kim, et al., 2015) (Pyo, Jin, & Hwang, 2014). However, a thorough study on effect of diverse juice processing techniques on phytochemical contents, compositions, and antioxidant activities of several vegetables is required to assay these variables.

Among all the processing techniques, thermal processing is considered the most common technique for processing fruit and vegetable juices due to its convenience and low cost of operation

(Odriozola-Serrano, Soliva-Fortuny, Hernández-Jover, & Martín-Belloso, 2009) (Jiménez-

Sánchez, Lozano-Sánchez, Segura-Carretero, & Fernández-Gutiérrez, 2017). However, thermal processing may have detrimental effects on physical textures, color attributes, sensory qualities and nutritional values of food products. Additionally, increasing consumer demand for safe and naturally processed foods, have intrigued researchers and manufacturers to develop techniques that will have minimal impact on the overall qualities of the processed foods (Bhat & Stamminger,

2015). As a result, alternatives to thermal processing are being sought by food industries. In order to produce food products with desirable sensory characteristics, improved nutritional values, reduced microbial activation, and enhanced health-promoting functionalities, a wide variety of non-thermal technologies, such as high pressure processing (HPP), high pressure homogenization

(HPH), irritation, pulsed electric files, ultrasound, supercritical CO2, ozone and oscillating magnetic field technologies have been used by food industries (Barba, Mariutti, Bragagnolo,

Mercadante, Barbosa-Cánovas, & Orlien, 2017a) (Knorr, Ade-Omowaye, & Heinz, 2002) (Pereira

& Vicente, 2010). Though the non-thermal processing treatments seem less detrimental than the thermal techniques, the effects are greatly influenced by the food matrix. Therefore, a comprehensive study concerning the effects that these techniques exert on the phytochemical

2 profiles and antioxidant activities is essential for food manufacturers to design and optimize technological parameters to produce products with balanced quality and sensorial parameters.

Beetroot (Beta vulgaris rubra) have been widely used as a natural food pigment and are now ubiquitously added in food products that include yogurts, ice creams, candies, and chewing gums (Chaitanya Lakshmi, 2014). Betalains are major phytochemicals widely found in beetroots and can be divided into red-violet betacyanins and yellow-orange betaxanthins based on the addition of betalamic acid residue attached to the main structure. Numerous studies have shown that betacyanin and betaxanthin have strong antioxidant and anti-inflammatory properties (Khan

& Giridhar, 2015) (Strack, Vogt, & Schliemann, 2003) (Clifford, Howatson, West, & Stevenson,

2015). These health beneficial characteristics of beetroot make it a health promoting “functional food” that is widely used in sports drinks and other functional food products (Clifford, Howatson,

West, & Stevenson, 2015) (Bazaria & Kumar, 2016). Despite the tinctorial function and health benefits, betalains have limited applications due to their poor stability during processing and storage and warrant a challenge in choosing a suitable solvent system (Celli & Brooks, 2017)

(Spórna-Kucab, Ignatova, Garrard, & Wybraniec, 2013). Previous researchers have extracted betalains by solvents with different polarity, type, and ratio, in one variety of beetroot

(Fathordoobady, Mirhosseini, Selamat, & Manap, 2016) (Osorio-Esquivel, Álvarez, Dorantes-

Álvarez, & Giusti, 2011) (Swamy, Sangamithra, & Chandrasekar, 2014).

In summary, food industries and manufacturers are still facing the challenge of developing or optimizing a processing technique that can provide products with a desired balance between nutritional and sensorial qualities. A bottleneck in the design of such process is the lack of insight into the impact of processing steps on the overall metabolic profile of the fruits and vegetables. In addition, the effect of different processing techniques, production systems, and solvent extraction

3 systems on phytochemical compositions of fruits and vegetables also remain untapped. Therefore, a comprehensive study investigating the effects of processing techniques, production systems and solvent extract systems on phytochemical profiles and antioxidant activities in different food matrix is much needed. The objectives of this research include:

1) To determine the effect of three juicing techniques on phytochemical contents and antioxidant activities of selected vegetables.

2) To evaluate the influence of thermal and non-thermal processing techniques on the levels and compositions of phytochemicals present in commercial juices

3) To optimize the extraction of betalain compounds and their identification by UPLC-HR-

ESI-QTOF-MS in conventionally grown red and golden, and organically grown red and golden colored beetroots.

4 2. REVIEW OF LITERAUTRE

2.1. Effect of solvent types on betalain compounds

Betalains are hydrophilic compounds whose hydroxyl groups lead to polarity and hydrogen bonding. Extraction solvent has a great influence on betalain extraction procedure and different solvent combinations could affect the extraction efficiency and stability due to intermolecular solute-solvent interactions.

Among all the extraction methods used till now, solid-liquid extraction is the most commonly used method to extract natural pigments (Cardoso-Ugarte, Sosa-Morales, Ballard,

Liceaga, & San Martín-González, 2014). Betalain compounds are normally extracted using organic solvents such as methanol, ethanol, acetone, and ethylene or a mixture of these solvents, after which the mixture is normally centrifuged, filtered, and vacuumed (Fathordoobady,

Mirhosseini, Selamat, & Manap, 2016). According to Alothman, Bhat and Karim, the mixture of water with ethanol is the most appropriate solvent for polar antioxidants extraction since the extracted product recovers the highest yield of total phenolic content, higher antioxidant activity, and is acceptable for human consumption (Alothman, Bhat, & Karim, 2009). Several authors have previously extracted beetroot and identified betalain compounds by using diverse solvents and methods (Narkprasom, Su, Cheng, Wang, Hsiao, & Tsai, 2012) (T. Kujala, Loponen, & Pihlaja,

2001), whereas the results varied considerably depending on the cultivar, genotype, and phytochemical distribution of the vegetable.

2.2. Effect of processing techniques on phytochemical properties

Previous studies have proposed that processing fruit and vegetables may result in irreversible effects on their sensory attributes, phytochemical profiles and antioxidant activities.

5 on vegetables. For example, our group (Uckoo, Jayaprakasha, Balasubramaniam, & Patil, 2012) processed grapefruits by three common household processing techniques and demonstrated that hand squeezed fruit juice had significantly higher contents of dihydrobergamottin than the juice processed by juicing or blending. Young-Hee and others (Pyo, Jin, & Hwang, 2014) investigated the influence of processing methods on phytochemical contents and antioxidant activity of blended and juiced Korean kernel fruits (apple, pear, persimmon, and mandarin orange). They concluded that the total polyphenols and antioxidant activities of blended juices were higher than ones processed by juicing. In contrast, ascorbic acid contents in apple, pear, and mandarin orange juices processed by juicing were significantly higher than from blending. Kim and others (M.-J. Kim, et al., 2015) investigated physiochemical properties, phytochemical contents, sensory evaluation and antioxidant activities of tomato juices obtained by high- and low-speed household juicers. They demonstrated that tomato juice obtained from low-speed juicer had better taste, higher phytochemical contents and DPPH values. Mendes Lopes and others (Mendes Lopes, Miguel,

Fialho, & Valente‐Mesquita, 2016) also investigated color parameters, antioxidant capacity, and microbial stability of grape juice processed by steam extraction, domestic blender, masticating juice extractor, and centrifugal juicer. Juices extracted using steam exhibited higher soluble polyphenols, anthocyanins and higher antioxidant capacity, however, very little information was narrated on phytochemical contents and antioxidant activity of other common vegetables. Thus, it is critical to clarify the effects of thermal and non-thermal processing techniques on physiochemical attributes, phytochemical profiles, and antioxidant activities of commercial and homemade juices.

Food industries are seeking advanced technologies to obtain juices with desirable physiochemical attributes, enhanced nutraceutical composition and potential microbial

6 inactivation due to increasing consumer demand for minimal and healthy foods. Thermal processing is the most common method for processing food, however, it may induce chemical and physical changes that impair the organoleptic properties and may reduce the content or bioavailability of some bioactive compounds. Therefore, non-thermal processing technologies were established in order to obtain food with “fresh-like” characteristics. Many studies have examined the effect of conventional and non-thermal processing technologies pertaining bioactive content and their products (Rawson, Patras, Tiwari, Noci, Koutchma, & Brunton, 2011). Patras and others (Patras, Brunton, Da Pieve, Butler, & Downey, 2009) processed tomato and carrot purée under thermal treatment (70 ºC/2min ) and high pressure treatment (400-600 MPa/15 min/20

ºC), and found that the latter retained more ascorbic acid and possessed stronger antioxidant capacities. Sánchez-Moreno and colleagues assessed the impact of high pressure, pulsed electric files, and traditional thermal processing and observed that high pressure leads to an increase in carotenoid, vitamin A, and naringenin release whereas traditional thermal treatment did not exert any changes in those compounds. In contrast, high pressure did not display higher DPPH radical scavenging activity. Although non-thermal processing juices seem to have more advantages than traditional processed juices, one major concern is that the price of popular nonthermal processed juice (example: cold-pressed juice) tends to be 5 folds higher than traditionally pasteurized juices and this may affect consumer’s preference.

Many studies have examined the effect of conventional and non-thermal processing technologies pertaining bioactive content and their products (Rawson, Patras, Tiwari, Noci,

Koutchma, & Brunton, 2011). Patras and others (Patras, Brunton, Da Pieve, Butler, & Downey,

2009) processed tomato and carrot purée under thermal treatment (70 ºC/2min ) and high pressure treatment (400-600 MPa/15 min/20 ºC), they found the latter retained more ascorbic acid and

7 possessed stronger antioxidant capacities compared to thermal processing. Sánchez-Moreno and colleagues assessed the impact of high pressure, pulsed electric files, and traditional thermal processing, the authors observed high pressure led to an increase carotenoid, vitamin A, and naringenin release whereas traditional thermal treatment did not exert any changes in these compounds. In contrast, high pressure did not display higher DPPH radical scavenging activity.

Although non-thermal processing juices seem to have more advantages than traditional processed juices, one concern is that the price of popular nonthermal processed juice (example: cold-pressed juice) tend to be 5 folds higher than traditionally pasteurized juices, which may affect consumer’s purchase desirability.

2.3. Variation of phytochemicals in fruits and vegetables

For example, our group (Uckoo, Jayaprakasha, Balasubramaniam, & Patil, 2012) processed grapefruits by three common household processing techniques and demonstrated that hand squeezed fruit juice had significantly higher contents of dihydrobergamottin than the juice processed by juicing or blending. Young-Hee and others (Pyo, Jin, & Hwang, 2014) investigated the influence of processing methods on phytochemical contents and antioxidant activity of blended and juiced Korean kernel fruits (apple, pear, persimmon, and mandarin orange). They concluded that the total polyphenols and antioxidant activities of blended juices were higher than ones processed by juicing. In contrast, ascorbic acid contents in apple, pear, and mandarin orange juices processed by juicing were significantly higher than from blending. Kim and others (M.-J. Kim, et al., 2015) investigated physiochemical properties, phytochemical contents, sensory evaluation and antioxidant activities of tomato juices obtained by high- and low-speed household juicers. They demonstrated that tomato juice obtained from low-speed juicer had better taste, higher phytochemical contents and DPPH values. Mendes Lopes and others (Mendes Lopes, Miguel, 8 Fialho, & Valente‐Mesquita, 2016) also investigated color parameters, antioxidant capacity, and microbial stability of grape juice processed by steam extraction, domestic blender, masticating juice extractor, and centrifugal juicer. Juices extracted using steam exhibited higher soluble polyphenols, anthocyanins and higher antioxidant capacity, however, very little information was narrated on phytochemical contents and antioxidant activity of other common vegetables. Thus, it is critical to clarify the effects of thermal and non-thermal processing techniques on physiochemical attributes, phytochemical profiles, and antioxidant activities of commercial and homemade juices.

Food industries are seeking advanced technologies to obtain juices with desirable physiochemical attributes, enhanced nutraceutical composition and potential microbial inactivation due to increasing consumer demand for minimal and healthy foods. Thermal processing is the most common method for processing food, however, it may induce chemical and physical changes that impair the organoleptic properties and may reduce the content or bioavailability of some bioactive compounds. Therefore, non-thermal processing technologies were established in order to obtain food with “fresh-like” characteristics. Many studies have examined the effect of conventional and non-thermal processing technologies pertaining bioactive content and their products (Rawson, Patras, Tiwari, Noci, Koutchma, & Brunton, 2011). Patras and others (Patras, Brunton, Da Pieve, Butler, & Downey, 2009) processed tomato and carrot purée under thermal treatment (70 ºC/2min ) and high pressure treatment (400-600 MPa/15 min/20

9 any changes in those compounds. In contrast, high pressure did not display higher DPPH radical scavenging activity. Although non-thermal processing juices seem to have more advantages than traditional processed juices, one major concern is that the price of popular nonthermal processed juice (example: cold-pressed juice) tends to be 5 folds higher than traditionally pasteurized juices and this may affect consumer’s preference.

2.4. Using UPLC-QTOF-HR-MS to identify phytochemicals

In general, mass spectrometry (MS) is a universal technique which is used in the measurement of mass-to-charge ratio (m/z) of ions formed from neutral species in food matrix.

Based on their discriminant m/z, these ions are separated after electrostatically directing them into the mass analyzers (Rubert, Zachariasova, & Hajslova, 2015). In 2004, the introduction of ultra- liquid-performance liquid chromatography (UPLC) system with faster separations and increased peak concentrations for qualitative and quantitative analysis of various plant compounds, made the technique extensively preferred to the traditional MS system (Swartz, 2005). Numerous improvements have been opportunely achieved, such as the development and introduction of high- resolution mass spectrometry (HRMS), low-resolution mass spectrometry (LRMS) and modern time-of-flight (TOF) techniques. The combination of UPLC with these advanced techniques allows the complementary performance of specific ion fragmentation as well as the possibility of identification of unknown compounds (Rubert, Zachariasova, & Hajslova, 2015). In addition, it is worth to mention that the coupling of UPLC with HRMS also achieves higher measurement accuracy (within 5 ppm), enhanced sensitivity, improved software handing capabilities, prolonged column lifetime, extended dynamic range and easier mass calibration, which makes it more attractive to the users (Rubert, Zachariasova, & Hajslova, 2015) (Kaufmann, 2014).

10 Fruits and vegetables and their processed products contain numerous phytochemical compounds that play an important role in reducing the risk or impact of chronic diseases. Recently, the characterization ad differentiation of variety or origin of fruits, vegetables, and derived products by using the UPLC-QTOF-HR-MS have been widely reported. For example, Singh et al.

(Singh, Jayaprakasha, & Patil, 2018) performed the rapid UPLC-QTOF-HR-MS technique to identify and quantify the known or novel glucuronide derivatives found in spinach. They found that the 5,3’4’-rtihydroxy-3-methoxy-6:7-methylendioxyflavone-4’-β-D-(2’-Oferuloyl- glucuronide) was the main glucuronide derivative in spinach. Lin and others analyzed the phenolic profiles of red mustard greens (Brassica juncea Coss Variety) and efficiently identified 67 anthocyanins, 102 flavanol glycosides, and 40 hydroxycinnamic acid derivatives and provided a database as reference for future analyses (Lin, Sun, Chen, & Harnly, 2011).

2.5. Metabolomics combined with chemometrics in food analysis

Metabolomics is a comprehensive assessment employing advanced approaches and the state-of-art analytical platforms to identify the compositions of small metabolites (< 1500 Da) (A.

Zhang, Sun, Wang, Han, & Wang, 2012). Fruits, vegetables and their processed products typically comprise a great varieties of components belonging to diver chemical classes and their wide concentration range (typically from millimolar to femtomolar), makes it a substantial challenge to conduct a comprehensive analysis of the entire metabolic composition (Castro-Puyana & Herrero,

2013). The development of metabolomic approaches has made it possible to profile metabolic constituents in complicated food matrix. Metabolomics consists of targeted (metabolic profiling) and non-targeted (metabolic fingerprinting) analysis. The targeted metabolic analysis focuses on a specific group of metabolites, whereas the non-targeted metabolic analysis is conducted to

11 develop the patterns of key metabolites that may be responsible for their discrimination (Medina,

Pereira, Silva, Perestrelo, & Camara, 2018).

Recently, the UPLC-QTOF-HR-MS has been extensively used in food metabolomics which achieves fast metabolomic analysis (Rubert, Zachariasova, & Hajslova, 2015). In addition, the non-targeted approach is employed with the chemometric tools to assess the key compounds/metabolites. Chemometrics is a statistical tool that extracts meaningful information from a large amount of data in the targeted and non-targeted approaches, to identify food components (Esteki, Simal-Gandara, Shahsavari, Zandbaaf, Dashtaki, & Vander Heyden, 2018).

Marsol-Vall et al. (Marsol-Vall, Balcells, Eras, & Canela-Garayoa, 2018) optimized an effective

Stir Bar Sorptive Extraction (SBSE) method combined to the GC-MS and chemometric to classify four varieties of peach juices under different processing conditions. The methodology included metabolomic profiling of the juices followed by chemometric tools to analyze the profiles of these metabolites. The PCA and SLDA successfully separated and characterized 14 variables under different chemical categories such as lactones, fatty acids, fatty aldehydes, hydrocarbons, and alcohols, which are mainly responsible for the sample separation, thus implementing the future use of SBSE technique in discriminating liquid samples.

The systems behind the production of different crops could potentially influence the levels and composition of certain phytochemicals, which may result in the identification of food production biomarkers. In this context, several studies have assayed the influence of metabolic profile of different food stuffs (food metabolome) (Krejčová, Návesník, Jičínská, & Černohorský,

2016), (dos Santos, Lima, dos Santos, Silva, de Santana, de Araujo, et al., 2019), (Hohmann,

Monakhova, Erich, Christoph, Wachter, & Holzgrabe, 2015). This discussion is particularly attributed to increasing consumer’s interest in organic foods.

12 The food metabolome can also be affected by the home-scale or industrial processing techniques. A recent study evaluated the impact of different industrial processing manners

(blending and heating order) on the phytochemical levels and compositions in carrot, tomato, and broccoli purees (Lopez-Sanchez, De Vos, Jonker, Mumm, Hall, Bialek, et al., 2015). By performing a hybrid of targeted and untargeted metabolomic approaches such as 1H NMR and

LC-QTOF MS, different key metabolites were identified that significantly affected the product quality. In addition, the results proved that the antioxidant compounds such as vitamin C and vitamin E, flavor and fragrance components like hexanal and decadienal are also influenced by the heating-blending order. Similar study has also been conducted to compare the effect of industrial and home processing techniques by employing untargeted LC-QTOF-MS analysis with PCA analysis (Tomas, Beekwilder, Hall, Sagdic, Boyacioglu, & Capanoglu, 2017). The PCA graph clearly separated the industrially and home processed samples, with the industrially processed samples having higher antioxidant activities. Additionally, during food processing the chemically modified metabolites were possibly obtained. Therefore, the food processing enriches the chemical pattern and could be perceived as reference for food authentication (Rubert, Zachariasova, &

Hajslova, 2015).

13 3. COMPREHENSIVE METABOLOMICS COMBINED CHEMOMETRICS

APPROACH TO EVALUATE THE IMPACT OF THREE PROCESSING

TECHNIQUES ON THE PHYTOCHEMICAL PROFILES AND ANTIOXIDANT

ACTIVITIES IN COMMONLY CONSUMED VEGETABLES

Epidemiological studies have shown that excessive generation of reactive oxygen species

(ROS) causes systemic oxidative stress, induces damages to cellular lipids, proteins, or DNA functions, and ultimately results in human diseases such as cardiovascular diseases, kidney disease, diabetes, cancers, strokes, inflammations, infections, retinal damages, and arthritis.(Forbes,

Coughlan, & Cooper, 2008; Pham-Huy, He, & Pham-Huy, 2008) Recent literatures have substantially investigated the correlations between the regular consumption of vegetables and the reduced risk of various oxidative stress.(Williams, Edwards, Hamernig, Jian, James, Johnson, et al., 2013) The beneficial potentials of vegetables are attributed to the presence of natural antioxidants in vegetables, such as vitamins, minerals, phenolics compounds, alkaloids, and other nitrogen-containing plant constituents that act as free radical scavengers in human bodies,(Dillard

& German, 2000; Nile & Park, 2014) while the composition and concentrations of phytochemicals are greatly varied in the specie, genotype, and variety of the vegetables.(Dillard & German, 2000;

Nile & Park, 2014)

Kale, cauliflower, and turnip are the commonly consumed vegetables of Brassicaceae family that are rich in natural antioxidants especially phenolic compounds.(Cartea, Francisco,

Soengas, & Velasco, 2011) Phenolic compounds are plants secondary metabolites synthesized by phenylalanine through shikimic acid pathway and categorized as free, esterified and insoluble- bound forms.(Shahidi & Yeo, 2016) In Brassica vegetables, flavonoids (flavanols and anthocyanins), hydroxycinnamic acid and phenolics are in the most abundant

14 concentrations.(Cartea, Francisco, Soengas, & Velasco, 2011) Carrots (Daucus carota L.) are economically important crop that are generally revered as “good for eyes” due to the presence of carotenoids. Recently, packaged baby carrots of various colors such as purple, yellow, white, and orange (rainbow carrots) are gaining popularity due to the convenience for consumption and attractive colors.(Arscott & Tanumihardjo, 2010) Rainbow carrots also have a wide variety of phytochemicals including carotenoids, phenolics compounds, and dietary fibers, which make them ideal functional food. Beetroot (Beta vulgaris L.) is a commonly consumed vegetable and ranked among the 10 most powerful vegetables int terms of their antioxidant activities, which is attributed to the presence of betalains, phenolics compounds, and other phytochemicals.(Vulić,

Čanadanović-Brunet, Ćetković, Tumbas, Djilas, Četojević-Simin, et al., 2012)

Despite their health promoting potentials, the unpalatable flavors and lesser convenience in consumption, often tends people to process vegetables into juices. However, this process may affect the phytochemicals present in them and their antioxidant activities by exposing the inner tissues to oxygen and light.(Tiwari & Cummins, 2013) Meanwhile, food processors are trying to optimize processing steps in order to prevent phytochemicals from reducing or losing their nutraceutical and pharmacological properties. Several studies have been devoted to investigating the effect of processing techniques on the overall antioxidant activities and phytochemical content in one particular fruit or vegetable, and the results are inconsistent or contradictory.(M.-J. Kim, et al., 2015; Mendes Lopes, Miguel, Fialho, & Valente‐Mesquita, 2016; Pyo, Jin, & Hwang, 2014)

Therefore, the composition and abundance of characteristic phytochemical compounds of low molecular weight (< 1500 Da) is affected by diverse processing techniques, and as only few reports are available in the literature, a reliable and consistent technique is needed.

15 Metabolomics is a functional approach that systematically identifies and quantifies numerous targeted and untargeted small metabolites present in food samples.(Castro-Puyana &

Herrero, 2013) The rapid growth of metabolomics has been attributed to the substantial development of modern analytical techniques. In particular, the introduction of ultrahigh pressure liquid chromatography (UHPLC) employs porous particles with a small internal diameter (< 2µm), combined with ion-trap-time-of-flight (QTOF) platform, allowing a broader analysis of compounds, obtaining higher peak capacity, enhanced resolution and enhanced sensitivity compared to the conventional HPLC columns, and results in faster separation of multiple compounds.(Castro-Puyana & Herrero, 2013) The data obtained from such analytical techniques by the metabolomic approach needed to be properly processed and interpreted by the use of cutting-edge data processing software and multivariate chemometric tools. Principle component analysis (PCA) is one of the most frequently used unsupervised method for sample clustering.

Partial least squares discriminant analysis (PLS-DA) is widely applied as a supervised technique for construction of classification and prediction models.

In this study, we aimed to compare the effects of three household-scale juicing techniques; blending, high-speed centrifugal juicing, and low-speed juicing on the composition and levels of phytochemicals of 21 commonly consumed vegetables. Using an untargeted UPLC-HR-ESI-

QTPF-MS analysis, a number of phytochemicals presented in processed vegetable juices were monitored and identified by comparing their retention time, exact mass and, characteristic fragmentation with the information available in databases. Then, the targeted metabolomics was combined with chemometric tools to identify the characteristic components responsible for differentiating the phytochemical profiles under the three processing techniques. In addition, the

16 color attributes, phytochemical contents, and antioxidant activities of the processed juices were also determined.

3.1. Materials and methods

3.1.1. Chemicals

L-ascorbic acid, gallic acid, phosphoric acid, sodium carbonate, 2,2-diphenyl-1-(2,4,6- trinitrophenyl) hydrazyl (DPPH), Folin Ciocalteu (FC) reagent, 2,2´-azinobis(3- etylbenzothiszoline-6-sulphonic acid) diammonium salt (ABTS), α-amylase, D-glucose, starch from potato, methanol and HPLC grade acetonitrile, were obtained from Sigma-Aldrich (St. Louis,

MO, USA). All other reagents and solvents were analytical grade. Nanopure water (NANOpure,

Barnstead, Dubuque, IA) was used for the entire study.

3.1.2. Sample preparation

Twenty-one vegetables with different varieties, productions systems, or colors were purchased from local markets. Vegetables include white, yellow and green cauliflowers (Brassica oleracea var. botrytis); green, green organic, red organic, and black kales (Brassica oleracea var. sabellica); purple-white and white baby turnips (Brassica rapa subsp. rapa); red, green

(Watermelon) and white (Daikon) radishes; red, red organic, golden and golden organic beetroots

(Beta vulgaris); orange, purple, yellow and white of baby carrots (Daucus carota subsp. sativus).

Detailed information is available in Table A-1. All vegetables were thoroughly washed, dipped into nano pure water, and then wiped completely dry. Each individual vegetable was cut into 1.5 cm × 1.5 cm piece and equally divided into three groups. Each group of samples was processed by an Osterizer 12-speed Blender (blending), Breville Juice Fountain Plus 850-watt 2-speed juice

17 extractor (high-speed centrifugal juicing), and Omega 8006 Nutrition System HD Low Speed

Juicer (low-speed juicing), respectively.

3.1.3. Instrumental color attributes

Color attributes of each sample were measured by a Minolta CR-400 Chroma Meter

(Konica Minolta Sensing, Inc., Osaka, Japan). The instrument was calibrated using a white plate

(Calibration Plate CR-A43, Minolta Cameras, Osaka, Japan) to standardize the equipment.

Afterwards, the processed vegetable juices were transferred into a glass cuvette for measuring the

Hunter Lab units L, a* and b* with the L indicates lightness (0 = black, 100 = white); a* represents redness-greenness (positive = red, negative = green); b* indicates yellowness-blueness (positive = yellow, negative = blue). The samples were filled in taking care of all air bubbles. Triplicate measurements were conducted, and the results were expressed as mean ± standard error.

3.1.4. Targeted phytochemicals quantification

Total ascorbic acid content was determined using our developed method (Chebrolu,

Jayaprakasha, Yoo, Jifon, & Patil, 2012a). Briefly, 4.0 mL of processed vegetable juice was added to 4.0 mL of 3% meta-phosphoric acid (3 g dissolved in 100 mL of nanopure water), and the mixture was vortexed (30 s), homogenized (9000 rpm for 2 min), sonicated (1h), and centrifuged

(9000 for 15 min) to obtain the supernatant. Further, 1mL of the supernatant was centrifuged at

10000 rpm for 5 min and 400 μL of the clean liquid mixed with 400 μL Tris (2-carboxyethyl) phosphine hydrochloride reagent (TCEP) was pipetted into HPLC vials. For HPLC analysis, an

Agilent 1200 Series HPLC System, equipped with an analytical C18 column (250 mm × 4.6 mm,

5 μm) and a photodiode array detector (PDA), was performed with an isocratic elution of

18 phosphoric acid as a mobile phase. A 10 μL of sample was injected to the column with a flow rate of 1 mL/min, and the peaks were monitored at 254 nm. Results were expressed as μg of ascorbic acid per g of fresh weight.

Analysis of nitrate was conducted by mixing 1mL of sample juice added 8 mL of nanopure water. The mixture was vortexed (30 s), homogenized (9000 rpm for 2 min), sonicated (1h), and centrifuged (9000 for 15 min) to acquire the supernatant. After that each sample was further filtered with 3 mL syringe (BD, Franklin Lakes, NJ, USA) and filter (VWR International, Radnor, PA,

USA). Agilent 1200 Series HPLC System was used to identify and quantify nitrate in samples.

Injection volume was 10 μL with flow rate set at 0.7 mL/min and wavelength at 210 nm. Mobile phase was 30 mM phosphoric acid solution with an isocratic solution. Results were expressed as

μg of nitrate per g of fresh weight.

3.1.5. Estimation of total phenolics

3.1.5.1. Sample extraction

Five milliliters of the obtained juice were first mixed with 10 mL of methanol, then the mixture was placed in the vortex for 30 s. After homogenizing the mixture at 9000 rpm for 1 min, the mixture was sonicated under ice for 1h. Afterwards, the mixture was centrifuged at 10000 rpm for 10 min and then collect supernatant. The residues were added into 3 mL methanol and centrifuge at 10000 rpm for 10 min to collect supernatant. Final volume was calculated by adding the two-supernatant collected as mentioned above.

19 3.1.5.2. Estimation of total phenolics

A Folin-Ciocalteu colorimetric method was adopted to spectrophotometrically measure the total phenolics (G. Jayaprakasha & Patil, 2007). The absorbance was set at 734 nm using a KC-4

Microplate Reader (Bio Tek Instruments, Winooski, VT, USA) Data were expressed as μg gallic acid equivalents (GAE)/g FW.

3.1.5.3. Untargeted UPLC-HR-ESI-QTPF-MS based identification

The methanol extract of each sample was analyzed by LC-MS. UPLC-HR-ESI-QTPF-MS analysis for phenolic compounds in the processed vegetables samples was performed on a 1290

Agilent HPLC LC system (Agilent Technologies, Santa Clara, CA, USA) equipped with a maXis impact mass spectrometer (Bruker Daltonics, Billerica, MA, USA). An eclipse plus C18 column

(1.8 μm, 50 × 2.1 mm; Agilent) was used for phytochemical compounds separation with the binary mobile phase consisting of 0.2% formic acid (A) and 0.1 % formic acid in water: acetonitrile (3:7, v/v) with gradient elution as follows, 100% A for 0 5 min, 100-98% A for 5 min, 100-98% for 5 to 10 min, 98-55% A from 10 to 22 min, 55-44% A from 22 to 27 min, 40-10% A from 27 to 31 min, isocratic for 31 to 34 min, 10-100% A from 34 to 40 min. Capillary voltage was set at 40 kV and nebulization pressure was 241.3 kPa. Nitrogen temperature was 350 °C and flow rate was 8.0

L/min. The column temperature was set at 65 °C. Injection volume was 10 μL and the flow rate was 0.2 mL/min. For MS spectral analysis, the following mass spectrum detection conditions were employed in positive mode with MS scan range 50-1000 m/z. The accurate mass data for were processed using he Data Analysis 4.3 software, and identification for each metabolite was performs by comparing the mass accuracy, isotopic patterns, adducts, and fragments using SmartFormaula.

20 3.1.6. Antioxidant activity

3.1.6.1. DPPH radical scavenging activity

The DPPH (2,2-diphenyl-1-picrylhydrazyl) assay was performed according to the method outlined by our published protocol (Bae, Jayaprakasha, Jifon, & Patil, 2012) with slight modifications. The DPPH radical scavenging activity was calculated by using a calibration curve of a series of ascorbic acid solutions and expressed as μg ascorbic acid equivalents per g for fresh weight for each vegetable (μg AA/g FW).

3.1.6.2. ABTS free radical scavenging activity

The ABTS (2,20 -Azinobis-3-ethylbenzotiazoline-6-sulphonic acid) assay was conducted according to our published protocol (G. K. Jayaprakasha, Girennavar, & Patil, 2008). The absorbance was measured at 734 nm and results were expressed as μg ascorbic acid equivalents per g for fresh weight for each vegetable (μg AA/g FW).

3.1.6.3. α-Amylase inhibition assay

In the α-Amylase inhibition experiment, 10 μL of the extracted sample was mixed with saline solution (0.9 %) to obtain a volume of 140 μL. After adding 45 μL of starch (10 mg/mL) and 45 μL of α-amylase (10 mg/mL), the microplate was incubated at 25 C for 1 h. Then, 50 μL of DNSA color reagent solution (96 mM 3,5-dinitrosalicylic acid) was added into a 96-well plate.

Then, the microplate was placed into a 75 °C oven for further reaction. The absorbance of the reaction mixture was measured at 540 nm. To eliminate the background absorbance produced by

21 sample extracts or fractions, an appropriate extract control without enzyme was included. The results were expressed as D-glucose equivalents (μg) of fresh weight (g).

α-Amylase inhibition% = [1-（Asample- Ablank /Atest – Acontrol ）]100% where A sample is the absorbance of the mixture of the sample, starch solution, enzyme and DNSA color reagent solution; A blank is the absorbance of the mixture of phenolic sample, starch solution and DNSA color reagent without enzyme; A test is the absorbance of the mixture of buffer (instead of sample), starch solution, enzyme and DNSA colour reagent; A control is the absorbance of the mixture of buffer, starch solution and DNSA color reagent without enzyme.

3.1.7. Data processing and chemometrics analysis

All samples were analyzed in triplicate and the results were express as the mean ± standard error. For comparisons with samples, data was analyzed by one-way ANOVA and Tukey's multiple comparison test using JMP software (SAS, NC, USA). A probability of 5% or less was accepted as statistically significant. All multivariate data analysis was carried out using

MetaboAnalyst software (http://www.metaboanalyst.ca/) to detect clustering and discriminate samples in the present study.

3.2. Results and discussions

3.2.1. Effect of household processing techniques on color attributes

When choosing a food product, color is the first attribute perceived by consumers which directly affects the acceptability and their purchasing preference. In a food matrix, color is also considered as an important indicator of food quality and occurrence of chemical or biochemical

22 reactions (Patras, Brunton, O'Donnell, & Tiwari, 2010). Previous literature has proved that the colors present in vegetable juices are mainly due to the presence of phytochemical pigments, such as chlorophylls, carotenoids, anthocyanins and betalains (Barrett, Beaulieu, & Shewfelt, 2010). In our study, the L (brightness), a*(redness-greeness), b*(yellowness-blueness) color space coordinated of the vegetable juices obtained by three processing techniques (blending, high-speed centrifugal juicing, and low-speed juicing) are shown in Table A-1. The vegetable juices obtained through blending had lower L values than juices in comparison to the juices obtained through high- speed centrifugal juicing and low-speed juicing, indicating that dark color was formed during blending. The blender crusting the whole vegetable using the high-speed spinning blades, generating heat and initiating serial biochemical reactions and color changes. In addition, the sediment and paste retained after processing could also cause dark color in the blended juice. In contrast, juices obtained by high and low-speed juicing were translucent, bright, and no heat was generated during the process, which, made the juices similar to industrialized juice products.

However, red organic kale, golden beet, and purple baby carrot were the exceptions, where the blended juices were brighter than their counterparts.

3.2.2. Variation in phytochemical concentration under three processing techniques

In our study, total ascorbic acid (TAA) and nitrate content of the 21 vegetables juices are given in Table 2. Among all the vegetables, white cauliflower had the highest TAA (418.7 µg/g) while the white baby carrot showed the lowest TAA (3.2 µg/g), With respect to the different proceeding techniques, juices obtained from the low-speed juicer showed the highest amounts of the TAA compared to the high-speed centrifugal juicer and blender, which generated heat during the processing and cause deterioration of the ascorbic acid. Similar results have also been reported

23 by previous literature (Pyo, Jin, & Hwang, 2014), which reported that the influence of juicing had an overall positive effect on the content on specific fruits. It is therefore, apparent that the low- speed juicer had potential to retain the ascorbic acid of those vegetables. However, three vegetables, green cauliflower, green radish, and organic red kale, their blended juices exhibited the higher

TAA than the juices obtained by the other two processing methods. Similar results have also been reported by previous literature (Pyo, Jin, & Hwang, 2014), which reported that the influence of juicing and blending on ascorbic acid content was crop-dependent wherein juicing had an overall positive effect on the content ascorbic acid.

Significant variations were found in nitrate contents of the processed juices, with red beet showed the greatest nitrate value (1270.7 µg/g) while orange baby carrot shows the least nitrate contents. Different from TAA, the effect of processing techniques on nitrate content depended on each vegetable. According to cauliflower, kale, turnip, and beet, their blended juices had higher nitrate content compared to the juices acquired from high-speed centrifugal juicer and low-speed juicer. In comparison, the carrot juices obtained by high- or low-speed juicers exhibited higher nitrate.

3.2.3. Influence of household processing techniques on total phenolics

Phenolic compounds are the secondary metabolites widely present in fruits and vegetables and are among the most desirable food bioactives due to their health-promoting potentials (Naczk

& Shahidi, 2006). In vegetables, flavonoids are present as conjugates in glycosylated or esterified forms (Liu, 2004). As a result of processing, these compounds convert to metabolites, especially to their aglycone forms (Cartea, Francisco, Soengas, & Velasco, 2010). The total phenolics (TP) of processed juices are shown in Fig 1A that ranged from 40.33 to 717.67 μg GAE/g FW with the

24 highest and the lowest value detected in purple baby carrot blended juice and white cauliflower high-speed centrifugal juice, respectively. The kale, radish, and beet juices obtained by low-speed juicing had significantly higher TP than the juices acquired from blending and high-speed centrifugal juicing. This difference could be attributed to the chemical reactions that occurs of the phenolic compounds during the processing. Kale, radish, and beet are mainly composed of kaempferol and quercetin glycosides, cyanidins, and betalains, respectively (Lin & Harnly, 2010;

Vulić, et al., 2012). Thermal processing such as blending or high-speed centrifugal juicing generates heat and causes glycosylation, and degrades these compounds, thus reducing the content of total phenolics (Nayak, Liu, & Tang, 2015). In comparison, the low-speed juice extractor squeezes juice with a horizontal auger that rotates food samples at a low speed of 80 rpm, had less effects to those compounds when compared to the blending and high-speed centrifugal juicing methods, since it generated less heat. In comparison, the blended cauliflower, turnip, and baby carrot juices had higher TP than the juices obtained by high-speed centrifugal juicer and low-speed juice extractor. Previous literature reported that the total phenolics differ on the basis of vegetable parts used in the assay and the highest amount was found in peels (D. Zhang & Hamauzu, 2004).

The juicing process released all pulps and peels of vegetables that had larger quantities of phenolic compounds (T. Kujala, Loponen, & Pihlaja, 2001), whereas blending retained the pulps and peels.

Therefore, turnip and carrot blended juices were significantly higher in total phenolics compared to the other two methods,

Accumulation of phenolic compounds is also differentiated by the color of each vegetable cultivars. In our study, the purple baby carrots contained most phenolic compounds compared to orange, yellow, and white carrots, with the amount 7 fold, 3 fold, and 4 fold in blended juices, for example, as higher than the three cultivars. In case of purple carrots, the presence of phenolic

25 compounds along with anthocyanins and polyphenolic compounds such as chlorogenic acid, caffeic, and others in a clearly higher concentration than orange, white and yellow carrots, also contributed to the total phenolics (Alasalvar, Grigor, Zhang, Quantick, & Shahidi, 2001). Hence, total phenolics were greatly influenced by genotypes, colors, and processing techniques.

3.2.4. Identification of bioactive compounds in 21 various vegetables processed by three

juicing techniques by UHPLC–QTOF-MS analysis

Methanol extracts of 21 vegetables were processed by the three juicing techniques and analyzed using LC-MS. According to the result (Table 1), 72 phytochemical compounds, including flavonols and their glycosides, anthocyanins, 36 betalains, 2 amino acids, and 2 phenolic acids were identified by UHPLC–QTOF-MS analysis (Table 1). These identified compounds were confirmed based on their retention time, accurate mass, possible fragmentation patterns from published papers (Lin & Harnly, 2010; Yang, Jayaprakasha, & Patil, 2018a). Kale extracts exhibited the highest varieties of nonacylated glycosides including kaempferol (m/z 287) and quercetin (m/z 303) glycosides as the main flavonoids (Table 1). The varieties were quercetin-3- diglucoside-7-glucoside and isomer (m/z 789), quercetin-3-sophoroside-7-diglucoside (m/z 951), kaempferol-3-O-diglucoside-7-glucoside (m/z 773), kaempferol-3-O-(caffeoyl)-sophoroside-7-O- glucoside and isomer (m/z 935), kaempferol-3-hydroxyferuloyl-diglucoside-7-glucoside (m/z

965), kaempferol-3-hydroxyferuloyl-diglucoside-7-diglucoside (m/z 1127), kaempferol-3-O-

(caffeoyl)-sophoroside-7-O-diglucoside (m/z 1097), quercetin-3-sinapoyl-diglucoside-7- diglucoside (m/z 995), quercetin-3-O-(feruloyl)-sophoroside (m/z 965), kaempferol-3-sinapoyl- diglucoside-7-diglucoside (m/z 1141), kaempferol-3-sinapoyl-diglucoside-7-glucoside (m/z 979), kaempferol-3-feruloyl-diglucoside-7-diglucoside (m/z 1111), kaempferol-3-(feruoyl)-

26 sophoroside-7-O-glucoside (m/z 949), kaempferol-3-O-sophoroside and isomer (m/z 611), kaempferol-3-O-sophoroside-7-glucoside (m/z 773), kaempferol-3-O-(sinapoyl)-sophoroside

(m/z 817), kaempferol-3-O-(feruloyl)-sophoroside (m/z 787), and kaempferol-3-O-glucoside (m/z

449). Previous study has also identified kaempferol and quercetin as the main phenolic compounds in different Brassica crops such as kale and cauliflower, in which 3-O-sophoroside-7-O-glucoside and its conjugations with hydroxycinnamic acids, were the main phenolics (Cartea, Francisco,

Soengas, & Velasco, 2011). A large quantity of hydroxycinnamic acids; gallic, protocatechuic, p- hydroxybenzoic, vanillic, syringic, p-coumaric, caffeic, ferulic, chlorogenic and sinapic acids were detected in leafy Brassica vegetables. In our study, only ferulic acid derivative (m/z 325), 5-p- coumaroylquinic acid (m/z 339), and 4-p-coumaroylquinic acid (m/z 339) were identified in kale, cauliflower, turnip, and radish samples. In other Brassica vegetables, including all colored cauliflower, turnip, and radish, several phytochemical compounds were identified.

Beet (Beta vulgaris) proved to have various betalain compounds which largely contribute to the onset of several degenerative diseases (Slatnar, Stampar, Veberic, & Jakopic, 2015a).

Betalains are categorized as red betacyanins and yellow betaxanthins and their levels are substantially influenced by the production systems and cultivars (Stintzing, Schieber, & Carle,

2002a). Our study used conventionally grown (red and golden colored), and organically grown

(red and golden colored) beet extracts to unravel the composition differences among the four beet varieties. Thirty-six metabolites include 13 betacyanins, 20 betaxanthins, and 3 amino acids, were tentatively identified. Betanin (m/z 551) and its C-15 isoform isobetanin (m/z 551) with the fragmentation ion at m/z 389 (betanidin) were found to be the main betacyanins in red beet extracts. Other minor betacyanins were mainly presented and protonated ion at m/z 631, 727, and

833, and their ion fragments at m/z at 551 (betanin) and 389 (betanin). The mass differences

27 between these betacyanins and betanin proposed the existence of extra pentose moiety. This finding is in agreement with the previous study (Stintzing, Schieber, & Carle, 2002a), which verified that betalain concentration differs among beet cultivars, and yellow colored beetroot completely lacked betacyanins. The novel finding of this study asparagine-betaxanthin (m/z 326), threonine-betaxanthin (m/z 313), alanine-betaxanthin (m/z 283), and methionine-betaxanthin (m/z

343), which were identified in beet samples for the first time when, compared to the beet samples from distinct origins or countries (Nemzer, Pietrzkowski, Spórna, Stalica, Thresher, Michałowski, et al., 2011; Slatnar, Stampar, Veberic, & Jakopic, 2015a). Thus, these four uniquely identified betaxanthin compounds may be potentially used as markers to characterize and compare beetroots grown at different geographical locations.

3.2.5. Effect of household processing techniques on DPPH and ABTS radical scavenging

activities

Many assays investigating antioxidant activity of vegetables have been developed and applied, however, due to the complex nature of biological systems, it is has been difficult to establish a single universal method, thus, at least two assays should be applied to provide an comprehensive overview of antioxidant activities in one experiment (Šamec, Maretić, Lugarić,

Mešić, Salopek-Sondi, & Duralija, 2016). In our study, DPPH and ABTS radical scavenging assays were performed and the activity of vegetable juices obtained by three processing techniques; blending, high-speed centrifugal juicing, and low-speed juice extracting, are given in

Fig. 2. Among the 21 vegetables, the highest ABTS activity was found in organic red beetroot processed by high-speed centrifugal juicing (440.97 μg AA/g FW), followed by purple baby carrot blended juice (373.74 AA/g FW), and the lowest ABTS activity was depicted in white cauliflower

28 blended juice (40.27 μg AA/g FW). The highest and lowest DPPH activities were detected in purple baby carrot juice processed by high-speed centrifugal juicer (715.77 μg AA/g FW), and in yellow baby carrot processed by low-speed juicing (46.46 μg AA/g FW), respectively. The major anthocyanin in purple carrot is cyanidin-3-(sinapoylxylosyl-glucosylgalactoside), which exhibited significant antioxidant activity due to the free hydroxyl groups on the 3´ and 4´ positions, which may have contributed to its high DPPH and ABTS activities of this study (H. Wang, Cao, & Prior,

1997).

Significant variations were found among the vegetables processed by the three techniques.

To sum, significant higher ABTS free radical scavenging values were observed in the three colored cauliflowers, organic black kale, turnips, and all baby carrot juices or pastes obtained by blender, compared to the juices obtained from the other two methods. Interestingly, contrasting results were found for green, green organic, red organic kale, four varieties of radishes, golden, and organic golden beetroot processed juices, whereas low-speed juicing showed higher ABTS values. The only exception was organic red beetroot obtained from high-speed centrifugal juicing that showed significantly higher ABTS activity compared to the other techniques. A similar trend was found in

DPPH results, where higher values were found in cauliflower, organic black kale, and the four baby carrots juices processed by the blending. While in green kale (conventional and organic), organic red kale, radish, and golden beetroot (conventional and organic), low-speed juicer produced juices showed higher DPPH scavenging activities. Different from ABTS results, turnip juices obtained from high-speed centrifugal juicer had the highest DPPH values. Disparities of these results could be attributed to their initiating mechanisms of the two assays, when either hydrogen or single electron transfer was the dominating reaction (Schaich, Tian, & Xie, 2015).

29 3.2.6. Inhibition of α-amylase enzymes

The inhibition of α-amylase is necessary as it plays an important role in decreasing postprandial hyperglycemia (Heo, Hwang, Choi, Han, Kim, & Jeon, 2009). In this study, the results of α-amylase inhibition percentage in processed vegetables are shown in Fig 1B. The blended vegetable juices had higher α-amylase inhibition rates when compared to the other two juiced products which can be explained by the retention of high amount of dietary fibers by blending. Dietary fibers from vegetables have proved to have effective anti-diabetic activities (P.

Y. Wang, Fang, Gao, Zhang, & Xie, 2016). The highest α-amylase inhibition percentage was found in organic red radish blended juice, with the value of 99.3%. Previous study found that the inhibitory effects of flavonoids were positively correlated with number of hydroxyl groups of the polyphenol ligands and formation of a conjugated-systems which stabilized the interaction on the active site (Sales, Souza, Simeoni, Magalhães, & Silveira, 2012). Brassica vegetables were rich in flavonoids; thus, their α-amylase inhibition activities were potent. The lowest α-amylase inhibition percentage was detected in yellow cauliflower juice obtained by high-speed centrifugal juicing, with the value of 57.41%. Organic golden beetroot juice obtained by low-speed juice extractor also had low inhibition percentage of 60.08%. The remaining vegetables juices showed high α- amylase inhibition percentage, with the values ranging from 70.47% to 96.96%.

3.2.7. Chemometrics-based analysis in discriminating phytochemicals profiles under three

processing techniques

The chemometric-based analysis was carried out based on the LC-MS data to visualize the characteristic components in the processed juice samples. The unsupervised principal component analysis (PCA) approach was not able to achieve the separation of the three processing techniques;

30 blending, high-speed centrifugal juicing, and low-speed juicing (Appendix Fig.1). This was due to the presence of similar compounds in the processed samples that only differs on the basis of peak intensities. In the next step, we performed partial least squares discriminant analysis (PLS-DA), the supervised pattern recognition platform to discriminate the phytochemical profiles in processed vegetables under the three techniques. With respect to Braccica vegetable juices, our study identified 20 metabolites, mainly kaempferol glycosides and phenolic acids, and are considered to be important for the differentiation of the blending, high-speed centrifugal juicing, and low-speed juicing samples. The levels of all the metabolites were highest in low-speed kale juices when compared to juices obtained by blending or high-speed centrifugal juicing (Fig.3). Based on the heatmap, the low-speed juicing retained more varieties of metabolites compared to the other techniques and a large percentage of kaempferol and quercetin glycosides were detected in abundance, indicating the potential development of nonthermal process techniques. It is worthy to mention that the processing techniques and vegetable varieties had effect on composition, amongst the green kale blended juices shows the presence of less metabolites than the high- or low-speed juices. However, this difference was not exhibited when the metabolites composition of black kale juices was compared from the three processing techniques. In order to find the metabolites that make the most significant contributions to classification, variable importance for projection (VIP) score plot (Appendix Fig.1) was generated to provide an overview of the levels of metabolites were selected by specific VIP values (>1) with the results indicated that the low-speed juicing has higher levels of these compounds.

The impact of processing techniques on phytochemical profiles in four varieties of beet were also analyzed by the metabolomics combined with chemometrics and the results are shown in Fig.3. Unlike kale samples whose major metabolites were generally higher in the low-speed

31 juicer compared to the other two methods, the levels of each metabolite varied in beet samples. In general, the blended conventional red beet samples retained higher amounts of isobetanin (m/z

551), neobtanin (m/z 549), prebetanin (m/z 631), 6’feruloyl-betanin and its isomer (m/z 727) but similar levels of betaxanthins compared to high-speed centrifugal juicer and low-speed juicer. The

VIP score plot (Appendix Fig.1) revealed four characteristic betalain compounds, in which the glutamine-betaxanthin (m/z 340) and isoleucine-betaxanthin (m/z 325) were the highest in blended juices, and dopamine-betaxanthin (m/z 347) were the highest in low-speed juicer, and neobetanin

(m/z 549) was the highest in high-speed centrifugal juicer, respectively.

3.3. Conclusions

Our study indicated that the three processing techniques; blending, high-speed centrifugal juicing, and low-speed juicing, substantially affected the compositions and antioxidant activities of the commonly consumed vegetables. 73 phytochemicals (36 betalains, 23 flavonols, 6 anthocyanidins, 6 phenolic acids and 2 amino acids) including four novel betalains (asparagine- betaxanthin, threonine-betaxanthin, alanine-betaxanthin, and methionine-betaxanthin), were identified by the untargeted UPLC-HR-ESI-QTOF-MS profiling technique. The targeted metabolomics approach combined with chemometrics revealed that several kaempferol glycosides and amino acid adducted betaxanthins were the potential key metabolites to discriminate the different processed kale and beet juices that varied among vegetable varieties and the processing techniques. In addition, the color attributes, phytochemical contents, and antioxidant activities of each vegetable were also significantly influenced by the three processing techniques. This study demonstrated that the metabolomics-based approach combined with chemometrics provides a fast and efficient tool to screen the impact of the processing techniques by highlighting the metabolomic differences of the commonly consumed vegetables. 32 Table 1. Identification of bioactive compounds from 21 processed vegetables using UPLC-HR-ESI-QTPF-MS. RT Identified compounds Molecular Experime Exact Mass error MS/MS Occurrence Reference (Min) formula ntal mass mass (ppm) fragments Flavonols and their derivatives Brasicc Beta D. a vulgari Caro s ta 2.45 Epigallocatechin C15H14O7 307.0953 307.0812 45.9 - ˣ 8.05 Quercetin-3-diglucoside-7-glucoside C30H40O22 789.2230 789.2084 18.5 541, 465, 303, ˣ (Yang, 237, 177 Jayaprakasha 8.15 Quercetin-3-diglucoside-7-glucoside C30H40O22 789.2238 789.2084 19.5 571, 478, 409, ˣ , & Patil, (isomer) 303, 163 2018a) 8.35 Quercetin-3-sophoroside-7-diglucoside C39H50O27 951.2772 951.2612 16.8 571, 449, 303, ˣ 237, 153 8.50 Kaempferol-3-O-diglucoside-7-glucoside C33H40O22 773.2263 773.2135 16.6 633, 541, 449, ˣ 347, 287, 177 8.70 Kaempferol-3-O-(caffeoyl)-sophoroside- C42H46O24 935.2800 935.2452 37.2 571, 287, 193, ˣ 7-O-glucoside 85 8.95 Kaempferol-3-hydroxyferuloyl- C43H48O25 965.2721 965.2557 17.0 539, 492, 355, ˣ diglucoside-7-glucoside 287, 193, 133 9.10 Kaempferol-3-hydroxyferuloyl- C49H58O30 1127.3283 1127.3086 17.5 539, 449, 355, ˣ diglucoside-7-diglucoside 287, 193 9.20 Kaempferol-3-O-(caffeoyl)-sophoroside- C42H46O24 935.2632 935.2452 19.2 409, 287, 163, ˣ 7-O-glucoside (isomer) 84 9.35 Kaempferol-3-O-(caffeoyl)-sophoroside- C45H60O31 1097.3190 1097.3191 -0.1 531, 287, 207, ˣ 7-O-diglucoside 163 9.45 Quercetin-3-sinapoyl-diglucoside-7- C50H60O31 995.2880 995.2663 21.8 553, 409, 303, ˣ diglucoside 207 9.55 Quercetin-3-O-(feruloyl)-sophoroside C43H48O25 965.2792 965.2557 24.3 523, 409, 339, ˣ 303, 177 9.85 Kaempferol-3-sinapoyl-diglucoside-7- C50H60O30 1141.3535 1141.3242 25.7 553, 369, 287, ˣ diglucoside 207 10.00 Kaempferol-3-sinapoyl-diglucoside-7- C44H50O25 979.3011 979.2714 30.3 707, 501, 369, ˣ glucoside 287, 177 10.05 Kaempferol-3-feruloyl-diglucoside-7- C49H58O29 1111.3503 1111.3137 32.9 707, 523, 449, ˣ diglucoside 339, 287, 177 10.20 Kaempferol-3-(feruloyl)-sophoroside-7- C43H48O24 949.2491 949.2608 -12.3 809. 624, 523, ˣ O-glucoside 449, 339, 287, 177 11.25 Kaempferol-3-O-sophoroside C27H30O16 611.1536 611.1607 -11.6 553, 462, 329, ˣ 287, 177

33 Table 1. Continued RT Identified compounds Molecular Experime Exact Mass error MS/MS fragments Occurrence Reference (Min) formula ntal mass mass (ppm) Flavonols and their derivatives Brasicca Beta D. vulgaris Carota 12.00 Kaempferol-3-O-sophoroside C27H30O16 611.1540 611.1607 -11.0 427, 347, 287, 177 ˣ (Yang, (isomer) Jayapraka 13.75 Kaempferol-3-O-sophoroside C27H30O16 611.1539 611.1607 -11.1 519, 369, 287, 207, ˣ sha, & (isomer) 175 Patil, 2018a) 13.95 Kaempferol-3-O-glucoside C21H20O11 449.1029 449.1078 -10.9 395, 287, 177, 91 ˣ 15.00 Disinapoyl-diglucoside C34H42O19 777.2139 777.2213 -9.5 665, 553, 479, 347, ˣ 287, 207, 91

15.40 1-Sinapoyl-2-feruloyl-diglucoside C33H40O18 747.2272 747.2107 22.1 523, 339, 287, 207, ˣ 177, 145

16.70 Trisinapoyl-diglucoside C45H52O23 983.2661 983.2797 -13.8 682, 523, 369, 287, ˣ 207, 177 Anthocyandins Devivatives + 2.10 Cyanidin C15H11O6 288.2081 ˣ (Algarra, Fernandes 8.65 Cyanidin 3-xylosyl-galactoside C26H29O15 581.1564 581.1000 479, 377, 287, 163 + , Mateus, de Freitas, 8.85 Cyanidin 3-xylosyl-galactoside C26H29O15 581.1559 581.1000 479, 377, 287, 163 + da Silva, (isomer) & Casado, 9.55 Cyanidin 3-xylosyl C43H49O24 949.2667 949.2608 6.2 673, 287 2014) (sinapoylglucosyl)galactoside +

10.00 Cyanidin 3- C42H47O23 919.2607 919.2503 11.3 823, 655, 575, 411, xylosyl(feruloylglucosyl)- + 365, 287 galactoside 10.80 Cyanidin 3- C42H47O23 919.2616 919.2503 12.3 823, 655, 575, 411, xylosyl(feruloylglucosyl)- + 365, 287 galactoside (isomer)

34 Table 1. Continued RT Identified compounds Molecular Experiment Exact mass Mass error MS/MS Occurrence Reference (Min) formula al mass (ppm) fragments Betalains Derivatives Brasicca Beta D. vulgaris Carota 1.00 Asparagine-betaxanthin C13H15N3O7 326.0990 326.0983 2.1 203, 137 ˣ (Nemzer, et (Vulgaxanthin III) al., 2011) 1.80 Glutamine-betaxanthin C14H17N3O7 340.1155 340.1139 4.7 321, 277 ˣ 2.50 Glutamine-isobetaxanthin C14H17N3O7 340.1206 340.1139 -15.0 - ˣ 3.20 Threonine-betaxanthin C13H16N2O7 313.1033 313.1030 1.0 - ˣ 3.80 Glutamic acid-betaxanthin C14H16N2O8 341.0987 341.0979 2.3 215 ˣ 4.05 Glutamic acid-isobetaxanthin C14H16N2O8 341.1056 341.0979 22.6 - ˣ 4.35 Alanine-betaxanthin C12H14N2O6 283.0928 283.0925 1.1 164, 84 ˣ + 4.50 17-Decarboxy-betanidin C17H17N2O6 345.1084 345.1081 0.9 - ˣ 4.55 Valine-isobetaxanthin C14H18N2O6 311.1302 311.1238 20.6 - ˣ + 4.55 2,17-Bidecarboxy- C22H27N2O9 463.1715 463.1711 0.9 242, 164 ˣ betnidin/isobetanidin 4.95 ℽ-Aminobutyric acid- C13H16N2O6 297.1084 297.1081 1.0 - ˣ betaxanthin 5.05 Proline-betaxanthin C14H16N2O6 309.1107 309.1081 8.4 283, 195 ˣ 5.55 Prebetanin C24H26N2O16S 631.1067 631.1076 -1.4 551, 389 ˣ 5.75 Betanin C24H26N2O13 551.1532 551.1508 4.4 389, 150 ˣ 5.85 Isobetanin C24H26N2O13 551.1523 551.1508 2.7 389, 150 ˣ 6.35 Dopamine-betaxanthin C17H18N2O6 347.1247 347.1238 2.6 ˣ (Miraxanthin V) 6.40 Tyrosine-isobetaxanthin C18H18N2O7 375.1263 375.1187 20.3 ˣ (Isoportulacaxanthin II) 6.45 Methionine-betaxanthin C14H18N2O6S 343.0968 343.0958 2.9 ˣ 6.75 Valine-betaxanthin C14H18N2O6 311.1242 311.1238 1.3 - ˣ 7.05 Miraxanthin III C17H18N2O5 331.1291 331.1288 0.9 121, 84 ˣ 7.15 17-Decarboxy-neobetanin C23H24N2O11 505.1459 505.1453 1.2 343, 297 ˣ 7.30 Neobetanin C24H24N2O13 549.1368 549.1352 2.9 387 ˣ 8.15 Isoleucine-isobetaxanthin C13H15N3O7 325.1403 325.1394 2.8 - ˣ

35 Table 1. Continued RT Identified compounds Molecular Experime Exact mass Mass error MS/MS Occurrence Reference (Min) formula ntal mass (ppm) fragments Betalains Derivatives Brasicc Beta D. a vulgari Ca s rot a 8.30 Isoleucine-betaxanthin C13H15N3O7 325.1410 325.1394 4.9 - ˣ (Nemzer, et al., 2011) 8.50 Phenylalanine-isobetaxanthin C18H18N2O6 359.1261 359.1238 6.4 303, 177 ˣ 8.60 S-tryptophan-betaxanthin C20H19N3O6 398.1348 398.1347 0.3 - ˣ 8.80 Leucine-isobetaxanthin (Isovulgaxanthin C13H15N3O7 325.1403 325.1394 2.8 ˣ IV) 8.95 2-Decarboxy-2,3-dehydro-neobetanin C23H22N2O11 503.1303 503.1296 1.4 341 ˣ 9.05 17-Decarboxy-2,3-dehydro-neobetanin C23H22N2O11 503.1298 503.1296 0.4 341 ˣ 9.15 15-Decarboxy-2,3-dehydro-neobetanin C23H22N2O11 503.1299 503.1296 0.6 341 ˣ 9.55 Betanidin C18H16N2O8 389.1016 389.0979 9.5 343 ˣ + 9.80 6´-feruloyl-betanin C34H35N2O16 727.1966 727.1981 -2.1 389 ˣ + 9.90 6´-feruloyl-isobetanin C34H35N2O16 727.1993 727.1981 1.7 389 ˣ 10.05 17-Decarboxy-betanin C22H26N2O11 507.1606 507.1609 -0.6 345 ˣ 10.05 15-Decarboxy-betanin C22H26N2O11 507.1603 507.1609 -1.2 345 ˣ Phenolic acids 0.80 Ferulic acid derivative 325.1229 ˣ ˣ ˣ (Kammerer, Carle, & Schieber, 2004) 6.95 Syringic acid C9H10O5 199.0590 199.0601 -5.5 - ˣ 7.55 5-P-Coumaroylquinic acid C16H18O8 339.1035 339.1074 -11.5 - ˣ 7.85 4-P-Coumaroylquinic acid C16H18O8 339.1036 339.1074 -11.2 - ˣ 8.30 3-O-Caffeoylquinic acid C16H18O9 355.1027 355.1024 0.8 - ˣ 8.70 5-O-Caffeoylquinic acid C16H18O9 355.1034 355.1024 2.8 - ˣ Amino acids 3.45 Phenylalanine C9H11NO2 166.0863 166.0863 0.0 - ˣ ˣ (Kammerer, Carle, & Schieber, 2004) 6.25 L-Tryptophan C11H12N2O2 205.0947 205.0972 -12.2 - ˣ ˣ (Kammerer, Carle, & Schieber, 2004)

36 Table 2. Levels of total ascorbic acid (TAA), and nitrate contents of processed vegetable samples.

Blender High-speed centrifugal Juicer Low-speed juicer

TAA Nitrate TAA Nitrate TAA Nitrate

Brassicaceae

White cauliflower 19.6 ± 0.6f 32.4 ± 2.4c 34.6 ± 0.9ef 24.6 ± 1.2cd 418.7 ± 20.5a 22.5 ± 0.8cde Yellow cauliflower 19.3 ± 3.1f 13.4 ± 0.3e 66.8 ± 1.1de 22.2 ± 1.2de 295.9 ± 5.2b 26.1 ± 0.3cd Green cauliflower 135.0 ± 7.7c 91.4 ± 7.7a 137.4 ± 6.7c 53.9 ± 0.7b 70.7 ± 0.2d 57.5 ± 0.6b Green kale 80.6 ± 4.5d 13.4 ± 0.6f 125.0 ± 2.4c 60.7 ± 0.7e 111.3 ± 7.1c 7.1 ± 0.3f Organic green kale 115.5 ± 9.4c 994.5 ± 50.71a 340.0 ± 7.2a 509.0 ± 17.5de 226.1 ± 8.3b 631.3 ± 17.2c Organic red kale 70.5 ± 9.9d 711.1 ± 26.6b 25.0 ± 0.5e 546.4 ± 8.4d 51.4 ± 1.7de 559.1 ± 3.3d Purple-white turnip 41.8 ± 0.3d 982.37 ± 6.5a 126.5 ± 0.4c 922.46 ± 21.3b 199.3 ± 1.2b 951.12 ± 14.7ab White baby turnip 38.2 ± 0.7d 405.55 ± 0.8c 196.8 ± 2.0b 377.67 ± 8.8c 268.6 ± 5.6a 315.03 ± 1.3d Red radish 50.5 ± 1.3d 578.1 ± 5.5a 174.0 ± 7.1ab 236.9 ± 7.1f 57.0 ± 1.0d 398.5 ± 5.9c Green radish 153.6 ± 15.5abc 279.9 ± 1.2e 126.9 ± 5.0bc 499.6 ± 8.0b 144.1 ± 15.0abc 315.7 ± 8.9d White radish 14.0 ± 0.4d 147.2 ± 1.7g 107.1 ± 7.1c 148.1 ± 4.9g 183.5 ± 18.5a 233.5 ± 0.9f Red Beet 12.3 ± 0.4cde 298.3 ± 19.9bc 12.1 ± 0.8cde 1270.7 ± 19.9a 22.0 ± 1.5ab 52.8 ± 2.2c Organic red beet 9.0 ± 0.4de 601.2 ± 3.2b 8.7 ± 0.4de 321.7 ± 4.9bc 13.4 ± 0.4cd 175.5 ± 0.6c

Golden beet 6.4 ± 0.3e 381.6 ± 17.3bc 17.7 ± 0.5bc 213.2 ± 0.8bc 25.0 ± 0.4a 275.4 ± 1.6bc

Organic golden beet 12.3 ± 0.2cd 30.3 ± 0.8c 23.3 ± 0.1ab 19.0 ± 0.4c 26.6 ± 3.4a 50.4 ± 0.8c Orange baby carrot 2.6 ± 0.3f 10.9 ± 0.4g 6.5 ± 0.8e 50.7 ± 1.9f 8.2 ± 0.6de 122.2 ± 0.1d Purple baby carrot 17.5 ± 0.3c 12.8 ± 1.7g 22.0 ± 0.7b 85.7 ± 0.9e 28.9 ± 0.5a 220.0 ± 2.0b Yellow baby carrot 7.7 ± 0.6e 170.9 ± 2.2c 11.0 ± 0.6d 305.7 ± 6.4a 7.8 ± 0.5e 86.2 ± 2.1e White baby carrot 285.5 ± 13.8a 3.2 ± 0.6f 16.1 ± 0.4g 8.3 ± 1.2de 129.6 ± 0.6d 8.1 ± 0.1de Data are expressed as mean ± SE (n = 3); values within each type of sample marked by the different letter within same column are significantly different (P < 0.05). All data were based on fresh weight basis.

37 Figure 1. The (A) total phenolics and (B) α-Amylase inhibitory activity of 21 vegetables processed by three techniques. Data are expressed as means ± SE of three replications. Means with same letter indicate no significant difference between treatments (P<0.05). W: white, Y: yellow, G: green, GO: green organic, BO: black organic, P: purple, R: red, RO: red organic; G: golden, GO: golden organic.

38 Figure 2. The (A) ABTS and (B) DPPH scavenging activity of 21 vegetables processed by three techniques. Data are expressed as means ± SE of three replications. Means with same letter indicate no significant difference between treatments (P<0.05). W: white, Y: yellow, G: green, GO: green organic, BO: black organic, P: purple, R: red, RO: red organic; G: golden, GO: golden organic.

39 Blender High-speed Low-speed A Centrifugal Juicer Juicer

Quercetin-3-diglucoside-7-glucoside Quercetin-3-sinapoyl-diglucoside-7-diglucoside Quercetin-3-O-(feruloyl)-sophoroside Kaempferol-3-O-(caffeoyl)-sophoroside-7-O-glucoside (isomer) Kaempferol-3-hydroxyferuloyl-diglucoside-7-glucoside Kaempferol-3-O-(caffeoyl)-sophoroside-7-O-diglucoside Kaempferol-3-feruloyl-diglucoside-7-diglucoside Kaempferol-3-sinapoyl-diglucoside-7-diglucoside Ferulic acid derivative Epigallocatechin Kaempferol-3-hydroxyferuloyl-diglucoside-7-diglucoside Kaempferol-3-O-(caffeoyl)-sophoroside-7-O-glucoside Quercetin-3-sophoroside-7-diglucoside Quercetin-3-diglucoside-7-glucoside (isomer) Trisinapoyl-diglucoside 5-P-Coumaroylquinic acid 4-P-Coumaroylquinic acid Cyanidin Kaempferol-3-(feruoyl)-sophoroside-7-O-glucoside Kaempferol-3-O-sophoroside Kaempferol-3-O-diglucoside-7-glucoside Kaempferol-3-sinapoyl-diglucoside-7-glucoside 1-Sinapoyl-2-feruloyl-diglucoside Disinapoyl-diglucoside Kaemphferol-3-xylosyl (feruloylglucosyl)-galactoside L-tryptophan Kaempferol-3-O-sophoroside (isomer) GKB GKB OGKB OGKB ORB ORB OBKB OBKB GKJ1 GKJ1 OGKJ1 OGKJ1 ORKJ1 ORKJ1 OBKJ1 OBKJ1 GKJ2 GKJ2 OGKJ2 OGKJ2 ORKJ2 ORKJ2 OBKJ2 OBKJ2 - - - - 1 2 1 2 - - - - 1 2 1 2 - - - - 1 2 1 2 ------1 2 1 2 2 2 1 2 1 2 1 2

Blender High-speed Low-speed B Centrifugal Juicer Juicer

Glutamine-betaxanthin Betanin 15-Decarboxy-2,3-dehydro-neobetanin S-tryptophan-betaxanthin Threonine-betaxanthin Glutamic acid-betaxanthin Glutamic acid-isobetaxanthin 17-Decarboxy-betanidin Asparagine-betaxanthin 17-Decarboxy-betanin Glutamine-isobetaxanthin 6´-feruloyl-betanin Miraxanthin III Dopamine-betaxanthin ℽ-Aminobutyric acid-betaxanthin Betanidin Phenylalanine-isobetaxanthin Prebetanin 2-Decarboxy-2,3-dehydro-neobetanin Isobetanin Neobetanin 6´-feruloyl-isobetanin Valine-isobetaxanthin Tyrosine-isobetaxanthin Phenylalanine L-tryptophan 17-Decarboxy-2,3-dehydro-neobetanin 17-Decarboxy-neobetanin Isoleucine-isobetaxanthin 2,17-Bidecarboxy-betnidin/isobetanidin Valine-betaxanthin Isoleucine-betaxanthin Leucine-isobetaxanthin Proline-betaxanthin Alanine-betaxanthin Methionine-betaxanthin RBB RBB ORBB ORBB GBB GBB OGBB OGBB RBJ1 RBJ1 ORBJ1 ORBJ1 GBJ1 GBJ1 OGBJ1 OGBJ1 RBJ2 RBJ2 ORBJ2 ORBJ2 GBJ2 GBJ2 OGBJ2 OGBJ2 - - - - 1 2 1 2 ------1 2 1 2 1 2 1 2 - - - - 1 2 1 2 ------1 2 1 2 1 2 1 2

Figure 3. Relative abundance of significantly changed metabolites are presented as box-and- whisker plot in (A) kale and (B) beet processed samples. The color box for each compound indicates the abundance of the compound, with the brown color annotates higher and the blue color represents lower abundance. The x and y axis represent sample type and compounds names, respectively. Sample types were shown as vegetable name plus processing techniques. Processing techniques were abbreviated as B/J1/J2 representing blending/high-speed centrifugal juicing/low- speed juicing. Kale sample name abbreviations: GK: green kale; OGK: organic green kale; OBK, organic black kale. Beet sample name abbreviations: RB: red beet; ORB: organic red beet; GB: golden beet; OGB: organic golden beet.

40 4. CHEMOMETRIC CHARACTERIZATION OF 30 COMMERCIAL THERMAL AND

COLD PROCESSED JUICES USING UPLC-QTOF-HR-MS FINGERPRINTS

Epidemiological studies have shown that fruits and vegetables are desirable sources of diverse health-promoting compounds with the potential to decrease the occurrence of oxidative stress-related diseases including cardiovascular disease, stroke, diabetes, Alzheimer’s disease, and neurodegenerative diseases (Hung, Joshipura, Jiang, Hu, Hunter, Smith-Warner, et al., 2004).

These various health-promoting compounds (ascorbic acid, phenolics, betalains, and polyphenols) quench the proliferation of radical oxygen (ROS) and reaction nitrogen (RNS) species, which are implicated in these diseases (D. Huang, Ou, & Prior, 2005).

Kale (Brassica oleracea) and beetroot (Beta vulgaris) are regarded as functional foods based on their putative health-promoting properties, but their tastes are not acceptable to certain consumers (Damunupola, Weerathilake, & Sumanasekara, 2014; S. Y. Kim, Sun, Kwon, Park, &

Lee-Kim, 2008). Moreover, many consumers find it inconvenient to consume large melons or prepare fresh vegetables. Therefore, in recent years, food manufacturers have focused on producing beverages with a multitude of functional ingredients to meet consumers’ need for convenience, palatability, and wellbeing.

To preserve the health-promoting properties of the functional foods in these beverages, numerous processing strategies have been used to obtain beverages with a refreshing taste, optimal nutrients, and few or no active microbes. Among the techniques used to process commercial juices, thermal processing is commonly used in the production of fruit and vegetable beverages due to its convenience and low cost (Jiménez-Sánchez, Lozano-Sánchez, Segura-Carretero, & Fernández-

Gutiérrez, 2017). Thermal processing transfers heat from the fastest processing medium to the slowest heating zone of the food, which causes detrimental effects on physical texture, color,

41 organoleptic qualities, and nutritional values, leading to consumer dissatisfaction with the resulting beverage (C.-Y. Wang, Huang, Hsu, & Yang, 2016).

Recent consumer demand for safer and more natural processed food has induced researchers and manufacturers to develop products that undergo minimal processing (Bhat &

Stamminger, 2015). Non-thermal processing technologies have been widely implemented and produce food products with desirable sensory characteristics, improved nutritional values, and enhanced health-promoting functionalities (Barba, Mariutti, Bragagnolo, Mercadante, Barbosa-

Cánovas, & Orlien, 2017b). In comparison to other non-thermal processing technologies (pulsed electric field, pulsed light, electron beam, plasma, etc), high-pressure processing (HPP) has been approved in United States and is one of the most successfully commercialized and promising non- thermal techniques used worldwide (H.-W. Huang, Wu, Lu, Shyu, & Wang, 2017). In HPP, food materials were treated with static high pressure for an appropriate period to preserve the flavor, color, and to extend shelf life by inactivating pathogenic microorganisms. HPP has proven to be an effective processing technology for liquid products with heat sensitivity, high-acid juices, blends, smoothies, fermented and fortified fruit and vegetable products, and processed beverages

(C.-Y. Wang, Huang, Hsu, & Yang, 2016).

Despite the advantages of the HPP technologies, consumers are still concerned with the authenticity of the ingredients of commercial juices, since they may not match the nutritional label claims (Borges, Mullen, & Crozier, 2010). Additionally, the price of commercially available non- thermal processed juice (example: cold-pressed juice) tends to be 5-fold higher than traditionally pasteurized juices (Table A-2). Previous studies have investigated the effect of HPP on bioactive compounds and antioxidant activities in fruits and vegetables, but a comprehensive study comparing the effects of thermal processing and HPP on phytochemical compounds and

42 antioxidant activities in commercial fruit and vegetable juices were not studied systematically due to the difficulty in screening the complicated chemical system in each juice.

Chemometrics is an efficient tool to classify products based on their chemical composition.

In the area of food and beverages, numerous investigations have been performed to discriminate origin, assess authenticity, and evaluate quality, by chemometrics coupled with analytical techniques such as mass spectrometry (MS) coupled to LC, GC, and nuclear magnetic resonance

(NMR), which is an effective tool which allows the characterization of the sensitive plant compounds and is able to identify active constituents with low abundance (Fidelis, Santos, Coelho,

Rodionova, Pomerantsev, & Granato, 2017; Jandrić, Roberts, Rathor, Abrahim, Islam, &

Cannavan, 2014). Next, in order to process and interpret complex data obtained within metabolomic-based studies, advanced data processing software algorithms and multivariate chemometric tools are needed.

In the present study, for the first time, the use of UPLC-QTOF-HR-MS fingerprints combined with multivariate data analysis were employed for classification of commercial fruit and vegetable juices with different processing techniques and prices. Highly complex HPLC-MS records were subjected to chemometric partial least square discriminant analysis (PLS-DA) analysis and heatmap to differentiate and identify unique health-promoting compounds. In addition, the variations in physicochemical attributes (color, Brix, and pH), phytochemical profiles

(ascorbic acid, total ascorbic acid, total phenolics), and radical-scavenging activities (DPPH and

ABTS) of these juices were also investigated.

43 4.1. Materials and methods

4.1.1. Juice samples

Twenty-seven fruit juices were collected from local retailers such as HEB, Kroger,

Walmart, and Farm Patch, based on their price, ingredients, and processing types (Table A-2). In addition, six melon juices (M5-M10) were obtained from Savor Fresh Farms (Yuma, AZ).

According to their ingredients, juices were divided into three major groups, which include kale, beetroot, and melon juices. Among the 30 juices, 13 were processed by thermal processing, and

17 were processed by cold-pressing combined with high-pressure processing (HPP).

4.1.2. Chemicals and reagents

L-ascorbic acid, gallic acid, sodium carbonate, 2,2-diphenyl-1-picryhydrazyl, 2,2’-azinobis (3-ethylbenzothiazoline-6-sulphonic acid), Folin-Ciocalteu reagent, HPLC grade methanol, and meta phosphoric acid were purchased from Sigma-Aldrich (St. Louis, MO, U.S.A.). Nitrate standards were purchased from Alfa Aesar (Wars Hill, MA, U.S.A.). HPLC-grade water

(resistivity 18.2 mΩ cm) was obtained from a Nanopure water purification system (Barnstead,

Dubuque, IA).

4.1.3. Color measurements

Lightness (L*), a* (green to red), b* (blue to yellow), and C (Chroma) were measured using a Minolta CR-200 Chroma Meter (Minolta, Osaka, Japan). The instrument was calibrated by a white tile standard. Hue was calculated by the equation H° = tan -1 (b*/ a*), where H° is the attribute which defines how the specific color is categorized.

44 4.1.4. pH and soluble solid measurements

The pH values were measured at room temperature with a pH meter (Mettler Toledo, OH,

U.S.A.). Total soluble solids contents were estimated with a portable refractometer (Reichert, NY,

U.S.A.). For each juice sample, the value was taken as the average of six measured results.

4.1.5. Determination of ascorbic acid, total ascorbic acid, and nitrate in commercial juices

Ascorbic acid (AA) and total ascorbic acid (TAA) were analyzed based on our published paper (Chebrolu, Jayaprakasha, Yoo, Jifon, & Patil, 2012b). AA and TAA were quantified by an

Agilent 1220 Series HPLC System, equipped with an Eclipse Plus C18 column (250 mm × 4.6 mm, 5 μm) and a photodiode array detector, was used with isocratic elution using 0.03 M aqueous phosphoric acid as a mobile phase. A 10 μL sample was injected into the column with a flow rate of 1 mL/min, and the peaks were monitored at 244 nm with a run time of 18 min.

Nitrate determination was based on our previously published protocol (Corleto, Singh,

Jayaprakasha, & Patil, 2018) with slight modifications. An aliquot of 5 µL was injected into an

Agilent 1200 Series HPLC System equipped with an Eclipse Plus C18 column (250 mm × 4.6 mm,

5 μm) and a photodiode array detector. The mobile phase consisted of an isocratic elution of 0.03

M aqueous phosphoric acid, as a mobile phase with a flow rate of 0.5 mL/min, was used.

Chromatograms were acquired at wavelength of 210 nm. The total run time was 15 min. Results were expressed as µg of nitrate per mL of fresh juice.

4.1.6. Sample preparation for total phenolics and antioxidant activities

Five milliliters of each juice sample were extracted with 10 mL of methanol by vortexing for 30 s and homogenization for 1 min. After the samples were centrifuged at 4480 g for 10 min,

45 the supernatant was measured. The residue was re-extracted by adding 3 mL methanol as mentioned above and the supernatant from both extractions was pooled, then the final volume was measured.

4.1.6.1. Total phenolics

Total phenolics were estimated by the Folin-Ciocalteu method as described by Chaudlhary et al (Chaudhary, Jayaprakasha, Porat, & Patil, 2012). The absorbance was monitored at 760 nm with a microplate reader (Bio Tek Instruments, Winooski, VT). Total phenolics were expressed as gallic acid equivalents in µg /mL of juice sample.

4.1.6.2. DPPH free radical scavenging activity

The DPPH free radical scavenging activity was performed according to our published protocols (Chaudhary, Jayaprakasha, Porat, & Patil, 2012) and results were expressed as µg of ascorbic acid equivalents per mL of juice sample.

4.1.6.3. ABTS free radical scavenging activity

The ABTS cation radical eliminating activity was determined according to the method outlined by Jayaprakasha and others (G. K. Jayaprakasha, Girennavar, & Patil, 2008). The reaction was initiated by adding 180 µL ABTS stock solution into the mixture and the absorbance was recorded at a wavelength of 734 nm. Results were expressed as ascorbic acid equivalents µg per mL of fresh juice.

46 4.1.7. Identification of phenolics by UPLC-HR-ESI-QTOF-MS

UPLC-HR-ESI-QTOF-MS was used for the identification of phenolic compounds in the

30 juice samples. The separation was performed on a 1290 Agilent HPLC LC system (Agilent

Technologies, Santa Clara, CA) equipped with a maXis impact mass spectrometer (Bruker

Daltonics, Billerica, MA, USA). A rapid resolution Eclipse plus C18 column (1.8 μm, 50 × 2.1 mm; Agilent) was used for separation of phenolic compounds with the binary mobile phase consisting of (A), 0.2% formic acid in water, and (B), 0.2% formic acid in water: 0.2% formic acid in acetonitrile (7:3). The column temperature was set at 35°C. The injection volume was 2 μL, the flow rate was 0.3 mL/min, and the runs were monitored at wavelengths of 280 and 320 nm. The following gradient was applied: 100% A (0–2 min), 100–20% A, 0–80% B (2–15 min), and 100–

0% B (19–20 min). The high-resolution mass spectral data were obtained by electrospray positive ionization. MS and the broadband collision-induced dissociation (bbCID) data were acquired at a m/z range of 50–1000 using electrospray ionization (ESI) mode. The capillary voltage of the ion source was 4,200 V. The nebulizer gas pressure was 2.8 bar and the drying gas flow rate 8.0 L/min.

Nitrogen was used for both nebulizer and drying gas. The drying gas temperature was 220°C. The transfer time of the source was 120.8 μs and the prepulse storage time was 1 μs. The quadrupole

MS collision energy and bbCID collision energy were set at 5 and 20 eV, respectively. The spectra rate was 1.4 Hz. For bbCID, the precursor ions were fragmented in the collision cell without pre- selection. By alternating the acquisition between MS and bbCID conditions, high and low collision energy data sets were collected simultaneously. External instrument calibration was performed with sodium formate. Nine sodium formate clusters were used in the calibration in high-precision calibration mode. An automated post-run internal mass scale calibration of individual samples was performed by injecting the above calibrant at the beginning and end of each run. The accurate mass

47 data were analyzed using the Data Analysis 4.3 software. The molecular formula for each compound was found by mass accuracy, isotopic patterns, adduct and fragment information using

SmartFormula. Furthermore, the mass data were exported to Bruker Compass Profile Analysis 2.1 software for background noise subtraction, data reduction, and peak alignment to obtain a table of mass and retention time pairs with associated intensities for all detected peaks. The Profile

Analysis parameters were set as follows, retention time range 0.1–18.9 min, mass range 100–1200

Da, and mass error window <25 ppm and retention time window 0.1 min. The marker intensities were normalized to the sum of the intensities in each sample to obtain the same total intensity of all the samples and data was processed by Pareto scaling and exported to Excel format and processed using MetaboAnalyst online software for data normalization and multivariate analysis.

4.1.8. Statistical analysis

All analyses, including physiochemical parameters (brix, pH, color), phytochemical contents (ascorbic acid, total ascorbic acid, nitrate, and total phenolics), and antioxidant activities

(DPPH and ABTS assay), were conducted using JMP Pro12 statistical data analysis software

(SAS, USA). The data were subjected to one-way analysis of variance (ANOVA) for mean comparison at p < 0.05. LC-MS data were subjected to multivariate statistical analysis including partial least square discriminant analysis (PLS-DA) and heatmaps were constructed using

MetaboAnalyst 4.0 software (http://www.metaboanalyst.ca). All results were expressed as means

± SE.

48 4.2. Results and discussion

4.2.1. Variation in color attributes, brix, and pH

Colors in vegetables, fruits, and processed juices are important indicators of food quality which also reflect the levels of some health-promoting compounds, including antioxidants such as betalains, anthocyanins and carotenoids (Dominy, 2004). The values for color attributes (L, a*, b*,

C, and h), pH, and °Brix of the 30 commercial juices are shown in Table A-3. In kale juices, the lightness* values ranged from 35.92 to 48.95. Grown Vegetable Juice (K3) and Healthy Greens

(K2), had a* values of 9.64 and 0.61, respectively, indicating the presence of red color in these juices. The reddish color can be partly attributed to the lycopene and carotenoids in the tomato and carrot juices in Grown Vegetable Juice (K3). The overall chroma and hue values in cold-pressed juices were lower than those of thermally processed juices. It is possible that cold-pressed juices were less saturated than thermally processed juices, due to the larger quantities of solids retained in cold-pressed juice products.

In beet juices, L, a*, b*, C, and H* were variable based on the juice processing techniques and ingredients. For example, the V8 brand juices showed the highest brightness followed by cold- pressed juices such as Organic Beet (B9) and Cucum Berry (B10). Furthermore, dark purple colored pure beetroot juices such as Beet Juice (B5) and Pure Beet (B6) had the lowest L and a value, which reflected higher betalain contents.

Among all melon juices, Antioxidant Infusion Juice (M2) had a bright red color and was the only juice that had a negative b* value. Watermelon juices were generally high in lightness and redness values, which could be attributed to the presence of red colored lycopene. Among all

Kiss Melon cold-pressed juices, Beet Boost Juice (M10) had the lowest L value and lower b* value due to presence of higher levels of betalain in beetroot juices. 49 Brix is another important factor affecting juice palatability. In general, among all juices, the sugar content varied from 3.20 (M2) to 14.47 (K1) °Brix (Table A-3). The pH of all juices ranged from 3.25 (M2) to 4.95 (M7), which gave the juices a bright, tangy taste.

4.2.2. Influence of juice ingredients and processing techniques on ascorbic acid, total

ascorbic acid, and nitrate

The results of AA, total AA (TAA), and nitrate contents in 30 commercial juices with three categories were presented in table 1. Among kale juices (K1–K10), Healthy Greens (K2) had the highest AA (46.22 µg/mL), which was produced thermally by combining fruits and vegetable juices with vitamin C as a preservative and its price was the lowest compared to other kale juices in this study (Table A-2). Followed by thermally processed Green Machine (K1), which had 19.03

µg/mL AA that coming from plant source. In comparison, the cold pressed kale juices (K3-K10) depicted lower AA and showed no significant difference among them. According to nitrate content, cold pressed Radiant Probiotic Organic (K6) showed the highest levels (510.37µg/mL), followed by thermally obtained Healthy Greens (K2), with the value of 404.90 µg/mL.

Considering that kale, celery and spinach are rich sources of nitrates, the results are in agreement with the ingredients found in the juices (Petersen & Stoltze, 1999).

Among the 11 various beetroot juices tested, V8 brand juices (B1-B4) had significantly higher amounts of AA and TAA than other beet juices, despite the prices were lower than its respective beet juices. The highest amounts of AA and TAA were found in Original 100%

Vegetable Juice Low Sodium (B3) and Spicy Hot 100% Vegetable Juice (B4), with values of

660.59 and 656.76 µg/mL, respectively. Both juices contained vitamin C as a preservative, which contributed substantially to the amounts of AA and TAA. The highest amount (907.79 -1074.66

50 µg/mL) of nitrate was detected in pure beetroot juices, Pure Beet (B6) and Beet Juice (B5), suggesting that beetroot juice is a good source of dietary nitrate. Significant nitrate differences observed between the cold-pressed juices such as Organic Beet (B9) and Cucum Berry (B10), which is likely due to their different ingredients present in each juice.

Among melon juices, Antioxidant Infusion (M2) had the highest amount of AA (44.80

µg/mL). Honey Kiss juice (M8) showed the highest TAA content (276.80 µg/mL), which may be due to added vitamin C. The highest nitrate was detected in Melon Beet Boost juice (M9, 209.35

µg/mL), since the ingredients kale and spinach are rich in nitrate. The present research demonstrated that the fruit and vegetable juices are rich in AA, TAA, nitrate and their levels were influenced by the ingredients than the processing techniques. Ascorbic acid is one of the most important free radical scavengers, but it is found in both reduced form (ascorbic acid) and oxidized form (dehydroascorbic acid) After treating with reducing reagent TCEP, the dehydroascorbic acid has been converted to AA, the TAA was measured by HPLC. In addition, nitrate acts as a substrate for in vivo generation of nitric oxide in the human body. The consumption of nitrate provides NO- like effects, including reduction of blood pressure, inhibition of platelet aggregation, and vasoprotective activities (Lundberg, Carlström, Larsen, & Weitzberg, 2010).

4.2.3. Free radical scavenging activity and total phenolics

Antioxidant activity is generally measured by more than one assay based on the different principle. In the present study, DPPH and ABTS assays were used to test the ability of antioxidants in the juice samples to scavenge the free radicals. The ABTS cation radical is scavenged by hydrophilic and hydrophobic antioxidants, whereas DPPH is scavenged by the majority of hydrophobic compounds in presence of organic solvents (Floegel, Kim, Chung, Koo, & Chun,

51 2011). Therefore, these two assays test different aspects of the antioxidant activity of juice samples. The results of radical scavenging activity and total phenolics (TP) were presented in

Appendix Fig.7. A significant variation in TP was observed among kale juices, with values ranging from 67.16 µg/mL to 172.05 µg/mL of gallic acid equivalents. Green Machine (K1), made up of

100% vegetables without additives or added water, showed the highest TP. The lowest TP was found in Farms Daily Greens (K1), which consisted of diluted mixed juices. In beetroot blended smoothies, Farms Daily Roots (B7), had a significantly higher content of TP (606.29 µg/mL) than other mixed juices. This result could be explained by Kujala and others (T. Kujala, Loponen, &

Pihlaja, 2001) who compared the TP in different parts of beetroot and found the highest amount of TP was found in peel, followed by crown and flesh. In our study, the blended beet smoothies retained more byproducts include peel and pulps that had various phenolics, which significantly contributed to TP. In addition, the added purple carrot juice, which is rich in phenolic compounds, could be another reason that Farms Daily Roots (B7) juice had high TP. Furthermore, Beet Juice

(B6) contained high TP contents due to the probiotic lactic acid bacteria (LAB) fermentation process, which converted complex phenolics into free forms and depolymerized high molecular weight phenolics by polyphenol oxidases. Additionally, acidification might have stabilized the phenolics, which led to the higher TP levels compared to other juices. The lowest TP was found in Very Veggie (105.56 µg/mL). In melon juices, the highest TP was found in Antioxidant Infusion

Juice (M2) and the lowest TP was in Watermelon Juice (M3) due to the presence of only 10% of juice.

In this study, the antioxidant activities of 30 commercial juices were tested and among kale juices, Green Machine (K1) was the most potent (385.64 µg/mL) scavenger of the ABTS radical, followed by Healthy Greens (K2, 243.67 µg/mL). The other mixed juices had a moderate

52 inhibitory effect, ranging from 63.91 µg to 180.08 µg of AA equivalents per mL of juice. Beetroot juices depicted efficient scavenging of the ABTS radical ranging from 164.00 µg/mL to 524.00

µg/mL, and the highest value was found in Farms Daily Roots (B7). The juice with the lowest value was Organic Beet (B9), which was obtained by blending beet, carrot, orange, and lemon juice, had an ABTS value of 164.00 µg/mL. In melon juices, the ABTS radical ranging from 24.52

µg/mL to 456.28 µg/mL. Antioxidant Infusion (M2) was the most effective scavenger of the ABTS radical and Watermelon Juice (M3) had the lowest activity among all tested juices. Similar to the

ABTS results, in kale juices, the highest DPPH value was obtained in Green Machine (K2) with

AA equivalents of 265.69 µg/mL of juice. Among melon juices, the levels of DPPH ranged from

75.82 to 317.91 µg/ mL AA equivalents, with the lowest DPPH activity found in Watermelon

Juice (M3), and the highest was found in Antioxidant Infusion (M2). The highest DPPH radical scavenging activity was observed in pure beetroot juices such as Beet Juice (B5) and Pure Beet

(B6), with DPPH values of 619.08 µg/mL and 544.67 µg/mL of AA equivalents, respectively.

Similar results were reported by Wootton-Beard, Moran, and Ryan,(Wootton-Beard & Ryan,

2011) who investigated antioxidant activities of 23 commercial juices with different types and ingredients. The authors demonstrated that beetroot juice had the highest DPPH and ABTS radical scavenging activities compared to other pure or mixed commercial juices.

In the present study, the discrepancies between the DPPH and ABTS radical scavenging activities were observed. It is possible that the nature of antioxidants present in each juice determines levels of ABTS and DPPH. Furthermore, different DPPH and ABTS results help to determine the discrepancies of reaction kinetic mechanisms between these assays (G. K.

Jayaprakasha, Girennavar, & Patil, 2008). According to previous study (Schaich, Tian, & Xie,

2015) two types of radical scavenging mechanisms, hydrogen atom transfer (HAT) and single

53 electron transfer (SET), occur in the food matrix. The ABTS radical quenching reaction was generally initiated by SET, which is a fast and efficient reaction system, whereby antioxidants donate two electrons that allow full access for ABTS radical site within milliseconds. Afterwards, the reaction is impeded as the adduction of phenolic rings and acid groups hinders the active site.

In contrast, DPPH reactions are more complicated and mostly attributed to the slow HAT mechanism, unless some potent hydrogen-bonding solvents interfere with the release of hydrogen atoms, which promotes SET over HAT in certain samples. Furthermore, certain compounds (AA

.- and phenolics) autoxidize oxygen to O2 , which reacts rapidly with ABTS radicals. In the DPPH solvent system, low antioxidant activity may result from weak reactions.

4.2.4. Pearson correlation analysis for variables

Pearson correlation analysis was performed to determine relationship among variables. As shown in Table 4, the Pearson correlation coefficients (r) of TP with DPPH and ABTS assays in kale juices were positive and high (r = 0.7993 with DPPH, r = 0.7842 with ABTS), suggesting that phenolic compounds were the main components responsible for free radical scavenging activities.

AA exhibited a moderate positive correlation with TAA (r=0.7532), DPPH (r=0.3117), and ABTS

(r=0.5309). These results suggested that phenolic compounds and AA contributed to the free radical scavenging activities of kale juices. Kale juices had numerous phenolic compounds and their higher antioxidant activities were possibly due to the number of acidic, phenolic hydroxyl groups, aromatic rings and free electron pairs on the phenolic oxygen, which induced an increase in electron delocalization (Miller & Rice-Evans, 1997). In beetroot juices, the correlations between

TP with DPPH (r = 0.9025) and ABTS results were also high (r = 0.7803). However, the AA and

TAA were low or negatively correlated to those assays (r = -0.1503 and 0.1102). These results

54 suggested that phenolic compounds were main contributors to DPPH and ABTS free radical scavenging activities in beetroot juices, which agreed to previous research (Bavec, Turinek,

Grobelnik-Mlakar, Slatnar, & Bavec, 2010). In melon juices, high and positive correlations were found for TP with DPPH (r = 0.7239) and ABTS (r = 0.7625) assays, but moderate correlations were observed between AA and TAA with these assays, suggesting phenolic compounds were main contributors in melon juices. Ascorbic acid has been considered as effective free radical scavengers, whereas the contribution to total antioxidant activities varied in different juice products, with percentage ranging from <5% in apple, pineapple, and vegetable juices, to 65–100% of citrus juice (Gardner, White, McPhail, & Duthie, 2000). Among all the assays, the correlation between DPPH and ABTS assay was higher than 0.9, suggesting both assays were suitable for detecting free radical scavenging activities in all 30 juices, despite the discrepancies of reaction mechanism. Our results suggest that it is difficult to specify the component responsible for antioxidant activities since the ratio of ingredients were not provided on the juice samples.

4.2.5. Untargeted metabolomics analysis in commercial juice samples

In the present study, UPLC-HR-ESI-QTOF-MS analysis was performed to obtain retention times, accurate molecular masses, and MS/MS fragmentations for the characterization of metabolites to discriminate the juice samples. Table 5 summarizes the molecular ion adducts, accurate mass and major MS/MS fragments of identified compounds in the juices. In the present study, we identified 48 metabolites representing three classes, i.e., flavonoids, phenolic acids, and betalains, in kale, beet, and melon juices. Kale juices mainly included flavonoid derivatives of kaempferol and quercetin. For instance, we tentatively identified quercetin-3-diglucoside-7- glucoside (m/z 788), kaempferol-3-O-diglcoside-7-glucoside (m/z 772), kaempferol-3-(feruoyl)-

55 sophoroside (m/z 934), quercetin-3-feruoyl-diglucoside-7-diglucoside (m/z 1126), kaempferol-3- feruloyl-diglucoside-7-diglucoside (m/z 948), and kaempferol-3-feruloyl-diglucoside-7- diglucoside (m/z 1110). The major health-promoting compounds found in beet juices include betacyanin derivatives in which betanidin (m/z 177) was the aglycone for most of the juices

(Azeredo, 2009). A total of 23 compounds were identified in different 11 commercial beet juices.

In addition to 14 betalains, 5 phenolics were found, which were 1,3-Dicaffeoylquinic acid (m/z

517), chlorogenic acid (isomer) (m/z 355), caffeoylquinic acid (m/z 731), ferulic acid derivative

(m/z 519). Further, melon juices predominantly contained quercetin (m/z 303) and kaempferol

(m/z 287) derivatives due to the blending of different juices including grape extract. A total of 11 compounds were identified in various melon juices tested in the present study. Interestingly, phenylalanine was found in all three juice categories.

4.2.6. Influence of processing techniques on phenolic compounds

In recent years, chemometrics has emerged as an efficient tool used in food industries to classify products, evaluate food quality, and detect food authenticity. In this section, chemometric methods OPLS-DA (Fig. 4A-C) was performed and perfectly separated thermal and cold processed kale, beet, and juices, and heatmap provides an overview of abundance of each metabolite.

According to the heatmap of kale juices (Fig 4A), most of the cold-pressed kale juices were abundant in kaempferol and quercetin glycosides. For instance, cold-pressed Organic Emerald

Green (K8) was abundant in quercetin-3-diglucoside-7-glucoside and its isomer (m/z 789), kaempferol-3-sinapoyl-diglucoside-7-glucoside (m/z 979), kaempferol-3-feruloyl-diglucoside7- diglucoside (m/z 1111) and epigallocatechin (m/z 307). This juice also contained spinacetin 3-O- glucosyl-(1-6)-glucoside (m/z 671) attributed to the presence of spinach as one of the ingredients

56 (Barkat, Singh, Jayaprakasha, & Patil, 2018). Similarly, cold-pressed Grown Vegetable Juice (K3) made of kale, spinach, yellow carrot, tomato and other fruits or vegetables, showed the presence of kaempferol-3-O-caffeoyl-sophoroside (m/z 935), kaempferol-3-O-sophoroside (m/z 611), gallocatechin (m/z 307), and phenylalanine (m/z 166). However, thermal-processed Healthy

Greens (K2) had medium levels of quercetin-3-diglucoside-7-glucoside isomer (m/z 789), sinapoyl-diglucoside-7-glucoside (m/z 979), and kaempferol-3-sinapoyl-diglucoside-7-glucoside

(m/z 979), indicating those compounds could be considered as potential metabolites screening the difference of thermal and cold processed kale juices.

The heatmap of beet juices discriminated the cold-pressed and thermally processed juices by identifying certain compounds such as 2, 17-bidecarboxy-2,3-dehydro-neobetanin and its isomer (m/z 459), 2-decarboxy-2,3-dehydro-neobetanin (m/z 503), and isobetanin (m/z 551).

These compounds were significantly higher in thermal-processed beet juices compared with cold- pressed juices (Fig. 4B). In cold-pressed beet juices, Organic Beet (B9) and Organic Cucum Berry

(B10), we found only two phenolic compounds, namely caffeolyquinic acid (m/z 731) and a ferulic acid derivative (m/z 503), in relatively higher amounts compared to other compounds. In sum, the betalains (betacyanins and betaxanthins) and derivatives, which were abundant in thermally processed juices, could be considered as potential health-promoting compounds based on their high abundance and unique existence in cold-pressed juices.

In the melon juice heatmap (Fig 4C), thermal processed Synergy Watermelon Wonder

(M1) was distinguished from other melon juices by its various ingredients such as watermelon, cherry, lime, and tea extract. This juice was abundant in kaempferol and quercetin glycosides, namely quercetin 3-rhamnosyl (1→2)-rhamnosyl-glucoside (m/z 757), kaempferol 3-O-(2- rhamnodyl-galatoside)-7-O-rhamnoside (m/z 741), kaempferol 3-O-glucosyl-rhamnosyl-

57 galatoside (m/z 757), kaempferol 3-O-glucosyl-rhamnosyl-glucoside (m/z 757). Another thermally processed juice, antioxidant infusion (M2), had significantly higher epigallocatechin 3-

O-gallate (m/z 459). In cold-pressed melon juices, phenylalanine (m/z 166) was found in each juice, except for Honey Kiss Juice (M7), which was rich in quercetin 3-O-galactoside 7-O- rhamnoside (m/z 611) and quercetin 3-O-rhamnosyl-galactoside (m/z 611). Summer Kiss Juice

(M6), a cold-pressed juice, also had those compounds along with kaempferol 3-O-galactoside-7-

O-rhamnoside (m/z 595).

To investigate the differences of other parameters such as TP and antioxidant activities of juices with thermal and cold process techniques, partial least square discriminant analysis (PLS-

DA) coupled to whisker plots was conducted. PLS-DA, an effective pattern recognition technique used to discriminate samples, was used to determine the significance of group separations, and search for potential health-promoting compounds. In each juice type, PLS-DA separated most cold-pressed and thermally processed juices (Fig.5A–C), except for a few samples were clustered or close, which had similar physiochemical attributes, phytochemical contents, or free radical scavenging activities. Thermal-processed kale, beet, and melon juices had higher total phenolics,

DPPH, and ABTS values. Table 5 shows the identified kaempferol and quercetin conjugated glucosides in kale and melon juices. During thermal processing, the sugar moiety in flavonoid glycosides, might be cleaved in kale and melon juices providing more free hydroxyl groups, which will increase the phenolics and radical scavenging activities. Therefore, thermal-processed kale and melon juices had higher phenolics and radical scavenging activities compared to cold-pressed juices. Kaempferol and quercetin derivatives are powerful antioxidants due to their hydroxy groups and the unsaturation in the C ring, which allowed electron delocalization across the molecules

(Rice-Evans, Miller, & Paganga, 1996). Another study investigated the effect of thermal

58 processing methods on antioxidant activities of red beet, and they found an increase after the treatment, which agreed with the results found in our study (Ravichandran, Saw, Mohdaly, Gabr,

Kastell, Riedel, et al., 2013).

4.2.7. Influence of production system on phenolic compounds

In recent years, consumers have increasingly preferred organic food. Although numerous studies have been conducted to determine the levels of antioxidant activities of organic and conventional crops, the results were not conclusive (Kazimierczak, Hallmann, Lipowski, Drela,

Kowalik, Püssa, Matt, Luik, Gozdowski, & Rembiałkowska, 2014; Uckoo, Jayaprakasha, & Patil,

2015). In the present study, PLS-DA was applied to classify the juices obtained from conventional and organic production systems based on their TP and antioxidant activities. The PLS-DA 3D plot

(Appendix Fig S8 A–C) showed two distinct clusters for conventional and organic production systems in kale, beet, and melon juices. Box and whisker plots demonstrated that commercial beet juices obtained from organically grown crops had higher TP, DPPH, and ABTS levels, whereas kale and melon juices acquired from conventionally grown crops had higher levels of phenolics,

DPPH, and ABTS. Similar findings reported by Bavec and others (Bavec, Turinek, Grobelnik-

Mlakar, Slatnar, & Bavec, 2010) showed that TP and DPPH activity were significantly higher in organically grown beets than in conventionally beets. Kazimierczak and coauthors found organic beetroots contained significantly higher amounts of specific phenolic compounds and antioxidant activities (Kazimierczak, Hallmann, Lipowski, Drela, Kowalik, Püssa, Matt, Luik, Gozdowski,

Rembiałkowska, et al., 2014). Additionally, Unal, Susanti, and Taher found significantly higher polyphenol content and antioxidant activities in conventionally grown Brassica leafy vegetables compared to the organically grown extracts (Unal, Susanti, & Taher, 2014). The authors explained

59 that the discrepancies in these results could be due to environmental factors such as season, geography, or agronomic practices.

4.3. Conclusion

The present study reports that the processing techniques, production system, and ingredients will affect significantly the phytochemical composition and antioxidant activities.

Untargeted UPLC-HR-ESI-QTOF-MS based metabolomics data revealed the presence of 48 metabolites including 27 flavonoids, 14 betalain derivatives, 5 phenolics and 2 free amino acids in

30 commercial juices. Multivariate statistical analysis illustrated that kaempferol and quercetin glycosides, decarboxylated betalains, and quercetin derivatives were could be used as potential markers in discriminating the processing techniques, production system, and ingredients in those kale, beet, and melon juices, separately.

Furthermore, results of antioxidant activities and phytochemical contents highlighted the health benefits of all the juices whereas the results were more affected by ingredients than processing techniques, suggesting the importance of analyzing food components. This study demonstrated that a metabolomic analysis, coupled to chemometric tools has potential as a fast and efficient approach for discriminating the processing techniques of commercial juices.

60 Table 3. Results* for ascorbic acid, total ascorbic acid, and nitrate content in 30 commercial juices.

Type* Code Juice and Brand Names Ascorbic acid Total ascorbic acid Nitrate * K1 Green Machine (Naked) 19.03 ± 0.71b 89.24 ± 1.00a 13.91 ± 0.51h K2 Healthy Greens (V8) 46.22 ± 2.51a 67.86 ± 2.53b 404.90 ± 4.51b K3 Grown Vegetable Juice (Estate) 3.45 ± 0.05c 6.85 ± 0.08g 318.03 ± 1.64c K4 Green Delight Organic (Suja) 5.06 ± 0.20c 8.13 ± 0.06fg 49.34 ± 1.76g K5 Uber Greens Organic (Suja) 3.32 ± 0.04c 22.17 ± 0.79c 208.45 ± 0.53e K6 Radiant Probiotic Organic (Suja) 3.79 ± 0.08c 18.08 ± 0.55cd 510.37 ± 2.22a K7 Organic Kale (1915) 4.05 ± 0.13c 9.23 ± 0.11fg 230.03 ± 4.30d

K8 Organic Emerald greens (Evolution) 3.08 ± 0.02c 15.59 ± 0.35de 164.25 ± 0.14f K9 Organic Green Devotion (Evolution) 4.68 ± 0.06c 11.56 ± 0.28ef 397.03 ± 1.79b K10 Super Fruit Greens (Evolution) c fg h

Kale Juices Kale 6.57 ± 0.17 10.24 ± 0.13 20.48 ± 0.31

B1 Strawberry Banana (V8) 243.05 ± 10.38b 427.80 ± 28.59d 93.65 ± 0.29b B2 Original 100% Vegetables juice (V8) 219.93 ± 25.54b 1003.25 ± 50.66b 79.80 ± 4.25c B3 Original 100% Vegetables Juice Low Sodium (V8) 660.59 ± 8.82a 803.83 ± 15.74c 85.13 ± 10.00c B4 Spicy Hot 100% Vegetables Juice (V8) 656.71 ± 2.69a 1182.86 ± 96.13a 86.71 ± 9.90c B5 Beet Juice (Biotta) 2.59 ± 0.05c 4.86 ± 0.03e 907.79 ± 8.37a B6 Organic Pure Beet (Lakewood) 3.93 ± 0.08c 5.30 ± 0.27e 1074.66 ± 8.48a B7 Farms Daily Roots (Bolthouse) 3.38 ± 0.04c 261.8 ± 28.3d 512.12 ± 3.42c

B8 Very Veggie (R.W. Knudsen) 3.16 ± 0.08c 29.78 ± 1.03e 18.63 ± 1.56c B9 Organic Beet (1915) 4.78 ± 0.08c 13.60 ± 0.21e 359.35 ± 5.05b B10 Organic Cucum Berry (Simple Truth) c e c

Beet Juices 3.80 ± 0.07 26.55 ± 0.87 41.96 ± 0.59

M1 Synergy Watermelon Wonder (GTS) 2.61 ± 0.04e 12.03 ± 0.39f 3.07 ± 0.37g M2 Antioxidant Infusion (Bai) 44.80 ± 0.56a 50.44 ± 0.77e 5.82 ± 0.64fg M3 Watermelon (Tropicana) 2.72 ± 0.01e 6.62 ± 0.03f 5.79 ± 0.47fg M4 MLN Watermelon (WTR) 3.35 ± 0.03de 11.15 ± 0.11f 60.12 ± 0.64c M5 Sugar Kiss Juice Raspberry (Kiss Melon) 7.79 ± 0.66b 159.15 ± 1.66c 42.15 ± 0.33d M6 Summer Kiss Juice (Kiss Melon) 5.22 ± 0.04c 244.09 ± 6.14b 49.16 ± 2.28cd M7 Honey Kiss Juice (Kiss Melon) cd a ef

4.30 ± 0.18 276.80 ± 13.65 18.65 ± 0.18 M8 Sugar Kiss Juice Apple (Kiss Melon) 3.51 ± 0.07de 18.56 ± 0.26f 27.40 ± 0.49e M9 Melon Garden Greens Juice (Kiss Melon) 3.30 ± 0.03de 160.52 ± 1.59c 209.35 ± 9.22a M10 Melon Beet Boost Juice (Kiss Melon) de d b

Melon Melon Juices 3.06 ± 0.03 130.81 ± 1.00 108.31 ± 0.27 *Values (μg/mL) are expressed as mean ± SE from two biological experiments with three replicates ** The above juices were categorized based on assumption that those juices may contain the major amount of respective juices (kale, beet, melon). However, labels do not state the composition of each juice.

61 Table 4. Pearson’s correlation coefficients (r) of color parameters, phytochemical contents, and antioxidant activities in commercial kale, beet, and melon juices. DPPH TP ABTS AA TAA Nitrate Kale Juices DPPH 1.0000 TP 0.7994 1.0000 ABTS 0.9351 0.7842 1.0000 AA 0.4943 0.3117 0.5309 1.0000 TAA 0.7721 0.4767 0.7495 0.7532 1.0000 Nitrate -0.4330 -0.3962 -0.3374 0.1425 -0.1476 1.0000 Beet Juices DPPH 1.0000 TP 0.9025 1.0000 ABTS 0.9043 0.7803 1.0000 AA -0.1503 -0.4059 0.1102 1.0000 TAA -0.0849 -0.3143 0.2278 0.8409 1.0000 Nitrate 0.6798 0.6916 0.4246 -0.4612 -0.5175 1.0000 Melon Juices DPPH 1.0000 TP 0.7239 1.0000 ABTS 0.9203 0.7625 1.0000 AA 0.6015 0.5802 0.4989 1.0000 TAA 0.3714 0.5459 0.3619 0.8615 1.0000 Nitrate -0.3681 -0.5036 -0.4100 -0.2980 -0.1414 1.0000 Abbreviations: TP: total phenolics; AA: ascorbic acid; TAA: total ascorbic acid.

62 Table 5. Characteristic marker compounds identified by UPLC-HR-MS in various juice samples. RT Identified compound Molecular Experimental Adduct Theoretical Mass MS/MS Juice Type (min) formula mass mass error fragments Reference (ppm) Kale Beet Melon + 1.40 Epigallocatechin C15H14O7 307.0925 [M + H] 307.0812 36.80 230, 84 X (Bresciani, Calani, Cossu, Mena, Sayegh, Ray, et al., 2015)

+ 2.65 2,17-Bidecarboxy-2,3-dehydro- C22H22N2O9 459.1601 [M + H] 459.1398 44.2 330, 284, 203 X (Nemzer, et al., neobetanin 2011)

+ 3.50 Phenylalanine C9H11NO2 166.0850 [M + H] 166.0863 -7.83 103 X X X (Ma, Tian, Luo, Zhou, Sun, & + 4.20 1,3-Dicaffeoylquinic acid C25H24O12 517.1558 [M + H] 517.1341 42.0 452, 325, 136 X Ma, 2013)

+ 5.75 L-Tryptophan C11H12N2O2 205.0960 [M + H] 205.0972 -5.9 - X

+ 6.00 Chlorogenic acid C16H18O9 355.1028 [M + H] 355.1024 1.1 163 X (Georgiev, Weber, + 6.05 Chlorogenic acid isomer C16H18O9 355.1025 [M + H] 355.1024 0.3 163 X Kneschke, Denev, Bley, & Pavlov, 2010)

+ 6.20 Betanin C24H26N2O13 551.1592 [M + H] 551.1508 15.2 389, 150 X (Nemzer, et al., 2011) + + 6.30 2’-O-Glucosyl- C30H37N2O18 713.2042 [M + H] 713.2036 0.8 551, 389 X betanin/isobetanin + 6.45 Isobetanin C24H26N2O13 551.1559 [M + H] 551.1508 9.3 389, 298, 136 X

+ 6.55 17-Decarboxy-isobetanin C23H26N2O11 507.1659 [M + H] 507.1609 9.9 345 X

+ 6.65 15-Decarboxy-betanin C23H26N2O11 507.1652 [M + H] 507.1609 8.5 345 X

+ 7.20 2-Decarboxy-isobetanin C23H26N2O11 507.1655 [M + H] 507.1609 9.1 345 X

+ + 7.30 2,17-Bidecarboxy- C22H27N2O9 463.1752 [M + H] 463.1711 8.9 301 X betanidin/isobetanidin + 7.60 2-Decarboxy-betanin C23H26N2O11 507.1649 [M + H] 507.1609 7.9 345 X

+ 7.60 Caffeoylquinic acid C16H18O9 731.1883 [M + H] 731.1794 12.2 377, 163 X (Yang, Jayaprakasha, + 7.65 Quercetin-3-diglucoside-7- C33H40O22 789.1884 [M + H] 789.2084 -25.3 541, 435, 387, X & Patil, 2018b) glucoside 303

63 Table 5. Continued RT Identified compound Molecular Experimental Adduct Theoretical Mass MS/MS Juice Type (min) formula mass mass error fragments Reference (ppm) Kale Beet Melon + 7.70 Neobetanin C24H24N2O13 549.1414 [M + H] 549.1351 11.5 287, 341 X (Nemzer, et al., + 7.85 17-Decarboxy-neobetanin C23H24N2O11 505.1515 [M + H] 505.1453 12.3 343, 297 X 2011)

+ 8.00 δ-Viniferin C28H22O6 455.1410 [M + H] 455.1489 -17.4 367, 195 X (Vitaglione, Sforza, & Del Rio, 2012) + 8.15 Kaempferol-3-O-diglucoside- C33H40O21 773.1958 [M + H] 773.2135 -22.9 633, 395, 287 X (Yang, 7-glucoside Jayaprakasha, & Patil, 2018b) + 8.55 Kaempferol-3-O-(caﬀeoyl)- C42H46O24 935.2477 [M + H] 935.2452 2.7 737, 633, X (Lin & Harnly, sophoroside 463, 287 2009)

+ 8.90 2-Decarbxy-neobetanin C23H24N2O11 505.1521 [M + H] 505.1453 13.5 343, 297 X (Nemzer, et al., 2011) + 9.05 2,17-Bidecarboxy-2,3-dehyo- C22H22N2O9 459.1414 [M + H] 459.1398 3.5 297 X neobetanin (isomer) + 9.10 Epigallocatechin 3-O-gallate C22H18O11 459.0906 [M + H] 459.0922 -3.5 287, 139 X (Davis, Cai, Davies, & Lewis, 1996)

+ 9.40 Quercetin-3-feruloyl- C49H58O30 1127.2766 [M + H] 1127.3086 -28.4 987, 825, X (Yang, diglucoside-7-diglucoside 523, 406, 303 Jayaprakasha, & + 9.80 Kaempferol-3-feruloyl- C49H58O29 1111.2821 [M + H] 1111.3137 -28.4 809, 541, X Patil, 2018b) digulcoside-7-diglucoside 411, 287, 177 + 9.85 C43H48O24 949.2327 [M + H] 949.2608 -29.6 809, 707, X Kaempferol-3-(feruoyl)- 523, 411, sophoroside-7-O-glucoside 339, 287, 177 9.85 Ferulic acid derivative 519.2527 X (Kammerer, Carle, & Schieber, 2004)

+ + 10.10 2-Decarboxy-2,3-dehydro- C23H23N2O11 503.1317 [M + H] 503.1296 4.2 341 X (Nemzer, et al., neobetanin 2011)

+ 10.95 Quercetin-3-diglucoside-7- C33H40O22 789.2026 [M + H] 789.2084 -7.3 651, 541, X (Yang, glucoside (isomer) 407, 303 Jayaprakasha, & + 11.45 Kaempferol-3-O-sophoroside C27H30O16 611.1458 [M + H] 611.1607 -24.4 287 X Patil, 2018b)

+ 11.60 Kaempferol-3-O-diglucoside- C33H40O21 773.1970 [M + H] 773.2135 11.6 633, 425, 287 X 7- glucoside (Isomer) + 11.70 Quercetin 3-O-galactoside 7-O- C27H30O16 611.1593 [M + H] 611.1607 -2.3 413, 303, 149 X rhamnoside

64 Table 5. Continued RT Identified compound Molecular Experimental Adduct Theoretical Mass MS/MS Juice Type (min) formula mass mass error fragments Reference (ppm) Kale Beet Mel on + 11.85 Kaempferol-3-sinapoyl-diglucoside- C50H60O30 1141.2915 [M + H] 1141.3242 -28.7 879, 619, 287, X (Yang, 7-diglucoside 129 Jayaprakasha, + 11.85 Eriocitrin/Neoeriocitrin C27H32O15 597.1712 [M + H] 597.1814 -17.08 463, 365, 289, X & Patil, 2018b) 153 + 11.90 Quercetin 3-O-rhamnosyl-galactoside C27H30O16 611.1587 [M + H] 611.1607 -3.3 413, 303, 149 X

+ 12.00 Quercetin 3-O-rutinoside C27H30O16 611.1458 [M + H] 611.1607 -24.4 555, 303 X

+ 12.10 Quercetin 3-rhamnosyl (1→2)- C33H40O20 757. 2156 [M + H] 757.2186 -4.0 633, 487, 303, X (McDowell, rhamnosyl-glucoside 240, 185 Bailey, & Howard, 1990)

+ 12.45 Isorhamnetin 3-O-diglucoside C28H32O17 641.1742 [M + H] 641.1712 4.68 317, 84 X (Lin & Harnly, 2009)

+ 12.50 Kaempferol 3-O-glucosyl- C33H40O20 757.2182 [M + H] 757.2186 -0.53 525, 413, 287, X (McDowell, rhamnosyl-galactoside 149 Bailey, & Howard, 1990) + 12.60 Kaempferol 3-O-glucosyl- C33H40O20 757.2167 [M + H] 757.2186 -2.5 525, 413, 287, X (Kelebek, 2016) rhamnosyl-glucoside 149 + 12.70 Kaempferol 3-O-(2’’-rhamnosyl- C33H40O19 741.2182 [M + H] 741.2237 -7.4 617, 525, 413, X galatoside)-7-O-rhmnoside 287, 203 + 12.95 Spinacetin 3-O-glucosyl-(1-6)- C29H34O18 671.1846 [M + H] 671.1818 4.17 411, 347, 269, X (Barkat, Singh, glucoside 140 Jayaprakasha, & Patil, 2018)

+ 13.15 Kaempferol 3-O-galactoside-7-O- C27H30O15 595.1626 [M + H] 595.1657 -5.2 487, 331, 287 X (Yang, rhamnoside Jayaprakasha, & Patil, 2018b)

+ 13.60 Naringin C27H32O14 581.1886 [M + H] 581.1865 3.61 271, 153 X (Sethiya, Trivedi, & Mishra, 2014) + 13.90 C44H50O25 979.2417 [M + H] 979.2714 -30.3 855, 655, 523, X (Yang, 347, 287 Jayaprakasha, Kaempferol-3-sinapoyl-diglucoside- & Patil, 2018b) 7-glucoside + 14.15 Qucertin-3-O-rutinoside C27H30O16 611.1822 [M + H] 611.1607 46.30 265, 303, 153 X (Yang, Jayaprakasha, & Patil, 2018b)

65 A) Kale Juice

OPLS-DA Score Plot Heatmap

Quercetin-3-feruloyl-diglucoside-7-diglucoside Kaempferol-3-(feruloyl)-sophoroside-7-O-glucoside Kaempferol-3-O-sophoroside Eriocitrin/Neoeriocitrin Kaempferol-3-sinapoyl-diglucoside-7-diglucoside Kaempferol-3-O-diglucoside-7-glucoside (Isomer) Isorhamnetin 3-O-diglucoside Naringin Qucertin-3-O-rutinoside Quercetin-3-diglucoside-7-glucoside(isomer) Spinacetin 3-O-glucosyl-(1-6)-glucoside Kaempferol-3-O-diglucoside-7-glucoside Kaempferol-3-O-(caﬀeoyl)-sophoroside

Orthogonal T score [1]score (24.8%) Orthogonal T Kaempferol-3-sinapoyl-diglucoside-7-glucoside Phenylalanine 4 2 0 2 4 - Kaempferol-3-feruloyl-digulcoside-7-diglucoside Epigallocatechin Quercetin-3-diglucoside-7-glucoside K2 K2 K8 K8 K9 K9 K3 K3 K7 K7 K4 K4 K5 K5 K6 K6 K10 K10 K1 K1 ------1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 -4 -3 -2 -1 0 1 2 - - 1 2 T score [1] (11.6%)

B) Beet Juices

OPLS-DA Score Plot Heatmap 17-Decarboxy-isobetanin 15-Decarboxy-betanin 17-Decarboxy-neobetanin Neobetanin 2,17-Bidecarboxy-betanidin/isobetanidin 2-Decarboxy-2,3-dehydro-neobetanin 2,17-Bidecarboxy-2,3-dehydro-neobetanin Isobetanin Betanin 2’-O-Glucosyl-betanin/isobetanin L-Tryptophan 2-Decarboxy-betanin Chlorogenic acid Chlorogenic acid isomer 2-Decarboxy-isobetanin Caffeoylquinic acid

5 0 5 10 1,3-Dicaffeoylquinic acid -

Orthogonal T score [1]score (49.2%) Orthogonal T δ-Viniferin Phenylalanine Quercetin 3-O-rutinoside Ferulic acid derivative 2-Decarbxy-neobetanin 10

- 2,17-Bidecarboxy-2,3-dehyo-neobetanin (isomer) B6 B6 B5 B5 B3 B2 B4 B8 B3 B4 B4 B9 B9 B7 B7 B1 B1 B8 B10 B10 ------

-1 0 1 2 3 4 1 2 1 2 2 2 1 2 1 1 2 1 2 1 2 1 2 1 - - 1 2 T score [1] (9.1%)

C) Melon Juices OPLS-DA Score Plot Heatmap

Epigallocatechin 3-O-gallate Phenylalanine Kaempferol 3-O-galactoside-7-O-rhamnoside Quercetin 3-rhamnosyl (1→2)-rhamnosyl-glucoside Kaempferol 3-O-glucosyl-rhamnosyl-glucoside Kaempferol 3-O-glucosyl-rhamnosyl-galactoside Kaempferol 3-O-(2’’-rhamnosyl-galatoside)-7-O-rhmnoside Quercetin 3-O-galactoside 7-O-rhamnoside 5 0 5 10 M2 M2 M3 M3 M1 M1 M7 M7 M6 M6 M10 M10 M5 M5 M4 M4 M9 M9 M82 Quercetin 3-O-rhamnosyl-galactoside ------1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 - - - 1 2 1 Orthogonal T score [1] scoreOrthogonal (50.6%)T 10 - -4 -2 0 2 T score [1] (29.6%) Figure 4. OPLS-DA score plot and heatmap based on LC-MS profiling of juice samples obtained from thermal and cold processed techniques. Color saturation in heatmap represents level of each metabolite with blue: the lowest; red: the highest.

66 Figure 5. PLS-DA-3D score plot shows the antioxidant activities and total phenolics present in 30 commercial juice samples from (A) kale, (B) beet and (C) melon. Results were expressed as ascorbic acid (AA) equivalents, and total phenolics were expressed as gallic acid (GA) equivalents. Results of DPPH and ABTS were expressed as gallic acid (GA) equivalents. The red clustered dots were thermal processed juices, and the green grouped dots were cold processed juices.

67 5. UPLC-QTOF-MS FINGERPRINTING COMBINED WITH CHEMOMETRICS TO

ASSESS THE SOLVENT EXTRACTION EFFICIENCY AND ANTIOXIDANT

ACTIVITIES OF BEETROOT (BETA VULGARIS)

Epidemiological studies have demonstrated that the excessive production of reactive oxygen species (ROS) induces oxidative stress and increases the risk of chronic diseases such as cancer, diabetes, and cardiovascular diseases (Alfadda & Sallam, 2012; Liou & Storz, 2010).

These studies also indicate that fruits and vegetables rich in bioactive compounds play a crucial role in the prevention of some chronic diseases and may provide desirable alternatives to some aspects of synthetic medicine due to their better compatibility with and fewer side effects to the human body (Sen, Chakraborty, Sridhar, Reddy, & De, 2010).

Beetroots (Beta vulgaris) are common vegetables cultivated worldwide and the increasing interest of consumers in the nutritional and heath-beneficial aspects of food has increased interest in this functional food (Wruss, Waldenberger, Huemer, Uygun, Lanzerstorfer, Müller, et al., 2015).

Beetroots have significant antioxidant activities due to the presence of betalain derivatives and phenolic compounds. These compounds remove free radicals and protect the human body against damage from ROS (Sawicki, Bączek, & Wiczkowski, 2016). Betalains are effective antioxidants due to the presence of phenolic hydroxyl groups, aromaticity, and other characteristic functional groups (Gandía-Herrero, Escribano, & García-Carmona, 2009). Betalains consist of red-violet betacyanins and yellow-orange betaxanthins, which are biosynthesized from tyrosine (Sawicki,

Bączek, & Wiczkowski, 2016). In addition to betalains, beetroots are rich in nitrate and other phytochemicals and the composition and levels of these compounds vary in different varieties of beets according to their phenotypes and genotypes. For example, red beetroot mainly contains betacyanins, whereas golden beetroot mainly contains betaxanthin.

68 Betalain levels, composition, and antioxidant activities are influenced by genetics, cultivars, production system, and processing techniques (Ravichandran, et al., 2013; Slatnar,

Stampar, Veberic, & Jakopic, 2015b). Recently, increasing consumption of organically grown foods has been associated with the consumer interest in healthier and safer foods. Compared to conventionally grown foods, the organically grown food production system uses natural manures instead of artificial fertilizers, potentially resulting in more ingestion of health-promoting phytochemicals, allowing organic food to be perceived as healthier and safer than conventional foods (Krejčová, Návesník, Jičínská, & Černohorský, 2016). Previous studies demonstrated beetroots grown under conventional and organic cultural practices tended to have different phytochemical contents, but the results were inconsistent or unsubstantiated (Asami, Hong,

Barrett, & Mitchell, 2003). Additionally, available studies comparing minerals in organically and conventionally grown beets are rare (Hansen, 1980; Pfiffner, Niggli, Velimirov, Boltzmann,

Balzer, Balzer, et al., 1992). Therefore, a comprehensive study of mineral content and phytochemical profiles in both production systems is needed.

Comparing phytochemical profiles requires accurate methods for extracting and measuring phytochemicals. The nature of the extraction solvent, polarity, and solvent combination plays a crucial role in extracting the hydrophilic betalines and measuring their levels (Celli & Brooks,

2017). Among various extraction techniques, solid-liquid extraction is commonly performed for extracting natural pigments (Cardoso-Ugarte, Sosa-Morales, Ballard, Liceaga, & San Martín-

González, 2014). Betalains are normally extracted from samples by different organic solvents such as methanol, ethanol, acetone, and mixtures of solvents (Fathordoobady, Mirhosseini, Selamat, &

Manap, 2016; T. S. Kujala, Vienola, Klika, Loponen, & Pihlaja, 2002; Narkprasom, Su, Cheng,

Wang, Hsiao, & Tsai, 2012); however, the reported levels of betalains and phytochemicals are

69 significantly different. Therefore, the present study was conducted to optimize the extraction efficiency phytochemicals using twenty different solvent compositions from red and golden beets grown in conventional and organic production systems. Further, HPLC and UPLC-QTOF-HR-MS were used to quantify and identify the phytochemicals present in extract. All the extracts were tested for total phenolics and radical scavenging activities to understand the effect of production system and extraction efficiency in each beet variety.

5.1. Material and Methods

5.1.1. Plant materials

Bunches of beetroots (Beta vulgaris) were purchased at the local Farm Patch and HEB grocery stores (College Station, TX, USA). Samples included conventionally and organically grown red and golden beets. The inedible parts such as the leaves and stems were removed, and the roots were washed with peel and wiped with paper towels. The beetroots were cut into cubes

(1.5 ×1.5 ×1.5 cm) and processed in a 12-speed Oster blender (Sunbeam, FL, USA), then a known amount of each sample was weighed in separate 50-mL tubes and the rest of the paste was stored at -20°C.

5.1.2. Chemicals

L-ascorbic acid, gallic acid, formic acid, acetic acid, phosphoric acid, sodium carbonate,

2,2-diphenyl-1-(2,4,6-trinitrophenyl) hydrazyl (DPPH), Folin Ciocalteu (FC) reagent, 2, 2´- azinobis (3-etylbenzothiszoline-6-sulphonic acid) diammonium salt (ABTS), methanol, ethanol,

LC-MS and HPLC grade acetonitrile, and crude betanin extract were obtained from Sigma-Aldrich

70 (St. Louis, MO, USA). All other reagents and solvents were analytical grade. Nanopure water

(NANOpure, Barnstead, Dubuque, IA) was used for the entire study.

5.1.3. Sample preparation for mineral analysis

The cleaned beetroots were cut into pieces and freeze-dried (LabConco, Kansas City, MO,

USA). The lyophilized samples (5 g) were submitted to Soil, Water, and Forage Testing

Laboratory, Texas A&M University, College Station, TX in triplicate. Micronutrient quantification was conducted by inductively coupled plasma atomic emission spectroscopy (ICP-

AES). First the beet samples were digested with nitric acid 125°C for 4 h and set aside at room temperature overnight. Then, the samples were diluted with distilled water and analyzed by ICP-

AES.

5.1.4. Extraction of betalains from beetroots

Five grams of beetroot paste was extracted with 10 mL of solvent (see Table A-4) in a 50- mL tube by vortexing (30 s), homogenizing (1 min), and sonicating (1 h). Afterwards, the tubes were centrifuged at 800 × g for 15 min. The supernatant was collected, and the residue was extracted again with 3 mL of the same solvent. The supernatants were pooled, and the total volume was measured. Two mL of each was passed through a 0.45-μm membrane filter paper for HPLC and mass spectrometry analysis and the rest of the sample was stored -20°C for bioassays. All extractions were carried out in triplicate and the results were expressed as means and standard error.

71 5.1.5. Purification of betanin by flash chromatography

Pure betanin is not commercially available for quantification of betalains. Therefore, crude beet extract was loaded on a C18 glass reverse phase flash column (particle size 40–63 µm, 200 ×

60 mm), (ACE Glass Inc, Vineland, NJ, USA). The separation of betanin was carried out on a ﬂash chromatography system (Combiﬂash Rf, Teledyne Isco, Lincoln, NE, USA). Before loading the sample, the C18 column was equilibrated with 1 L of 1% aqueous formic acid for 30 min. Then, the separation of betanin was performed by a gradient program using solvent A (1% formic acid) and solvent B (acetonitrile) with a flow rate of 40 mL/min. The betalains were monitored at 480 and 540 nm with a peak width of 15 s and threshold of 0.05 AU. A total of 180 fractions of 15 mL each were collected. All fractions were analyzed by HPLC and fractions 48–56 containing the same peak were pooled and lyophilized to obtain pure compound. The purity and structure of betanin was confirmed by HPLC and UPLC-HR-MS.

5.1.6. Quantification the major betalains by HPLC

HPLC was performed using an Agilent 1200 HPLC series (Agilent Technologies, Palo

Alto, CA, USA) connected to a photodiode array detector. The separation was carried out on a

Gemini C18 Column (250 mm × 4.6 mm i.d.) (Phenomenex, Torrance, CA, USA) at 30°C. The mobile phase consisted of 0.3 M phosphoric acid (solvent A) and acetonitrile (solvent B). At a flow rate of 0.8 mL/min, different betalains were monitored at 540, 480, and 420 nm and identified by comparing retention times and UV spectra from published papers (Slatnar, Stampar, Veberic,

& Jakopic, 2015b). Different concentrations (31.25–500 µg/mL) of purified betanin were injected into the HPLC and a calibration curve was prepared. Samples of 10 μL were injected and the betalain content was expressed as µg betanin equivalents/g of fresh weight.

72 5.1.7. Total phenolics, DPPH, and ABTS radical scavenging activity

5.1.7.1. Estimation of total phenolics

The total phenolic content was assessed using the Folin-Ciocalteu assay according to our previous publication (G. K. Jayaprakasha, Girennavar, & Patil, 2008). The absorbance was measured at λ = 734 nm and total phenolics were expressed as µg gallic acid equivalents/g of fresh weight.

5.1.7.2. Estimation of total phenolics

The 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay was conducted according to our published paper (Bae, Jayaprakasha, Jifon, & Patil, 2012) and results were expressed as µg ascorbic acid equivalents/g of fresh weight.

5.1.7.3. ABTS radical scavenging activity

A slight modification of the published method (G. K. Jayaprakasha, Girennavar, & Patil,

2008) was used to assess the 2,2´-azinobis-(3-ethylbenzotiazoline-6-sulphonic acid) radical scavenging activity. Results were expressed as µg ascorbic acid equivalents/g of fresh weight.

5.1.8. Identification of phytochemicals by UHPLC-QTOF-MS

Ultra-high-performance liquid chromatography (UHPLC) separation was performed with the 1290 Agilent HPLC LC system (Agilent Technologies, Santa Clara, CA) equipped with a maXis impact mass spectrometer (Bruker Daltonics, Billerica, MA, USA). An Eclipse Plus rapid resolution C18 column (1.8 μm, 50 × 2.1 mm) was used for the separation of phytochemicals with

73 a binary mobile phase consisting of 0.2% formic acid in water (A), and 0.2% formic acid in acetonitrile (B). The temperature of the autosampler compartment was set at 35°C. The flow rate was 0.5 mL/min. The gradient program consisted of 0% B (0–2 min), linear gradient from 0% B to 35% B (2–9 min), then increased to 100% B (9–14 min) and back to 0% B (14–16 min). The post-run equilibration time was 2 min. The total run time was 18 min.

For quadrupole time-of-flight mass spectrometry (QTOF-MS), the maXis Impact mass spectrometer was operated in positive electrospray ionization mode and was equipped with a six- port divert valve for calibration. MS and bbCID data (line spectra) were acquired in the m/z range of 50–1200. The capillary voltage of the ion source was 4,200 V. The nebulizer (nitrogen) gas pressure was 4.0 bar and the drying gas flow rate 12.0 L/min. The drying gas temperature was

250°C. The transfer time of the source was 120.8 μs and the prepulse storage time 1 μs. The quadrupole MS collision energy and bbCID collision energy were set at 5 and 55 eV, respectively.

The spectra rate was 1.4 Hz. In bbCID, the precursor ions were fragmented in the collision cell without pre-selection. By alternating the acquisition between MS and bbCID conditions, high and low collision energy data sets were collected simultaneously. External instrument calibration was performed with a sodium formate solution containing 1 mM sodium hydroxide in isopropanol with

0.2% formic acid (1:1 v/v). Nine sodium formate clusters were used in the calibration using the high-precision calibration mode. An automated post-run internal mass scale calibration of individual samples was performed by injecting the above calibrant at the end of each run.

Calibration of each sample was performed at the end of the run.

74 5.1.9. Statistical and chemometric analysis

The significance of variation in the levels of minerals were analyzed by one-way analysis of variance (ANOVA) by employing JMP Pro12 software (SAS, NC, USA). Results were expressed as mean value ± standard error. A probability of 5% or less was accepted as statistically significant. Multivariate data analysis was performed by translating the LC-MS data in csv format and subjecting to the online MetaboAnalyst software 4.0 (https://www.metaboanalyst.ca/).

5.2. Results and Discussion

5.2.1. Differences in mineral contents of conventional and organic beets

In the present study, we measured the relative levels of minerals in red and golden beets from conventional and organic production systems (Table A-5). Significantly higher levels of some minerals (N, P, Mg, Na, Fe, Mn, and B) were found in conventional red beets, whereas organic beets had higher levels of K, Ca, and Cu, but the difference in Zn was non-significant. In golden beets, the conventionally produced beets had higher accumulation of all minerals except P and N, which were higher in the organic beets. There are no comprehensive data correlating the effects of conventional and organic production systems on mineral levels of beetroots (Hansen,

1980; Pfiffner, et al., 1992). One study found that Mg and Cu were higher in organically grown beets than in conventionally grown beets. However, variation in the levels of P and K were dependent on the growing locations (Hansen, 1980). Pfiffner and coauthors found K was higher in conventional beets, but the P, Ca, Mg contents fluctuated each year. Therefore, genetic, agronomic, and environmental factors could significantly influence the content and composition of minerals

(Rouphael, Cardarelli, Bassal, Leonardi, Giuffrida, & Colla, 2012).

75 5.2.2. Identification of phytochemicals from beetroots by UHPLC-QTOF-MS

The individual constituents of the samples obtained by extracting with twenty solvents were assessed by UHPLC-QTOF-MS. Twenty-seven phytochemicals including 23 betalain compounds, 2 amino acids, and 2 phenolic acids, were identified using high resolution mass spectral data. The retention time, molecular formula, molecular mass, and MS/MS fragments of individual compounds are presented in Table 7.

Betalains include betacyanins and betaxanthins. Betacyanins are condensed products of betalalamic acid and have various substitutions (glycosylation or acylation) of one or both hydroxyl groups at position 5 or 6 of the betanidin (Belhadj Slimen, Najar, & Abderrabba, 2017).

In red beetroot varieties, the main betacyanin peaks were identified as betanin (m/z 551), the simplest 5-O-glucosylated betacyanin, and its C-15 isoform isobetanin (m/z 551) with the fragment ion at m/z 389 (betanidin). Compared to the organic red beet, conventional red beet extracts had the more betalains, which included acylated betacyanins such as 2-O-glucosyl-betanin (m/z 713),

6-feruloyl betanin (m/z 727), and 6-feruloyl-isobetanin (m/z 727). These were modified through the bond of the acyl group to the sugar moiety (glucose, glucuronic acid, and apiose) via an ester linkage and had two contiguous glucosyl groups attached to the C5 carbon, and the 2,17- decarboxylzed betacyanin compounds, which were 17-decarboxy-(iso) betanidin (m/z 345), 17- decarboxy-betanin (m/z 507), 2,17-decarboxy-neobetanin (m/z 505), 2,17-bidecarboxy-2,3- dehydro-neobetanin (m/z 459), and 2-decarboxy-2,3-dehydro-neobetanin (m/z 503). Betanidin

(m/z 389) and 17-decarboxy-isobetanidin (m/z 345) were not detected in the organic beetroot extracts. Consistent with previous research, betacyanins were not detected at significant levels in conventional and organic golden beetroots (Slatnar, Stampar, Veberic, & Jakopic, 2015b).

76 In contrast to betacyanins, betaxanthins react with free amino acids and form new compounds with amino acid adducts. In golden beet extracts, we identified betaxanthins with glutamine, valine, leucine, and phenylalanine adducts. These betaxanthin derivatives were also present in conventional and organic red beet extracts. In addition, other amino acids, phenylalanine

(m/z 166) and L-tryptophan (m/z 205), were identified based on their molecular mass and MS/MS fragmentation. Further, hydroxy caffeic acid (m/z 197) and syringic acid (m/z 199) were present in four beet cultivars. Previous studies identified these two phenolic acids in beetroot samples

(Nemzer, et al., 2011; Obata, Senba, & Koshika, 1963).

5.2.3. Variation in betalains in conventional and organic red and golden beets measured by

HPLC

The total betalains of red and golden beet extracts are shown in Table A-6 and the levels were varied from 1138- 4039 µg/g fresh weight (FW). The highest amount of total betalains was detected in the ethanol: water extract (S6), followed by methanol extract (S13), and the lowest amount was in the water: ascorbic acid extract (S2). Similar concentrations of total betalains were reported in previous study of 13 red beet varieties from Poland (Sawicki, Bączek, & Wiczkowski,

2016), where the total betalains of red beet were in the range of 1.57–2.70 mg/g FW, and the amount significantly differed depending on the beet variety and also extraction solvent. In comparison, red beets grown in Australia had less total betalains with contents of 0.38–0.65 mg/g

FW (Wruss, et al., 2015).

In organic red beet extracts, we observed higher variation compared to conventional red beet extracts, with the organic beets having 0.5–12.3 mg/g FW betalain. Similar to the results for conventionally grown red beets, the total betalain concentration was high in the methanol extract

77 (S13), and the lowest amount was detected in the water extract (S1). Furthermore, the beetroot extracted with water with or without acid gave a lower yield of betalains, compared to the organic solvents. This may be due to the mucilaginous effect of water-soluble pectin compounds

(Fathordoobady, Mirhosseini, Selamat, & Manap, 2016). Hence, water may not be a useful solvent for the extraction of betalains from organic red beet.

Our results were consistent with the literature, which illustrated that betalain contents might be influenced by several factors, including varietal, growing season, and climatic and cultivation conditions (Sawicki, Bączek, & Wiczkowski, 2016). In addition, the average amount of total betalains were significantly higher in 18 organic red beet extracts than in their conventional counterparts, except for extracts obtained from water (S1) and ethanol : water : acetic acid (S11), which had 4-fold and 1-fold less betalains than the conventional red beet extracts. This result indicated that the production system also affect the betalain contents, which could be partly explained by the difference in nitrogen levels (Nemzer, et al., 2011)

Significant variations of total betalains were also found in golden beet extracts, wherein the total betalains varied from 0.0–0.8 mg/g FW for conventionally grown golden beets, and 0.0–

1.3 mg/g FW for organic golden beets. Conventional golden beets extracted by methanol: water : ascorbic acid (S17) had the highest total phenolics. By contrast, betalain levels were not detectable in the water (S1), water/formic acid (S2), ethanol: water：acetic acid or methanol ：water ： acetic acid mixture (S11 and S19), and methanol：water ：formic acid (S20) extracts. In organic golden beet extracts, the highest total betalains were found in the methanol ：water ：formic acid extract (S20). To the best of our knowledge, little information regarding the content of betalains in different beet extracts has been reported so far.

78 In general, total betalains were higher in red beet than in golden beet, with amounts being

3-fold higher in conventionally grown red beets, and 8-fold higher in organically grown cultivars.

This finding was in accordance with previous research, where total betalain content in red beetroot was significantly higher than that in yellow beetroot, regardless of the extraction solvent (Sawicki,

Bączek, & Wiczkowski, 2016). The higher amount of betalains in red beet indicate that the limited utilization of tyrosine, the precursor of betalain synthesis, occurs in yellow beetroot compared to the red beetroot. In the biosynthetic pathway of betalains, tyrosine is first oxidized to L-dihydroxy phenylalanine (L-DOPA) by reacting with CYP76AD1, AD5, and AD6 L-DOPA is then converted to betalamic acid and cyclo-DOPA, which are required for betalain production. Betalamic acid and cyclo-DOPA are needed for betacyanin productions, whereas only betalamic acid along with amino acids or amines are required for betaxanthins. The limited amounts of tyrosine in golden beet may cause the overall low betalain content (M. Wang, Lopez-Nieves, Goldman, & Maeda,

2017). To verify this, peak areas were generated for betalain biosynthesis-related metabolites (Fig

9). Indeed, the levels of tyrosine were much higher in conventionally and organically grown red beets than in golden beets. As a result, the levels of L-DOPA (m/z 198) were higher, and the cyclo-

DOPA (m/z 196) and betalamic acid (m/z 212) were higher, ultimately causing higher betalain levels in red beet than golden beets. This was consistent with previously reported findings (Slatnar,

Stampar, Veberic, & Jakopic, 2015b; M. Wang, Lopez-Nieves, Goldman, & Maeda, 2017), showing that the primary and secondary metabolites within the betalain biosynthesis pathway can be influenced by the variety of vegetable.

The levels of betanin and vulgaxanthin I quantified by HPLC were expressed as betanin equivalents (Table 6), since vulgaxanthin I is not commercially available. The conventional red beet extracted with methanol：water： formic acid (S20) had the highest betanin content (2791.0

79 µg/g FW), and the water ：ascorbic acid extract (S2) had the lowest betanin (578.8 µg/g FW). The isobetanin was highest in the water ：acetic acid (S4) extract, 5–9 fold higher than in other water- containing solvents (S1, S2, S3). Interestingly, conventional red beet extracted by aqueous methanol mixed with organic acids (S17, S18, S19) had higher betanin contents than the other methanol solvent extract (S16). This result is in agreement with Narkprasom and others, who demonstrated that organic acids enhanced betalain retention through oxygen scavenging and complexation of metal cations (Narkprasom, Su, Cheng, Wang, Hsiao, & Tsai, 2012). Another study indicated that slight acidification of the extraction medium enhances betacyanin stability and avoids oxidation by polyphenol oxidases (Schliemann, Kobayashi, & Strack, 1999).

In the present study, the highest vulgaxanthin I and valine-betaxanthin content was found in the ethanol ：water extract (S6, 1260.6 and 193.9 µg/g FW). In organic red beet samples, the highest betanin and vulgaxanthin I content was found in the methanol extract (8222.3 and 4031.5

µg/g FW), and the water extract had the lowest betanin (364.2 µg/g FW). In comparison, the highest isobetanin was found in the ethanol ：water ： formic acid (S12) extract (549.5 µg/g FW), followed by methanol ：water ：formic acid (S18).

With respect to conventionally grown golden beet, the highest vulgaxanthin I content was detected in samples extracted by methanol ：water ：ascorbic acid (S17, 746.1 µg/g FW); however, no valine-betaxanthin was found in this extract. The highest valine-betaxanthin was found in the aqueous methanol (S16) extract, with a content of 80.9 µg/g FW. Organic golden beet extracted by aqueous ethanol (S6, 836.2 µg/g FW) had the highest vulgaxanthin I content compared to other solvents. Whereas in water extract, no vulgaxanthin I was detected. Organic golden beet extracted by aqueous ethanol S8 had the highest valine-betaxanthin content (104.6

µg/g FW), suggesting that aqueous ethanol was efficient at extracting betaxanthins. We note here

80 that betalains, betacyanins, and betaxanthins were measured by UV spectroscopy due to the lack of a pure standard, whereas we purified betanin as a standard and carried out HPLC analysis, which proved to be a suitable method for separation of betalains (Stintzing, Schieber, & Carle, 2002b).

5.2.4. Influence of solvent combination on total phenolics and radical scavenging activities

Figure 7 shows the results of total phenolics as well as DPPH and ABTS free radical scavenging activities for the samples from conventional and organic red beets. The application of diverse solvent ratios and combinations resulted in beet extracts with significantly different total phenolics and DPPH and ABTS activities. Conventional red beetroot extracted by methanol alone

(S13) had the highest phenolics (323.67 µg gallic acid equivalents [GAE]/g FW). A previous study

(Boeing, Barizão, e Silva, Montanher, de Cinque Almeida, & Visentainer, 2014) reported that methanol was an effective solvent due to the interactions between the polar sites of the antioxidant molecules and the solvent. The lowest total phenolics value was found in the methanol ：water extract (S16, 159.57 µg GAE/g FW), which indicated that the ratio of methanol significantly affects the extraction of total phenolics. Interestingly, the conventional red beet extracted by aqueous methanol solvents with added ascorbic, formic, or acetic acid had lower total phenolics than the methanol alone (S13, 191.21 to 292.16 µg GAE/g FW), suggesting that acidification might increase the recovery of phenolic compounds in red beet. However, this trend was not observed in the ethanol extracts of red beetroot. The highest total phenolics of organic red beetroot was obtained from the ethanol ：water (S8) extract (436.69 µg GAE/g FW), and the lowest total phenolics was found in the water ：acetic acid (S4) extract (153.64 µg GAE/g FW). Other water- containing solvent (S1, S2, S3) extracts showed moderate amounts of total phenolics.

81 Among the various extracts of golden beets (Fig. 8), conventionally grown golden beetroot extracted by pure ethanol (S13) had the highest total phenolics (212.35 µg GAE/g FW), and the lowest amount was found in the methanol ：water ：formic acid extract (S18, 35.59 µg GAE/g

FW). In contrast to conventionally grown red beet, the water extract of conventionally grown golden beet had high total phenolics. Significant variation in total phenolics was observed in organic golden beet extracts, with the highest value found in the methanol ：water ：ascorbic acid extract (S15, 123.55 µg GAE/g FW), and the lowest in the methanol ：water：acetic acid extract

(S19, 27.54 µg GAE/g FW). Interestingly, total phenolics in conventional and organic golden beets were higher in the extracts with solvents containing ascorbic acid than those with formic or acetic acid, suggesting that ascorbic acid acidified solvents could be the potential favorite solvent for extracting health-promoting compounds in golden beet.

DPPH and ABTS assays were performed to evaluate the in vitro antioxidant activities of the different beet extracts. The highest DPPH and ABTS radical scavenging activities were found in aqueous methanol ：formic acid (S18) extracts, with ascorbic acid (AA) equivalents of 400.76 and 229.83 µg AA/g FW, respectively. The lowest DPPH and ABTS activities were found in the methanol ：ascorbic acid (S17) extract (91.64 and 88.01 µg/AA g FW). In comparison, organic red beet extracted with methanol ：water ：formic acid (S20), and methanol ：water ：acetic acid (S19) had the highest DPPH activity (453.50 and 376.44 µg/AA g FW). The lowest DPPH

(104.92 µg/AA g FW) and ABTS (44.03 µg/AA g FW) activities were found in water: ascorbic acid (S4), and ethanol: water: ascorbic acid (S9) extracts respectively. Consistent with the total phenolics results, the overall DPPH and ABTS activities of organic red beet extracted by organic solvents were significantly higher than the samples extracted by water solvents. In some of the ethanol-containing solvents, conventional and organic red beet ethanol ：water (S6), ethanol：

82 water：formic acid (S10), and ethanol ：water ：acetic acid (S11) extracts, high DPPH and ABTS activities were present. Given their high extraction efficiency and lower toxicity compared with other solvents, aqueous ethanol combined with acid might be considered as a desirable replacement for methanol.

For conventionally grown golden beet, the ethanol：water：formic acid (S10) extract had the highest DPPH activity (164.04 µg AA/g FW) and the ethanol：water extract (S6) had the lowest DPPH activity (37.16 µg AA/g FW). Consistent with the total phenolics results, the highest

ABTS activity was detected in the ethanol extract (S5, 96.57 µg AA/g FW). However, moderate

DPPH inhibitory activity was found in this extract, consistent with the differing reaction mechanisms in the two assays. This was consistent with the DPPH and ABTS results in organic golden beet extracts, wherein the water with acid extract exhibited high ABTS but low DPPH scavenging activities.

The overall DPPH and ABTS radical scavenging activities of red beetroot were significantly higher than golden beetroot. In our present results, betanin was the predominant betacyanin in red beetroot, whereas vulgaxanthin I was the main betaxanthin in golden beetroot.

Betanin contains an aromatic ring with the betalamic acid moiety, a second ring combined with an indoline, which increases the radical scavenging activity. The antiradical activities of betanin and its isomer were further enhanced by the additional hydroxyl group in their benzene rings (Fig. 10)

(Gandía-Herrero, Escribano, & García-Carmona, 2010). In comparison, vulgaxanthin I was the main betalain in golden beet, and had minimal antiradical activities due to its structure lacking aromatic resonance, charged, or hydroxyl groups. Therefore, the radical scavenging activities of golden beetroot were t significantly lower compared to red beets.

83 5.2.5. Chemometrics-based approach to identify the influence of extraction solvent on

phytochemical profiles

In the present study, multivariate statistical analysis was applied to build an intuitive overview of the beet extract results. The abundances of phytochemicals identified by LC-MS are presented as a heatmap in Fig.10. Significant variations in phytochemicals were detected in conventional red beet extracted with the 20 solvents. Among these, beets extracted by water ： ascorbic acid (S2), ethanol (S5), different concentration of ethanol with ascorbic acid (S7 and S9), and methanol : water : formic acid (S20) had higher amounts of betacyanin derivatives, namely betanidin (m/z 389), 6-feruloyl-betanin and its isomer (m/z 727), prebetanin (m/z 631), betanin

(m/z 551), 2-glucosyl-betanin (m/z 713), 2,17-bidecarboxy-2,3-dehydro-neobetanin (m/z 459),

17-decarboxy-neobetanin (m/z 505), neobetanin (m/z 549), 17-decarboxy-betanidin (m/z 345), and amino acid-adducted betaxanthins including valine-betaxanthin (m/z 311), leucine- betaxanthin (m/z 325), proline-betaxanthin (m/z 309), phenylalanine-betaxanthin (m/z 359), and glutamic acid-betaxanthin (m/z 341).

Higher levels of betanin, one of the main betacyanins in red beet, was found in aqueous ethanol ：ascorbic acid extracts (S7 and S9). Another main compound, isobetanin (m/z 551), was highest in water ：formic acid (S3) extracts, with the mass area 1- to 430-fold higher than the conventional red beet extracted with other water-containing solvents (S1–3). In addition, amino acids such as phenylalanine (m/z 166), L-tryptophan (m/z 205), and the phenolic acid syringic acid

(m/z 199), were also identified in those extracts. Two decarboxylated betacyanins, 17-decarboxy- betanin (m/z 507) and 2-decarbocy-neobetanin (m/z 505), were found at the highest levels in the aqueous ethanol ：formic acid (S10) extract, with an area 1 to 3-fold higher than the ethanol：

84 acetic acid (S11) extract. Another compound, 2-decarboxy-2,3-dehydro-neobetanin (m/z 503) had a significantly higher area in the aqueous ethanol (S8) extract. The water ：ethanol solvent system affects the stability of betanin, since ethanol has a high electron density on the oxygen atom, leading to nucleophilic attack on the oxygen atom, and ultimately causing decarboxylation

(Azeredo, 2009).

Conventional red beet extracted by water or aqueous combined with ascorbic acid solvents

(S2, S7, S9) obtained larger quantities of phytochemicals compared to the extracts obtained from formic ：acetic acid (S3, S4) or aqueous ethanol (S6), indicating ascorbic acid with water or ethanol might be an effective solvent combination for obtaining large quantities of betalains. The overall different abundance of betalains in beet extracts may be attributed to their interaction with the extracting solvents, which altered the linear symmetry restrictions of the betanin molecule and thus changed their characteristics (Thankappan, Thomas, & Nampoori, 2013). Similarly, in organic red beet extracts, water and ascorbic mixture (S2), ethanol with or without ascorbic acid

(S5, S7, and S9), and methanol ：water ：formic acid (S20) solvents were efficient in obtaining various betalain compounds such as decarboxylated betacyanins, namely 2-decarboxy-neobetanin

(m/z 505), 17-decarboxy-neobetanin (m/z 505), 17-decarboxy-betanidin (m/z 345), 2-decarboxy-

2,3-dehydro-neobetanin (m/z 503), and 2,17-bidecarboxy-2,3-dehydro-neobetanin (m/z 459). In water/formic acid (S3) extract, and ethanol ： water ： acid (S10, S12) extracts, only one betacyanin with relative high levels was found. For instance, isobetanin (m/z 551) was identified in water ：formic acid extract (S3) with a mass area 4-fold higher than water extract (S1), and 17- fold higher than methanol ：water ：formic acid extract (S20). In other solvent combinations (S1,

S8, S13, S15-19), the levels of phytochemicals were negligible. However, betalains include betanidin (m/z 389) and 17-decarboxy-isobetanidin (m/z 345), glutamic acid-betaxanthin (m/z

85 341), leucine-betaxanthin (m/z 325), and phenolic acids, hydroxy caffeic acid (m/z 197) and syringic acid (m/z 199), were not detected in all organic red beet extracts, suggesting that those compounds might be considered as biomarkers to discriminate conventional and organic red beets.

The conventional golden beet samples extracted by methanol (S13), aqueous ethanol and ascorbic acid mixtures (S7 and S9) were rich in L-tryptophan (m/z 205) and valine-betaxanthin

(m/z 311). Phenylalanine (m/z 166) was detected in extracts obtained by water with or without formic/acetic acid (S1, S3 and S4) extracts, aqueous methanol with ascorbic acid mixture (S15 and

S17) were detected. Similar to conventional red beet, -aminobutyric acid-betaxanthin (m/z 297) was also detected in S15 and S17 extracts. Glutamine-isobetaxanthin (m/z 340) was only detected in ethanol, water, and acetic acid extract (S11) with high levels. In other extracts, this compound was not detected. Proline-betaxanthin (m/z 309) was detected in ethanol (S5) and aqueous methanol (S14) extracts. Other solvents, which were S2, S6, S8, S18-20 were absent in those compounds.

In organic golden beet, the methanol, water, and formic acid mixture (S20) solvent extract namely leucine-betaxanthin (m/z 325), glutamine-betaxanthin (m/z 340), -aminobutyric acid- betaxanthin (m/z 297) exhibited the highest mass areas, with the levels 19 to 91-folds, 1 to 49- folds, and 14 folds higher than in aqueous ethanol or methanol extracts, respectively. The glutamine-betaxanthin (m/z 340) was only detected in ethanol, water, and ascorbic acid (S7) extract. However, few amino acids were found in aqueous ethanol and methanol extracts (S6 and

S16). The other extracts contained only low levels of those phytochemicals.

86 5.3. Conclusion

The present study indicated that solvent combination significantly influences the composition and content of phytochemicals in beet samples. UHPLC-QTOF-MS analysis combined with chemometrics identified 27 phytochemicals of which 27, 21, 6, and 6 phytochemicals were in conventional red, organic red, conventional golden, and organic golden beets, respectively. The levels of these compounds differed based on each solvent composition.

Distinct compounds identified from heatmap analysis might be considered as potential biomarkers to discriminate beet extracts obtained from various solvents or raw beets from different production systems. Conventional red beet extracted by S18 showed the highest DPPH and total phenolics, and methanol extract (S13) had the highest total phenolics.

In organic red beet, aqueous ethanol extract with or without acid (S8 and S19) had the highest total phenolics, DPPH, and ABTS values. Conventional and organic golden beet extracted by ethanol (S7 and S10) had higher antioxidant activities than other extracts. This provides useful information for optimizing methods for identification of phytochemicals and biomarkers.

87 Table 6. Levels of betanin, isobetanin, vulgaxanthin I, and valine-betaxanthin in beet extracts. Conventional Red Organic Red Conventional Golden Organic Golden Valine- Valine- Valine- Valine- Vulgaxant Vulgaxanth Beta Isobeta Vulgaxant Beta Isobe Vulgaxa No. Betanin Isobetanin betaxanthi Betanin Isobetanin betaxanthi betaxanthi betaxanthi hin I in I nin nin hin I nin tanin nthin I n n n n 2116.1 ± 82.8 ± 2.6 694.1 ± 14.7 ± 0.6 ND ND 320.1 ± ND ND S1 39.5 14.7 97.2 ± 5.1 364.2 ± 21.1 113.7 ± 8.9 31.9 ± 0.8 7.6 ND ND ND 578.8 ± 56.4 ± 0.8 454.0 ± 77.0 ± 2.1 2125.2 ± 191.4 ± ND ND 456.7 ± ND ND 289.4 ± S2 19.1 5.5 49.1 ± 1.4 2861.1 ± 93.9 280.5 8.5 29.9 27.5 ± 1.1 13.0 ND 1693.8 ± 95.4 ± 1.2 121.9 ± 93.2 ± 2.0 597.9 ± ND ND ND ND 30.8 ± S3 5.5 4.2 58.7± 1.6 3219.8 ± 105.9 10.6 80.6 ± 1.5 ND 39.0 ± 2.0 3.0 ND 2758.3 ± 601.8 ± 618.2 ± 116.2 ± 159.7 ± 313.3 ± ND ND ND ND S4 91.9 24.5 15.4 58.6 ± 1.2 3270.5 ± 142.6 1.3 18.3 16.4 47.4 ± 2.6 ND 9.6 ± 0.3 ND 835.1 ± 39.6 ± 2.8 232.1 ± 94.4 ± 3.0 162.6 ± ND ND 230.5 ± ND ND 148.1 ± S5 80.5 9.5 61.3 ± 1.5 3199.4 ± 149.1 851.0 ± 5.8 3.2 77.0 30.5 ± 2.0 1.2 10.5 ± 0.2 2545.3 ± 39.1 ± 1.9 1260.6 ± 193.9 ± 77.3 ± 3.5 922.4 ± 193.7 ± ND ND 491.8 ± ND ND 836.2 ± S6 42.8 8.1 3.4 3862.6 ± 60.1 34.3 5.4 7.4 22.6 ± 6.3 5.0 18.8 ± 1.8 1321.6 ± 73.7 ± 1.3 471.4 ± 115.9 ± 1673.5 ± 218.3 ± ND ND 348.9 ± ND ND 363.5 ± S7 21.4 4.8 65.6 ± 0.7 3752.6 ± 30.6 3.4 29.4 5.3 6.8 19.7 ± 0.9 7.4 23.6 ± 0.7 2472.0 ± 84.7 ± 4.8 885.4 ± 103.2 ± 1752.1 ± 207.6 ± ND ND 461.1 ± ND ND 234.4 ± 104.6 ± S8 62.3 30.7 75.2 ± 4.9 3583.1 ± 26.1 2.1 7.8 2.6 26.4 33.5 ± 0.7 25.0 9.2 1516.3 ± 74.5 ± 1.6 545.1 ± 62.8 ± 3.6 1180.3 ± 214.8 ± ND ND 448.1 ± ND ND 529.0 ± S9 6.0 2.7 83.6 ± 2.2 2544.9 ± 23.4 1.0 2.3 14.7 24.4 ± 1.5 3.0 44.6 ± 0.9 2328.3 ± 146.8 ± 1.2 460.6 ± 264.8 ± 662.3 ± 122.0 ± ND ND ND ND 62.4 ± S10 24.6 7.7 65.3 ± 1.7 3019.9 ± 156.9 13.8 41.6 7.6 54.3 ± 0.9 48.1 ± 2.0 0.5 6.4 ± 0.2 2712.9 ± 121.0 ± 3.3 775.9 ± 62.8 ± 1.7 581.6 ± ND ND ND ND 17.4 ± S11 24.8 7.4 68.9 ± 0.7 1725.0 ± 46.9 21.7 80.6 ± 1.9 ND 18.3 ± 0.5 2.3 ND 1149.0 ± 106.6 ± 3.1 228.3 ± 549.5 ± 170.8 ± ND ND 93.5 ND ND 131.1 ± S12 11.5 10.5 83.4 ± 2.9 3575.9 ± 74.1 15.9 380.6 ± 7.8 6.0 ±11.9 ND 15.4 17.7 ± 3.6 2448.8 ± 89.3 ± 2.7 1133.6 ± 162.1 ± 163.8 ± 4031.5 ± ND ND 659.4 ± ND ND 701.9 ± S13 21.8 7.4 2.0 8222.3 ± 471.6 14.0 212.3 67.9 ± 4.1 4.2 7.5 ± 0.2 30.5 16.6 ± 2.6 1421.2 ± 53.4 ± 1.6 535.6 ± 75.0 ± 2.7 1391.4 ± 153.3 ± ND ND 428.7 ± ND ND 423.9 ± S14 8.3 4.3 63.6 ± 1.2 2546.2 ± 76.8 59.4 4.9 15.8 17.3 ± 0.7 37.4 19.0 ± 0.5 1071.6 ± 51.5 ± 2.5 385.6 ± 186.3 ± 2085.8 ± 179.3 ± ND ND 699.7 ± ND ND 363.5 ± S15 58.2 22.9 46.9 ± 4.1 5479.4 ± 243.1 8.9 63.9 5.7 26.4 24.2 ± 1.3 7.4 23.6 ± 0.7 1287.3 ± 42.7 ± 0.8 499.0 ± 85.7 ± 2.4 1758.0 ± 157.4 ± ND ND 235.5 ± ND ND 588.5 ± S16 39.1 7.5 75.6 ± 1.9 3542.8 ± 63.5 4.0 3.8 20.3 80.9 ± 2.8 25.7 29.0 ± 2.2 2014.1 ± 65.6 ± 1.8 638.9 ± 134.0 ± 358.6 ± 109.8 ± ND ND 746.1 ± ND ND 710.5 ± S17 26.4 16.4 97.8 ± 3.8 2621.2 ± 141.8 4.6 25.3 9.6 4.3 ND 28.1 45.4 ± 1.9 2791.0 ± 220.7 ± 7.8 335.3 ± 460.0 ± 556.8 ± ND ND 120.4 ± ND ND 83.2 ± S18 60.2 17.9 62.6 ± 2.1 3776.8 ± 214.6 12.4 29.7 83.0 ± 2.6 6.9 70.3 ± 2.8 7.1 9.6 ± 0.4 2335.7 ± 76.9 ± 1.7 511.2 ± 109.9 ± 1505.7 ± ND ND ND ND 24.6 ± S19 22.4 9.0 44.1 ± 1.9 4727.2 ± 20.8 1.2 26.2 75.6 ± 4.5 ND 12.7 ± 1.9 3.8 11.1 ± 2.2 1453.7 ± 53.9 ± 1.8 595.5 ± 154.8 ± 3507.0 ± ND ND 320.1 ± ND ND S20 7.2 8.2 71.7 ± 3.9 8183.9 ± 67.5 4.9 13.9 78.2 ± 2.7 7.6 ND ND ND

88 Table 7. Identified phytochemicals found in conventionally and organically grown red and golden beets. No Identified compounds RT Molecularfor Experiment Exactmass Mass error MS/MS Beet Varieties . (min) mula almass (ppm) fragments Con Or Con Org Red g Golden Golden Reference Re d 1 Glutamine-isobetaxanthin 1.30 C14H17N3O7 340.1172 340.1139 9.7 321, 277 ˣ ˣ ˣ ˣ (Nemzer, et 2 Glutamine-betaxanthin 1.55 C14H17N3O7 340.1172 340.1139 9.7 321, 277 ˣ ˣ ˣ al., 2011) 3 Phenylalanine 3.15 C9H11NO2 166.0877 166.0863 8.4 - ˣ ˣ ˣ (Goodban, Stark, & Owens, 1953) 4 Glutamic acid-betaxanthin 3.50 C14H16N2O8 341.1009 341.0979 8.8 215 ˣ (Nemzer, et 5 Hydroxy caffeic acid 3.85 C9H8O5 197.0431 197.0445 -7.1 - ˣ al., 2011) + 6 17-Decarboxy-betanidin 4.15 C17H17N2O6 345.1109 345.1081 8.1 - ˣ ˣ + 7 17-Decarboxy-isobetanidin 4.25 C17H17N2O6 345.1102 345.1081 6.1 - ˣ 8 -Aminobutyric acid-betaxanthin 4.65 C13H16N2O6 297.1103 297.1081 7.4 - ˣ ˣ ˣ ˣ

9 Proline-betaxanthin 4.80 C14H16N2O6 309.1107 309.1081 8.4 283, 195 ˣ ˣ ˣ 10 L-tryptophan 5.15 C11H22N2O2 205.0986 205.0972 6.8 - ˣ ˣ ˣ ˣ 11 Prebetanin 5.35 C24H26N2O16S 631.1127 631.1076 8.1 551, 389 ˣ ˣ 12 Betanin 5.45 C24H26N2O13 551.1511 551.1508 0.5 389, 150 ˣ ˣ + 13 2´-O-glucosyl-betanin 5.65 C34H37N2O15 713.2086 713.2189 -14.4 551, 389 ˣ ˣ 14 Isobetanin 5.85 C24H26N2O13 551.1502 551.1508 -1.1 389, 150 ˣ ˣ 15 Betanidin 6.35 C18H16N2O8 389.1016 389.0979 9.5 343 ˣ 16 Valine-betaxanthin 6.50 C14H18N2O6 311.1263 311.1238 8.0 - ˣ ˣ ˣ 17 17-Decarboxy-betanin 6.75 C22H26N2O11 507.1723 507.1609 22.5 345 ˣ ˣ 18 Syringic acid 6.95 C9H10O5 199.0590 199.0601 -5.5 - ˣ (Obata, Senba, & Koshika, 1963) 19 Neobetanin 7.05 C24H24N2O13 549.1389 549.1352 6.7 387 ˣ ˣ (Nemzer, et 20 17-Decarboxy-neobetanin 7.05 C23H24N2O11 505.1565 505.1453 22.2 343, 297 ˣ ˣ al., 2011) 21 2-Decarboxy-neobetanin 7.10 C23H24N2O11 505.1568 505.1453 22.8 343, 297 ˣ ˣ 22 2,17-Bidecarboxy-2,3-dehydro- 7.90 C22H22N2O9 459.1501 459.1398 22.4 - ˣ ˣ neobetanin 23 Leucine-betaxanthin 8.00 C13H15N3O7 325.1419 325.1394 7.7 - ˣ ˣ (Vulgaxanthin IV) 24 Phenylalanine-betaxanthin 8.25 C18H18N2O6 359.1261 359.1238 6.4 313 ˣ 25 2-Decarboxy-2,3-dehydro- 8.60 C23H22N2O11 503.1336 503.1296 8.0 341 ˣ ˣ neobetanin + 26 6´-feruloyl-betanin 9.40 C34H35N2O16 727.2053 727.1981 9.9 453, 389 ˣ + 27 6´-feruloyl-isobetanin 9.60 C34H35N2O16 727.2044 727.1981 8.7 453, 389 ˣ

89 200 300 400 Wavelength [nm] 200 300 400 Wavelength [nm] Intens. Intens. Intens. UV, 6.0-6.3min A) Red Beet at 480 nm 470 UV, 2.0-2.3min F) Betanin 536 [mAU] Vulgaxanthin I Betanin [mAU] E) Vulgaxanthin I [mAU] Betanin Red Beet at 480 nm 200 200 300 150 200 Isobetanin 100 100 100 Valine-betaxanthin 50 258 268

0 0 +MS, 6.0-6.3min Intens.0 +MS, 2.0-2.3min Betanin B) Red Beet at 540 nm 551.15005 [mAU] 1.5 340.11541 Red Beet at 540 nm 1.5 1000 1.0 1.0 Isobetanin 500 0.5 0.5 157.08237 0.0 0.0 m/z -200 0 200 400 m/z 200 400 Intens.0 C) Golden Beet at 480 nm 200 300 400 Wavelength [nm] 300 350 400 450 Wavelength [nm] [mAU] Vulgaxanthin I Intens. Intens. 216 G) Isobetanin UV, 6.5-6.6min H) Valine-betaxanthin UV, 9.5-9.5min Golden Beet at 480 nm [mAU] 30 [mAU] 3 60 20 2 Valine-betaxanthin 40 536 10 1 20 0 Intens. D) Golden Beet at 540 nm 0 0 +MS, 9.5-9.5min [mAU] +MS, 6.5-6.5min Golden Beet at 540 nm 551.14947 325.13834 2.5 3 2 2.0 157.08256 1.5 2 1.0 0 157.08250 1 0.5 0.0 0 100 200 300 400 m/z 0 5 10 15 Time [min] 200 400 600 m/z Figure 6. UV and UPLC chromatograms of (A, B) red beet and (C, D) golden beet, with mass spectra of betalains of (E–H) red beet and (G–H) golden beet obtained by HR-ESI-QTOFMS analysis in positive ionization mode.

90 Figure 7. Total phenolics, plus DPPH and ABTS radical scavenging activity of (A) conventional and (B) organic red beets extracted with twenty different solvent combinations (see Table S1). Data for total phenolics are expressed as µg gallic acid equivalents per g of fresh weight. Data for DPPH and ABTS are expressed as µg ascorbic acid equivalents per g of fresh weight. X axis: solvent code, Y axis: ascorbic acid equivalents. Values were expressed as mean ± SE. Different letters indicate significant differences at P ≤ 0.05.

91 Figure 8. Total phenolics, plus DPPH and ABTS radical scavenging activity of (A) conventionally and (B) organically grown golden beets extracted with twenty solvent combinations (see Table S1). Data for total phenolics expressed as µg gallic acid equivalents per g of fresh weight. Data for DPPH and ABTS expressed as µg ascorbic acid equivalents per g of fresh weight. X axis: solvent code, Y axis: ascorbic acid equivalent values. Values were expressed as mean ± SE. Different letters indicate significant differences at P ≤ 0.05.

92 Figure 9. Betalain biosynthetic pathway and relative contents of main metabolites in conventionally and organically grown red and golden beet extracts. The y axis represents the sum of peak areas for each compound. Modified from (M. Wang, Lopez-Nieves, Goldman, & Maeda, 2017).

93 Conventional Organic

2-Decarboxy-2,3-dehydro-neobetanin 17-Decarboxy-betanin 17-Decarboxy-isobetanidin 2-Decarboxy-neobetanin Isobetanin Glutamine-isobetaxanthin Hydroxy caffeic acid 17-Decarboxy-neobetanin Neobetanin 17-Decarboxy-betanidin Glutamine-betaxanthin ℽ-Aminobutyric acid-betaxanthin Valine-betaxanthin Proline-betaxanthin 2,17-Bidecarboxy-2,3-dehydro-neobetanin Phenylalanine-betaxanthin Betanin 2’-O-glucosyl-betanin Phenylalanine L-tryptophan Syringic acid 6’-feruloyl-isobetanin Prebetanin 6’-feruloyl-betanin Betanidin Glutamic acid-betaxanthin Leucine-betaxanthin (Vulgaxanthin IV) C C C C C C C C C C C C C C C C C C C C O O O O O O O O O O O O O O O O O O O O ------S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20

Conventional Organic

Phenylalanine

ℽ-Aminobutyric acid-betaxanthin

Glutamine-betaxanthin

Leucine-betaxanthin

L-tryptophan

Valine-betaxanthin

Glutamine-isobetaxanthin

Phenylalanine-betaxanthin C C C C C C C C C C C C C C C C C C C C O O O O O O O O O O O O O O O O O O O O ------S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20

Figure 10. Heatmap of metabolites from conventionally and organically grown (A) red beet and (B) golden beet grown extracted by 20 solvents (see Table S1) based on Pearson distances and Ward clustering. With O: organic, C: conventional. Colored squares represent the abundance of each compound with blue indicating the lowest values and red the highest values.

94 Figure 11.Chemical structures of (A) betaxanthins and (B, C) betacyanins present in conventional and organic beets. The number in parenthesis of each compound matches Table 7.

95 6. SUMMARY AND CONCLUSION

Fruits and vegetables contain a wealth of phytochemicals. Accumulative studies have reported the relevance of regular consumptions of these phytochemicals to maintain health or reduce the risk of chronic diseases. Therefore, a comprehensive study concerns the effects of domestic and industrial processing and extraction on the phytochemicals of the fruits, vegetables, and their processed products is needed to provide the overall metabolite profile and assist food manufacturers optimize the products with desirable sensorial and nutritional balance. In the present study, a range of targeted and non-targeted metabolomic platforms, combined with chemometric approaches are applied to investigate the impact of processing techniques, production system, and extraction solvents on the metabolites profile and antioxidant activities in the fruits, vegetables, and their processed products. The first study deployed the three processing techniques (blending, high-speed centrifugal juicing and low-speed juicing) to unravel their effects to phytochemical profiles in 21 vegetables. Kaempferol and quercetin glycosides, decarboxylated betalains, and quercetin derivatives were found to be representative metabolites in separating the processing techniques and production system in the respective kale, beet, and melon juices. The effects of three processing techniques (blending, high-speed centrifugal juicing, and low-speed juicing) on phytochemical profiles and antioxidant activities were investigated by using UHPLC–QTOF-MS coupled to complementary targeted and untargeted metabolomics approaches. The results exhibited 73 different phytochemicals belonging to various chemical classes, such as flavonoids and betalains, and four novel betalains. Combined with chemometric principal component analysis

(PCA) and partial least squares discriminant analysis (PLS-DA), characteristic metabolites such as kaempferol glycosides and amino acid attached betaxanthins were chosen for discriminating the three processing techniques between kale and beet extracts, with the low-speed juicing retains

96 more kaempferol glycosides in Brassica vegetables, whereas the high-speed centrifugal juicing acquires more betalains. The antioxidant activities were significantly different in juices based on the three processing techniques and vegetable varieties, with the purple baby carrot blended juice had the highest total phenolics (717.67 µg/g GAE) and DPPH value (715.77 µg/g AA). This research provides a thorough insight for manufacturers in optimizing the process techniques to produce high-standard vegetable products.

The second study investigated the phenolic fingerprinting by using untargeted metabolites analysis through UPLC-QTOF-MS combined with chemometrics to identify potential metabolites by discriminating the 30 commercially obtained thermally and cold processed juices. HPLC results indicated all juices were desirable sources of phytochemicals, with the varied ascorbic acid (3-661

µg/mL) and total ascorbic acid (7-1183 µg/mL) content. The pure beet juice had the highest nitrate content (1075 µg/mL). Antioxidant activity results demonstrated that food ingredients and processing technique massively affected the results, in which the thermally processed kale, beet, and melon juices exhibited higher total phenolics and antioxidant activities than the cold-pressed juices. The results demonstrated that chemometrics is an efficient tool for discriminating thermally and cold-pressed commercial juices.

The present study assessed twenty solvent mixtures containing water, methanol, and ethanol alone or combined with an acid (ascorbic, formic, acetic) for extraction efficiency and antioxidant activities. These were tested on conventionally or organically grown red and golden beets (Beta vulgaris). Red beet extracted with methanol with or without acid had the highest betanin content (2791.0 µg/g and 8222.3 µg/g of fresh weight [FW]), and the water extracts had the lowest betanins (578.8 µg/g and 364.2 µg/g of FW). Golden beet extracted with methanol: ascorbic acid: water had the highest vulgaxanthin I (193.7 µg/g and 15.0 µg/g of FW). Tests of

97 radical-scavenging activity and total phenolics in beet extracts reflected the different extraction efficiency of each solvent. Ultra-high-performance liquid chromatography quadrupole time-of- flight mass spectrometry (UHPLC-QTOF-MS) identified 25 phytochemicals in conventional red,

20 in organic red, 6 in conventional golden, and 6 in organic golden beet extracts, respectively.

The untargeted metabolomics combined chemometrics discriminated the beet varieties and different extracts within on variety based on the composition and abundance of the key phytochemicals, which were decarboxylated betacyanins in red beet (conventional and organic), and amino acid adducted betaxanthins in golden beet (conventional and organic) extracts, separately.

98 REFERENCES

Alasalvar, C., Grigor, J. M., Zhang, D., Quantick, P. C., & Shahidi, F. (2001). Comparison of

volatiles, phenolics, sugars, antioxidant vitamins, and sensory quality of different colored

carrot varieties. Journal of Agricultural and Food Chemistry, 49(3), 1410-1416.

Alfadda, A. A., & Sallam, R. M. (2012). Reactive oxygen species in health and disease. BioMed

Research International, 2012.

Algarra, M., Fernandes, A., Mateus, N., de Freitas, V., da Silva, J. C. E., & Casado, J. (2014).

Anthocyanin profile and antioxidant capacity of black carrots (Daucus carota L. ssp.

sativus var. atrorubens Alef.) from Cuevas Bajas, Spain. Journal of Food Composition and

Analysis, 33(1), 71-76.

Alothman, M., Bhat, R., & Karim, A. (2009). Antioxidant capacity and phenolic content of

selected tropical fruits from Malaysia, extracted with different solvents. Food chemistry,

115(3), 785-788.

Arscott, S. A., & Tanumihardjo, S. A. (2010). Carrots of many colors provide basic nutrition and

bioavailable phytochemicals acting as a functional food. Comprehensive Reviews in Food

Science and Food Safety, 9(2), 223-239.

Asami, D. K., Hong, Y.-J., Barrett, D. M., & Mitchell, A. E. (2003). Comparison of the total

phenolic and ascorbic acid content of freeze-dried and air-dried marionberry, strawberry,

and corn grown using conventional, organic, and sustainable agricultural practices. Journal

of Agricultural and Food Chemistry, 51(5), 1237-1241.

Azeredo, H. M. (2009). Betalains: properties, sources, applications, and stability–a review.

International journal of food science & technology, 44(12), 2365-2376.

99 Bae, H., Jayaprakasha, G., Jifon, J., & Patil, B. S. (2012). Variation of antioxidant activity and the

levels of bioactive compounds in lipophilic and hydrophilic extracts from hot pepper

(Capsicum spp.) cultivars. Food Chemistry, 134(4), 1912-1918.

Barba, F. J., Mariutti, L. R., Bragagnolo, N., Mercadante, A. Z., Barbosa-Cánovas, G. V., & Orlien,

V. (2017a). Bioaccessibility of bioactive compounds from fruits and vegetables after

thermal and nonthermal processing. Trends in Food Science & Technology, 67, 195-206.

Barba, F. J., Mariutti, L. R., Bragagnolo, N., Mercadante, A. Z., Barbosa-Cánovas, G. V., & Orlien,

V. (2017b). Bioaccessibility of bioactive compounds from fruits and vegetables after

thermal and nonthermal processing. Trends in Food Science and Technology, 67, 195-206.

Barkat, N., Singh, J., Jayaprakasha, G. K., & Patil, B. S. (2018). Effect of harvest time on the levels

of phytochemicals, free radical‐scavenging activity, α‐amylase inhibition and bile acid‐

binding capacity of spinach (Spinacia oleracea). Journal of the Science of Food and

Agriculture, 98, 3468-3477.

Barrett, D. M., Beaulieu, J. C., & Shewfelt, R. (2010). Color, flavor, texture, and nutritional quality

of fresh-cut fruits and vegetables: desirable levels, instrumental and sensory measurement,

and the effects of processing. Critical Reviews in Food Science and Nutrition, 50(5), 369-

389.

Bavec, M., Turinek, M., Grobelnik-Mlakar, S., Slatnar, A., & Bavec, F. (2010). Influence of

industrial and alternative farming systems on contents of sugars, organic acids, total

phenolic content, and the antioxidant activity of red beet (Beta vulgaris L. ssp. vulgaris

Rote Kugel). Journal of Agricultural and Food Chemistry, 58(22), 11825-11831.

100 Bazaria, B., & Kumar, P. (2016). Compositional changes in functional attributes of vacuum

concentrated beetroot juice. Journal of Food Processing and Preservation, 40(6), 1215-

1222.

Belhadj Slimen, I., Najar, T., & Abderrabba, M. (2017). Chemical and antioxidant properties of

betalains. Journal of Agricultural and Food Chemistry, 65(4), 675-689.

Bhat, R., & Stamminger, R. (2015). Preserving strawberry quality by employing novel food

preservation and processing techniques–Recent updates and future scope–An overview.

Journal of Food Process Engineering, 38(6), 536-554.

Boeing, J. S., Barizão, É. O., e Silva, B. C., Montanher, P. F., de Cinque Almeida, V., &

Visentainer, J. V. (2014). Evaluation of solvent effect on the extraction of phenolic

compounds and antioxidant capacities from the berries: application of principal component

analysis. Chemistry Central Journal, 8(1), 48.

Borges, G., Mullen, W., & Crozier, A. (2010). Comparison of the polyphenolic composition and

antioxidant activity of European commercial fruit juices. Food & Function, 1(1), 73-83.

Bresciani, L., Calani, L., Cossu, M., Mena, P., Sayegh, M., Ray, S., & Del Rio, D. (2015). (Poly)

phenolic characterization of three food supplements containing 36 different fruits,

vegetables and berries. PharmaNutrition, 3(2), 11-19.

Cardoso-Ugarte, G., Sosa-Morales, M., Ballard, T., Liceaga, A., & San Martín-González, M.

(2014). Microwave-assisted extraction of betalains from red beet (Beta vulgaris). LWT-

Food Science and Technology, 59(1), 276-282.

Caristi, C., Bellocco, E., Panzera, V., Toscano, G., Vadalà, R., & Leuzzi, U. (2003). Flavonoids

detection by HPLC-DAD-MS-MS in lemon juices from Sicilian cultivars. Journal of

Agricultural and Food Chemistry, 51(12), 3528-3534.

101 Cartea, M. E., Francisco, M., Soengas, P., & Velasco, P. (2010). Phenolic compounds in Brassica

vegetables. Molecules, 16(1), 251-280.

Cartea, M. E., Francisco, M., Soengas, P., & Velasco, P. (2011). Phenolic compounds in Brassica

vegetables. Molecules, 16(1), 251-280.

Castro-Puyana, M., & Herrero, M. (2013). Metabolomics approaches based on mass spectrometry

for food safety, quality and traceability. TrAC Trends in Analytical Chemistry, 52, 74-87.

Celli, G. B., & Brooks, M. S.-L. (2017). Impact of extraction and processing conditions on

betalains and comparison of properties with anthocyanins—a current review. Food

Research International, 100, 501-509.

Chaitanya Lakshmi, G. (2014). Food coloring: the natural way. Res J Chem Sci, 2231(8), 606X.

Chaudhary, P., Jayaprakasha, G., Porat, R., & Patil, B. S. (2012). Degreening and postharvest

storage influences ‘Star Ruby’grapefruit (Citrus paradisi Macf.) bioactive compounds.

Food Chemistry, 135(3), 1667-1675.

Chebrolu, K. K., Jayaprakasha, G., Yoo, K. S., Jifon, J. L., & Patil, B. S. (2012a). An improved

sample preparation method for quantification of ascorbic acid and dehydroascorbic acid by

HPLC. LWT-Food Science and Technology, 47(2), 443-449.

Chebrolu, K. K., Jayaprakasha, G., Yoo, K. S., Jifon, J. L., & Patil, B. S. (2012b). An improved

sample preparation method for quantification of ascorbic acid and dehydroascorbic acid by

HPLC. LWT- Food Science and Technology, 47(2), 443-449.

Clifford, T., Howatson, G., West, D. J., & Stevenson, E. J. (2015). The potential benefits of red

beetroot supplementation in health and disease. Nutrients, 7(4), 2801-2822.

102 Corleto, K. A., Singh, J., Jayaprakasha, G., & Patil, B. S. (2018). Storage Stability of Dietary

Nitrate and Phenolic Compounds in Beetroot (Beta vulgaris) and Arugula (Eruca sativa)

Juices. Journal of Food Science, 83(5), 1237-1248.

Damunupola, D., Weerathilake, W., & Sumanasekara, G. (2014). Evaluation of quality

characteristics of goat milk yogurt incorporated with beetroot juice. International Journal

of Scientific and Research Publications, 4(10).

Davis, A. L., Cai, Y., Davies, A. P., & Lewis, J. (1996). 1H and 13C NMR assignments of some

green tea polyphenols. Magnetic Resonance in Chemistry, 34(11), 887-890.

Dillard, C. J., & German, J. B. (2000). Phytochemicals: nutraceuticals and human health. Journal

of the Science of Food and Agriculture, 80(12), 1744-1756.

Dominy, N. J. (2004). Color as an indicator of food quality to anthropoid primates: ecological

evidence and an evolutionary scenario. In Anthropoid Origins, (pp. 615-644): Springer. dos Santos, A. M., Lima, J. S., dos Santos, I. F., Silva, E. F., de Santana, F. A., de Araujo, D. G.,

& dos Santos, L. O. (2019). Mineral and centesimal composition evaluation of

conventional and organic cultivars sweet potato (Ipomoea batatas (L.) Lam) using

chemometric tools. Food chemistry, 273, 166-171.

Esteki, M., Simal-Gandara, J., Shahsavari, Z., Zandbaaf, S., Dashtaki, E., & Vander Heyden, Y.

(2018). A review on the application of chromatographic methods, coupled to

chemometrics, for food authentication (Chromatography-chemometrics in food

authentication). Food control.

Fathordoobady, F., Mirhosseini, H., Selamat, J., & Manap, M. Y. A. (2016). Effect of solvent type

and ratio on betacyanins and antioxidant activity of extracts from Hylocereus polyrhizus

103 flesh and peel by supercritical fluid extraction and solvent extraction. Food chemistry, 202,

70-80.

Fidelis, M., Santos, J. S., Coelho, A. L. K., Rodionova, O. Y., Pomerantsev, A., & Granato, D.

(2017). Authentication of juices from antioxidant and chemical perspectives: a feasibility

quality control study using chemometrics. Food control, 73, 796-805.

Floegel, A., Kim, D.-O., Chung, S.-J., Koo, S. I., & Chun, O. K. (2011). Comparison of

ABTS/DPPH assays to measure antioxidant capacity in popular antioxidant-rich US foods.

Journal of Food Composition and Analysis, 24(7), 1043-1048.

Forbes, J. M., Coughlan, M. T., & Cooper, M. E. (2008). Oxidative stress as a major culprit in

kidney disease in diabetes. Diabetes, 57(6), 1446-1454.

Gandía-Herrero, F., Escribano, J., & García-Carmona, F. (2010). Structural implications on color,

fluorescence, and antiradical activity in betalains. Planta, 232(2), 449-460.

Gandía-Herrero, F., Escribano, J., & García-Carmona, F. (2009). The role of phenolic hydroxy

groups in the free radical scavenging activity of betalains. Journal of Natural Products,

72(6), 1142-1146.

Gardner, P. T., White, T. A., McPhail, D. B., & Duthie, G. G. (2000). The relative contributions

of vitamin C, carotenoids and phenolics to the antioxidant potential of fruit juices. Food

Chemistry, 68(4), 471-474.

Georgiev, V. G., Weber, J., Kneschke, E.-M., Denev, P. N., Bley, T., & Pavlov, A. I. (2010).

Antioxidant activity and phenolic content of betalain extracts from intact plants and hairy

root cultures of the red beetroot Beta vulgaris cv. Detroit dark red. Plant Foods for Human

Nutrition, 65(2), 105-111.

104 Goodban, A. E., Stark, J. B., & Owens, H. S. (1953). Amino Acids, Content of Sugar Beet

Processing Juices. Journal of Agricultural and Food Chemistry, 1(3), 261-264.

Hansen, H. (1980). Comparison of chemical composition and taste of biodynamically and

conventionally grown vegetables. Plant Foods for Human Nutrition, 30(3-4), 203-211.

Heo, S.-J., Hwang, J.-Y., Choi, J.-I., Han, J.-S., Kim, H.-J., & Jeon, Y.-J. (2009).

Diphlorethohydroxycarmalol isolated from Ishige okamurae, a brown algae, a potent α-

glucosidase and α-amylase inhibitor, alleviates postprandial hyperglycemia in diabetic

mice. European Journal of Pharmacology, 615(1-3), 252-256.

Hohmann, M., Monakhova, Y., Erich, S., Christoph, N., Wachter, H., & Holzgrabe, U. (2015).

Differentiation of organically and conventionally grown tomatoes by chemometric analysis

of combined data from proton nuclear magnetic resonance and mid-infrared spectroscopy

and stable isotope analysis. Journal of Agricultural and food Chemistry, 63(43), 9666-

9675.

Huang, D., Ou, B., & Prior, R. L. (2005). The chemistry behind antioxidant capacity assays.

Journal of Agricultural and Food Chemistry, 53(6), 1841-1856.

Huang, H.-W., Wu, S.-J., Lu, J.-K., Shyu, Y.-T., & Wang, C.-Y. (2017). Current status and future

trends of high-pressure processing in food industry. Food control, 72, 1-8.

Hung, H.-C., Joshipura, K. J., Jiang, R., Hu, F. B., Hunter, D., Smith-Warner, S. A., Colditz, G.

A., Rosner, B., Spiegelman, D., & Willett, W. C. (2004). Fruit and vegetable intake and

risk of major chronic disease. Journal of the National Cancer Institute, 96(21), 1577-1584.

Jandrić, Z., Roberts, D., Rathor, M., Abrahim, A., Islam, M., & Cannavan, A. (2014). Assessment

of fruit juice authenticity using UPLC–QToF MS: A metabolomics approach. Food

chemistry, 148, 7-17.

105 Jayaprakasha, G., & Patil, B. S. (2007). In vitro evaluation of the antioxidant activities in fruit

extracts from citron and blood orange. Food chemistry, 101(1), 410-418.

Jayaprakasha, G. K., Girennavar, B., & Patil, B. S. (2008). Antioxidant capacity of pummelo and

navel oranges: Extraction efficiency of solvents in sequence. LWT-Food Science and

Technology, 41(3), 376-384.

Jiménez-Sánchez, C., Lozano-Sánchez, J., Segura-Carretero, A., & Fernández-Gutiérrez, A.

(2017). Alternatives to conventional thermal treatments in fruit-juice processing. Part 2:

effect on composition, phytochemical content, and physicochemical, rheological, and

organoleptic properties of fruit juices. Critical reviews in food science and nutrition, 57(3),

637-652.

Kammerer, D., Carle, R., & Schieber, A. (2004). Characterization of phenolic acids in black carrots

(Daucus carota ssp. sativus var. atrorubens Alef.) by high‐performance liquid

chromatography/electrospray ionization mass spectrometry. Rapid Communications in

Mass Spectrometry, 18(12), 1331-1340.

Kaufmann, A. (2014). Combining UHPLC and high-resolution MS: a viable approach for the

analysis of complex samples? TrAC Trends in Analytical Chemistry, 63, 113-128.

Kazimierczak, R., Hallmann, E., Lipowski, J., Drela, N., Kowalik, A., Püssa, T., Matt, D., Luik,

A., Gozdowski, D., & Rembiałkowska, E. (2014). Beetroot (Beta vulgaris L.) and naturally

fermented beetroot juices from organic and conventional production: metabolomics,

antioxidant levels and anticancer activity. Journal of the Science of Food and Agriculture,

94(13), 2618-2629.

Kazimierczak, R., Hallmann, E., Lipowski, J., Drela, N., Kowalik, A., Püssa, T., Matt, D., Luik,

A., Gozdowski, D., Rembiałkowska, E. J. J. o. t. S. o. F., & Agriculture. (2014). Beetroot

106 (Beta vulgaris L.) and naturally fermented beetroot juices from organic and conventional

production: metabolomics, antioxidant levels and anticancer activity. 94(13), 2618-2629.

Kelebek, H. (2016). LC-DAD–ESI-MS/MS characterization of phenolic constituents in Turkish

black tea: Effect of infusion time and temperature. Food Chemistry, 204, 227-238.

Khan, M. I., & Giridhar, P. (2015). Plant betalains: chemistry and biochemistry. Phytochemistry,

117, 267-295.

Kim, M.-J., Kim, J.-I., Kang, M.-J., Kwon, B., Jun, J.-G., Choi, J.-H., & Kim, M.-J. (2015). Quality

evaluation of fresh tomato juices prepared using high-speed centrifugal and low-speed

masticating household juicers. Food Science and Biotechnology, 24(1), 61-66.

Kim, S. Y., Sun, Y., Kwon, S. M., Park, K. S., & Lee-Kim, Y. C. (2008). Kale Juice Improves

Coronary Artery Disease Risk Factors in Hypercholesterolemic Men1. Biomedical and

Environmental Sciences, 21(2), 91-97.

Knorr, D., Ade-Omowaye, B., & Heinz, V. (2002). Nutritional improvement of plant foods by

non-thermal processing. Proceedings of the nutrition society, 61(2), 311-318.

Krejčová, A., Návesník, J., Jičínská, J., & Černohorský, T. (2016). An elemental analysis of

conventionally, organically and self-grown carrots. Food Chemistry, 192, 242-249.

Kujala, T., Loponen, J., & Pihlaja, K. (2001). Betalains and phenolics in red beetroot (Beta

vulgaris) peel extracts: extraction and characterisation. Zeitschrift für Naturforschung C,

56(5-6), 343-348.

Kujala, T. S., Vienola, M. S., Klika, K. D., Loponen, J. M., & Pihlaja, K. (2002). Betalain and

phenolic compositions of four beetroot (Beta vulgaris) cultivars. European Food Research

and Technology, 214(6), 505-510.

107 Lin, L.-Z., & Harnly, J. M. (2009). Identification of the phenolic components of collard greens,

kale, and Chinese broccoli. Journal of Agriculture and Food Chemistry, 57(16), 7401-

7408.

Lin, L.-Z., & Harnly, J. M. (2010). Phenolic component profiles of mustard greens, yu choy, and

15 other Brassica vegetables. Journal of Agricultural and Food Chemistry, 58(11), 6850-

6857.

Lin, L.-Z., Sun, J., Chen, P., & Harnly, J. (2011). UHPLC-PDA-ESI/HRMS/MS n analysis of

anthocyanins, flavonol glycosides, and hydroxycinnamic acid derivatives in red mustard

greens (Brassica juncea Coss variety). Journal of Agricultural and food Chemistry, 59(22),

12059-12072.

Liou, G.-Y., & Storz, P. (2010). Reactive oxygen species in cancer. Free Radical Research, 44(5),

479-496.

Liu, R. H. (2004). Potential synergy of phytochemicals in cancer prevention: mechanism of action.

The Journal of Nutrition, 134(12), 3479S-3485S.

Lopez-Sanchez, P., De Vos, R., Jonker, H., Mumm, R., Hall, R., Bialek, L., Leenman, R.,

Strassburg, K., Vreeken, R., & Hankemeier, T. (2015). Comprehensive metabolomics to

evaluate the impact of industrial processing on the phytochemical composition of vegetable

purees. Food chemistry, 168, 348-355.

Lundberg, J. O., Carlström, M., Larsen, F. J., & Weitzberg, E. (2010). Roles of dietary inorganic

nitrate in cardiovascular health and disease. Cardiovascular Research, 89(3), 525-532.

Ma, T., Tian, C., Luo, J., Zhou, R., Sun, X., & Ma, J. (2013). Influence of technical processing

units on polyphenols and antioxidant capacity of carrot (Daucus carota L.) juice. Food

Chemistry, 141(3), 1637-1644.

108 Marsol-Vall, A., Balcells, M., Eras, J., & Canela-Garayoa, R. (2018). Development of a SBSE-

TD method coupled to GC–MS and chemometrics for the differentiation of variety and

processing conditions in peach juices. Food chemistry, 239, 119-125.

McDowell, I., Bailey, R. G., & Howard, G. (1990). Flavonol glycosides in black tea. Journal of

the Science of Food and Agriculture, 53(3), 411-414.

Medina, S., Pereira, J. A., Silva, P., Perestrelo, R., & Camara, J. S. (2018). Food fingerprints-A

valuable tool to monitor food authenticity and safety. Food chemistry.

Mendes Lopes, M. L., Miguel, M. A. L., Fialho, E., & Valente‐Mesquita, V. L. (2016). Grape juice

obtained using steam extraction and other small‐scale extraction methods: phenolic

content, antioxidant capacity and stability during storage. International Journal of Food

Science & Technology, 51(7), 1696-1702.

Miller, N. J., & Rice-Evans, C. A. (1997). The relative contributions of ascorbic acid and phenolic

antioxidants to the total antioxidant activity of orange and apple fruit juices and

blackcurrant drink. Food Chemistry, 60(3), 331-337.

Naczk, M., & Shahidi, F. (2006). Phenolics in cereals, fruits and vegetables: Occurrence,

extraction and analysis. Journal of Pharmaceutical and Biomedical Analysis, 41(5), 1523-

1542.

Narkprasom, K., Su, W. L., Cheng, M. Y., Wang, S. P., Hsiao, S. M., & Tsai, P. J. (2012). Relative

Effects of Alcohol and pH on Betacyanin Stability in Aqueous D julis Extracts and Their

Color Qualities after Organic Acid Addition. Journal of Food Quality, 35(4), 283-291.

Nayak, B., Liu, R. H., & Tang, J. (2015). Effect of processing on phenolic antioxidants of fruits,

vegetables, and grains—a review. Critical Reviews in Food Science and Nutrition, 55(7),

887-918.

109 Nemzer, B., Pietrzkowski, Z., Spórna, A., Stalica, P., Thresher, W., Michałowski, T., &

Wybraniec, S. (2011). Betalainic and nutritional profiles of pigment-enriched red beet root

(Beta vulgaris L.) dried extracts. Food chemistry, 127(1), 42-53.

Nile, S. H., & Park, S. W. (2014). Edible berries: Bioactive components and their effect on human

health. Nutrition, 30(2), 134-144.

Obata, Y., Senba, Y., & Koshika, M. (1963). Detection of phenolic compounds by chromatography

in beet sugar molasses. Agricultural and Biological Chemistry, 27(5), 340-341.

Odriozola-Serrano, I., Soliva-Fortuny, R., Hernández-Jover, T., & Martín-Belloso, O. (2009).

Carotenoid and phenolic profile of tomato juices processed by high intensity pulsed electric

fields compared with conventional thermal treatments. Food chemistry, 112(1), 258-266.

Osorio-Esquivel, O., Álvarez, V. B., Dorantes-Álvarez, L., & Giusti, M. M. (2011). Phenolics,

betacyanins and antioxidant activity in Opuntia joconostle fruits. Food Research

International, 44(7), 2160-2168.

Patras, A., Brunton, N., Da Pieve, S., Butler, F., & Downey, G. (2009). Effect of thermal and high

pressure processing on antioxidant activity and instrumental colour of tomato and carrot

purées. Innovative food science & emerging technologies, 10(1), 16-22.

Patras, A., Brunton, N. P., O'Donnell, C., & Tiwari, B. (2010). Effect of thermal processing on

anthocyanin stability in foods; mechanisms and kinetics of degradation. Trends in Food

Science & Technology, 21(1), 3-11.

Pereira, R., & Vicente, A. (2010). Environmental impact of novel thermal and non-thermal

technologies in food processing. Food Research International, 43(7), 1936-1943.

Petersen, A., & Stoltze, S. (1999). Nitrate and nitrite in vegetables on the Danish market: content

and intake. Food Additives & Contaminants, 16(7), 291-299.

110 Pfiffner, L., Niggli, U., Velimirov, A., Boltzmann, L., Balzer, U., Balzer, F., & Besson, J.-M.

(1992). Effect of three farming systems (bio-dynamic, bio-organic, conventional) on yield

and quality of beetroot (Beta vulgaris L. var. esculenta L.) in a seven year crop rotation. In

Workshop on Ecological Aspects of Vegetable Fertilization in Integrated Crop Production

in the Field 339, (pp. 11-32).

Pham-Huy, L. A., He, H., & Pham-Huy, C. (2008). Free radicals, antioxidants in disease and

health. International journal of biomedical science: IJBS, 4(2), 89.

Pyo, Y.-H., Jin, Y.-J., & Hwang, J.-Y. (2014). Comparison of the effects of blending and juicing

on the phytochemicals contents and antioxidant capacity of typical korean kernel fruit

juices. Preventive nutrition and food science, 19(2), 108.

Ravichandran, K., Saw, N. M. M. T., Mohdaly, A. A., Gabr, A. M., Kastell, A., Riedel, H., Cai,

Z., Knorr, D., & Smetanska, I. (2013). Impact of processing of red beet on betalain content

and antioxidant activity. Food Research International, 50(2), 670-675.

Rawson, A., Patras, A., Tiwari, B., Noci, F., Koutchma, T., & Brunton, N. (2011). Effect of thermal

and non thermal processing technologies on the bioactive content of exotic fruits and their

products: Review of recent advances. Food Research International, 44(7), 1875-1887.

Rekhy, R., & McConchie, R. (2014). Promoting consumption of fruit and vegetables for better

health. Have campaigns delivered on the goals? Appetite, 79, 113-123.

Rice-Evans, C. A., Miller, N. J., & Paganga, G. (1996). Structure-antioxidant activity relationships

of flavonoids and phenolic acids. Free Radical Biology and Medicine, 20(7), 933-956.

Rouphael, Y., Cardarelli, M., Bassal, A., Leonardi, C., Giuffrida, F., & Colla, G. (2012). Vegetable

quality as affected by genetic, agronomic and environmental factors. Journal of Food,

Agriculture & Environment, 10(3&4), 680-688.

111 Rubert, J., Zachariasova, M., & Hajslova, J. (2015). Advances in high-resolution mass

spectrometry based on metabolomics studies for food–a review. Food Additives &

Contaminants: Part A, 32(10), 1685-1708.

Sales, P. M., Souza, P. M., Simeoni, L. A., Magalhães, P. O., & Silveira, D. (2012). α-Amylase

inhibitors: a review of raw material and isolated compounds from plant source. Journal of

Pharmacy & Pharmaceutical Sciences, 15(1), 141-183.

Šamec, D., Maretić, M., Lugarić, I., Mešić, A., Salopek-Sondi, B., & Duralija, B. (2016).

Assessment of the differences in the physical, chemical and phytochemical properties of

four strawberry cultivars using principal component analysis. Food chemistry, 194, 828-

834.

Sawicki, T., Bączek, N., & Wiczkowski, W. (2016). Betalain profile, content and antioxidant

capacity of red beetroot dependent on the genotype and root part. Journal of Functional

Foods, 27, 249-261.

Schaich, K., Tian, X., & Xie, J. (2015). Hurdles and pitfalls in measuring antioxidant efficacy: A

critical evaluation of ABTS, DPPH, and ORAC assays. Journal of functional foods, 14,

111-125.

Schliemann, W., Kobayashi, N., & Strack, D. (1999). The decisive step in betaxanthin biosynthesis

is a spontaneous reaction1. Plant Physiology, 119(4), 1217-1232.

Sen, S., Chakraborty, R., Sridhar, C., Reddy, Y., & De, B. (2010). Free radicals, antioxidants,

diseases and phytomedicines: current status and future prospect. International Journal of

Pharmaceutical Sciences Review and Research, 3(1), 91-100.

112 Sethiya, N. K., Trivedi, A., & Mishra, S. (2014). The total antioxidant content and radical

scavenging investigation on 17 phytochemical from dietary plant sources used globally as

functional food. Biomedicine & Preventive Nutrition, 4(3), 439-444.

Shahidi, F., & Yeo, J. (2016). Insoluble-bound phenolics in food. Molecules, 21(9), 1216.

Singh, J., Jayaprakasha, G., & Patil, B. S. (2018). An optimized solvent extraction and

characterization of unidentified flavonoid glucuronide derivatives from spinach by

UHPLC-HR-QTOF-MS. Talanta, 188, 763-771.

Slatnar, A., Stampar, F., Veberic, R., & Jakopic, J. (2015a). HPLC‐MSn Identification of Betalain

Profile of Different Beetroot (Beta vulgaris L. ssp. vulgaris) Parts and Cultivars. J. Food

Sci., 80(9), C1952-C1958.

Slatnar, A., Stampar, F., Veberic, R., & Jakopic, J. (2015b). HPLC‐MSn identification of betalain

profile of different beetroot (Beta vulgaris L. ssp. vulgaris) parts and cultivars. Jounal of

Food Science, 80(9), C1952-C1958.

Spórna-Kucab, A., Ignatova, S., Garrard, I., & Wybraniec, S. (2013). Versatile solvent systems for

the separation of betalains from processed Beta vulgaris L. juice using counter-current

chromatography. Journal of chromatography B, 941, 54-61.

Stintzing, F. C., Schieber, A., & Carle, R. (2002a). Identification of betalains from yellow beet

(Beta vulgaris L.) and cactus pear [Opuntia ficus-indica (L.) Mill.] by high-performance

liquid chromatography− electrospray ionization mass spectrometry. J. Agric. Food Chem.,

50(8), 2302-2307.

Stintzing, F. C., Schieber, A., & Carle, R. (2002b). Identification of betalains from yellow beet

(Beta vulgaris L.) and cactus pear [Opuntia ficus-indica (L.) Mill.] by high-performance

113 liquid chromatography− electrospray ionization mass spectrometry. Journal of

Agricultural and Food Chemistry, 50(8), 2302-2307.

Strack, D., Vogt, T., & Schliemann, W. (2003). Recent advances in betalain research.

Phytochemistry, 62(3), 247-269.

Swamy, G. J., Sangamithra, A., & Chandrasekar, V. (2014). Response surface modeling and

process optimization of aqueous extraction of natural pigments from Beta vulgaris using

Box–Behnken design of experiments. Dyes and Pigments, 111, 64-74.

Swartz, M. E. (2005). UPLC™: an introduction and review. Journal of Liquid Chromatography

& Related Technologies, 28(7-8), 1253-1263.

Thankappan, A., Thomas, S., & Nampoori, V. (2013). Solvent effect on the third order optical

nonlinearity and optical limiting ability of betanin natural dye extracted from red beet root.

Optical Materials, 35(12), 2332-2337.

Tiwari, U., & Cummins, E. (2013). Factors influencing levels of phytochemicals in selected fruit

and vegetables during pre-and post-harvest food processing operations. Food Research

International, 50(2), 497-506.

Tomas, M., Beekwilder, J., Hall, R. D., Sagdic, O., Boyacioglu, D., & Capanoglu, E. (2017).

Industrial processing versus home processing of tomato sauce: Effects on phenolics,

flavonoids and in vitro bioaccessibility of antioxidants. Food chemistry, 220, 51-58.

Uckoo, R. M., Jayaprakasha, G., & Patil, B. S. (2015). Phytochemical analysis of organic and

conventionally cultivated Meyer lemons (Citrus meyeri Tan.) during refrigerated storage.

Journal of Food Composition and Analysis, 42, 63-70.

114 Uckoo, R. M., Jayaprakasha, G. K., Balasubramaniam, V., & Patil, B. S. (2012). Grapefruit (Citrus

paradisi Macfad) phytochemicals composition is modulated by household processing

techniques. Journal of food science, 77(9), C921-C926.

Unal, K., Susanti, D., & Taher, M. (2014). Polyphenol content and antioxidant capacity in

organically and conventionally grown vegetables. Journal of Coastal Life Medicine, 2(11),

864-871.

Vitaglione, P., Sforza, S., & Del Rio, D. (2012). Occurrence, bioavailability, and metabolism of

resveratrol. In Flavonoids and related compounds: bioavailability and function, (pp. 167-

182): CRC Press, Boca Raton.

Vulić, J., Čanadanović-Brunet, J., Ćetković, G., Tumbas, V., Djilas, S., Četojević-Simin, D., &

Čanadanović, V. (2012). Antioxidant and cell growth activities of beet root pomace

extracts. Journal of functional foods, 4(3), 670-678.

Wang, C.-Y., Huang, H.-W., Hsu, C.-P., & Yang, B. B. (2016). Recent advances in food

processing using high hydrostatic pressure technology. Critical Reviews in Food Science

and Nutrition, 56(4), 527-540.

Wang, H., Cao, G., & Prior, R. L. (1997). Oxygen radical absorbing capacity of anthocyanins.

Journal of Agricultural and Food Chemistry, 45(2), 304-309.

Wang, M., Lopez-Nieves, S., Goldman, I. L., & Maeda, H. A. (2017). Limited tyrosine utilization

explains lower betalain contents in yellow than in red table beet genotypes. Journal of

Agricultural and Food Chemistry, 65(21), 4305-4313.

Wang, P. Y., Fang, J. C., Gao, Z. H., Zhang, C., & Xie, S. Y. (2016). Higher intake of fruits,

vegetables or their fiber reduces the risk of type 2 diabetes: A meta‐analysis. Journal of

Diabetes Investigation, 7(1), 56-69.

115 Williams, D. J., Edwards, D., Hamernig, I., Jian, L., James, A. P., Johnson, S. K., & Tapsell, L. C.

(2013). Vegetables containing phytochemicals with potential anti-obesity properties: A

review. Food Research International, 52(1), 323-333.

Wootton-Beard, P. C., & Ryan, L. (2011). A beetroot juice shot is a significant and convenient

source of bioaccessible antioxidants. Jounal of Functional Foods, 3(4), 329-334.

Wruss, J., Waldenberger, G., Huemer, S., Uygun, P., Lanzerstorfer, P., Müller, U., Höglinger, O.,

& Weghuber, J. (2015). Compositional characteristics of commercial beetroot products and

beetroot juice prepared from seven beetroot varieties grown in Upper Austria. Journal of

Food Composition and Analysis, 42, 46-55.

Yahia, E. M. (2017). The contribution of fruit and vegetable consumption to human health. Fruit

and Vegetable Phytochemicals; De La Rosa, LA, Alvarez-Parrilla, E., González-Aguilar,

GA, Eds, 3-51.

Yang, I., Jayaprakasha, G. K., & Patil, B. (2018a). In vitro digestion with bile acids enhances the

bioaccessibility of kale polyphenols. Food Funct., 9(2), 1235-1244.

Yang, I., Jayaprakasha, G. K., & Patil, B. (2018b). In vitro digestion with bile acids enhances the

bioaccessibility of kale polyphenols. Food & Function, 9(2), 1235-1244.

Zhang, A., Sun, H., Wang, P., Han, Y., & Wang, X. (2012). Modern analytical techniques in

metabolomics analysis. Analyst, 137(2), 293-300.

Zhang, D., & Hamauzu, Y. (2004). Phenolic compounds and their antioxidant properties in

different tissues of carrots (Daucus carota L.). Journal of Food Agriculture and

Environment, 2, 95-100.

116 APPENDIX A

TABLES FOR ADDITIONAL INFORMATION

Table A-1. Commercial name, scientific name, yield, and color measurement of 21 vegetables processed by three juicing techniques. Scientif Name (color) Processing Yield (%) L* a* b* ic name Cauliflower (W) Oster Blender 93.1 73.62 ± 0.40 0.23 ± 0.40 26.16 ± 0.36 Cauliflower (W) Breville Juice Extractor 35.1 77.08 ± 0.39 -5.68 ± 0.11 25.32 ± 0.16 Cauliflower (W) Omega Juicer 35.6 80.15 ± 0.71 -3.17 ± 0.04 19.76 ± 0.55 Cauliflower (Y) Oster Blender 88.2 71.61 ± 0.38 8.13 ± 0.11 47.17 ± 0.49 Cauliflower (Y) Breville Juice Extractor 27.8 74.11 ± 0.78 5.99 ± 0.38 46.92 ± 0.81 Cauliflower (Y) Omega Juicer 29.6 70.31 ± 0.65 6.11 ± 0.88 49.02 ± 1.38 Cauliflower (G) Oster Blender 92.1 60.49 ± 0.40 -9.04 ± 0.01 31.72 ± 0.80 Cauliflower (G) Breville Juice Extractor 29.8 74.93 ± 0.22 12.79 ± 0.10 39.95 ± 0.48 Cauliflower (G) Omega Juicer 31.2 74.03 ± 0.02 10.01 ± 0.10 31.23 ± 0.32 Brassica oleracea var botrytis botrytis var oleracea Brassica Kale (G) Oster Blender 94.3 33.90 ± 0.01 -6.40 ± 0.08 12.38 ± 0.19 Kale (G) Breville Juice Extractor 17.6 45.81 ± 0.95 17.21 ± 0.95 28.54 ± 2.38 Kale (G) Omega Juicer 36.8 36.41 ± 0.27 10.31 ± 0.08 11.70 ± 0.16 Kale (GO) Oster Blender 92.3 30.43 ± 0.34 -3.82 ± 0.05 4.23 ± 0.06 Kale (GO) Breville Juice Extractor 33.7 32.57 ± 0.17 -6.53 ± 0.14 7.98 ± 0.28 Kale (GO) Omega Juicer 42.8 31.14 ± 0.37 -6.53 ± 0.12 7.22 ± 0.27 Kale (RO) Oster Blender 92.7 30.78 ± 0.34 -2.87 ± 0.13 5.99 ± 0.53 Kale (RO) Breville Juice Extractor 35.9 29.16 ± 0.77 -1.39 ± 0.89 3.06 ± 1.15 Kale (RO) Omega Juicer 55.0 28.87 ± 0.82 -0.65 ± 0.33 1.43 ± 0.28 Kale (BO) Oster Blender 94.6 29.27 ± 0.18 -4.86 ± 0.05 5.01 ± 0.59

Kale (BO) Breville Juice Extractor 27.2 30.57 ± 0.08 -6.22 ± 0.07 5.49 ± 0.12 Kale (BO) Omega Juicer 52.3 29.41 ± 0.64 -5.38 ± 0.38 5.47 ± 0.56 Turnip (P) Oster Blender 93.1 59.7 ± 0.08 9.35 ± 0.12 21.49 ± 0.14 Turnip (P) Breville Juice Extractor 44.9 78.74 ± 1.13 0.28 ± 0.22 11.52 ± 1.38 Turnip (P) Omega Juicer 48.6 77.81 ± 0.38 0.34 ± 0.18 9.84 ± 1.19 Turnip (W) Oster Blender 79.4 68.44 ± 0.31 2.78 ± 0.04 25.99 ± 0.15 Turnip (W) Breville Juice Extractor 52.1 79.45 ± 0.88 -2.17 ± 0.07 12.67 ± 1.00 Turnip (W) Omega Juicer 47.0 82.85 ± 1.02 -0.77 ± 0.08 8.65 ± 0.95 Brassica oleracea var. sabellica var. oleracea Brassica Radish (R) Oster Blender 92.0 54.30 ± 0.53 17.81 ± 0.48 19.3 5± 0.32 Radish (R) Breville Juice Extractor 50.6 66.96 ± 2.52 15.69 ± 1.04 5.78 ± 0.21

Radish (R) Omega Juicer 53.3 80.19 ± 0.24 9.54 ± 0.38 2.63 ± 0.09 Radish (RO) Oster Blender 93.6 50.28 ± 1.33 31.13 ± 0.98 7.28 ± 0.76 sativus Radish (RO) Breville Juice Extractor 52.9 63.24 ± 1.05 20.08 ± 0.35 4.67 ± 0.19 Radish (RO) Omega Juicer 56.6 67.36 ± 2.17 15.86 ± 1.63 3.97 ± 0.71 Radish (G) Oster Blender 85.8 35.53 ± 0.07 25.77 ± 0.17 8.43 ± 0.09 Radish (G) Breville Juice Extractor 50.1 47.81 ± 2.53 43.74 ± 1.44 4.44 ± 0.77 Radish (G) Omega Juicer 51.5 46.55 ± 0.52 42.84 ± 0.61 4.05 ± 0.46 Radish (W) Oster Blender 87.7 72.57 ± 0.72 -1.74 ± 0.01 17.17 ± 0.27 Radish (W) Breville Juice Extractor 56.0 84.14 ± 1.58 -0.42 ± 0.06 3.85 ± 0.15 Radish (W) Omega Juicer 63.2 85.46 ± 0.77 -0.17 ± 0.09 3.53 ± 0.71 Raphanus raphanistrum subsp. subsp. raphanistrum Raphanus

117 Table A-1. Continued Scientif Name (color) Processing Yield (%) L* a* b* ic name Beet (R) Oster Blender 92.0 52.55 ± 0.21 7.74 ± 0.16 29.46±0.05 Beet (R) Breville Juice Extractor 45.4 71.31 ± 0.72 -4.11 ± 0.52 44.58±1.20

Beet (R) Omega Juicer 53.7 75.81 ± 0.58 -5.90 ± 0.14 38.72±0.87 Beet (RO) Oster Blender 93.6 48.40 ± 0.45 21.92 ± 0.27 31.85±0.33 ulgaris

v Beet (RO) Breville Juice Extractor 37.6 60.45 ± 0.82 32.03 ± 0.94 47.07±1.98 Beet (RO) Omega Juicer 39.4 62.00 ± 0.72 29.94 ± 1.18 50.01±1.06 Beta Beet (G) Oster Blender 91.4 32.47 ± 0.18 2.03 ± 0.01 12.72 ± 0.09 Beet (G) Breville Juice Extractor 37.8 34.25 ± 1.16 6.72 ± 0.63 17.11 ± 1.77 Baby Carrot (O) Omega Juicer 44.3 62.00 ± 0.72 29.94 ± 1.18 50.01±1.06 Baby Carrot (P) Oster Blender 88.8 29.20 ± 0.07 5.19 ± 0.16 2.59±0.14 Baby Carrot (P) Breville Juice Extractor 38.1 25.75 ± 0.98 6.45 ± 0.17 -2.20±0.34

Baby Carrot (P) Omega Juicer 37.9 24.83 ± 1.40 5.42 ± 0.63 -2.10±0.17 Baby Carrot (Y) Oster Blender 76.9 46.09 ± 0.32 8.95 ± 0.14 30.45±0.28 Baby Carrot (Y) Breville Juice Extractor 43.9 62.44 ± 1.66 9.32 ± 0.34 52.19±0.24 Baby Carrot (Y) Omega Juicer 33.7 59.62 ± 0.67 10.47 ± 0.31 51.79±1.27 Baby Carrot (W) Oster Blender 91.5 52.55 ± 0.21 7.74 ± 0.16 29.46±0.05 Baby Carrot (W) Breville Juice Extractor 52.0 71.31 ± 0.72 -4.11 ± 0.52 44.58±1.20 Baby Carrot (W) Omega Juicer 40.4 75.81 ± 0.58 -5.90 ± 0.14 38.72±0.87 Daucus carota subsp. sativus subsp. carota Daucus Color: W: white, Y: yellow, G: green, GO: green organic, BO: black organic, P: purple, WB: white baby, R: red, RO: red organic; G: golden, GO: golden organic. L*: brightness; a*: redness; b*yellowness; C*: Chroma; h: hue angle.

118 Table A-2. Thirty thermal, cold, and high-pressure processed juices categorized as kale (K1–K10), beet (B1–B10), and melon (M1–10) juices* Code Juice Name (Brand) Processe Ingredients Present in the Juice Volume Price/B Price/ d (mL) ottle ($) Oz by ($) K1 Green Machine (Naked) Thermal Kale, apple and pineapple juice, mango, kiwi and banana puree, spirulina, 450 2.68 0.176 natural flavors, alfalfa, broccoli, spinach, barley grass, wheatgrass, parsley, ginger root, odorless garlic K2 Healthy Greens (V8) Thermal Spinach, kale, cucumber, celery, romaine lettuce, green bell pepper, 1360 2.87 0.062 pineapple, apples, yellow carrots, huito juice, watermelon juice, vitamin C K3 Grown Vegetable Juice Cold Tomatoes, carrots, celery, kale, spinach, lime juice, beets, parsley, onions, 354 3.49 0.291 (Estate) coriander, watercress, basil, sea salt, garlic, oregano, thyme, pepper K4 Green Delight Organic (Suja) Cold Kale, organic apple, lemon, spinach juice, organic banana mango puree, 354 2.98 0.248 organic spirulina, chlorella, barley grass powder K5 Uber Greens Organic (Suja) Cold Organic cucumber, celery, grapefruit, green chard, leaf lettuce, lemon, 354 2.98 0.248 kale, spinach, parsley juice, Tea (peppermint, spearmint) K6 Radiant Probiotic Organic Cold Kale, celery, cucumber, fennel, apple, collard greens, lemon, spinach 354 2.98 0.248 (Suja) juice, ground cayenne pepper, Tea (peppermint, spearmint), probiotic Bacillus coagulans K7 Organic Kale (1915) Cold Kale, organic apple, romaine lettuce, cucumber, spinach, lemon juice 354 3.99 0.333

K8 Organic Emerald greens Cold Kale, organic cucumber, celery, lemon, ginger, lime, spinach juice 325 3.99 0.363 (Evolution) K9 Organic Green Devotion Cold Kale, organic cucumber, celery, spinach, romaine lettuce, lemon, parsley 325 3.99 0.363 (Evolution) juice K10 Super Fruit Greens Cold Kale juice, organic orange, apple, pineapple, cucumber, spinach, romaine 325 3.99 0.363 (Evolution) lettuce, spirulina, chlorella

119 Table A-2. Continued Code Juice Name (Brand) Processed Ingredients Present in the Juice Volume Price Price/Oz by (mL) /Bottl ($) e ($) B1 Strawberry Banana (V8) Thermal Beet, apple, carrot, sweet potato, strawberry, banana, grapes, additives (citric 1360 2.87 0.062 acid, beta carotene, vitamin C, sucralose) B2 Original 100% Vegetables Thermal Beet, tomato, carrot, celery, beets, parsley, lettuce, watercress, additives 1360 2.44 0.062 juice (V8) (salt, vitamin C, natural flavoring, citric acid) B3 Original 100% Vegetables Thermal Beets, tomato, carrot, celery, parsley, lettuce, watercress, additives 340 0.88 0.077 Juice Low Sodium (V8) (potassium chloride, salt, vitamin C, natural flavoring, citric acid) B4 Spicy Hot 100% Vegetables Thermal Beets, tomato, carrot, celery, parsley, lettuce, watercress, spinach, additives 1360 2.44 0.053 Juice (V8) (salt, vitamin C, natural flavoring, citric acid) B5 Beet Juice (Biotta) Thermal Organic beetroot juice (lacto fermented) 500 5.49 0.325

B6 Organic Pure Beet Thermal Organic beetroot juice,organic lemon juice (1%) 946 4.95 0.155 (Lakewood) B7 Farms Daily Roots Thermal Beet, purple carrot, cucumber, purple sweet potato, lemon, monk fruit juice 450 2.97 0.195 (Bolthouse) from concentrate, red bell pepper puree, parsley, lettuce, watercress, spinach, juice, vitamin (C, A, B6, B9, B12,) zinc, iron, magnesium, potassium, sea salt, natural flavor B8 Very Veggie (R.W. Knudsen) Thermal Water, tomato paste, organic carrot and celery juice, organic grain vinegar, 946 2.49 0.078 organic lemon juice concentrate, organic parsley and beet green, bell peppers, lettuce, watercress and spinach juice B9 Organic Beet (1915) Cold Organic beet, carrot, orange, lemon juice 354 3.99 0.333 B10 Organic Cucum Berry (Simple Cold Organic cucumber, apple, beet, lemon juice, organic strawberry, banana, 354 3.99 0.333 Truth) puree

120 Table A-2. Continued Code Juice Name (Brand) Processed Ingredients Present in the Juice Volume Price/ Price/O by (mL) Bottle z ($) ($) M1 Synergy Watermelon Wonder (GTS) Thermal Organic kombucha culture, black tea, green tea, kiwi juice, fresh- 473 2.97 0.186 pressed watermelon and lime juice, cherry juice M2 Antioxidant Infusion (Bai) Thermal Water, erythritol, stevia leaf extract, natural flavors, citric acid, 530 1.50 0.083 watermelon juice concentrate, vegetables juice, coffee fruit extract, white tea extract, malic acid, vitamin C, sodium citrate M3 Watermelon (Tropicana) Thermal Water, sugar, watermelon, grapefruit, and apple juice concentrate, 1750 2.00 0.034 citric acid, natural flavors M4 MLN Watermelon (WTR) Cold Watermelon flesh and rind, organic lemon, ginger juice, organic 354 2.98 0.248 ginger extract M5 Sugar Kiss Juice Raspberry (Kiss Cold Melon, raspberry, lemon 354 3.99 0.333 Melon) M6 Summer Kiss Juice (Kiss Melon) Cold Melon, ginger, mint 354 3.99 0.333

M7 Honey Kiss Juice (Kiss Melon) Cold Melon, pear, lemon 354 3.99 0.333

M8 Sugar Kiss Juice Apple (Kiss Melon) Cold Melon, apple, lemon 354 3.99 0.333 M9 Melon Garden Greens Juice (Kiss Cold Melon, apple, spinach, kale, romaine lettuce, celery 354 3.99 0.333 Melon) M10 Melon Beet Boost Juice (Kiss Cold Melon, beet, ginger, mint, cucumber 354 3.99 0.333 Melon) * The above juices were categorized based on assumption that those juices may contain the major amount of respective juices (kale, beet, melon). However, labels do not state the composition of each juice.

121 Table A-3. Color attributes, brix, and pH of tested juices Juice Type** No. Name of juice L a* b* C* Hue Brix pH Kale K1 Green Machine (Naked) Juice 41.78 -5.33 13.21 14.24 -1.19 14.47 4.27 K2 Healthy Greens (V8) 48.95 0.61 30.38 30.38 1.55 7.78 4.32 K3 Grown Vegetable Juice (Estate) 38.28 9.64 13.27 16.40 0.94 6.00 4.41 K4 Green Delight Organic (Suja) 44.59 -1.26 23.09 23.12 -1.52 13.17 4.00 K5 Uber Greens Organic (Suja) 46.04 -3.39 21.72 21.99 -1.42 5.37 4.53 K6 Radiant Probiotic Organic (Suja) 46.98 -6.81 25.17 26.08 -1.31 4.83 4.63 K7 Organic Kale (1915) 48.95 -1.32 30.41 30.44 -1.53 9.55 3.91 K8 Organic Emerald greens (Evolution) 41.49 -9.14 19.98 21.97 -1.14 6.50 4.65 K9 Organic Green Devotion (Evolution) 45.23 -9.61 22.16 24.15 -1.16 4.85 4.65 K10 Super Fruit Greens (Evolution) 35.92 -5.44 9.74 11.15 -1.06 13.23 4.39

Beet B1 Strawberry Banana (V8) Juice 44.79 39.67 28.55 48.87 0.62 11.98 4.01 B2 Original 100% Vegetables juice (V8) 37.88 24.95 16.80 30.08 0.59 6.53 4.36 B3 Original 100% Vegetables Juice Low Sodium (V8) 39.13 25.77 19.27 32.17 0.64 6.47 4.52 B4 Spicy Hot 100% Vegetables Juice (V8) 38.42 28.20 20.57 34.90 0.63 6.63 4.39 B5 Beet Juice (Biotta) 24.64 15.99 0.36 16.00 0.02 12.15 4.74 B6 Organic Pure Beet (Lakewood) 26.52 17.72 1.19 17.75 0.07 10.20 4.62 B7 Farms Daily Roots (Bolthouse) 39.13 25.77 19.27 32.17 0.64 10.35 4.59 B8 Very Veggie (R.W. Knudsen) 38.10 27.92 16.20 32.28 0.53 6.25 4.49 B9 Organic Beet (1915) 24.92 4.74 -1.30 4.92 -0.27 9.13 4.46 B10 Organic Cucum Berry (Simple Truth) 50.14 13.40 14.80 19.97 0.84 10.40 4.16

Melon M1 Synergy Watermelon Wonder Juice (GTS) 59.41 20.78 20.06 28.88 0.77 6.13 3.47 M2 Antioxidant Infusion (Bai) 73.95 28.42 -0.63 28.43 -0.02 3.20 3.25 M3 Watermelon (Tropicana) 78.19 10.02 9.43 13.75 0.76 10.03 3.38 M4 MLN Watermelon (WTR) 48.27 36.12 24.59 43.69 0.60 8.93 4.70 M5 Sugar Kiss Juice Raspberry (Kiss Melon) 67.71 10.99 28.61 30.65 1.20 14.07 4.67 M6 Summer Kiss Juice (Kiss Melon) 74.62 -4.89 26.08 26.53 -1.39 11.88 4.95 M7 Honey Kiss Juice (Kiss Melon) 75.69 4.93 29.07 29.49 1.40 14.15 4.40 M8 Sugar Kiss Juice Apple (Kiss Melon) 71.69 6.35 30.67 31.32 1.37 11.33 4.86 M9 Melon Garden Greens Juice (Kiss Melon) 49.83 -4.36 29.74 30.06 -1.43 11.90 4.80 M10 Melon Beet Boost Juice (Kiss Melon) 30.11 32.35 6.47 32.99 0.20 11.57 4.84

**Categorized based on assumption that those juices may contain the major amount of respective juices (kale, beet, melon). However, labels do not state the composition of each juice.

122 Table A-4. Solvents used for extraction of betalains. Solvent Combination Abbreviation

Water S1

Water: ascorbic acid = (98:2) S2

Water: formic acid = (98:2) S3

Water: acetic acid = (98:2) S4

Ethanol S5

Ethanol: water = (70:30) S6

Ethanol: water: ascorbic acid = (40:58:2) S7

Ethanol: water = (30:70) S8

Ethanol: water: ascorbic acid = (30:68:2) S9

Ethanol: water: formic acid = (30:68:2) S10

Ethanol: water: acetic acid = (30:68:2) S11

Ethanol: water: formic acid = (18:80:2) S12

Methanol S13

Methanol: water = (70:30) S14

Methanol: water: ascorbic acid = (40: 58: 2) S15

Methanol: water = (30:70) S16

Methanol: water: ascorbic acid = (30:68:2) S17

Methanol: water: formic acid = (30:68:2) S18

Methanol: water: acetic acid = (30:68:2) S19

Methanol: water: formic acid = (18:80:2) S20

123 Table A-5. Mineral contents in conventional and organic beets. Red beets Golden beets

Minerals Conventional Organic Conventional Organic N 2.99 ± 0.12bc 2.78 ± 0.01c 3.82 ± 0.10a 3.09 ± 0.10b

P 2327.30 ± 56.25b 2102.77 ± 11.85c 3287.94 ± 83.62a 3423.79 ± 211.35a

K 27816.20 ± 771.65c 32700.80 ± 648.88a 30458.7 ± 388.57b 28175.00 ± 1255.13c

Ca 1597.72 ± 43.17a 1716.42 ± 84.39a 1648.74 ± 74.94a 795.19 ± 67.81b

Mg 2448.46 ± 56.62a 2096.09 ± 95.04b 2085.55 ± 22.44b 1492.88 ± 4.90c

Na 12862.00 ± 449.32c 9998.01 ± 96.41d 20903.60 ± 720.57a 18155.40 ± 162.36b

Zn 26.02 ± 3.31a 26.09 ± 1.60a 25.21 ± 0.67a 21.46 ± 0.87b

Fe 55.07 ± 3.30a 47.99 ± 2.98b 60.57 ± 4.85a 29.93 ± 2.86c

Cu 7.00 ± 0.37c 29.30 ± 4.59a 14.48 ± 0.16b 10.40 ± 0.31bc

Mn 32.98 ± 0.63b 28.74 ± 0.87c 38.95 ± 0.61a 22.68 ± 0.85d

S 1235.59 ± 37.14b 1537.87 ± 33.53a 1450.92 ± 10.13a 1202.89 ± 82.66b

B 21.15 ± 0.51b 18.24 ± 0.14c 22.93 ± 0.48a 16.82 ± 0.23d

Different letters followed by values represented significant difference. Nitrogen was expressed as %, other minerals are mg/kg.

124 Table A-6. Levels of total betalains (betanin, isobetanin, valine-betaxanthin, and vulgaxanthin I) in extracts from conventional and organic beets.

Red Beets Golden Beets Solvent Code Conventional Organic Conventional Organic Water S1 2990.1 524.5 347.6 0.0 Water: ascorbic acid = (98:2) S2 1138.4 5254.6 495.8 289.4 Water: formic acid = (98:2) S3 1969.8 3991.5 0.0 30.8 Water: acetic acid = (98:2) S4 4036.9 3859.7 77.9 9.6 Ethanol S5 1168.1 4307.4 253.1 158.6 Ethanol: water = (70:30) S6 4038.9 5056.0 526.5 855.0 Ethanol: water: ascorbic acid = (40:58:2) S7 1932.4 5760.3 394.5 395.9 Ethanol: water = (30:70) S8 3517.3 5646.0 485.5 339.0 Ethanol: water: ascorbic acid = (30:68:2) S9 2219.4 4002.8 522.0 588.8 Ethanol: water: formic acid = (30:68:2) S10 3001.0 4069.0 72.6 68.9 Ethanol: water: acetic acid = (30:68:2) S11 3678.7 2450.0 0.0 17.4 Ethanol: water: formic acid = (18:80:2) S12 1567.3 4676.8 108.1 156.7 Methanol S13 3833.8 12485.6 676.7 730.8 Methanol: water = (70:30) S14 2073.8 4165.9 452.9 443.0 Methanol: water: ascorbic acid = (40: 58: 2) S15 1555.5 7930.8 780.5 395.9 Methanol: water = (30:70) S16 1904.6 5544.0 243.2 617.5 Methanol: water: ascorbic acid = (30:68:2) S17 2816.3 3223.6 816.4 755.8 Methanol: water: formic acid = (30:68:2) S18 3409.6 4876.6 140.6 92.8 Methanol: water: acetic acid = (30:68:2) S19 2967.9 6418.4 0.0 35.7 Methanol: water: formic acid = (18:80:2) S20 2174.8 11923.9 0.0 1316.2 Values were expressed as µg/g.

125 APPENDIX B

FIGURES FOR ADDITIONAL INFORMATION

A) Kale Samples B) Beet Samples

C) Kale Samples D) Beet Samples

K-3-sinapoyl-diglucoside-7-diglucoside Glutamine-betaxanthin K-3-O-(caffeoyl)-sophoroside-7-O-glucoside Dopamine-betaxanthin K-3-feruloyl-diglucoside-7-diglucoside Isoleucine-isobetaxanthin K3-hydroxyferuloyl-diglucoside-7-diglucoside Neobetanin K-3-hydroxyferuloyl-diglucoside-7-glucoside Proline-betaxanthin L-tryptophan Isoleucine-betaxanthin K-3-O-diglucoside-7-glucoside Betanidin K-3-(feruoyl)-sophoroside-7-O-glucoside 15-Decarboxy-2,3-dehydro-neobetanin Q-3-sophoroside-7-diglucoside 17-Decarboxy-2,3-dehydro-neobetanin K-3-O-(caffeoyl)-sophoroside-7-O-diglucoside Miraxanthin III K-3-sinapoyl-diglucoside-7-glucoside Leucine-isobetaxanthin Q-3-diglucoside-7-glucoside Methionine-betaxanthin Cyanidin 6´-feruloyl-betanin K-3-O-(caffeoyl)-sophoroside-7-O-glucoside (isomer) Betanin 4-P-Coumaroylquinic acid 17-Decarboxy-neobetanin Q-3-O-(feruloyl)-sophoroside L-tryptophan Q-3-sinapoyl-diglucoside-7-diglucoside 2-Decarboxy-2,3-dehydro-neobetanin Ferulic acid derivative Valine-betaxanthin 5-P-Coumaroylquinic acid Phenylalanine-isobetaxanthin Kaempferol-3-O-sophoroside (isomer) Glutamic acid-betaxanthin

Figure B-1. Multivariate data analysis revealed the influence of processing techniques on metabolites. Principal component analysis (PCA) of (A) kale juices and (B) juices. Variable importance of projection (VIP) scores presents a overview of abundance of metabolites, with the degree of color saturation indicates the level of metabolites.

126 Intens. Intens. [M+H]+ +MS, 2.2-2.7min #263-327 [M+H]++MS, 8.0-8.1min Intens. +MS, 1.8-2.0min #211-245 x104 x104 [M+H]+ 307.0953 789.2230 288.1999 Q-3-diglucoside-7-glucoside Epigallocatechin 1.0 6000 2 423.0953 84.9585 Cyanidin 84.9612 4000 161.0100 1 0.5 346.0508 84.9626 203.0594 2000 261.0551 399.2647 0.0 04 4 0 x10 +bbCID MS, 49.0-140.0eV, 2.0-2.9min #236-348 x10 +bbCID MS, 49.0-140.0eV, 8.0-8.1min x104 +bbCID MS, 49.0-140.0eV, 1.7-2.0min #208-240 4 1.00 365.1182 303.0555 1.00 305.1171 0.75 3 0.75 0.50 2 0.50 84.9626 203.0591 527.1768 0.25 1 84.9612 152.0547 541.1633 811.2051 0.25 84.9584 365.1010 0.00 0 0.00 100 200 300 400 500 600m/z 100 200 300 400 500 600 700 800 900 m/z 100 150 200 250 300 350 m/z

Intens. Intens. +MS, 8.1-8.2min #975-981 +MS, 8.3-8.4min #993-1005 Intens. +MS, 8.4-8.6min #1009-1029 4 4 x10 x10 x104 305.1626 495.1174 K-3-O-diglucoside-7-glucoside 773.2263 1.00 Q-3-sophoroside-7-diglucoside 2.0 [M+H]+ [M+H]+ 0.75 Q-3-diglucoside-7-glucoside (isomer) 2 386.0572 951.2772 1.5 415.0968 84.9612162.0100 0.50 + 1.0 [M+H] 1 773.2269 0.25 501.1692 789.2238 0.5 84.9609 627.1675 0.00 05 0.0 x104 +bbCID MS, 49.0-140.0eV, 8.1-8.2min #978-988 x10 +bbCID MS, 49.0-140.0eV, 8.3-8.4min #992-1006 x105 +bbCID MS, 49.0-140.0eV, 8.4-8.6min #1010-1030 1.0 1.0 303.0553 303.0554 287.0600 0.8 0.8 1.0 84.9611 0.6 0.6

0.5 0.4 0.4 478.1776 541.1622 0.2 0.2 811.2064 571.1733 973.2576 85.0296 795.2083 0.0 0.0 0.0 100 200 300 400 500 600 700 800 900 m/z 100 200 300 400 500 600 700 800 900 m/z 100 200 300 400 500 600 700 800 900 m/z

Intens. +MS, 8.9-9.0min #1071-1077 Intens. +MS, 8.6-8.8min #1035-1057 Intens. 4 K-3-O-(caffeoyl)-sophoroside-7-O-glucoside x104 K-3-hydroxyferuloyl-diglucoside-7-glucoside + +MS, 9.0-9.2min #1085-1101 x10 531.1364 [M+H] x104 487.1186 965.2721 583.1436 + [M+H] 1.0 3 K-3-hydroxyferuloyl- 3 935.2800 diglucoside [M+H]+ 2 2 0.5 308.1176 -7-diglucoside 1127.3283 1 84.9609 294.0725 1 773.2248 349.1896 0.0 965.2792 05 x104 +bbCID MS, 49.0-140.0eV, 8.9-9.0min #1070-1080 0 x10 +bbCID MS, 49.0-140.0eV, 8.6-8.8min #1036-1058 x104 +bbCID MS, 49.0-140.0eV, 9.0-9.1min #1084-1096 193.0525 2.0 287.0596 8 287.0606 3 1.5 6 2 1.0 4 492.1559 1 355.1077 0.5 2 85.0295 571.1726 987.2530 539.1476 1149.3112 0.0 0 100 200 300 400 500 600 700 800 900 m/z 0 100 200 300 400 500 600 700 800 900 m/z 200 400 600 800 1000 m/z

Intens. +MS, 9.2-9.2min #1105-1111 Intens. +MS, 9.3-9.4min #1115-1125 Intens. +MS, 9.4-9.5min #1127-1139 x104 x104 x104 409.1910 568.1387 K-3-O-(caffeoyl)-sophoroside- 598.1514 K-3-hydroxyferuloyl-diglucoside-7 1.5 Q-3-sinapoyl-diglucoside- 1.0 2 207.0693 222.0871 7-O-diglucoside -diglucoside 679.1786 + 7-diglucoside 84.9612 1.0 [M+H] 1157.3435 1097.3190 409.1198 + 0.5 1 [M+H] 516.1309 935.2632 [M+H]+ 0.5 995.2880 791.2177 1127.3303 0.0 0.0 0 x104 +bbCID MS, 49.0-140.0eV, 9.2-9.3min #1100-1112 x104 +bbCID MS, 49.0-140.0eV, 9.3-9.3min #1116-1122 x104 +bbCID MS, 49.0-140.0eV, 9.4-9.5min #1126-1142 303.0569 409.1910 6 163.0419 6 4 207.0696 287.0606 4 4 2 287.0603 409.1200 2 531.1814 2 715.2216 1119.3010 1179.3239 0 0 0 200 400 600 800 1000 m/z 200 400 600 800 1000 m/z 200 400 600 800 1000 m/z

Intens. +MS, 9.5-9.6min #1145-1155 Intens. +MS, 9.8-9.9min #1173-1191 Intens. 4 4 +MS, 10.0-10.0min #1197-1201 x10 x10 x104 583.1472 590.1567 K-3-sinapoyl-diglucoside- 656.1822 K-3-sinapoyl-diglucoside-7- + Q-3-O-(feruloyl)-sophoroside 4 7-diglucoside [M+H] 2.0 1.5 glucoside 1141.3535 1.5 1.0 1127.3362 409.1939 2 1.0 1273.4045 207.1425 [M+H]+ 979.2979 362.1243 [M+H]+ 0.5 369.1279 144.0009 965.2792 162.0114 0.5 979.3011 0 0.04 5 0.0 x10 +bbCID MS, 49.0-140.0eV, 9.5-9.7min #1146-1160 x10 +bbCID MS, 49.0-140.0eV, 9.8-9.9min #1174-1192 x104 +bbCID MS, 49.0-140.0eV, 9.9-10.0min #1194-1202 177.0586 1.5 287.0631 287.0637 4 303.0572 1.0 4 369.1283 2 2 0.5 501.1760 707.2755 1163.3350 1149.3163 1001.2832 1295.3839 0 0.0 0 200 400 600 800 1000 m/z 200 400 600 800 1000 m/z 200 400 600 800 1000 1200 1400 m/z

Intens. +MS, 10.0-10.1min #1207-1217 Intens. +MS, 10.2-10.2min #1221-1229 Intens. +MS, 11.2-11.3min #1347-1353 4 4 x10 K-3-feruloyl-diglucoside-7-diglucoside x10 [M+H]+ 575.1548 200.0147 949.2491 4000 611.1536 + 4 1.5 [M+H] K-3-O-sophoroside + K-3-(feruoyl)-sophoroside-7- 3000 [M+H] 329.1532 1.0 1111.3503 O-glucoside 2000 162.0049 255.1174 2 339.1035 1111.3006 0.5 449.1041 949.2919 449.1029 1000 144.0013 339.1190 773.2388 773.2048 0 0.0 0 x105 +bbCID MS, 49.0-140.0eV, 10.0-10.1min #1204-1216 x104 +bbCID MS, 49.0-140.0eV, 10.2-10.2min #1220-1230 x104 +bbCID MS, 49.0-140.0eV, 11.2-11.3min #1342-1358 2.0 177.0604 287.0518 287.0516 1.5 1.0 4 1.0 971.2310 0.5 2 523.1364 633.1362 0.5 329.1533 84.9583 462.1682 707.2761 971.2738 1133.3315 809.1805 177.0522 553.1468 0.0 0 0.0 200 400 600 800 1000 m/z 200 400 600 800 1000 m/z 100 200 300 400 500 600 m/z Figure B-2. Protonated mass spectra of phytochemical compounds of retention time 1-11min in extracts of Brassica vegetables.

127 Intens. +MS, 11.2-11.3min #1347-1353 Intens. +MS, 11.9-12.1min #1429-1449 Intens. +MS, 13.9-14.0min #1665-1679 4 + x10 4000 [M+H] 611.1536 [M+H]+ 611.1540 225.1457 K-3-O-sophoroside 1.00 K-3-O-sophoroside (isomer) 6000 3000 K-3-O-glucoside 329.1532 0.75 287.0518 4000 + 162.0049 255.1174 [M+H] 2000 0.50 185.1126 449.1029 449.1041 2000 1000 0.25 449.1032 844.2898 0 0.00 0 x104 +bbCID MS, 49.0-140.0eV, 11.2-11.3min #1342-1358 x104 +bbCID MS, 49.0-140.0eV, 11.9-12.1min #1428-1448 +bbCID MS, 49.0-140.0eV, 13.9-14.0min #1666-1680 2.0 8000 287.0516 287.0520 287.0521 3 633.1363 1.5 6000 2 471.0852 1.0 4000 347.0913 633.1362 1 0.5 329.1533 2000 844.2913 84.9583 177.0522 462.1682 553.1468 84.9585 177.0522 427.1892 0.0 0 0 100 200 300 400 500 600 m/z 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 800 900 m/z

Intens. +MS, 12.5-12.6min #1501-1511 Intens. +MS, 12.8-12.9min #1533-1545 Intens. +MS, 13.4-13.5min #1605-1617 2000 162.0053 369.1137 339.1036 4000 1500 K-3-O-sophoroside-7-glucoside K-3-O-(sinapoyl)-sophoroside 4000 K-3-O-(feruloyl)-sophoroside 587.3338 3000 [M+H]+ 213.1069 817.2091 + 1000 162.0050 [M+H] + 2000 2000 162.0054 427.1890 531.1660 [M+H] 787.1984 500 457.6006 681.2869 773.1864 1000 442.5971 0 0 0 x104 +bbCID MS, 49.0-140.0eV, 12.5-12.6min #1502-1514 x104 +bbCID MS, 49.0-140.0eV, 12.8-12.9min #1534-1546 x104 +bbCID MS, 49.0-140.0eV, 13.4-13.4min #1608-1616 287.0515 287.0515 0.8 287.0520 1.00 1.00 681.2864 177.0522 0.6 207.0623 0.75 0.75 839.1906 523.1366 0.4 0.50 553.1464 0.50 207.0627 91.0529 0.2 427.1896 545.2512 647.2455 0.25 0.25 0.0 0.00 0.00 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 800 900 m/z 100 200 300 400 500 600 700 m/z

Intens. +MS, 15.3-15.5min #1843-1863 Intens. +MS, 16.7-16.7min #2001-2005 x104 382.1007 162.0053 501.1717 Trisinapoyl-diglucoside 2 1-Sinapoyl-2-feruloyl- 2000 737.2200 162.0106 diglucoside [M+H]+ 1 1000 [M+H]+ 983.2661 747.2272 0 0 x104 +bbCID MS, 49.0-140.0eV, 15.4-15.5min #1846-1866 +bbCID MS, 49.0-140.0eV, 16.6-16.7min #2000-2010 3 177.0581 207.0624 4000 2 84.9613 287.0513 759.2019 2000 1 523.1538 747.2273 369.1138 523.1365 339.1149 0 0 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 800 900 m/z Figure B-3. Protonated mass spectra of phytochemical compounds of retention time 11-16min in extracts of Brassica vegetables. .

128 Intens. Intens. +MS, 1.7-2.1min #199-253 Intens. + +MS, 1.0-1.0min #115-125 [M+H]+ + +MS, 2.4-2.5min #285-303 x105 [M+H] x106 x104 [M+H] 326.0990 340.1155 268.1094 3 AsparagineAsparagine-betaxanthin-betaxanthin 1.0 Glutamine-betaxanthin Glutamine-isobetaxanthin 2 215.0165 2 130.0500 0.5 84.9616 340.1206 1 1 161.0151 184.5823 0 0.0 0 x105 +bbCID MS, 49.0-140.0eV, 0.9-1.2min #104-138 x105 +bbCID MS, 49.0-140.0eV, 1.7-2.0min #204-246 x104 +bbCID MS, 49.0-140.0eV, 2.3-2.5min #272-298 1.25 3 340.1148 84.9616 365.1062 365.1126 1.00 1.00 2 0.75 0.75 136.0644 0.50 137.0599 0.50 1 0.25 527.1589 166.0498 0.25 203.0562 268.1094 203.0522 0.00 0 0.00 100 200 300 400 500 600m/z 100 200 300 400 500 600m/z 50 100 150 200 250 300 350 400 450 m/z

Intens. Intens. Intens. + +MS, 3.1-3.3min #367-395 [M+H]+ +MS, 3.3-3.6min #399-429 [M+H]+ +MS, 3.7-3.9min #443-463 x104 [M+H] x105 x105 313.1033 166.0863 341.0987 1.00 2.0 0.6 Threonine-betaxanthin 0.75 1.5 120.0808 Phenylalanine Glutamic acid-betaxanthin 84.9597 0.4 0.50 1.0 191.0588 0.5 0.2 0.25 84.9598 228.0500 84.9597 191.0588 0.0 0.0 0.00 x104 +bbCID MS, 49.0-140.0eV, 3.0-3.2min #358-380 x104 +bbCID MS, 49.0-140.0eV, 3.3-3.5min #392-422 x104 +bbCID MS, 49.0-140.0eV, 3.7-3.9min #442-464 365.1058 1.00 84.9597 365.1057 1.5 164.0703 1.0 84.9597 103.0541 0.75 152.0567 84.9598 1.0 0.50 0.5 203.0524 0.25 0.5 203.0521 245.0630 0.0 0.00 0.0 50 100 150 200 250 300 350 400 450 500 m/z 50 100 150 200 250 m/z 50 100 150 200 250 300 350 400 450 500m/z

Intens. Intens. Intens. +MS, 4.0-4.1min #483-487 + +MS, 4.3-4.4min #519-525 + +MS, 4.4-4.6min #533-547 x104 x104 [M+H] x104 [M+H] 84.9619 161.0153 283.0928 345.1084 1.00 3 Glutamic acid-isobetaxanthin 6 Alanine-betaxanthin 17-Decarboxy-betanidin 0.75 [M+H]+ 2 4 0.50 341.1056 252.0789 438.1325 84.9597 1 191.0588 463.1714 0.25 2 156.0653 84.9598 358.1135 538.1270 0.00 0 0 x104 +bbCID MS, 49.0-140.0eV, 4.0-4.0min #482-486 x104 +bbCID MS, 49.0-140.0eV, 4.3-4.4min #514-528 x104 +bbCID MS, 49.0-140.0eV, 4.4-4.6min #532-552 1.5 84.9620 438.1326 84.9598 365.1058 3 164.0705 1.0 1.0 2

365.1133 0.5 164.0704 84.9598 365.1056 0.5 1 283.0922 276.0769 455.0236 485.1529 0.0 0.0 0 50 100 150 200 250 300 350 400 450 m/z 100 200 300 400 500 m/z 100 200 300 400 500 m/z

Intens. Intens. Intens. +MS, 4.5-4.6min #545-553 +MS, 4.5-4.6min #541-547 + +MS, 4.9-5.0min #585-595 x104 + x104 x105 [M+H] 84.9617 [M+H] 84.95982,17-Bidecarboxy-betnidin/isobetanidin 297.1087 [M+H]+ 2.0 311.1302 1.00 191.0587 1.0 191.0629 Valine-isobetaxanthin 463.1715 ℽ-Aminobutyric acid-betaxanthin 0.75 283.0929 1.5

0.5 0.50 1.0 261.1421 369.3616 0.25 0.5 404.1264 529.1668 84.9598 143.0013 191.0586 251.1021 0.0 0.00 0.0 x104 +bbCID MS, 49.0-140.0eV, 4.5-4.6min #542-556 x104 +bbCID MS, 49.0-140.0eV, 4.5-4.6min #542-556 x104 +bbCID MS, 49.0-140.0eV, 4.9-4.9min #586-592 1.5 1.25 84.9618 84.9599 297.1082 84.9597 1.00 1.0 365.1056 1.0 0.75 365.1061 0.50 164.0708 0.5 365.1131 0.5 242.1002 0.25 485.1530 205.0966 180.0668 265.0968 0.0 0.00 0.0 50 100 150 200 250 300 350 400 450 m/z 100 200 300 400 500 600 m/z 100 150 200 250 300 350 400 m/z

Intens. Intens. Intens. +MS,+ 5.0-5.1min #597-609 +MS, 5.4-5.5min #649-657 +MS, 5.5-5.6min #659-675 x105 [M+H] x105 x105 309.1084 188.0707 212.0550 0.8 2.0 [M+H]+ Proline-betaxanthin 205.0974 1.0 0.6 1.5 L-Tryptophan 345.1083 319.1361 Prebetanin 0.4 1.0 0.5 + 0.2 84.9596 0.5 391.1130 [M+H] 161.0119 84.9596 84.9595 631.1067 0.0 0.0 0.0 x104 +bbCID MS, 49.0-140.0eV, 5.0-5.1min #600-608 x104 +bbCID MS, 49.0-140.0eV, 5.4-5.5min #650-660 x104 +bbCID MS, 49.0-140.0eV, 5.5-5.6min #664-674 3 353.0844 115.0543 2.0 115.0539 6 91.0543 2 1.5 4 389.0973 84.9598 1.0 1 2 150.0546 188.0702 227.0788 0.5 496.1417 0 0 0.0 50 100 150 200 250 300 350 400 m/z 50 100 150 200 250 m/z 100 200 300 400 500 600 700 m/z

Intens. Intens. Intens. +MS, 5.6-5.9min #677-705 +MS, 6.1-6.2min #727-743 [M+H]++MS, 6.3-6.4min #751-767 x106 x105 x105 551.1532 551.1523 347.1247 + 4 + [M+H] [M+H] 4 1.0 Betanin 3 Isobetanin Dopamine-betaxanthin 2 2 0.5 1 388.1241 353.0849 462.1607 0.0 0 0 x106 +bbCID MS, 49.0-140.0eV, 5.6-5.9min #676-704 x105 +bbCID MS, 49.0-140.0eV, 6.1-6.2min #728-742 x105 +bbCID MS, 49.0-140.0eV, 6.3-6.4min #752-764 389.0997 389.0990 91.0544 1.00 4 1.00

0.75 3 0.75 347.1242 0.50 2 0.50 551.1521 137.0601 551.1520 389.0983 0.25 150.0549 343.0930 1 0.25 150.0547 255.1123 0.00 0 0.00 100 200 300 400 500 600 m/z 100 200 300 400 500 600 m/z 50 100 150 200 250 300 350 400 450 m/z

Figure B-4. Protonated mass spectra of phytochemical compounds of retention time 1-6min in beet extracts.

129 Intens. Intens. Intens. + +MS, 6.3-6.5min #759-779 + +MS, 6.4-6.5min #769-785 + +MS, 6.7-6.8min #801-811 x104 [M+H] x104 [M+H] x105 [M+H] 375.1263 6 343.0968 311.1249 3 Tyrosine-betaxanthin Methionine-betaxanthin 1.5 Valine-betaxanthin 4 2 1.0 84.9617 161.0153 2 0.5 1 84.9600 191.0592 551.1519 84.9600 152.0706 0 0 0.0 x104 +bbCID MS, 49.0-140.0eV, 6.3-6.4min #756-774 x104 +bbCID MS, 49.0-140.0eV, 6.4-6.5min #774-786 x104 +bbCID MS, 49.0-140.0eV, 6.7-6.8min #800-816 84.9618 1.5 84.9599 1.5 84.9598 1.5 1.0 1.0 1.0

365.1066 0.5 0.5 0.5 365.1060 365.1127 177.0586 311.1240 0.0 0.0 0.0 100 200 300 400 500 m/z 100 200 300 400 500 600m/z 50 100 150 200 250 300 350 400 450 500m/z

Intens. + +MS, 7.0-7.0min #837-841 Intens. +MS, 7.1-7.2min #853-865 Intens. +MS, 7.3-7.4min #871-889 x104 Miraxanthin III [M+H] x104 x105 84.9599 331.1296 17-Decarboxy-neobetanin 505.1467 549.1375 + Neobetanin 161.0119 [M+H] [M+H]+ 1.0 379.1007 1.5 84.9599 2 161.0122 1.0 0.5 1 0.5 261.1366 84.9599 161.0123 0.0 0.0 0 x104 +bbCID MS, 49.0-140.0eV, 7.0-7.0min #842-844 x104 +bbCID MS, 49.0-140.0eV, 7.1-7.2min #856-864 x104 +bbCID MS, 49.0-140.0eV, 7.2-7.5min #870-896 8 1.5 84.9599 84.9599 387.0837 1.5 341.0780 6 1.0 1.0 549.1373 297.0874 379.1008 4 0.5 0.5 147.0445 365.1062 2 84.9600 505.1468 0.0 0.0 0 100 150 200 250 300 350 400 450 500 m/z 100 200 300 400 500 600m/z 100 200 300 400 500 600m/z

Intens. +MS, 8.1-8.2min #969-985 Intens. +MS, 8.2-8.4min #983-1011 Intens. +MS, 8.5-8.5min #1017-1023 [M+H]+ + x105 x105 [M+H] x104 [M+H]+ 325.1409 3 325.1410 359.1236 4 4 Phenylalanine-isobetaxanthin Isoleucine-isobetaxanthin Isoleucine-betaxanthin 3 2 3 398.1345 2 2 84.9597 325.1390 1 143.0012 191.0586 1 1 84.9598 84.9599 161.0122 0 0 0 x104 +bbCID MS, 49.0-140.0eV, 8.1-8.2min #976-980 x104 +bbCID MS, 49.0-140.0eV, 8.2-8.4min #988-1006 x104 +bbCID MS, 49.0-140.0eV, 8.4-8.5min #1014-1022 2.0 2.0 119.0604 84.9600 84.9596 1.5 1.5 1.5 1.0 1.0 1.0 379.1008 0.5 409.1107 0.5 325.1394 365.1060 0.5 177.0514 277.0930 277.0928 303.1411 0.0 0.0 0.0 100 150 200 250 300 350 400 m/z 100 150 200 250 300 350 400 m/z 100 150 200 250 300 350 400 m/z

Intens. +MS, 8.5-8.7min #1023-1047 Intens. +MS, 8.8-8.8min #1057-1063 Intens. +MS, 8.9-9.0min #1067-1081 x104 x104 x104 398.1348 84.9600 503.1303 191.0596 + 3 [M+H] 1.0 2 2-Decarboxy-2,3-dehydro-neobetanin + + Leucine-isobetaxanthin 2 S-tryptophan-betaxanthin359.1234[M+H] [M+H] 84.9597 84.9596 325.1403 161.0118 161.0117 325.1393 0.5 1 347.1679 565.1740 1 503.1316 425.1458 0 0.0 0 x104 +bbCID MS, 49.0-140.0eV, 8.5-8.6min #1022-1030 x104 +bbCID MS, 49.0-140.0eV, 8.8-8.9min #1058-1064 x104 +bbCID MS, 49.0-140.0eV, 8.9-9.0min #1070-1076 2.0 84.9596 2.0 84.9600 84.9598 1.5 1.5 1.5 130.0647 1.0 1.0 1.0 295.0717 0.5 365.1060 0.5 0.5 313.0817 365.1060 426.1520 0.0 0.0 0.0 100 150 200 250 300 350 400 m/z 100 200 300 400 500 600 m/z 100 200 300 400 500 600 m/z

Intens. +MS, 9.0-9.1min #1083-1093 Intens. +MS, 9.1-9.2min #1099-1101 Intens. +MS, 9.5-9.6min #1147-1157 x104 x104 x105 393.0793 17-Decarboxy-2,3- 84.9597 15-Decarboxy-2,3-dehydro-neobetanin 389.1422 3 + dehydro-neobetanin 161.0116 1.0 Betanidin [M+H] + 393.0795 [M+H]+ [M+H] 1.0 2 503.1299 84.9596 503.1298 161.0120 0.5 1 0.5 185.1145 84.9597 281.0920 0 0.0 0.0 x104 +bbCID MS, 49.0-140.0eV, 9.0-9.1min #1082-1092 x104 +bbCID MS, 49.0-140.0eV, 9.1-9.2min #1098-1102 x104 +bbCID MS, 49.0-140.0eV, 9.6-9.6min #1150-1156 2.0 2.0 84.9597 2.0 84.9597 84.9597 389.1414 1.5 1.5 1.5

1.0 393.0796 1.0 1.0

0.5 0.5 0.5 271.0420 185.0412 365.1053 0.0 0.0 0.0 100 200 300 400 500 600 m/z 100 200 300 400 500 600 m/z 50 100 150 200 250 300 350 400 450 m/z

Intens. +MS, 9.8-9.8min #1179-1183 Intens. +MS, 9.9-9.9min #1187-1193 Intens. +MS, 10.0-10.1min #1207-1209 x104 x104 x104 84.9598 84.9595 84.9595 + 1.5 1.5 [M+H] 161.0118 161.0117 507.1606 1.0 17-Decarboxy-betanin 1.0 6´-feruloyl-betanin 1.0 389.1416 6´-feruloyl-isobetanin + 437.1418 + 0.5 [M+H] 0.5 [M+H] 0.5 389.1410 468.2494 727.1966 549.1296 727.1993 727.1978 0.0 0.0 0.0 x104 +bbCID MS, 49.0-140.0eV, 9.8-9.9min #1182-1186 x104 +bbCID MS, 49.0-140.0eV, 9.9-10.0min #1190-1196 x104 +bbCID MS, 49.0-140.0eV, 10.1-10.1min #1208-1212 2.0 84.9597 84.9596 84.9596 2.0 2 1.5 1.5 1.0 1 1.0 0.5 389.0988 365.1051 0.5 365.1050 545.1985 0.0 0 0.0 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z Figure B-5. Protonated mass spectra of phytochemical compounds of retention time 6-10min in beet extracts.

130 Intens. Intens. +MS, 4.0-4.2min #483-507 Intens. + +MS, 0.5-0.6min #65-73 [M+H]+ + +MS, 8.2-8.4min #987-1011 5 [M+H] x105 x105 [M+H] x10 166.2018 355.1027 325.3392 1.5 Phenylalanine 3-O-Caffeoylquinic acid 6 Ferulic acid derivative 1.0 120.1643 1.0 4 163.0389 0.5 381.3443 0.5 2 147.1786 731.1791 203.1936 446.4966 85.0187 235.0545 551.1242 0 0.04 0.0 x105 +bbCID MS, 49.0-140.0eV, 0.6-0.6min #66-70 x10 +bbCID MS, 49.0-140.0eV, 4.0-4.2min #484-500 x105 +bbCID MS, 49.0-140.0eV, 8.2-8.5min #984-1022 6 381.3448 103.1257 2.0 377.0851 1.5 4 325.3394 91.1174 1.5 1.0 210.1958 1.0 77.0920 163.0390 2 85.0876 163.1735 543.5097 0.5 120.1641 0.5 261.2179 188.1984 541.1534 731.1797 0 0.0 0.0 100 200 300 400 500 m/z 60 80 100 120 140 160 180 200 220 m/z 100 200 300 400 500 600 700 m/z

Intens. + +MS, 8.6-8.8min #1037-1055 Intens. x104 [M+H] Intens. +MS, 8.6-8.7min #1035-1049 +MS, 8.8-8.9min #1055-1073 355.1034 4 x104 [M+H]+ 163.0393 x10 581.1559 4 163.0405 355.1063 Cy3-galactoside (isomer) 1.5 5-O-Caffeoylquinic acid 2.0 355.1057 3 Cy3-galactoside 163.0403 1.0 1.5 2 [M+H]+ 1.0 0.5 517.1568 731.1836 1 581.1564 0.5 517.6658 235.0570 731.1869 0.04 x10 +bbCID MS, 49.0-140.0eV, 8.7-8.8min #1040-1052 0 0.05 2.5 x104 +bbCID MS, 49.0-140.0eV, 8.6-8.8min #1038-1056 x10 +bbCID MS, 49.0-140.0eV, 8.8-8.9min #1054-1072 163.0393 287.0579 2.0 6 287.0578 0.8 377.0855 1.5 89.0389 163.0403 0.6 287.0558 4 377.0881 1.0 0.4 643.1914 541.1544 0.5 673.1980 2 367.1036 581.1563 0.2 163.0402 581.1561 0.0 100 200 300 400 500 600 700 m/z 0 0.0 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z

Intens. +MS, 9.5-9.6min #1139-1159 Intens. +MS, 9.8-10.2min #1181-1221 Intens. +MS, 10.7-10.9min #1287-1305 x104 x105 + 339.1092 [M+H]919.2607 365.1251Cy3-xylosyl(feruloylglucosyl)-galactoside (isomer) 2.0 3000 Cy3-xylosyl (sinapoylglucosyl)galactoside [M+H]+ 2 673.1990 1.5 Cy3-xylosyl(feruloylglucosyl)-galactoside 445.1394 2000 177.0552 919.2616 + 1.0 1 501.1625 [M+H] 949.2667 1000 0.5 707.1889 1060.3059 339.1105 0 479.1075 5 +bbCID MS, 49.0-140.0eV, 9.5-9.7min #1138-1164 0.0 04 x10 x106 +bbCID MS, 49.0-140.0eV, 9.8-10.1min #1182-1216 x10 +bbCID MS, 49.0-140.0eV, 10.7-10.9min #1288-1314 2.5 673.2005 3 287.0589 365.1244 2.0 1.0 2 1.5 1.0 655.1925 1 0.5 177.0556 0.5 575.1804 541.1560 673.2021 919.2603 919.2600 0 0.0 0.0 100 200 300 400 500 600 700 800 900 m/z 200 300 400 500 600 700 800 900 1000 m/z 300 400 500 600 700 800 900 1000 1100 m/z

Figure B-6. Protonated mass spectra of phytochemical compounds of retention time 1-10min in carrot extracts.

131 450 A) Kale Juices ABTS DPPH a 400 Total Phenolics 350

300 a b b 250

200 a b c c a cd c d b 150 b b d de e e ef c de e e 100 de f e f de de 50

AA/GA Equivalents Equivalents AA/GA g/mL) (μ 0 K1 K2 K3 K4 K5 K6 K7 K8 K9 K10

ABTS B) Beet Juices DPPH 700 Total Phenolics a a 600 b b a a a c 500 c g/mL) b d

μ b 400 d d c c e e 300 f d d d de 200 e e d g g f g 100

AA/GA Equivalents Equivalents ( AA/GA 0 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10

C) Melon Juices ABTS 500 a DPPH 450 a Total phenolics 400 b

g/mL) 350 a μ 300 b c cd b 250 d d cd a 200 e b cd cd c c de bc 150 e e c c de d e 100 f

AA/GA Equivalents Equivalents AA/GA ( 50 f f 0 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 Figure B-7. Free radical scavenging activities and total phenolics of commercial juices: (A) kale juices; (B) beet juices; (C) melon juices. DPPH and ABTS were expressed as ascorbic acid (AA) equivalents, and total phenolics were expressed as gallic acid (GA) equivalents. Values followed by the same letter in the same assay are not significantly different (p<0.05).

132 A). Kale Juices B). Beet Juices C). Melon Juices %) %) %) 1 1 45.4 (15. (65. Component Component 2 ( Component Component 2 Component Component 2

Conventional Organic Conventional Organic Conventional Organic

Figure B-8. PLS-DA and antioxidant activities of different juices. (A) Kale juices; (B) Beet juices; (C) Melon juices. The red clustered dots represent juices obtained from conventional raw materials, and the green grouped dots were juices partially obtained from organic raw materials. DPPH and ABTS were expressed as ascorbic acid (AA) equivalents, and total phenolics were expressed as gallic acid (GA) equivalents.

133 Intens. +MS, 7.6-7.7min #915-929 Intens. +MS, 1.3-1.5min #159-175 Intens. [M+H]+ +MS, 3.3-3.7min #397-449 x104 x105 x105 231.1063 182.0793 166.0850 2 132.1006 0.75 Quercetin-3-diglucoside-7-glucoside Epigallocatechin 4 Phenylalanine 120.0799 0.50 [M+H]+ 86.0955 316.2151 1 789.1884 [M+H]+ 2 0.25 245.0739 307.0925 0.00 0 0 +bbCID MS, 49.0-140.0eV, 7.6-7.7min #912-922 x104 +bbCID MS, 49.0-140.0eV, 1.3-1.5min #158-180 x104 +bbCID MS, 49.0-140.0eV, 3.3-3.7min #398-446 2500 541.1404 91.0535 2000 387.1530 4 6 103.0534 3 1500 4 2 1000 299.0710 2 500 1 230.9870 166.0844 811.1726 957.2205 307.0924 381.0752 0 0 0 200 300 400 500 600 700 800 900 1000 m/z 100 150 200 250 300 350 400 m/z 100 150 200 250 300 m/z

200 250 300 350 400 450 500 Wavelength [nm] Intens. Intens. +MS, 8.1-8.2min #977-989 Intens. +MS, 8.5-8.6min #1025-1037 +MS, 9.3-9.5min #1113-1139 4 Kaempferol-3-O-diglucoside-7-glucoside + x10 [M+H] 443.2371 162.0022 0.8 395.1217 773.1958 6000 4000 Quercetin-3-feruloyl-diglucoside-7-diglucoside 0.6 162.0019 328.2131 405.1612 4000 Kaempferol-3-O-(caﬀeoyl)-sophoroside + 162.0029 [M+H] 0.4 2000 1127.2766 2000 [M+H]+ 583.1163 0.2 935.2362 0.0 0 0 4 395.1219 x104 +bbCID MS, 49.0-140.0eV, 8.5-8.6min #1022-1032 +bbCID MS, 49.0-140.0eV, 9.3-9.5min #1114-1136 x10 +bbCID MS, 49.0-140.0eV, 8.0-8.3min #962-1000 8000 1.5 463.1441 406.1642 1.5 6000 293.0919 1.0 287.0464 1.0 541.1401 84.0780 4000 84.9573 523.1269 0.5 2000 0.5 795.1766 737.2048 957.2209 1149.2548 825.1576 973.2187 0.0 0.0 0 0 200 400 600 800 1000 m/z 0 200 400 600 800 1000 m/z 200 400 600 800 1000 1200 1400 m/z

Intens. +MS, 9.7-9.9min #1167-1187 Intens. +MS, 9.7-10.0min #1169-1205 Intens. +MS, 10.9-11.0min #1307-1319 Kaempferol-3-feruloyl-digulcoside-7-diglucoside x104 162.0023 [M+H]+ 162.0022Kaempferol-3-(feruoyl)-sophoroside-7-O-glucoside 332.2153 4000 411.1874 1111.2821 4000 [M+H]+ 575.1199 411.1872 949.2327 2 Quercetin-3-diglucoside-7-glucoside(isomer) 3000 3000 [M+H]+ 2000 2000 1111.2813 789.2026 1 1000 1000 162.0055 0 0 0 x104 +bbCID MS, 49.0-140.0eV, 9.7-10.0min #1168-1196 x104 +bbCID MS, 49.0-140.0eV, 9.7-10.0min #1166-1202 x104 +bbCID MS, 49.0-140.0eV, 10.9-11.1min #1312-1328 2.0 2.5 3 541.2121 411.1869 333.0579 1.5 287.0465 2.0 287.0469 811.1839 2 177.0490 1.5 177.0493 1.0 1.0 120.0797 479.1339 1 1133.2640 84.9569 707.2327 0.5 971.2146 287.0524 971.2152 0.5 543.2376 0 0.0 0.0 200 400 600 800 1000 1200 1400 m/z 0 200 400 600 800 1000 1200 m/z 100 200 300 400 500 600 700 800 900 m/z

Intens. +MS, 11.8-11.9min #1419-1425 Intens. +MS, 11.4-11.5min #1369-1387 Intens. 4 +MS, 11.6-11.6min #1391-1399 x10 x104 597.1659 657.1501 476.2947 1.00 0.8 6000 Kaempferol-3-O- 162.0028 Kaempferol-3-sinapoyl-diglucoside-7- 0.75 Kaempferol-3-O-sophoroside 0.6 162.0030 162.0030 diglucoside-7- glucoside 4000 diglucoside 348.0527 + 0.50 [M+H] 0.4 344.2457 (Isomer) + 2000 [M+H] 611.1458 + 0.25 0.2 [M+H] 1141.2915 657.1482 773.1970 04 0.004 0.0 x10 +bbCID MS, 49.0-140.0eV, 11.8-11.9min #1420-1426 x10 +bbCID MS, 49.0-140.0eV, 11.4-11.5min #1370-1386 84.9573 +bbCID MS, 49.0-140.0eV, 11.6-11.6min #1392-1398 84.9570 333.0525 0.8 6000 1.0 0.6 287.0479 679.1318 287.0478 287.0471 4000 0.4 0.5 633.1280 511.1094 0.2 619.1478 2000 879.2280 1163.2760 679.1311 0.0 0.0 0 0 200 400 600 800 1000 1200 1400 m/z 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z

Intens. Intens. Intens. +MS, 12.9-13.0min #1545-1563 +MS, 11.8-11.9min #1413-1427 +MS, 12.4-12.5min #1495-1505 4 x104 x104 [M+H]+ x10 597.1712 641.1742 564.3614 + Spinacetin 3-O-glucosyl- 1.00 [M+H] 0.8 1.0 162.0077 Isorhamnetin 3-O (1-6)-glucoside Eriocitrin/Neoeriocitrin 0.6 -diglucoside 162.0076 0.75 162.0039 471.2029 [M+H]+ 0.4 340.0650 0.5 0.50 84.9581 84.9597 84.9598 671.1846 0.25 356.0890 0.2 0.0 0.00 0.0 x104 +bbCID MS, 49.0-140.0eV, 12.9-13.0min #1548-1558 +bbCID MS, 49.0-140.0eV, 11.8-11.9min #1414-1424 x104 +bbCID MS, 49.0-140.0eV, 12.4-12.5min #1490-1504 84.9599 8000 84.9581 663.1560 0.8 569.3165 1.5 6000 0.6 289.0650 1.0 347.0817 693.1673 4000 84.9597 317.0664 0.4 140.0684 153.0155 411.1997 365.0988 269.1359 619.1521 0.5 0.2 2000 463.2066 633.1464 0.0 0 0.0 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 800 900 m/z

Intens. Intens. +MS, 13.5-13.7min #1627-1647 +MS, 13.9-13.9min #1665-1675 Intens. +MS, 14.1-14.2min #1691-1707 4 Kaempferol-3-sinapoyl-diglucoside-7-glucoside 4 [M+H]+ x10 273.0767 + 162.0021 x10 6 [M+H] 979.2417 611.1822 581.1886 6000 [M+H]+ Naringin 3 Qucertin-3-O-rutinoside 4 4000 509.1006 833.1881 2 2 348.0987 2000 1349.1949 162.0076 1 162.0029 363.5925 0 05 0 x10 +bbCID MS, 49.0-140.0eV, 13.5-13.7min #1628-1652 +bbCID MS, 49.0-140.0eV, 13.9-14.0min #1666-1680 x104 +bbCID MS, 49.0-140.0eV, 14.1-14.2min #1692-1704 0.8 271.0612 6000 633.1642 2.0 347.0667 303.0785 145.0235 1001.2228 0.6 4000 1.5 0.4 523.1266 153.0140 153.0186 603.1713 1.0 2000 655.1650 0.2 1348.9122 0.5 495.1711 0.0 0 0.0 100 200 300 400 500 600 m/z 0 200 400 600 800 1000 1200 1400 m/z 100 200 300 400 500 600 700 m/z Figure B-9. LC-MS spectra of identified compounds in kale juice samples.

134 Intens. Intens. +MS, 2.5-2.8min #295-331 [M+H]+ +MS, 3.3-3.7min #393-447 Intens. +MS, 4.1-4.3min #493-511 x105 x105 166.0869 x104 1.00 230.0842 166.0869 1.00 1,3-Dicaffeoylquinic acid 0.75 2,17-Bidecarboxy-2,3-dehydro- 4 120.0812 Phenylalanine neobetanin 0.75 365.1936 0.50 [M+H]+ 120.0811 430.1587 364.0696 152.0583 459.1601 2 0.50 0.25 284.1020 [M+H]+ 0.25 401.1448 517.1558 0.005 0 x10 +bbCID MS, 49.0-140.0eV, 2.4-2.8min #284-342 x105 +bbCID MS, 49.0-140.0eV, 3.3-3.6min #396-438 0.004 1.25 x10 +bbCID MS, 49.0-140.0eV, 4.1-4.2min #492-508 365.1102 0.8 103.0545 517.1560 1.00 0.8 0.6 0.75 136.0621 152.0586 0.6 0.50 0.4 325.1143 452.1409 459.1603 0.4 85.0287 0.25 0.2 188.0682 84.0452 314.0853 365.1058 0.2 0.00 100 150 200 250 300 350 400 450 m/z 0.0 0.0 50 100 150 200 250 300 350 400m/z 100 200 300 400 500 600 m/z

Intens. +MS, 6.0-6.1min #723-727 Intens. Intens. +MS, 6.0-6.0min #715-719 4 +MS, 5.7-5.8min #683-699 4 x10 x105 x10 0.8 163.0392 188.0696 3 163.0389 [M+H]+ [M+H]+ 0.8 0.6 + 205.0960 Chlorogenic acid derivative[M+H] 0.6 2 Chlorogenic acid 355.1029 355.1025 L-Tryptophan 0.4 0.4 243.0473 105.0384 243.0474 1 0.2 0.2 146.0591 105.0387 289.0708 0.0 0.0 x104 +bbCID MS, 49.0-140.0eV, 5.7-5.9min #690-708 0 x104 +bbCID MS, 49.0-140.0eV, 6.0-6.0min #720-726 x104 +bbCID MS, 49.0-140.0eV, 5.9-6.0min #712-716 1.5 115.0537 163.0387 287.0554 91.0538 2.5 163.0390 1.0 1.0 2.0 0.8 89.0386 89.0388 127.0389 188.0689 135.0440 0.6 317.0842 1.5 377.0852 0.5 146.0588 205.0955 243.0478 361.1106 163.0584 1.0 0.4 0.2 0.0 0.5 0.0 60 80 100 120 140 160 180 200 220 240m/z 0.0 50 100 150 200 250 300 350 400 m/z 100 150 200 250 300 350 400 m/z

Intens. +MS, 6.1-6.3min #731-751 Intens. Intens. +MS, 6.4-6.5min #765-777 x106 +MS, 6.3-6.3min #751-755 551.1592 x104 x104 0.8 383.0953 298.0993 Isobetanin + 1.5 [M+H] 2’-O-Glucosyl-betanin/isobetanin 2 0.6 Betanin 1.0 551.1513 212.0565 [M+H]+ 0.4 [M+H]+ 199.0595 1 358.1161 551.1559 0.2 0.5 713.2042 166.0506 505.2444 0.0 x106 +bbCID MS, 49.0-140.0eV, 6.1-6.2min #730-750 0.0 0 x105 +bbCID MS, 49.0-140.0eV, 6.3-6.3min #752-754 x104 +bbCID MS, 49.0-140.0eV, 6.4-6.5min #766-778 0.8 389.1040 496.1469 0.8 383.0955 2.0 0.6 1.5 0.6 136.0625 0.4 551.1589 298.0990 389.1011 0.4 1.0 0.2 150.0567 0.2 0.5 287.0544 619.1288 767.1996 0.0 0.0 0.0 100 200 300 400 500 600 m/z 100 200 300 400 500 600 700 800 m/z 100 200 300 400 500 600 m/z

Intens. Intens. +MS, 6.5-6.6min #781-787 Intens. +MS, 6.6-6.7min #791-807 +MS, 7.1-7.3min #857-873 x105 x105 x104 507.1655 507.1659 507.1652 1.5 + + [M+H] [M+H]+ [M+H] 1.5 17-Decarboxy-isobetanin 4 15-Decarboxy-betanin 1.0 2-Decarboxy-isobetanin 1.0 2 0.5 0.5 358.1164 352.1318 105.0397 212.0565 358.1158 0.0 0 0.05 x105 +bbCID MS, 49.0-140.0eV, 6.5-6.6min #780-788 x106 +bbCID MS, 49.0-140.0eV, 6.6-6.7min #790-810 x10 +bbCID MS, 49.0-140.0eV, 7.1-7.3min #854-876 345.1112 345.1116 0.8 389.1023 2.0 1.0 507.1662 0.6 1.5 507.1656 0.4 1.0 0.5 0.5 0.2 507.1658 106.0659 106.0659 150.0561 0.0 0.0 0.0 100 200 300 400 500 600m/z 100 200 300 400 500 600m/z 100 150 200 250 300 350 400 450 500 m/z

Intens. Intens. +MS, 2.5-2.8min #295-331 [M+H]+ +MS, 3.3-3.7min #393-447 Intens. +MS, 4.1-4.3min #493-511 5 x105 4 x10 166.0869 x10 1.00 230.0842 166.0869 1.00 1,3-Dicaffeoylquinic acid 0.75 2,17-Bidecarboxy-2,3-dehydro- 4 120.0812 Phenylalanine 0.75 365.1936 neobetanin + 120.0811 430.1587 0.50 [M+H] 0.50 364.0696 459.1601 2 152.0583 [M+H]+ 0.25 284.1020 0.25 401.1448 517.1558 0.00 0 0.00 x105 +bbCID MS, 49.0-140.0eV, 2.4-2.8min #284-342 x105 +bbCID MS, 49.0-140.0eV, 3.3-3.6min #396-438 x104 +bbCID MS, 49.0-140.0eV, 4.1-4.2min #492-508 1.25 365.1102 0.8 103.0545 517.1560 1.00 0.8 0.6 136.0621 0.75 0.6 325.1143 152.0586 0.4 452.1409 0.50 0.4 85.0287 459.1603 0.2 188.0682 0.25 314.0853 0.2 84.0452 365.1058 0.00 0.0 0.0 100 150 200 250 300 350 400 450 m/z 50 100 150 200 250 300 350 400m/z 100 200 300 400 500 600 m/z

Intens. +MS, 6.0-6.1min #723-727 Intens. Intens. +MS, 6.0-6.0min #715-719 4 +MS, 5.7-5.8min #683-699 4 x10 x105 x10 0.8 163.0392 188.0696 3 163.0389 [M+H]+ [M+H]+ 0.8 0.6 [M+H]+ 205.0960 Chlorogenic acid derivative 0.6 2 Chlorogenic acid 355.1029 355.1025 L-Tryptophan 0.4 0.4 243.0473 105.0384 243.0474 1 0.2 0.2 146.0591 105.0387 289.0708 0.0 0.0 x104 +bbCID MS, 49.0-140.0eV, 5.7-5.9min #690-708 0 x104 +bbCID MS, 49.0-140.0eV, 6.0-6.0min #720-726 x104 +bbCID MS, 49.0-140.0eV, 5.9-6.0min #712-716 1.5 115.0537 163.0387 287.0554 91.0538 2.5 163.0390 1.0 1.0 2.0 0.8 89.0386 89.0388 127.0389 188.0689 135.0440 0.6 317.0842 1.5 377.0852 0.5 146.0588 205.0955 243.0478 361.1106 163.0584 1.0 0.4 0.2 0.0 0.5 0.0 60 80 100 120 140 160 180 200 220 240m/z 0.0 50 100 150 200 250 300 350 400 m/z 100 150 200 250 300 350 400 m/z Figure B-10. LC-MS spectra of identified compounds in beet juice samples.

135 Intens. 2,17-Bidecarboxy-betanidin/isobetanin +MS, 7.3-7.3min #881-883 Intens. +MS, 7.6-7.6min #907-915 Intens. +MS, 7.5-7.7min #897-931 4 6000 + x10 x104 358.1161 [M+H] 507.1649 3 355.1068 2-Decarboxy-betanin + 463.1752 2 [M+H] Caffeoylqunic acid 4000 2 147.0446 163.0406 275.1057 + 2000 1 [M+H] 1 731.1883 222.1499 358.1154 231.1148 660.1785 84.9600 162.0084 507.1672 04 0 0 x10 +bbCID MS, 49.0-140.0eV, 7.3-7.3min #878-882 x10 4 +bbCID MS, 49.0-140.0eV, 7.6-7.6min #908-916 x104 +bbCID MS, 49.0-140.0eV, 7.6-7.7min #908-928 365.1088 345.1107 6 377.0891 1.0 2.0 1.5 4 485.1571 163.0405 0.5 1.0 150.0554 284.0935 507.1652 2 0.5 150.0555 731.1884 0.0 0.0 0 100 150 200 250 300 350 400 450 500 m/z 100 150 200 250 300 350 400 450 500 m/z 0 100 200 300 400 500 600 700 800 m/z

Intens. +MS, 7.6-7.8min #915-939 Intens. +MS, 7.8-7.9min #939-947 Intens. +MS, 7.9-8.1min #947-975 5 5 x104 x10 x10 303.1263 549.1414 1.00 505.1515 Neobetanin + 17-Decarboxy-neobetanin 4 [M+H] [M+H]+ 2 0.75 3 δ-Viniferin 0.50 2 1 0.25 1 [M+H]+ 358.1171 84.9572 162.0027 455.1410 0 0.005 04 x105 +bbCID MS, 49.0-140.0eV, 7.6-7.8min #918-934 x10 +bbCID MS, 49.0-140.0eV, 7.8-7.9min #936-946 x10 +bbCID MS, 49.0-140.0eV, 7.8-8.0min #940-966 549.1419 1.5 505.1521 4 455.1414 387.0869 3 2 1.0 343.0966 2 341.0808 387.0870 367.1272 1 0.5 297.0904 549.1417 195.0861 1 84.0784 104.0507 181.0386 0.0 0 0 100 150 200 250 300 350 400 450 500 m/z 100 200 300 400 500 600m/z 100 200 300 400 500 600 m/z

Intens. Intens. +MS, 9.0-9.1min #1081-1091 +MS, 8.8-9.0min #1059-1081 Intens. +MS, 9.8-9.9min #1183-1195 x104 505.1521 6000 459.1414 x104 4 2,17-Bidecarboxy-2,3-dehyo-neobetanin isomer 387.2080 [M+H]+ [M+H]+ [M+H]+ 0.8 519.2527 3 2-Decarbxy-neobetanin 4000 0.6 162.0076 505.1475 Ferulic acid 105.0392 339.0623 162.0098 279.1043 2 0.4 derivative 2000 203.0346 1 177.0564 314.1274 423.0953 0.2 04 0 0.0 x10 +bbCID MS, 49.0-140.0eV, 8.8-8.9min #1060-1072 +bbCID MS, 49.0-140.0eV, 9.0-9.1min #1080-1092 x104 +bbCID MS, 49.0-140.0eV, 9.8-10.0min #1176-1198 297.0907 8000 365.1068 2.0 4 541.2359 1.5 6000 505.1519 3 1.0 4000 409.1119 2 177.0565 0.5 2000 1 511.1426 405.1801 0.0 0 0 100 200 300 400 500 600 m/z 100 150 200 250 300 350 400 450 500 m/z 100 200 300 400 500 600 m/z

Intens. Intens. +MS, 10.0-10.2min #1201-1223 ++MS, 11.9-12.1min #1429-1453 x104 x104 [M+H] 503.1317 611.1458 3 [M+H]+ 3 2-Decarboxy-2,3-dehydro-neobetanin Quercetin 3-O-rutinoside 2 2

1 1 334.0554 162.0073 252.0873 162.0029 388.2561 0 0 x104 +bbCID MS, 49.0-140.0eV, 10.0-10.2min #1200-1226 x104 +bbCID MS, 49.0-140.0eV, 11.9-12.1min #1430-1452 5 1.00 303.0426 365.1067 4 633.1275 0.75 3 0.50 295.0719 409.1125 2 135.0030 0.25 1 84.9573 555.2278 0.00 0 100 200 300 400 500 m/z 100 200 300 400 500 600 700 800 900 m/z Figure B-10. Continued

136 Intens. +MS, 0.7-0.9min #87-103 Intens. ++MS, 3.3-3.8min #393-455 Intens. x105 5 [M+H] +MS, 9.0-9.2min #1083-1101 325.1146 x10 x104 166.0871 459.0906 3 + 2 Epicatechin-(2a-7) (4a-8)-epicatechin [M+H] 3-O-galatoside 1.0 Phenylalanine Epigallocatechin 3-O-gallate 120.0814 2 289.0695 1 156.0772 [M+H]+ 0.5 1 460.2046 707.2245 139.0378 391.2824 84.9598 0 x105 +bbCID MS, 49.0-140.0eV, 0.7-0.9min #88-106 0.04 0 x10 +bbCID MS, 49.0-140.0eV, 3.3-3.6min #394-438 x104 +bbCID MS, 49.0-140.0eV, 9.0-9.2min #1084-1104 365.1073 5 103.0547 139.0384 1.5 91.0547 1.5 4 425.1402 120.0813 1.0 3 85.0286 1.0 77.0387 203.0532 0.5 527.1609 149.0232 2 443.1265 0.5 707.2249 166.0864 185.0424 1 287.0534 0.0 0.0 100 200 300 400 500 600 700 m/z 0 80 100 120 140 160 180 200 m/z 100 150 200 250 300 350 400 450 500 m/z

Intens. Intens. +MS, 11.7-11.7min #1405-1407 +MS, 11.8-12.0min #1423+ -1441 Intens. 4 x104 [M+H] +MS, 12.0-12.2min #1445-1461 x10 611.1587 x104 0.8 162.0066 185.1140 Quercetin 3-O-galactoside 7-O-rhamnoside 0.8 Quercetin 3-O-galactoside 7-O-rhamnoside 162.0064 0.8 Quercetin 3-rhamnosyl (1→2)-rhamnosyl-glucoside 0.6 203.0329 203.0327 0.6 0.6 391.2824 595.1627 391.2828 465.1008 391.2828 0.4 + 0.4 [M+H] 334.0623 0.4 [M+H]+ 611.1593 0.2 0.2 0.2 579.1685 757.2156 0.0 0.04 0.0 x104 +bbCID MS, 49.0-140.0eV, 11.7-11.7min #1400-1410 x10 +bbCID MS, 49.0-140.0eV, 11.8-12.0min #1424-1440 x104 +bbCID MS, 49.0-140.0eV, 12.0-12.2min #1446-1462 1.5 303.0488 1.0 0.8 0.8 1.0 303.0486 0.6 149.0223 0.6 149.0224 0.4 149.0225 0.4 303.0476 0.5 487.0831 633.1407 413.2641 487.0829 0.2 413.2650 0.2 481.2598 591.2012 779.1979 0.0 0.0 0.0 100 200 300 400 500 600 m/z 100 200 300 400 500 600 m/z 100 200 300 400 500 600 700 m/z

Intens. +MS, 12.7min #1525 Intens. +MS, 12.5-12.5min #1499-1505 Intens. +MS, 12.6-12.6min #1509-1515 x104 162.0064 8000 162.0065 162.0065 Kaempferol 3-O-glucosyl-rhamnosyl-glucoside 0.8 Kaempferol 3-O-(2’’-rhamnosyl-galatoside)- Kaempferol 3-O-glucosyl-rhamnosyl-galactoside [M+H]+ 0.6 6000 6000 757.2167 7-O-rhmnoside 391.2831 391.2831 447.3457 447.3462 4000 84.9593 447.3456 0.4 4000 520.3319 [M+H]+ 520.3314 [M+H]+ 0.2 741.2182 2000 520.3320 2000 595.1621 757.2182 0.04 0 0 x10 +bbCID MS, 49.0-140.0eV, 12.7-12.7min #1522-1526 x104 +bbCID MS, 49.0-140.0eV, 12.5-12.5min #1498-1506 x104 +bbCID MS, 49.0-140.0eV, 12.5-12.6min #1506-1520 1.00 1.0 287.0541 0.8 1.00 84.9593 0.75 0.6 0.75 140.0671 287.0539 149.0226 0.50 149.0224 0.50 0.4 287.0540 0.25 413.2632 413.2649 525.2852 763.2036 0.2 525.2856 0.25 413.2648 763.2040 779.2008 617.1463 0.00 0.0 0.00 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z

Intens. +MS, 13.1-13.2min #1579-1583 x104 0.8 162.0066 Kaempferol 3-O-galactoside-7-O-rhamnoside

0.6 + 391.2835 [M+H] 0.4 84.9592 595.1626 0.2 663.5889 0.0 x104 +bbCID MS, 49.0-140.0eV, 13.1-13.2min #1580-1582 1.0 84.9593 0.8 0.6 331.0804 0.4 569.3105 0.2 413.2639 0.0 100 200 300 400 500 600 700 m/z Figure B-11. LC-MS spectra of identified compounds in melon juice samples.

137 Figure B-12. Identified betalains with retention times 1.2 to 7.0 min, from conventional and organic red and golden beet samples.

138 Intens. +MS, 6.5-6.5min #775-785 Intens. Intens. +MS, 6.9-7.0min #823-837 4 +MS, 6.7-6.8min #807-813 [M+H]+ x10 x10 4 x104 311.1263 152.0737 199.0590 + [M+H] 1.0 2.0 2 84.9617 17-Decarboxy-betanin Syringic acid Valine-betaxanthin 1.5 311.1311 1 0.5 1.0 84.9603 84.9602 + 0.5 161.0131 389.1015 [M+H] 161.0128 253.0335 307.0447 423.2713 507.1723 389.1012 0 0.0 0.0 +bbCID MS, 49.0-140.0eV, 6.4-6.5min #772-786 +bbCID MS, 49.0-140.0eV, 6.7-6.8min #808-812 +bbCID MS, 49.0-140.0eV, 6.9-7.0min #828-836 3000 3000 84.9603 84.9618 3000 84.9602

2000 2000 2000

1000 1000 1000 389.1014 177.0557 311.1264 345.1187 341.0801 389.1004 554.2582 0 0 0 100 150 200 250 300 350 m/z 100 200 300 400 500 600m/z 100 150 200 250 300 350 m/z

Intens. Intens. +MS, 7.0-7.1min #841-851 +MS, 7.0-7.1min #845-847 Intens. +MS, 7.1-7.1min #853-855 x10 4 4 84.9603 84.9617 x10 84.9618 6000 0.8 Neobetanin 17-Decarboxy-neobetanin 240.0859 0.6 0.75 2-Decarboxy-neobetanin 4000 161.0130 + 0.4 161.0152 [M+H] 0.50 423.0926 + 505.1565 161.0153 + 2000 [M+H] 278.0692 [M+H] 549.1389 0.2 0.25 505.1568 358.1222 358.1224 0 0.0 0.00 +bbCID MS, 49.0-140.0eV, 7.0-7.1min #838-850 +bbCID MS, 49.0-140.0eV, 7.0-7.1min #842-850 +bbCID MS, 49.0-140.0eV, 7.1-7.1min #852-856 177.0556 3000 84.9617 84.9617 3000 4000 84.9601 2000 2000 2000 1000 297.0926 1000 297.0941 423.0928 204.9499 0 0 0 100 200 300 400 500 m/z 100 200 300 400 500 600m/z 100 200 300 400 500 600m/z

Intens. +MS, 7.8-8.0min #943-959 Intens. +MS, 7.8-8.1min #939-971 Intens. +MS, 8.2-8.3min #985-993 x10 4 x104 x104 84.9615 325.1419 359.1261 0.8 2.0 [M+H]+ 0.8 84.9603 [M+H]+ 0.6 2,17-Bidecarbosy-2,3-dehydro-neobetanin 1.5 0.6 161.0151 Leucine-betaxanthin Phenylalanine-betaxanthin 0.4 1.0 0.4 161.0126 325.1464 [M+H]+ 84.9601 0.2 459.1501 0.5 161.0128 0.2 398.1376 360.2206 274.0706 0.0 0.0 0.0 +bbCID MS, 49.0-140.0eV, 7.9-8.0min #948-960 +bbCID MS, 49.0-140.0eV, 7.9-8.0min #946-966 +bbCID MS, 49.0-140.0eV, 8.2-8.3min #982-996 4000 84.9613 84.9602 84.9601 3000 3000 3000 110.0610 2000 2000 2000 130.0656 1000 1000 1000 389.0997 204.9497 325.1420 204.9470 403.0880 0 0 0 50 100 150 200 250 300 350 400 450 m/z 100 150 200 250 300 350 m/z 50 100 150 200 250 300 350 400 450 m/z

Intens. +MS, 8.5-8.7min #1027-1041 Intens. +MS, 9.3-9.5min #1123-1137 Intens. +MS, 9.6-9.6min #1149-1155 x104 x104 8000 84.9603 84.9604 84.9604 2-Decarbosy-2,3-dehydro-neobetanin 0.8 341.0800 6000 0.6 [M+H]+ 0.6 4000 161.0130 6’-feruloyl-betanin 161.0128 297.0892 503.1336 0.4 + 0.4 161.0128 6’-feruloyl-isobetanin [M+H] + 525.2931 [M+H] 2000 0.2 727.2053 0.2 315.1081 727.2044 0 0.0 0.0 +bbCID MS, 49.0-140.0eV, 8.5-8.7min #1026-1042 +bbCID MS, 49.0-140.0eV, 9.3-9.5min #1122-1140 +bbCID MS, 49.0-140.0eV, 9.5-9.7min #1144-1162 4000 4000 84.9603 4000 84.9603 84.9604 389.1013 3000 3000 3000

2000 2000 2000 389.1014 1000 1000 295.0733 1000 525.2930 445.0980 621.1340 677.1609 0 0 0 100 200 300 400 500 600 m/z 100 200 300 400 500 600 700 m/z 100 200 300 400 500 600 700 m/z Figure B-13. Identified bioactive compounds with retention times from 7.0 to 9.6 min, from conventional and organic red and golden beet samples.

139