1-s2 0-S0308814620310840-main

Prévia do material em texto

Contents lists available at ScienceDirect
Food Chemistry
journal homepage: www.elsevier.com/locate/foodchem
Microfiltered red–purple pitaya colorant: UPLC-ESI-QTOF-MSE-based
metabolic profile and its potential application as a natural food ingredient
Ana Carolina Viana de Limaa, Ana Paula Dionisiob,⁎, Fernando Antonio Pinto de Abreub,
Gisele Silvestre da Silvab, Rodolfo Dantas Lima Juniorc, Hilton César Rodrigues Magalhãesb,
Deborah dos Santos Garrutib, Idila Maria da Silva Araújob, Adriana Guirado Arturb,
Carlos Alberto Kenji Taniguchib, Maria do Carmo Passos Rodriguesa, Guilherme Julião Zocolob
a Department of Food Engineering, Federal University of Ceará, 60356-000 Fortaleza, Ceará, Brazil
b Embrapa Agroindústria Tropical, Sara Mesquita Street, 2270, 60511-110 Fortaleza, Ceará, Brazil
c Biotechnology and Mass Spectrometry Research Group, Federal University of Ceará, 60440-900 Fortaleza, Ceará, Brazil
A R T I C L E I N F O
Chemical compounds studied in this article:
Phyllocactin (PubChem CID: 101056997)
Sucrose (PubChem CID: 5988)
Betanine (PubChem CID: 12300103)
Quercetin (PubChem CID: 528045)
Luteolin (PubChem CID: 5280445)
Keywords:
Hylocereus polyrhizus (F.A.C. Weber) Britton &
Rose
Storage conditions
Chemometric methods
Colorant properties
Yogurt
A B S T R A C T
Complete characterization of microfiltered red–purple pitaya colorant (MRPPC) and its potential applications in
foods is described. Using sensorial analysis, products that use carmine or beetroot dye as a food colorant in their
formulations were compared. The effect of storage under refrigeration on the microbiological, physicochemical,
and chemical changes of MRPPC were evaluated. The results showed that UPLC-ESI-QTOF-MSE was effective for
the simultaneous determination of twenty metabolites, putatively identified as carbohydrates, flavonoids, and
betalains. The MRPPC was shown to have microbiological and physicochemical stability through twelve weeks
of storage, and chemometric analyses efficiently distinguished the metabolic profile in each storage period.
Sensory analysis revealed that the MRPPC was useful as a food colorant in yogurt, where it improved color
quality without affecting aroma and other characteristics. These results indicate that MRPPC is promising food
ingredient as a natural red–purple colorant.
1. Introduction
Color plays an important role in enhancing the aesthetic appeal of
food products. Colorants are commonly used to recover the loss of
natural food color as a result of food processing procedures (e.g., heat
treatment, acidification, etc.) and enhance the appearance of food
products (Yee & Wah, 2017). Public concern about possible or proven
harmful effects of artificial food colorants has motivated the search for
natural sources of colorants (Sigurdson, Tang, & Giusti, 2017). Conse-
quently, natural pigments extracted from biological sources such as
plants, fungi, bacteria, and algae have attracted significant attention.
Recently, the use of natural colorant carmine, a pigment derived
from the scale insect cochineal (Dactylopius coccus Costa), has received
widespread criticism because of to its “non-vegan” origin, undesired
aluminum content of carmine lakes, recurring microbiological issues,
and its ability to induce allergic reactions (Schweiggert, 2018). The
https://doi.org/10.1016/j.foodchem.2020.127222
Received 16 March 2020; Received in revised form 27 May 2020; Accepted 31 May 2020
Abbreviations: MRPPC, Microfiltered red–purple pitaya colorant; UPLC-ESI-QTOF-MSE, ultra-performance liquid chromatography-quadrupole time-of-flight mass
spectrometry; iPCA, interactive principal component analysis; HCA, hierarchical cluster analysis; Heatmap2, two-way heatmap analysis; GAE, gallic acid equivalent;
SD, standard deviation; HS-SPME, headspace solid-phase microextraction; PCs, principal components; 3D, three dimensions; GC–MS, gas chromatograph equipped
with a mass spectrometer detector; tR, mass data (m/z) and retention time; PPO, polyphenol oxidase; Cfu, (colony-forming unit); ΔE, difference in color; BPI, base
peak intensity; MRPPCT(n), where (n): n= 0 1 2 and 3 refer to period of storage MRPPCT0 after processing MRPPCT1 after four weeks of storage MRPPCT2 after
eight weeks of storage and MRPPCT3 after twelve weeks of storage similarity index (SI) and mass error = (detected m/z –theoretical m/z)/ theoretical m/z x 106 ppm
⁎ Corresponding author.
E-mail addresses: carolv6lima@gmail.com (A.C.V.d. Lima), ana.dionisio@embrapa.br (A.P. Dionisio), Fernando.abreu@embrapa.br (F.A.P.d. Abreu),
gihchemistry@gmail.com (G.S.d. Silva), rodolfodantasquimica@alu.ufc.br (R.D. Lima Junior), hilton.magalhaes@embrapa.br (H.C.R. Magalhães),
deborah.garruti@embrapa.br (D.d.S. Garruti), idila.araujo@embrapa.br (I.M.d.S. Araújo), driguirado@yahoo.com.br (A.G. Artur),
carlos.taniguchi@embrapa.br (C.A.K. Taniguchi), carminha@ufc.br (M.d.C.P. Rodrigues), guilherme.zocolo@embrapa.br (G.J. Zocolo).
Food Chemistry 330 (2020) 127222
Available online 02 June 2020
0308-8146/ © 2020 Elsevier Ltd. All rights reserved.
T
http://www.sciencedirect.com/science/journal/03088146
https://www.elsevier.com/locate/foodchem
https://doi.org/10.1016/j.foodchem.2020.127222
https://doi.org/10.1016/j.foodchem.2020.127222
mailto:carolv6lima@gmail.com
mailto:ana.dionisio@embrapa.br
mailto:Fernando.abreu@embrapa.br
mailto:gihchemistry@gmail.com
mailto:rodolfodantasquimica@alu.ufc.br
mailto:hilton.magalhaes@embrapa.br
mailto:deborah.garruti@embrapa.br
mailto:idila.araujo@embrapa.br
mailto:driguirado@yahoo.com.br
mailto:carlos.taniguchi@embrapa.br
mailto:carminha@ufc.br
mailto:guilherme.zocolo@embrapa.br
https://doi.org/10.1016/j.foodchem.2020.127222
http://crossmark.crossref.org/dialog/?doi=10.1016/j.foodchem.2020.127222&domain=pdf
search for alternatives sources of carmine has gained momentum
worldwide because it is one of the most commonly used colors for fruit
preparations and dairy products (e.g., strawberry yogurt (Roca,
Lemonnier, & Roubille, 2015)).
Some major categories of plant pigments include anthocyanins and
other flavonoids, carotenoids, chlorophylls, and betalains. The latter
are a class of natural pigments comprising yellow betaxanthins and
betacyanins. For a long time, red beetroot has been considered as the
only source of betalains and used exclusively to fulfill 10% of the total
global demand of food colorants (Slimen, Najar, & Abderrabba, 2017).
However, beetroot pigments have major drawbacks owing to the co-
presence of aroma-intense off-flavors, such as earthy geosmin and
several pyrazine derivatives, which are not favored by some consumers
(Schweiggert, 2018).
In recent years, promising new sources of betalains have been re-
ported (Esatbeyoglu, Wagner, Schini-Kerth, & Rimbach, 2015; Slimen
et al., 2017), including the Hylocereus species. In this context, pitaya
(Hylocereus polyrhizus (F.A.C. Weber) Britton & Rose) or dragon fruit,
has attracted attention as a potential source of natural colorants be-
cause of to its red–purple skin and flesh color (Santos et al., 2020), in
addition to its functional properties such as anxiolytic activity (Lira,
Dionísio, Holanda, & Marques, 2020). In terms of agronomy and en-
vironmental conditions, pitaya grows and multiplies easily in arid/dry
lands, which implies a lower investment for its cultivation. Therefore,
these plants can be used as a source of phytochemicals and as animal
feed after colorant extraction (Slimen et al., 2017). In this context,
betalain extracted from pitaya as an alternative source of red beetroot
betalain is optimistic.
In this study, we investigated the complete characterization of mi-
crofiltered red–purple pitaya colorant (MRPPC) and its potential ap-
plication in foods using sensorial analysis, which involved comparing
products that use carmine or beetroot dye as food colorants in their
formulations. The storage stability of MRPPC under refrigeration was
also evaluated. In addition, the UPLC-ESI-QTOF-MSE technique was
combined with multivariatedata analysis models (interactive principal
component analysis (iPCA), hierarchical cluster analysis (HCA), and
two-way heatmap analysis (Heatmap2)) to determine the correlation
between the chemical profile and storage period. These results can be
used to elucidate the properties of MRPPC as a natural food colorant.
2. Materials and methods
2.1. Chemicals
All chemicals were of analytical or higher grade and purchased from
Sigma-Aldrich Canada Ltd. (Oakville, ON, Canada). Aqueous solutions
were prepared with water purified by a Milli-Q System (Millipore Lab.,
Bedford, MA, USA).
2.2. Preparation of the MRPPC
The pitaya (Hylocereus polyrhizus (F.A.C. Weber) Britton & Rose)
was supplied by Frutacor, located in Vale do Jaguaribe, Ceará State,
Brazil (05°53′26″S, 38°37′19″W). After washing and sanitizing, the fruit
was cut in quarters and the peel was manually removed before the
pulping process (the fruit was strained through a 0.8ʹʹ sieve) (Santos
et al., 2020). The procedure to obtain the MRPPC was developed by
Embrapa Agroindústria Tropical (Fortaleza, Ceará State, Brazil).
Briefly, the pitaya pulp was treated with Pectinex® Ultra AFP (2000 mg
L-1, treated at 4 °C, during 45 min at 150 rpm) and filtered through a
microfiltration system (Pall industry, model Membralox, Saint-Ger-
main-en-Laye, France) (0.2 µm pore diameter). Then, the pitaya juice
was concentrated by evaporation (40 ± 5 °C) under vacuum pressure
(700 mmHg) until 63 °Brix was achieved. The MRPPC was stored at
7 ± 2 °C and subjected to specific analysis.
2.3. Methods of analyses
2.3.1. Proximate composition
The protein content was determined using the Dumas method (VELP
Scientific, model Dumas NDA 702). The total lipid content and moisture
in the samples were estimated by following the Am 5–04 (AOCS, 2005)
method using a high pressure and high temperature extraction system
(Ankom, model XT15). Further, ash content was determined by in-
cinerating the sample at 550 °C in a muffle furnace for 6 h (923.03
AOAC) and carbohydrate by difference (AOAC, 2005).
2.3.2. Mineral analyses
Samples were digested following the procedures described by
Miyazawa, Pavan, Muraoka, Carmo, and Melo (2009) with some
modifications. An aliquot (1.0 g) was placed into a digestion tube and
reacted overnight with nitric acid and perchloric acid (3:1, v/v). Di-
gestion was carried out using a digester dry block at 200 °C for 4 h.
After cooling, the volume was made up to 50 mL with deionized water
and filtered through a quantitative filter paper. Reagent blanks were
prepared in a similar manner to the samples. The digests were analyzed
by inductively coupled plasma optical emission spectrometry (Agilent,
model 5100, Mulgrave, Australia) for phosphorus, potassium, calcium,
magnesium, sulfur, sodium, copper, iron, zinc, and manganese.
2.3.3. Water activity, soluble solids, and color
Water activity (aw) was measured at 25 °C using a water activity
meter (Aqualab Decagon Devices Inc. Pullman, model Pawkit,
Washington, USA). Soluble solids content (°Brix) was determined using
a refractometer (Atago, model Pocket PAL-3, Tokyo, Japan) at 20 °C, as
recommended by AOAC (2005). Color was measured with a colorimeter
(HunterLab, model ColorQuest XE, Virginia, USA) and expressed by
color coordinates: L* (white or bright/dark), a* (red/green), and b*
(yellow/blue). The color differences (ΔE) were calculated using Eq. (1),
according to Mokrzycki and Tatol (2011):
= ∗ + ∗ + ∗E L a bΔ ((Δ ) (Δ ) (Δ ) )2 2 2 1/2 (1)
2.3.4. pH and titratable acidity
The pH was measured using a digital pH meter (Mettler Toledo,
model F20, Ohio, USA). Titratable acidity was assayed using an auto-
matic titrator (Hanna Instruments, model HI90C1-02, Romania) and the
results were expressed as grams of malic acid per 100 g of sample
weight (AOAC method, 2005).
2.3.5. Total polyphenols
Total polyphenols were determined by the Folin–Ciocalteu method
(Obanda, Owuor, & Taylor, 1997) and the results were expressed as μg
gallic acid equivalent (GAE) per g of sample.
2.3.6. UPLC-ESI-QTOF-MSE measurements
The UPLC-ESI-QTOF-MSE analysis was performed using an Acquity
UPLC-QTOF-MS (Xevo™, Waters®, Milford, MA, USA) system with an
electrospray ionization (ESI) source. Mobile phases were water with
0.1% formic acid (A) and acetonitrile with 0.1% formic acid (B). The
gradient was 0–15 min, 2–95% B; 15.1–17 min, 100% B;
17.1–19.1 min, 2% B. A Waters Acquity UPLC BEH column
(150 × 2.1 mm, 1.7 µm) with flow rate of 0.4 mL min−1 was main-
tained at 40 °C. The sample injection volume was 5 μL. The MS con-
ditions were as follows: negative ionization mode; acquisition range:
110–1180 Da; source temperature: 120 °C; desolvation gas temperature:
350 °C; desolvation gas flow: 500 L h−1; extract cone voltage: 0.5 V;
capillary voltage: 2.6 kV; acquisition mode by MSE. Leucine enkephalin
was used as lock mass. The equipment was controlled by Masslynx 4.1
(Waters® Corporation) software.
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
2
2.3.7. Chemometric analysis of data from UPLC-QTOF-MSE
Data processing was performed before statistical analysis for all
UPLC-QTOF-MSE data obtained using MarkerLynx XS (Waters
Corporation) software and MetaboAnalyst 4.0 software (Chong,
Wishart & Xia, 2019). For data collection to alignment, deconvolution,
and obtaining the centralized data matrix, the MakerLynx XS software
was used. For the data collection step, the method parameters were
defined as the retention time interval (tR, 0.55–12.0 min) and mass
interval (110–800 Da). For data analysis, a data matrix containing the
detected peaks was generated using data pairs of mass data (m/z) and
retention time (tR) as identifiers for each peak (tR-m/z) as well as the
intensity of the peaks, names of the samples, and groups in which they
are contained (MRPPCT0, MRPPCT1, MRPPCT2, and MRPPCT3, where
each MRPPCT(n) consists of five replicates).
The resulting data matrix was submitted to MetaboAnalyst software
in .csv format, where data filtering was applied using standard devia-
tion (SD) to prevent noise and variables with low intensity from ne-
gatively influencing the results. The ion intensities were normalized by
logarithmic transformation and scaled via the Pareto scale (centered on
the mean and divided by the square root of SD of each variable) to make
the individual characteristics more comparable. Subsequently, un-
supervised data analyses – which do not require prior knowledge about
the nature of the samples, were performed. These analyses are able to
provide groupings of the sample set based on the similarity of the
variables involved in the study, making it possible to identify simila-
rities and differences between the groups obtained.
The first stage of multivariate analysis consisted of the application
of HCA, which is based on the reduction of the dimensionality of the
data, to obtain clusters between samples containing similar variables.
Next, a time-series analysis was performed, based on the visualization
of the formation of significant patterns involving samples analyzed at
different storage periods. For the latter, interactive principal compo-
nent analysis (iPCA) and two-way heatmap (Heatmap2) analysis were
used. Ward's algorithm and Euclidean distance were used for the HCA
and Heatmap tools, respectively, to analyze the data set. The applica-
tion of chemometric methods was limited to the metabolites tentatively
identified between 0 min and 10.5 min.
2.3.8. Microbiological analyses
The presence of total coliform and Escherichia coli (Feng et al.,
2013), and mesophilic aerobic, mold, and yeast counts (Tournas, Stack,
Mislivec, Koch, & Bandler, 2001) were determined in the MRPPC. To
verify that the MRPPC was suitable for human consumption, micro-
biological analysis was performed before the sensory analyses.
2.3.9. Storage stability of the MRPPC under refrigeration
To evaluate the effects of storage at 7 ± 2 °C on the stability of the
MRPPC, the following analyses were performed: water activity,soluble
solids, color (L*, a*, and b* coordinates, and ΔE), pH, and titratable
acidity, total polyphenols, phenolic profile by UPLC-ESI-QTOF-MSE,
and microbiological analyses, as described previously. All the analyses
were performed after processing and every four weeks, for a period of
twelve weeks. The samples were named as follows: MRPPCT(n); where
(n): n = 0, 1, 2 and 3 refer to period of storage; MRPPCT0: after pro-
cessing; MRPPCT1: after four weeks of storage; MRPPCT2: after eight
weeks of storage and MRPPCT3: after twelve weeks of storage.
2.4. Sensory analyses
2.4.1. Focus group
The focus group was tasked with suggesting applications of the
MRPPC in food products. The test was conducted according to Dutcosky
(2013), in two sessions, with eight and ten participants, respectively,
ranging from 18 to 25 years old, recruited from their involvement with
correlated areas, such as gastronomy, food science or food engineering,
and agronomy. A moderator and note-taker also participated, and the
discussions were recorded using audio. The terms were described by the
participants as well as suggestions for the application of the MRPPC.
Finally, the most frequent food applications were selected to apply in a
test-product.
2.4.2. Affective tests of yogurt with MRPPC
A commercial natural yogurt was used for sensory acceptance, as
defined in the focus group. The yogurt was prepared with the addition
of 0.5, 1.0, 1.5, and 2% of the MRPPC (named as Formulations A, B, C,
and D, respectively). The tests were performed with 51 untrained pa-
nelists, 50% women, with ages ranging from 18 to 55 years old. The
sensory protocols were previously approved by the National Research
Ethics Commission (No 3.117.036). The samples were served at
10 + 2 °C, in disposable cups labeled with random three-digit numbers
and presented in a balanced order. The sensory test for color was pre-
sented in Petri dishes, under white lights, for better visualization. Tests
were described below:
(a) Just right scale. Panelists expressed their opinion about what
they thought to be the ideal color for a red-colored yogurt, using a 7-
point scale (1 = much less than ideal, 4 = just right, and 7 = much
more than ideal). In this test, two different commercial yogurt samples
were included, totalizing seven formulations (Formulation E, commer-
cial yogurt containing beetroot colorant, and Formulation F, commer-
cial yogurt containing carmine colorant);
(b) Acceptance and preference tests. The four formulations con-
taining the MRPPC were submitted to acceptance tests for aroma and
color, using a 9-point structured hedonic scales (1 = ‘disliked ex-
tremely, 5 = neither like nor dislike, and 9 = ‘liked extremely’). In
addition, the panelists ranked the samples in order of their preference
regarding the color (preference ranking test).
(c) Intensity of off-flavor. In the same session, panelists were also
asked to rate the intensity of any flavor that is not characteristic in a
natural yogurt using a 9-cm non-structure scale (0 = “none” to 9 =
“strong”).
(d) Purchase intent. A 5-point structured scale (1 = “certainly
would not buy” to 5 = “certainly would buy”), was used to evaluate
consumers’ willingness to buy the product if it was for sale.
2.4.3. Difference tests
A Triangle test was used to determine if panelists perceived any
difference in aroma between the formulated yogurts with MRPPC and
the control (commercial yogurt, without MRPPC). Only two formula-
tions were tested (C and D).
2.4.4. Volatile compounds of yogurt formulated with the MRPPC
The volatile compounds in yogurt and MRPPC Formulations A–D
and the control were compared. For this, 1.20 g of NaCl was added to
4 g of each sample material. This method was adapted from the report
by Dan et al. (2017). Prior to the analysis, the fiber was conditioned
according to the temperature recommended by the manufacturer. The
samples were stirred for 5 min at 50 °C to achieve equilibrium of the
volatile compounds. Subsequently, the volatile compounds were iso-
lated from the matrix by headspace solid-phase microextraction (HS-
SPME) using the DVB/CAR/PDMS 50/30 μm × 1 cm fiber (Supelco,
Bellefonte, PA, USA) for 60 min at 50 °C. The fiber was then im-
mediately inserted into the injection port (splitless mode) of a 7890B
gas chromatograph (GC, Agilent Technologies, Inc., Palo Alto, CA, USA)
equipped with a mass spectrometer detector (model 5977A). The
chromatography column employed was Rtx-5MS (30 m size, 0.25 mm
internal diameter, 0.25 μm film thickness). Helium was used as the
carrier gas at the flow rate of 1 mL/min. The GC oven temperature was
initially maintained at 40 °C for 5 min and increased at a rate of 4 °C/
min up to 140 °C, maintained for 5 min, ramped at 10 °C/min up to
200 °C, maintained for 5 min, and again increased at a rate of 10 °C/min
up to 270 °C, and maintained for another 5 min. The interface tem-
perature between the chromatograph and selective mass detector was
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
3
270 °C and ionization was performed by electron impact (70 eV) with
the ion source maintained at 150 °C.
2.4.5. Characterization of yogurt without (control) and with the MRPPC
To support the results indicated by the sensorial analysis and
characterization of the products, some chemical and physicochemical
analyses were performed for yogurt without (control) and with the
MRPPC, as follows: pH, titratable acidity, and color (L*, a*, and b*
coordinates, and ΔE). These analyses are described in sections 2.3.4 and
2.3.5.
2.5. Statistical analysis
The peak areas of the volatile compounds obtained from their
chromatograms were normalized by the sum treated and staggered
according to Auto scaling. Chemometric analysis was performed using
Metaboanalyst 3.0 (www.metaboanalyst.ca) based on the non-normal-
ized correlation matrices of normalized data. The other results were
subjected to analysis of variance (ANOVA) at 5% probability by the F
test (P < 0.05) and Tukey's multiple-comparison test (P < 0.05)
using XLSTAT software (version 18.01, New York, NY, USA).
3. Results and discussion
3.1. Compositional characteristics of the MRPPC
The characteristics of the MRPPC are presented in Table 1. The
product had low pH values (3.88 ± 0.01), acidity of 1.61 ± 0.03%,
water content of 38.15 ± 0.62%, and water activity (aw) of 0.82.
According to Beuchat et al. (2013), foods with aw < 0.85 are con-
sidered to be low-aw foods, considering that the minimum aw for growth
of most bacteria is ~ 0.87. This result is related to the higher content of
soluble solids (63.10 ± 0.08 °Brix). In addition, the MRPPC contained
low concentrations of protein (1.31 ± 0.04%), lipids (0.17 ± 0.01%),
and ash (2.06 ± 0.28%), and high carbohydrate content
(58.32 ± 0.02%). These results are in accordance with those reported
by Khalili et al. (2011) and Chik, Bachok, and Babaet (2011), who
evaluated the pitaya pulp and obtained protein, lipid, ash, and carbo-
hydrate contents in the range of 0.16–5.2%, 0.23–0.1%, 0.70–4.1%,
and 1.48–90.60%, respectively. The variation in these concentrations
was attributable to the cultivars used, physiological factors (e.g., plant
age), and harvest and post-harvest conditions.
The minerals in the MRPPC were potassium (14.31 g kg−1), phos-
phorus (1.02 g kg−1), calcium (0.10 g kg−1), magnesium (1.48 g kg−1),
sodium (0.22 g kg−1), copper (3 mg kg−1), iron (10 mg kg−1), zinc
(8 mg kg−1), and manganese (6 mg kg−1). Among these minerals,
potassium was present in the highest concentration. This mineral re-
duces blood pressure and risks of cardiovascular disease, stroke, and
coronary heart disease in adults (Aburto, Hanson, Gutierrez, Hooper,
Elliott, & Cappuccio, 2013). The World Health Organization (WHO,
2012) recommends potassium intake of at least 3.51 g/day for adults.
Even if the MRPPC potassium concentration is high, the colorant will be
used in food in small concentrations, so the MRPPC has little impact on
the mineral quality of the finalproduct to which it is added.
The metabolic profile of MRPPC was assessed by UPLC-ESI-QTOF-
MSE. The structures were tentatively identified based on the exact mass
value (molecular formula) and typical mass fragments reported in the
literature. All bibliographic research in the search for pitaya metabo-
lites was based on the chemotaxonomy of pitaya (Hylocereus polyrhizus
(F.A.C. Weber) Britton & Rose), in which the gender, family, and spe-
cies are considered. The UPLC-QTOF-MSE chromatographic and MS
data obtained are summarized along with the retention time, theore-
tical mass, molecular formula, observed mass, MS, and MS/MS frag-
ments in Table 2. In total, twelve compounds were putatively identified
as carbohydrates, flavonoids, and betalains (2, 3, and 7, respectively).
Among these, betacyanins are the target of our study as they are re-
sponsible for the color of the MRPPC. The data for each identified
compound is discussed in section 3.2.
3.2. Microbiological, physicochemical, and chemical stability of the MRPPC
stored under refrigeration
Table 3 shows the microbiological, physicochemical, and chemical
stability of the MRPPC stored under refrigeration at 7 ± 2 °C for
twelve weeks.
The MRPPC showed higher yeast and mold counts in the last period
(twelfth week). For this reason, all analyses involved in the stability of
the colorant were performed before this time. This could occur because
the MRPPC was concentrated in a rotary evaporator at 40 °C, and this
temperature is inadequate for the inactivation of heat-sensitive micro-
organisms such as mold and yeasts. The water activity was reduced in
the process, but it served only as a mild preservative. By week-12, the
colorant stored at 7 °C had yeast and mold count of 1.0 × 104 cfu/mL
(Table 3), which is undesirable.
In all storage periods, the soluble solids remained at ~ 63 °Brix.
Thus, the pH remained acidic (3.85–3.96), and the titratable acidity
ranged from 1.61 to 1.81 (% in malic acid) in the first four weeks and
remained stable until the end of the period. A higher degradation of the
phenolic compounds of the MRPPC was observed after four weeks
(38.5%), with a loss of almost 52% at the end of the period. The total
phenolic content decreased the most rapidly during the first period of
the entire storage period. This could be ascribed to the damage of the
cell structure of pitaya during the pulping process. Consequently,
polyphenol oxidase (PPO, EC 1.14.18.1), which is present in high
concentrations in pitaya (Santos et al., 2020), could interact with the
phenolic compounds and catalyze their oxidation to quinones in the
presence of molecular oxygen (Huang et al., 2005). Thus, the data in-
dicates the high susceptibility of these compounds to degradation,
which is in accordance with previous studies (Deng et al., 2018). For-
tunately, as the phenolic contents decreased during storage, the color
remained stable in all the evaluated periods, measured by the L*, a*,
and b* coordinates. In addition, the difference in color (ΔE) was< 1.0
in all storage periods, considerably imperceptible to the human eyes
Table 1
Microfiltered red–purple pitaya colorant (MRPPC) compositional char-
acteristics.
Characteristics Contents
Proximate composition (%)
Protein 1.31 ± 0.04
Moisture 38.15 ± 0.62
Ash 2.06 ± 0.28
Lipids 0.17 ± 0.01
Carbohydrates 58.32 ± 0.02
General characteristics
L* 0.53 ± 0.03
a* 1.20 ± 0.08
b* 0.2 ± 0.10
ΔE 31.85
pH 3.88 ± 0.01
Acidity (% malic acid) 1.61 ± 0.03
Soluble solids (°Brix) 63.10 ± 0.08
Total polyphenols(GAE 100 g−1) 118.57 ± 0.42
Aw 0.82 ± 0.01
Mineral composition
Phosphorus (g kg−1) 1.02 ± 0.05
Potassium (g kg−1) 14.31 ± 0.5
Calcium (g kg−1) 0.41 ± 0.02
Magnesium (g kg−1) 1.47 ± 0.06
Sulfur (g kg−1) 0.14 ± 0.01
Sodium (g kg−1) 0.22 ± 0.01
Copper (mg kg−1) 2.75 ± 0.5
Iron (mg kg−1) 9.75 ± 0.5
Zinc (mg kg−1) 8.00 ± 0.01
Manganese (mg kg−1) 6.00 ± 0.01
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
4
Ta
bl
e
2
U
PL
C
-Q
-T
O
F-
M
SE
ch
ro
m
at
og
ra
ph
ic
an
d
m
as
s
sp
ec
tr
om
et
ry
da
ta
of
m
ic
ro
fi
lt
er
ed
re
d–
pu
rp
le
pi
ta
ya
co
lo
ra
nt
(M
R
PP
C
0,
M
R
PP
C
1,
M
R
PP
C
2
an
d
M
R
PP
C
3)
fr
om
pi
ta
ya
(H
yl
oc
er
eu
s
po
ly
rh
iz
us
(F
.A
.C
.W
eb
er
)
Br
it
to
n
&
R
os
e)
ob
ta
in
ed
by
U
PL
C
-Q
TO
F-
M
SE
in
th
e
po
si
ti
ve
io
ni
za
ti
on
m
od
e.
n°
t R
(m
in
)
Po
si
ti
ve
io
n
m
od
e
(M
S)
Fr
ag
m
en
t
(M
S2
)
M
ol
ec
ul
ar
Fo
rm
ul
a
Te
nt
at
iv
e
id
en
ti
fi
ca
ti
on
M
ic
ro
fi
lt
er
ed
re
d–
pu
rp
le
pi
ta
ya
co
lo
ra
nt
(M
R
PP
C
)
R
ef
er
en
ce
A
dd
uc
t
io
n
O
bs
er
ve
d
C
al
cu
la
te
d
M
as
s
Er
ro
r
(p
pm
)
T0
T1
T2
T3
1
0.
82
[M
+
K
+
H
2
O
]+
39
9.
08
92
39
9.
09
01
−
2.
25
21
9.
02
19
20
3.
05
33
C
1
2
H
2
4
O
1
2
Su
cr
os
e(
D
is
ac
ch
ar
id
e)
+
+
–
–
Li
ra
et
al
.(
20
20
),
W
ei
et
al
.
(2
01
9)
2
0.
88
[M
+
H
]+
66
7.
23
01
66
7.
22
97
0.
60
70
5.
18
32
54
3.
14
73
39
9.
09
77
21
9.
02
78
20
3.
05
63
16
3.
06
28
C
2
4
H
4
2
O
2
1
M
al
to
te
tr
ao
se
or
St
ac
hy
os
e
(T
et
ra
sa
cc
ha
ri
de
)
+
+
–
–
Li
ra
et
al
.(
20
20
),
W
ei
et
al
.
(2
01
9)
,W
ic
hi
en
ch
ot
et
al
.
(2
01
0)
3
0.
99
M
+
63
7.
15
24
63
7.
15
17
1.
10
59
3.
16
92
54
9.
18
21
55
1.
14
31
38
9.
10
03
C
2
7
H
2
9
N
2
O
1
6
+
Ph
yl
lo
ca
ct
in
+
+
–
–
Li
ra
et
al
.(
20
20
),
W
yb
ra
ni
ec
et
al
.(
20
10
)
4
2.
00
[M
+
H
]+
55
1.
15
13
55
1.
15
13
0.
00
38
9.
02
39
C
2
4
H
2
6
N
2
O
1
3
Be
ta
ni
ne
+
+
–
–
W
yb
ra
ni
ec
et
al
.(
20
10
5
2.
40
[M
+
H
]+
63
7.
15
16
63
7.
15
17
−
0.
16
55
1.
15
37
59
3.
16
33
38
9.
10
49
34
5.
10
81
C
2
7
H
2
8
N
2
O
1
6
Ph
yl
lo
ca
ct
in
is
om
er
+
+
–
–
Li
ra
et
al
.(
20
20
),
W
yb
ra
ni
ec
et
al
.(
20
10
)
6
2.
47
[M
+
H
]+
63
7.
15
00
63
7.
15
17
−
2.
67
55
1.
15
37
38
9.
10
49
34
5.
09
39
C
2
7
H
2
8
N
2
O
1
6
Ph
yl
lo
ca
ct
in
is
om
er
+
+
–
–
Li
ra
et
al
.(
20
20
),
W
yb
ra
ni
ec
et
al
.(
20
10
)
7
2.
55
[M
+
H
]+
76
9.
19
43
76
9.
19
39
0.
52
63
7.
15
36
59
3.
15
02
50
5.
15
63
38
9.
15
19
C
3
2
H
3
7
N
2
O
2
0
+
A
pi
os
yl
-m
al
on
yl
-b
et
an
in
+
+
–
–
Li
ra
et
al
.(
20
20
),
W
yb
ra
ni
ec
et
al
.(
20
10
)
8
3.
06
[M
+
H
]+
59
3.
16
18
59
3.
16
19
−
0.
16
59
3.
16
73
38
9.
10
40
34
5.
11
29
C
2
6
H
2
9
N
2
O
1
4
+
6′
-M
al
on
yl
-2
′-
de
sc
ar
bo
xy
-b
et
an
in
is
om
er
+
–
–
–
Li
ra
et
al
.(
20
20
),
G
ar
cí
a-
C
ru
z
et
al
.(
20
17
).
9
3.
11
M
+
59
3.
16
18
59
3.
16
19
−
0.
16
54
9.
18
21
34
5.
16
00
C
2
6
H
2
9
N
2
O
1
4
+
6′
-M
al
on
yl
-2
′-
de
sc
ar
bo
xy
-b
et
an
in
+
+
–
–
Li
ra
et
al
.(
20
20
),
G
ar
cí
a-
C
ru
z
et
al
.(
20
17
).
10
3.
59
[M
+
H
]+
46
5.
09
62
46
5.
09
54
1.
72
30
3.
10
09
C
2
1
H
2
0
O
1
2
Q
ue
rc
et
in
-3
-O
-h
ex
os
id
e
+
+
–
–
Li
ra
et
al
.(
20
20
),
A
m
ay
a-
C
ru
z
et
al
.(
20
19
)
11
4.
16
[M
+
H
]+
30
3.
05
05
30
3.
05
04
0.
33
–
C
1
5
H
1
0
O
7
Q
ue
rc
et
in
+
+
–
–
Y
i,
W
u,
W
an
g,
Y
e,
an
d
Zh
an
g
(2
01
1)
12
4.
39
[M
+
H
]+
41
5.
16
05
41
5.
16
04
0.
2
C
1
9
H
2
6
O
1
0
U
nk
no
w
n
13
4.
50
[M
+
H
]+
28
7.
05
66
28
7.
05
56
3.
48
–
C
1
5
H
1
0
O
6
Lu
te
ol
in
+
+
–
–
C
oh
en
et
al
.(
20
13
)
14
7.
51
[M
+
H
]+
27
9.
11
89
27
9.
11
92
−
1.
1
–
C
1
0
H
1
8
N
2
O
7
U
nk
no
w
n
+
+
–
–
Li
ao
tr
ak
oo
n
et
al
.(
20
13
)
15
7.
81
[M
+
N
a]
+
27
9.
09
66
27
9.
09
70
0.
4
11
9.
05
43
C
1
1
H
1
5
N
2
O
5
U
nk
no
w
n
+
+
–
–
16
8.
22
[M
+
H
]+
27
9.
10
11
27
9.
10
21
−
1.
0
–
C
1
8
H
1
4
O
3
U
nk
no
w
n
+
+
–
–
17
8.
30
[M
+
H
2
O
]+
27
4.
27
44
27
4.
27
46
−
0.
72
25
6.
26
35
C
1
6
H
3
6
N
O
2
U
nk
no
w
n
–
+
+
–
18
9.
11
[M
+
H
2
O
]+
35
8.
33
28
35
8.
33
21
1.
95
34
0.
32
25
C
2
1
H
4
3
N
O
3
U
nk
no
w
n
–
+
+
+
19
9.
27
[M
+
H
]+
40
3.
26
38
40
3.
26
37
0.
2
23
9.
14
68
C
2
8
H
3
4
O
2
U
nkno
w
n
–
+
+
–
20
9.
56
[M
+
H
2
O
]+
30
2.
30
58
30
2.
30
59
−
0.
33
28
4.
29
51
C
1
8
H
4
0
N
O
2
U
nk
no
w
n
–
+
–
–
21
9.
86
[M
+
N
a]
+
47
3.
31
44
47
3.
31
44
0.
00
43
7.
19
80
C
2
9
H
4
1
N
2
O
2
U
nk
no
w
n
–
+
+
–
*
M
et
ho
d
de
te
ct
io
n
lim
it
.M
R
PP
C
T0
:a
ft
er
pr
oc
es
si
ng
;M
R
PP
C
T1
:a
ft
er
fo
ur
w
ee
ks
of
st
or
ag
e;
M
R
PP
C
T2
:a
ft
er
ei
gh
tw
ee
ks
of
st
or
ag
e
an
d
M
R
PP
C
T3
:a
ft
er
tw
el
ve
w
ee
ks
of
st
or
ag
e.
W
it
h
eq
ua
ll
et
te
rs
,i
n
th
e
sa
m
e
lin
e,
do
no
t
di
ff
er
at
th
e
le
ve
l
of
5%
of
si
gn
ifi
ca
nc
e
fo
r
th
e
Tu
ke
y
te
st
.
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
5
(Mokrzycki & Tatol, 2011).
Although the difference in color was imperceptible to the human
eyes, some degradation of the key compounds of the MRPPC may have
occurred. These degradations can occur for different reasons, owing to
the fact that the betalains exhibit an optimum stability in the mildly
acidic pH range from 4 to 7 and the pH of the MRPPC was 3.85–3.96.
Degradation mechanisms under acidic conditions are still unclear, al-
though isomerized forms of betanin (isobetanin), deglycosylated forms
(betanidin), and 14,15-dehydrobetanin (neobetanin) have been ob-
served after acid treatment (Schweiggert, 2018). Thus, owing to its
acidic nature, the stability of each compound in the MRPPC was as-
sessed when it was stored under refrigeration. This information will be
used to determine the chromatic properties and tinctorial strength of
the MRPPC, for and help with color modulation by targeted betacyanin
degradation. The representative base peak intensity (BPI) chromato-
grams from MRPPC at different storage times are shown in Figure S1
(Supplementary material). Briefly, all twelve compounds were puta-
tively identified as carbohydrates, betalains, and flavonoids (2, 7, and 3
compounds, respectively). Thus, all these class of compounds will be
discussed separately, as follows.
3.2.1. Carbohydrates
The analysis of saccharides 1 and 2 (tR: 0.82 and 0.88, respectively)
was challenging because of possible association with water molecules
and sodium and potassium ions. The MS1 spectra showed a base peak at
m/z 399.0892 [C6H12O6 + K + H2O]+ and 667.2301[M + H]+, re-
spectively. In the MS2 spectra for ions 1 and 2, the base peak was found
at m/z 219 [glucose + K]+ and 203 [glucose + Na]+ (Lira et al.,
2020), respectively. Similar cationic ions have been observed for hexose
trisaccharide and hexose tetrasaccharide using matrix-assisted laser
desorption ionization quadrupole orthogonal time-of-flight mass spec-
trometry (Lee & Ni, 2019). The base peak at m/z 667.2301 represents
the molecular ion [M + K]+ that corresponds to tetrasaccharides such
as maltotetrose or stachyose (C24H42O21), which are commonly found
in Hylocereus polyrhizus (Lira et al., 2020). The MS2 spectra of meta-
bolite 2 showed a fragment peak at m/z 705.1832 corresponding to the
potassium adduct, [C24H42O21 + K]+. In addition, the peaks at m/z
543.1473, 399.0977, 219.0278, and 163.0628 were assigned to the
main glycosidic cleavage products C3, C2, and C1 formed via the
neutral loss of one, two, and three hexose moieties, respectively. The
mass loss was 486 Da (m/z 705.1832 [M + K]+ − 219.0278 [glu-
cose + K]+) and 326 Da (m/z 543.1473 [M + K]+ − 219.0278
[glucose + K]+), corresponding to the loss of a disaccharide and tri-
saccharide, respectively.
3.2.2. Betalains
Before starting the experiment (MRPPCT0 – Figure S1), seven
betalain derivatives (3–9) were found in the MRPPC, which have been
previously reported for the Hylocereus species (Table 2). It is important
to note that the degradation of the compounds responsible for the
characteristic color of pitaya was prioritized (Liao, Zhu, Zhong, & Liu,
2020).
The three phyllocactin isomeric forms (3, 5, and 6) were observed at
different retention times (tR: 0.99, 2.40, and 2.47 at m/z: 637.1524,
637.1516, and 637.1500, respectively). The expected protonated mo-
lecular fragment ions [M + H]+ of the pigments betanin (m/z 551) and
betanidin (m/z 389) were also observed for all tentatively identified
phyllocactin isomers. The technique of liquid chromatography separa-
tion did not allow us to distinguish the isomers from the compounds
identified unequivocally (Cai, Xing, Sun, & Corke, 2006).
The MS1 and MS2 spectra of metabolite 4 showed the presence of
[M + H]+ at m/z 551.1513 for betanin isomer (tR = 2.00). The
common fragment ion at m/z 389.0239 (551–162 [C6H12O6]) resulted
from the loss of the sugar (García-Cruz, Dueñas, Santos-Buelgas, Valle-
Guadarrama, & Salinas-Moreno, 2017).
Peak 7 (tR = 2.55 min) was tentatively identified as apiosyl-mal-
onyl-betanin at m/z 769.1943. The fragments ions observed at m/z
593.1502 (637–CO2), m/z 505.1563 (637–3CO2) and m/z 389.1519
(betanidin) agreed with those reported in the literature (Liao et al.,
2020).
Decarboxylation is common in thermal and oxidative processes of
betalains (Wybraniec et al., 2013). However, the cleavage of the car-
boxyl group in the malonyl portion of betacyanin 7 has not been re-
ported to date. The cleavage of the carboxyl groups occurs at positions
C-2, C-15, or C-17 of the betanidine/isobetanidine moiety
(C24H27N2O13) (Cai et al., 2006).
The MS1 data of peaks 8 and 9 indicated that this compound exists
in the cationic form (C26H29N2O14
+) at m/z 593.1618 (9, tR = 3.06 and
3.11 min). The MS2 spectra showed fragments at m/z 549.1821 (44 mu,
indicating loss of CO2, corresponding to a carboxyl portion) and
345.1600 (86 mu, corresponding to the loss of a malonylhexoside re-
sidue), which allowed identification of both peaks as 6ʹ-malonyl-2ʹ-
descarboxy-betanin (Imtiyaj Khan & Giridhar, 2015; García-Cruz et al.,
2017).
Representative MS1 spectra showing the structure of the base peaks
of phyllocactins isomers (3, 5, and 6), betanin (4), apiosyl-malonyl-
betanine (7), and 6′-malonyl-2′-decarboxy-betanine isomers (8 and 9),
and the main structures of the reported fragments are given in the
Supplementary Material (Figures S2–4).
3.2.3. Flavonoids
Compounds 10, 11, and 13 were tentatively identified as quercetin-
3-O-hexoside, quercetin, and lutein, respectively. The mass spectrum of
10 exhibited a protonated base peak [M + H]+ at m/z 465.0962
Table 3
Effects of refrigerated storage on the physicochemical, chemical and microbiological characteristics of the microfiltered red–purple pitaya colorant (MRPPC).
Characteristics MRPPCT0 MRPPCT1 MRPPCT2 MRPPCT3
Physicochemical and chemical
pH 3.88 ± 0.01b 3.89 ± 0.01b 3.96 ± 0.01a 3.85 ± 0.02c
Acidity (% malic acid) 1.61 ± 0.03b 1.82 ± 0.07a 1.87 ± 0.05a 1.79 ± 0.01a
Soluble solids (°Brix) 63.1 ± 0.08a 63.03 ± 0.04a 63.17 ± 0.04a 62.57 ± 0.18b
Total polyphenols (GAE 100 g−1) 118.57 ± 0.42a 72.9 ± 0.89b 68.79 ± 0.45c 56.3 ± 0.99d
L* 0.53 ± 0.02a 0.57 ± 0.04a 0.58 ± 0.03a 0.55 ± 0.04a
a* 1.24 ± 0.07a 1.18 ± 0.05a 1.06 ± 0.03a 1.05 ± 0.06a
b* 0.34 ± 0.09a 0.37 ± 0.01a 0.51 ± 0.04a 0.31 ± 0.13a
ΔE – 0.77 0.25 0.19
Microbiological
Aerophilic mesophiles (CFU/mL) Abcense 3.7 × 105 1.6 × 106 1.5 × 106
Fecal coliforms and E. coli (NMP/mL) < 3* < 3* < 3* < 3*
Mold and yeast (CFU/mL) < 10* 2.2 × 102 9.0 × 103 1.0 × 104
* Method detection limit. MRPPCT0: after processing; MRPPCT1: after four weeks of storage; MRPPCT2: after eight weeks of storage and MRPPCT3: after twelve
weeks of storage. With equal letters, in the same line, do not differ at the level of 5% of significance for the Tukey test.
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
6
(tR = 3.59 min). The typical fragment at m/z 303.1009 obtained by the
loss of the sugar moiety (Wang & Sporns, 2000) suggested the presence
of a glycosylated flavone. Therefore, molecule 10 was identified as
quercetin-3-O-hexoside (Amaya-Cruz et al., 2019; Lira et al., 2020).
Quercetin (11, tR = 4.16) and lutein (13, tR = 4.50) were tenta-
tively identified as protonated ions [M + H]+ from peaks at m/z
303.0505 and 287.0566,respectively. Luteolin (13) and quecertins (10
and 11) has already been observed in Hylocereus species (Cohen, Fait, &
Tel-Zur, 2013; Li, Meng, Zhu, & Li, 2019).
Metabolites with retention times above 8.30 min (17–21 –
MRPPCT1) appeared to form during the storage period, as their total
absence was observed in the MRPPCT0 (Figure S1). Unfortunately,
some metabolites that appeared during storage could not be identified.
These possible side reactions suggest that the chemical process in Hy-
locereus species led to metabolite alterations at various levels that are
not completely understood, but could be correlated with temperature,
as previously reported (Liao et al., 2020). However, processing and
storage may include a series of chemical reactions such as isomeriza-
tion, deglycosylation, hydrolysis, decarboxylation, and dehydrogena-
tion that could result in color changes and, consequently, changes in
absorption (Esquivel, 2016). As no major color changes were observed
at the end of processing, chemical reactions may have occurred in a
non-significant manner.
The isomerization process predominated at the beginning
(MRPPCT0), mainly because of the presence of phyllocactins (3, 5, and
6) and 6ʹ-malonyl-2ʹ-descarboxy-betanin isomers (8 and 9). When
comparing the starting point to the end of the experiment (MRPPCT3),
it is clear that the betalain pigments had degraded. It is important to
note that metabolites such as betaxanthins responsible for yellow col-
oring were not detected, which could explain the absence of yellow
color even at the end of the process (MRPPCT3).
3.2.4. Multivariate data analysis
First, the data were subjected to analysis by HCA, a multivariate
analysis tool responsible for groupings between samples based on si-
milarities among the variables (m/z peaks for compounds) that com-
pose them. From this analysis, a dendrogram was obtained (Fig. 1),
whose branches varied in length from 0 to 80. From a similarity index
(SI) 10 < SI < 20 represented by the vertical line drawn in the
dendrogram, it was possible to identify four groups of the samples
MRPPCT0 (red), MRPPCT1 (green), MRPPCT2 (dark blue), and
MRPPCT3 (light blue). These groups are related to the classification of
the MRPPC samples analyzed via UPLC-QTOF-MSE at different storage
times, T0 (after processing), T1 (four weeks), T2 (eight weeks), and T3
(twelve weeks).
In the clusters, an overlap of samples from the T2 and T3 groups was
observed, where the MRPPC3T3 replicate (referring to T3) was classi-
fied in the group referred to the eight-week samples (T2), as well as the
MRPPC5T2 replicate classification (T2) in the twelve-week sample
group (T3). From 30 > SI > 20 (Fig. 1), it was possible to obtain a
grouping of the samples in two large distinct groups. A large group was
composed of samples with storage times T0 and T1, and another with
samples from times T2 and T3. The observed trend makes it evident that
the chemical profile of MRPPC had changed considerably after eight
weeks; however, the material still maintained its initial color, implying
that the substances responsible for the color showed a high level of
stability (see discussion on physicochemical characteristics).
Thus, it was confirmed that HCA was able to determine the dis-
tribution profile of samples with high homogeneity in the intergroups,
implying that the chemical composition of the four groups of samples is
significantly different.
Given the characteristic groupings for the different metabolite
profiles of the MRPPC in two large groups, a study of the distribution of
the relative abundance of the main metabolites responsible for the
colorant staining was carried out. Different storage times were con-
sidered to visualize the trend of stability in the period T2 (MRPPCT2) to
T3 (MRPPCT3) compared to the other times (T0 and T1). For this
procedure, only the data of the compounds obtained after the spectral
deconvolution process by the MakerLynx XS software were used, with
emphasis on the compounds responsible for the dye staining.
For this purpose, time-series analysis was conducted, where it was
possible to apply the iPCA tool in an attempt to observe the trend of
clustering patterns between the samples based on their storage times,
and the variation in relative abundance of the compounds of interest
over time. In iPCA, the data were resized in a new system of axes
(principal components, PCs), making it possible to view the graphics of
scores and loadings in three dimensions (3D), describing the main
characteristics that involved the variables.
From the analysis of the data in the interactive scores graph
(Fig. 2a), in which the similarity relationship between the samples
could be observed, it was possible to verify the formation of four
groups. This trend was explained by a percentage of the variance of
71.7% equivalent to PC1, 14.1% to PC2, and 7.0% to PC3, indicating
that 92.8% of the original information was described by the method
employed. The group of samples corresponding to immediate analysis
after processing (MRPPCT0, in red) was observed in the negative re-
gions of PC1 (between −4 and −6) and positive regions of PC2 (be-
tween 2 and 7). The group of samples referring to four weeks of storage
(MRPPCT1, in blue) was found in the negative regions of PC1 (between
−4 and −6), same as MRPPCT0, except it was located in the negative
region of PC2 (between −2 and −4).
For the eight- and twelve-week storage periods, the two groups were
observed in the positive regions of PC1 (between 4 and 6), being
grouped in an almost overlapping manner, implying a similarity be-
tween the profiles of substances that comprised these last two sample
groups. Such behavior confirms the stability of the compounds after
twelve weeks of storage, and corroborates with the results obtained by
HCA, indicating that there is a similarity in the chemical profile of the
samples that constitute the two analysis groups (MRPPCT2 and
MRPPCT3), in contrast to the other samples.
From the characteristic values of the contribution of each variable in
the new axis system, represented in the interactive Loadings graph
(Fig. 2b), iPCA revealed the variables that were responsible for the
grouping of the samples when considering the storage times.
Thus, it was observed that the compounds tentatively identified as
isomers of phyllocactin (peak 3, tR = 0.99, peak 5, tR = 2.40), betanine
(peak 4, tR = 2.00), apiosyl-malonyl-betanin (peak 7, tR = 2.55), and
6ʹ-malonyl-2ʹ-descarboxy-betanin (peak 9, tR = 3.11), found in the
positive regions of Loading 2 (Fig. 2b), had a greater contribution in the
formation of group 0 (MRPPCT0) formed by all samples in T0.
This trend proves that these compounds had a higher relative
abundance when compared to their abundances in the samples kept for
other storage times. This difference in the abundances was responsible
for the groupings observed in the scores graph (Fig. 2a). This behavior
was confirmed when the relative abundance graphs were analyzed from
the Loadings graph (Fig. 2b) of compounds 3–5, 7, and 9 as a function
of the colorant storage time (Fig. 2c–g).
The variation in abundance decreased over time, with a sudden
decay after eight weeks of storage, and remained constant until the end
of twelve weeks. A summary of the variation in the abundance of the
compounds can be seen in the heatmap obtained for the samples
(Fig. 3).
Therefore, it was concluded that the relative abundance of com-
pounds responsible for the coloring effect of the MRPPC in the samples
analyzed at zero and four weeks of storage were greater than in the
samples stored for eight and twelve weeks. Despite this profile, it was
possible to perceive that the color of the MRPPC had maintained over
time, which was proven by the constancy of the analytical results of
relative abundance of compounds.
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
7
3.3. Sensorial analyses and characterization of the product (yogurt)
Microbiological analyses showed that the MRPPCwas suitable for
consumption. After quality evaluation, a focus group methodology was
applied to illicit participants' suggestions on foods that would be ac-
ceptable with MRPPC as a food colorant. After visual analysis of the
MRPPC by each participant, the initial step was to brainstorm and de-
velop a list of applications. The main suggestions obtained from the
focus group included yogurt and beverages. According to Chhikara,
Kushwaha, Sharma, Gat, and Panghalet (2019), betalains from beetroot
can be used to color a variety of foods such as dairy products, yogurt,
processed cheese, and candy. Indeed, beetroot is used as a natural
colorant in several brands of yogurt in Brazil, and this product can be
used as a commercial comparative for sensorial analysis. Based on these
observations, the selected product was yogurt.
First, formulations were prepared using different concentrations of
MRPPC (0.5, 1.0, 1.5, and 2.0%, named as Formulations A, B, C, and D,
respectively, and a control, without MRPPC addition). Next, each for-
mulation was characterized (results are given in Table S1,
Supplementary Material) with the pH ranging from 4.07 to 4.17 and
titratable acidity ranging from 0.10 to 0.11 (%, in malic acid). The
content of soluble solids was not statistically significant between the
formulations. In practical terms, these results showed that the MRPPC
had no influence on these characteristics of yogurt, and thus had great
potential for use as a food colorant in the industry.
As expected, the MRPPC influenced all tested color parameters, i.e.,
altering the lightness of the color (decreasing L*, where L* = 0 yields
black and L* = 100 indicates diffuse white), increasing a* (where ne-
gative values indicate green while positive values indicate magen-
ta), and decreasing b* (where negative values indicate blue and positive
values indicate yellow). The color difference is defined as the numerical
comparison of a sample's color to the standard and indicates the dif-
ference of absolute color coordinates (ΔE). The values of ΔE between all
formulations were higher than 5, showing that the differences in color
were visible to the human eye, mainly in Formulations A vs. B, and A
vs. C.
To confirm these observations, sensorial analysis was performed.
Initially, a just right scale was used in order to compare the ex-
perimental MRPPC yogurt formulations versus two red colored com-
mercial products (a) yogurt with beetroot colorant (named as
Formulation E) and (b) yogurt with carmine colorant (named as
Formulation F). The panelists (yogurt consumers) considered the color
of Formulation B and C (1.0 and 1.5%) as “just right” (ideal for a red-
colored yogurt). Moreover, the lowest concentration of MRPPC
Fig. 1. Dendrogram representing hierarchical clustering of the chemical profile of the microfiltered red–purple pitaya colorant (MRPPC) stored under refrigeration,
analyzed via UPLC-QTOF-MSE. MRPPCT(n); where (n): n= 0, 1, 2 and 3 refer to period of storage; MRPPCT0: after processing; MRPPCT1: after four weeks of storage;
MRPPCT2: after eight weeks of storage and MRPPCT3: after twelve weeks of storage. (For interpretation of the references to color in this figure legend, the reader is
referred to the web version of this article.)
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
8
Fig. 2. iPCA analysis of microfiltered red–purple pitaya colorant (MRPPC) stored under refrigeration and the behavior of variation in relative abundance (Fig. c, d, e,
f, and g) of the main metabolites. The graphs of scores (Fig. a) and loadings (Fig. b) show the tendency of grouping from the contribution of each variable at different
storage times. The arrangements of the four groups (MRPPCT0, MRPPCT1, MRPPCT2 and MRPPCT3) are equivalent to the set of samples formed by the replicates
(MRPPC1 to MRPPC5) for each period (0 to 3). MRPPCT(n); where (n): n= 0, 1, 2 and 3 refer to period of storage; MRPPCT0: after processing; MRPPCT1: after four
weeks of storage; MRPPCT2: after eight weeks of storage and MRPPCT3: after twelve weeks of storage. (For interpretation of the references to color in this figure
legend, the reader is referred to the web version of this article.)
Fig. 3. Heatmap with hierarchical clustering of part of the main metabolites obtained for the microfiltered red–purple pitaya colorant (MRPPC) analyzed for a period
of twelve weeks. Samples are in columns and variables are in rows. The colors vary from deep blue to dark red to indicate relative abundance values. MRPPCT(n);
where (n): n= 0, 1, 2 and 3 refer to period of storage; MRPPCT0: after processing; MRPPCT1: after four weeks of storage; MRPPCT2: after eight weeks of storage and
MRPPCT3: after twelve weeks of storage. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
9
(Formulation A, 0.5%) was statistically similar to Formulation E (1.70,
between “much less than ideal” and “less than ideal”) and the highest
concentration of MRPPC (Formulation D, 2.0%) was statistically similar
to Formulation F (4.55, between “more than ideal” and “much more
than ideal”). These results showed that the product colored with pitaya
colorant is able to reach a more adequate color tonality than the natural
dyes available on the Brazilian market.
There were also significant differences in the color acceptability
among MRPPC yogurts, varying from 4.5 to 7.9 in the scores based on
the 9-point hedonic scale. However, no statistical differences were ob-
served between formulations with 1.5 and 2.0% colorant, indicating
that consumers equally liked both products. In fact, in the ranking
preference test, these formulations did not show preference over one
another, but were most preferred over the other two formulations (0.5
and 1.0%). When the panelists were asked to express their purchase
intent, the Formulations C and D exhibited 90% of positive purchasing
responses (“would probably buy” + “certainly would buy”), while
Formulations A and B did not reach 50%.
For aroma acceptance and intensity of off-flavor, the results showed
no statistical differences among the formulations (Table S2, in the
Supplementary Material). In addition, the results of the triangular test
for aroma showed no significant difference among Formulations C and
D when compared to a yogurt without MRPPC addition (control), in-
dicating that the addition of MRPPC did not altered the aroma of the
yogurt. In order to reinforce these results, the volatile compounds
profile of the yogurts formulations was determined (Figure S5, in the
Supplementary Material). Thus, all the yogurts have a similar profile,
confirming the results obtained from the sensorial analysis.
4. Conclusion
Microfiltered red–purple pitaya colorant (MRPPC) is a mixture of
diverse compounds, including carbohydrates, flavonoids, and betalains.
Thus, MRPPC was shown to have microbiological and physicochemical
stability through twelve weeks of storage, and chemometric analyses
efficiently distinguished the metabolic profile in each storage period.
Sensory analysis revealed that the MRPPC was useful as a food colorant
in yogurt, where it improved color quality without affecting aroma and
other characteristics. The results of this study are expected to be useful
for further development and application of MRPPC as a natural food
colorant.
Author contribution
Guilherme Julião Zocolo conceived the idea Ana Paula Dionísio,
Gisele Silvestre da Silva and Rodolfo Dantas Lima Junior wrote the
manuscript Ana Carolina Viana de Lima, Fernando Antonio Pinto de
Abreu, Gisele Silvestre da Silva and Rodolfo Dantas Lima Junior per-
formed the experiments, Deborah dos Santos Garruti, Maria do Carmo
Passos Rodrigues and Idila Maria da Silva Araújo supported the sen-
sorial analysis, Hilton César Rodrigues Magalhães, Adriana Guirado
Artur and Carlos Alberto Kenji Taniguchi supported the chemical and
physicochemical essays, GuilhermeJulião Zocolo and Ana Paula
Dionísio supported the discussion of the data. All the authors read,
discussed, and approved the final version of this manuscript.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influ-
ence the work reported in this paper.
Acknowledgements
The authors would like to thank Brazilian Agricultural Research
Corporation (EMBRAPA), the INCT BioNat, National Institute of
Science and Technology (grant # 465637/2014-0) and the
Coordination for the Improvement of Higher Education Personnel
(Capes) for the financial support.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://
doi.org/10.1016/j.foodchem.2020.127222.
References
Aburto, N. J., Hanson, S., Gutierrez, H., Hooper, L., Elliott, P., Cappuccio, F. P. (2013).
Effect of increased potassium intake on cardiovascular risk factors and disease, sys-
tematic review and meta-analyses. British Medical Journal, 346, f1378. https://doi:
10.1136/bmj.f1378.
Amaya-Cruz, D. M., Pérez-Ramírez, I. F., Delgado-García, J., Mondragón-Jacobo, C.,
Dector-Espinoza, A., & Reynoso-Camacho, R. (2019). An integral profile of bioactive
compounds and functional properties of prickly pear (Opuntia ficus indica L.) peel
with different tonalities. Food Chemistry, 278, 568–578. https://doi.org/10.1016/j.
foodchem.2018.11.03.
American Oil Chemists’ Society – AOCS (2005). Official Method Am 5-04. Rapid de-
termination of oil/fat utilizing high temperature solvent extraction. Urbana: Official
Methods and Recommended Practices of the American Oil Chemists’ Society.
Association of Official Analytical Chemistry - AOAC (2005). Official methods of analysis.
Gaithersburg, Maryland, 18 ed.
Beuchat, L. R., Komitopoulou, E., Beckers, H., Betts, R. P., Bourdichon, F., Fanning, S.,
et al. (2013). Low–water activity foods:Increased concern as vehicles of foodborne
pathogens. Journal of Food Protection, 76(1), 150–172. https://doi.org/10.4315/
0362-028x.jfp-12-211.
Cai, Y. Z., Xing, J., Sun, M., & Corke, H. (2006). Rapid identification of betacyanins from
Amaranthus tricolor, Gomphrena globosa, and Hylocereus polyrhizus by matrix-assisted
laser desorption/ionization quadrupole ion trap time-of-flight mass spectrometry
(MALDI QIT-TOF MS). Journal of Agricultural and Food Chemistry, 54(18), 6520–6526.
https://doi.org/10.1021/jf0609983.
Chhikara, N., Kushwaha, K., Sharma, P., Gat, Y., & Panghalet, A. (2019). Bioactive
compounds of beetroot and utilization in food processing industry: A critical review.
Food Chemistry, 272, 192–200. http://dx.doi.org/10.1016/j.foodchem.2018.08.022.
Chik, C. T., Bachok, S., & Babaet, N. (2011). Quality characteristics and acceptability of
three types of pitaya fruits in a consumer acceptance test. Journal of Tourism, 3(1),
89–98.
Cohen, H., Fait, A., & Tel-Zur, N. (2013). Morphological, cytological and metabolic
consequences of autopolyploidization in Hylocereus (Cactaceae) species. BMC Plant
Biology, 13, 173.
Dan, T., Wang, D., Wu, S., Jin, R., Ren, W., & Sun, T. (2017). Profiles of volatile flavor
compounds in milk fermented with different proportional combinations of
Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus. Molecules,
22(10), 1633–1647. https://doi.org/10.3390/molecules22101633.
Deng, M., Deng, Y., Dong, L., Ma, Y., Liu, L., Huang, F., et al. (2018). Effect of storage
conditions on phenolic profiles and antioxidant activity of litchi pericarp. Molecules,
23(9), 2276–2288. https://doi.org/10.3390/molecules23092276.
Dutcosky, S.D. (2013). Análise sensorial de alimentos. 4 ed. Curitiba, 531p.
Esatbeyoglu, T., Wagner, A. E., Schini-Kerth, V. B., Rimbach, G., et al. (2015). Betanin - A
food colorant with biological activity. Molecular Nutrition & Food Research, 59(1),
36–47. https://doi.org/10.1002/mnfr.201400484.
Esquivel, P. (2016). Betalains. In R. M. Schweiggert (Ed.). Handbook on natural pigments in
food and beverages (pp. 81–99). (1st ed.). Elsevier.
García-Cruz, L., Dueñas, M., Santos-Buelgas, C., Valle-Guadarrama, S., & Salinas-Moreno,
Y. (2017). Betalains and phenolic compounds profiling and antioxidant capacity of
pitaya (Stenocereus spp.) fruit from two species (S. pruinosus and S. stellatus). Food
Chemistry, 234, 111–118. https://doi.org/10.1016/j.foodchem.2017.04.174.
Huang, X., Wanhd, H., Yuan, W., Lu, J., Yin, J., Luo, S., et al. (2005). A study of rapid
senescence of detached litchi: Roles of water loss and calcium. Postharvest Biology and
Technology, 36(2), 177–189. https://doi.org/10.1016/j.postharvbio.2004.12.005.
Khalili, M. A., Norhayati, A. H., Rokiah, M. Y., Asmah, R., Mohd, Nasir, & M. T., Muskinah
M. S. (2011). Proximate composition and selected mineral determination in organi-
cally grown red pitaya (Hylocereus sp.). Journal of Tropical Agriculture and Food
Science, 34(2), 269–275.
Lira, S. M., Dionísio, A. P., Holanda, M. O., Marques, C, G., Dilva, G. S., Correa, L. C.,
Santos, G. B. M., Abreu, F. A. P., Magalhães, F. E. A., Rebouças, E. L., Guedes, J. A. C.,
Oliveira, D. F., Guedes, M. I. F., & Zocolo, G. J. (2020). Metabolic profile of pitaya
(Hylocereus polyrhizus (F.A.C. Weber) Britton & Rose) by UPLC-QTOF-MSE and as-
sessment of its toxicity and anxiolytic-like effect in adult zebrafish. Food Research
International, 127, 108701. http://dx.doi.org/10.1016/j.foodres.2019.108701.
Miyazawa, M., Pavan, M. A., Muraoka, T., Carmo, C. A. F. S., & Melo, W. J. (2009).
Análise química de tecido vegetal. In: Silva, F. C. (Ed.). Manual de análises químicas
de solos, plantas e fertilizantes. 2 ed. rev. e ampl. Brasília, 191–234.
Lee, C., & Ni, C. K. (2019). Soft matrix-assisted laser desorption/ionization for labile
glycoconjugates. Journal of the American Society for Mass Spectrometry, 30(8),
1455–1463.
Li, G., Meng, X., Zhu, M., & Li, Z. (2019). Research progress of betalain in response to
adverse stresses and evolutionary relationship compared with anthocyanin.
Molecules, 24(17), 3078-3092.http://dx.doi.org/10.3390/molecules24173078.
Liao, H., Zhu, W., Zhong, K., & Liu, Y. (2020). Evaluation of colour stability of clear red
pitaya juice treated by thermosonication. LWT, 121, 108997v4, http://dx.doi.org/10.
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
10
https://doi.org/10.1016/j.foodchem.2020.127222
https://doi.org/10.1016/j.foodchem.2020.127222
https://doi.org/10.1016/j.foodchem.2018.11.03
https://doi.org/10.1016/j.foodchem.2018.11.03
https://doi.org/10.4315/0362-028x.jfp-12-211
https://doi.org/10.4315/0362-028x.jfp-12-211
https://doi.org/10.1021/jf0609983
https://doi.org/10.3390/molecules22101633
https://doi.org/10.3390/molecules23092276
https://doi.org/10.1002/mnfr.201400484
http://refhub.elsevier.com/S0308-8146(20)31084-0/h9000
http://refhub.elsevier.com/S0308-8146(20)31084-0/h9000
https://doi.org/10.1016/j.foodchem.2017.04.174
https://doi.org/10.1016/j.postharvbio.2004.12.005
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0085
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0085
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0085
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0085
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0100
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0100
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0100
1016/j.lwt.2019.108997.
Mokrzycki, W. S., & Tatol, M. (2011). Color difference ΔE: A survey. Machine Graphics and
Vision, 20(4), 383–411.
Roca, E., Lemonnier, P., & Roubille, R. (2015). Carmine food coloring composition with
high stability. Depositante, CHR Hansen Natural Color as. USA n° US9192183B2. 30
mar. 2012, 24 nov. 2015.
Santos, G. B. M., Dionísio, A. P., Magalhães, H. C. R., Abreu, F. A. P., Lira, S. M., Lima, A.
C. V., et al. (2020). Effects of processing on the chemical, physicochemical, enzy-
matic, and volatile metabolic composition of pitaya (Hylocereus polyrhizus (F.A.C.
Weber) Britton & Rose). Food Research International,127, 108710–108711. https://
doi.org/10.1016/j.foodres.2019.108710.
Schweiggert, R. M. (2018). Perspective on the ongoing replacement of artificial and an-
imal-based dyes with alternative natural pigments in foods and beverages. Journal of
Agricultural and Food Chemistry, 66(12), 3074–3081. https://doi.org/10.1021/acs.
jafc.7b05930.
Sigurdson, G. T., Tang, P., & Giusti, M. M. (2017). Natural colorants: Food colorants from
natural sources. Annual Review of Food Science and Technology, 8(1), 261–280.
https://doi.org/10.1146/annurev-food-030216-025923.
Slimen, I. B., Najar, T., & Abderrabba, M. (2017). Chemical and antioxidant properties of
betalains. Journal of Agricultural and Food Chemistry, 65(4), 675–689. https://doi.org/
10.1021/acs.jafc.6b04208.
Tournas, V., Stack, M. E., Mislivec, P. B., Koch, H. A., & Bandler, R. (2001). Yeasts, molds
and mycotoxins. In Food and Drug Administration – FDA (Ed.), Bacteriological
Analytical Manual (BAM), Chap. 18. https://www.fda.gov/food/laboratory-methods-
food/bam-yeasts-molds-and-mycotoxins.
Wang, J., & Sporns, P. (2000). MALDI-TOF MS Analysis of food flavonol glycosides.
Journal of Agricultural and Food Chemistry, 48(5), 1657–1662.
Wei, W., Cheng, M. N., Ba, L. J., Zeng, R. X., Luo, D. L., Qin, Y. H., et al. (2019). Pitaya
HpWRKY3 is associated with fruit sugar accumulation by transcriptionally mod-
ulating sucrose metabolic genes HpINV2 and HpSuSy1. International Journal of
Molecular Sciences, 20(8), 1–15.
WHO (2012). Guideline Potassium intake for adults and children. Geneva, World Health
Organization (WHO). https://www.who.int/elena/titles/guidance_summaries/
potassium_intake/en/ Accessed 28 fev. 2020.
Wybraniec, S., Starzak, K., Skopinska, A., Nemzer, B., Pietrzkowski, Z., & Michalowski, T.
(2013). Studies on nonenzymatic oxidation mechanisms in neobetanin, betanin, and
decarboxylated betanins. Journal of Agricultural and Food Chemistry, 61(26),
6465–6476. https://doi.org/10.1021/jf400818s.
Yee, L. P., & Wah, C. S. (2017). Application of red pitaya powder as a natural food col-
ourant in fruit pastille. Jurnal Gizi Klinik Indonesia, 13(3), 111–120.
Yi, Y., Wu, J., Wang, Y., Ye, W., & Zhang, Q. (2011). Studies on the flavonoids from the
flowers of Hylocereus undatus. Journal of Chinese Medicinal Materials, 34(5), 712–718.
A.C.V.d. Lima, et al. Food Chemistry 330 (2020) 127222
11
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0125
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0125
https://doi.org/10.1016/j.foodres.2019.108710
https://doi.org/10.1016/j.foodres.2019.108710
https://doi.org/10.1021/acs.jafc.7b05930
https://doi.org/10.1021/acs.jafc.7b05930
https://doi.org/10.1146/annurev-food-030216-025923
https://doi.org/10.1021/acs.jafc.6b04208
https://doi.org/10.1021/acs.jafc.6b04208
https://www.fda.gov/food/laboratory-methods-food/bam-yeasts-molds-and-mycotoxins
https://www.fda.gov/food/laboratory-methods-food/bam-yeasts-molds-and-mycotoxins
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0175
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0175
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0180
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0180
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0180
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0180
https://www.who.int/elena/titles/guidance_summaries/potassium_intake/en/
https://www.who.int/elena/titles/guidance_summaries/potassium_intake/en/
https://doi.org/10.1021/jf400818s
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0195
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0195
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0200
http://refhub.elsevier.com/S0308-8146(20)31084-0/h0200
	Microfiltered red–purple pitaya colorant: UPLC-ESI-QTOF-MSE-based metabolic profile and its potential application as a natural food ingredient
	Introduction
	Materials and methods
	Chemicals
	Preparation of the MRPPC
	Methods of analyses
	Proximate composition
	Mineral analyses
	Water activity, soluble solids, and color
	pH and titratable acidity
	Total polyphenols
	UPLC-ESI-QTOF-MSE measurements
	Chemometric analysis of data from UPLC-QTOF-MSE
	Microbiological analyses
	Storage stability of the MRPPC under refrigeration
	Sensory analyses
	Focus group
	Affective tests of yogurt with MRPPC
	Difference tests
	Volatile compounds of yogurt formulated with the MRPPC
	Characterization of yogurt without (control) and with the MRPPC
	Statistical analysis
	Results and discussion
	Compositional characteristics of the MRPPC
	Microbiological, physicochemical, and chemical stability of the MRPPC stored under refrigeration
	Carbohydrates
	Betalains
	Flavonoids
	Multivariate data analysis
	Sensorial analyses and characterization of the product (yogurt)
	Conclusion
	Declaration of Competing Interest
	Acknowledgements
	Supplementary data
	References