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Analytical Letters
ISSN: 0003-2719 (Print) 1532-236X (Online) Journal homepage: http://www.tandfonline.com/loi/lanl20
Determination of Aflatoxins in Plant-based Milk
and Dairy Products by Dispersive Liquid–Liquid
Microextraction and High-performance Liquid
Chromatography with Fluorescence Detection
Ahmed M. Hamed, Mahmoud Abdel-Hamid, Laura Gámiz-Gracia, Ana M.
García-Campaña & Natalia Arroyo-Manzanares
To cite this article: Ahmed M. Hamed, Mahmoud Abdel-Hamid, Laura Gámiz-Gracia, Ana
M. García-Campaña & Natalia Arroyo-Manzanares (2018): Determination of Aflatoxins in
Plant-based Milk and Dairy Products by Dispersive Liquid–Liquid Microextraction and High-
performance Liquid Chromatography with Fluorescence Detection, Analytical Letters, DOI:
10.1080/00032719.2018.1467434
To link to this article: https://doi.org/10.1080/00032719.2018.1467434
Published online: 26 Jul 2018.
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FOOD ANALYSIS
Determination of Aflatoxins in Plant-based Milk and Dairy
Products by Dispersive Liquid–Liquid Microextraction
and High-performance Liquid Chromatography with
Fluorescence Detection
Ahmed M. Hamed
a
, Mahmoud Abdel-Hamid
a
, Laura G
amiz-Gracia
b
,
Ana M. Garc
ıa-Campa~
na
b
, and Natalia Arroyo-Manzanares
b
a
Department of Dairy Science, Faculty of Agriculture, Cairo University, Giza, Egypt;
b
Department of
Analytical Chemistry, Faculty of Sciences, University of Granada, Granada, Spain
ABSTRACT
The consumption of plant-based milk has increased due to their
nutritional attributes. However, these products may contain aflatoxins
if contaminated raw materials were used, although little concern is
present in international regulation regarding this topic. In this work,
dispersive liquid–liquid microextraction (DLLME) was used for the
determination of the most important aflatoxins (B
1
,B
2
,G
1
, and G
2
)in
oat, rice, coconut, almond, and birdseed plant-based milk and milk-
based products enriched with oats, almonds, and walnuts using
high-performance liquid chromatography (HPLC) with photochemical
derivatization and fluorescence detection. Calibrations in matrix were
performed for all of the samples, obtaining satisfactory linearity, with
correlation coefficients exceeding 0.994 for all of the aflatoxins. The
precision in terms of repeatability and intermediate precision,
expressed as the relative standard deviation, was lower than 9.7%,
and recoveries ranged between 82 and 104%, fulfilling current
legislation for the determination of aflatoxins. In addition, the limits
of quantification were 0.5 mgL
1
for the aflatoxins, allowing the
determination of these compounds below the maximum levels estab-
lished by European Commission in these commodities. Finally, 23
commercial products were analyzed to characterize the presence of
these toxins.
ARTICLE HISTORY
Received 9 March 2018
Accepted 17 April 2018
KEYWORDS
Aflatoxins; dispersive liquid-
liquid microextraction
(DLLME); high-performance
liquid chromatography
(HPLC) with fluorescence
detection; plant product
enriched milk; vegetable-
based milk
Introduction
Currently, an increasing number of consumers prefer nondairy plant-based milk
substitutes due to a lifestyle choice or medical reasons, including lactose intolerance
(affecting up to 75% world population), cow’s milk allergies, or the prevalence of
hypercholesterolemia. Much attention has been paid to soy milk as an alternative to
bovine milk. However, other commodities such as cereals, oilseeds, or nuts have been
explored recently for new food uses (including plant-based milks) on the basis of their
functional properties. These beverages are manufactured by extracting the plant material
CONTACT Natalia Arroyo-Manzanares narroyo@ugr.es Department of Analytical Chemistry, Faculty of Sciences,
University of Granada, Campus Fuentenueva s/n, E-18071, Granada, Spain
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/lanl.
ß2018 Taylor & Francis
ANALYTICAL LETTERS
https://doi.org/10.1080/00032719.2018.1467434
(nuts, cereals, legumes, seeds, or other products) in water, separating the liquid, and for-
mulating the final product. They resemble cow’s milk in appearance, but their composi-
tions differ significantly (M€
akinen et al. 2016; Sethi, Tyagi, and Anurag 2016).
On the other hand, currently the dairy industry is trying to offer new innovative prod-
ucts with added values. This is the case of enriched milks, which offer to the consumer
the nutritional properties of the milk, as well as other health benefits from the added
ingredients. Among these products are some beverages, which include nuts or cereals in
their composition. Taking into account that plant sources (cereals and legumes) are
accepted as functional food and nutraceuticals because of presence of health promoting
components, their derived products (nondairy plant-based milk and enriched dairy prod-
ucts) can also be considered as functional foods. However, if the raw plant material has
suffered contamination, these derived products are susceptible to be contaminated too.
Mycotoxins are one of the most common natural contaminants of plants, they are toxic
secondary metabolites produced by filamentous fungi. According to the Food and
Agriculture Organization, up to 25% of the crops all over the world are contaminated with
mycotoxins, including the highly toxic aflatoxins B
1
,B
2
,G
1
,andG
2
,producedby
Aspergillus flavus and Aspergillus parasiticus fungi. Aflatoxin contamination can occur dur-
ing the storage and poor processing conditions in a wide variety of commodities including
various cereals, oilseeds, spices, and nuts, as well as their derivative products. Aflatoxins
infect humans by consumption of contaminated foods, being a remarkable public health
problem, as chronic toxicity by aflatoxins can cause liver damage, immunosuppressive and
carcinogenic effects.AFB
1
is the most toxic and classified by the International Agency for
Research on Cancer as a human carcinogen. The high number of recent publications
devoted to mycotoxins, including aflatoxins, is an indicative of the relevance of this prob-
lem (Alshannaq and Yu 2017; Kumar et al. 2017;Sarmaetal.2017).
Considering the above, in order to protect health consumers and to ensure the inter-
national food trade, different countries have set maximum limits for mycotoxins. Thus,
around 100 countries have regulations to control mycotoxin levels in food and most
include maximum permitted or recommended levels for specific commodities (Anukul,
Vangnai, and Mahakarnchanakul 2013; Lawley 2013; Anfossi, Giovannoli, and Baggiani
2016). In this regard, the European Commission has set maximum contents for AFB
1
and for total aflatoxins in nuts, almonds, hazelnuts, dried fruits, rice, cereals, and spices,
ranging from 2–12 μgkg
1
for AFB
1
and from 4–15 μgkg
1
for total aflatoxins, depend-
ing upon the commodity (European Commission 2006b,2010).
Quantitative analytical methods for determination of aflatoxins are mainly based on
sample treatments based on liquid extraction, followed by a clean-up step in order to
remove interferents, with subsequent quantification by liquid chromatography with
fluorescence or mass spectrometry (MS) detection. Recent reviews have compiled the
most relevant applications (Bakirdere et al. 2012; Selvaraj et al. 2015; Yao, Hruska, and
Di Mavungu 2015; Anfossi, Giovannoli, and Baggiani 2016; Xie, Chen, and Ying 2016;
Alshannaq and Yu 2017). The bottleneck of all these methods is the sample treatment,
as aflatoxins must be efficiently extracted from the samples in order to reduce matrix
effects, allowing quantification at the very low concentration levels required. Besides
traditional liquid extraction, solid phase extraction (SPE) and the use of immunoaffinity
columns, other alternative extraction methods, such as the well-known quick, easy,
cheap, effective, rugged, and safe (QuEChERS) (Sartori et al. 2015; Zhu et al. 2015;
2A. M. HAMED ET AL.
Geary et al. 2016; Zhao et al. 2016) and dispersive liquid–liquid microextraction
(DLLME) (Campone et al. 2011; Afzali et al. 2012; Campone et al. 2013; Hamed et al.
2017b) approaches have been recently applied for determination of aflatoxins in com-
modities. Moreover, both methodologies have been combined in order to achieve
cleaner extracts (Arroyo-Manzanares et al. 2014). However, the effectiveness for the
determination of aflatoxins in plant-based milks has not been demonstrated.
Due to advantages that include simplicity, reduced solvent consumption and high
enrichment factors, DLLME has obtained widespread acceptance in food analysis,
including several applications in milk and dairy products (Saraji and Boroujeni 2014;
Quigley, Cummins, and Connolly 2016). Considering the scarce attention that functional
vegetable milks have received concerning the possible contamination by mycotoxins, as
only few articles are devoted to this aspect (Hamed et al. 2017a; Mir
o-Abella et al.
2017); in this article, DLLME has been proposed combined with HPLC coupled with
photochemical derivatization and fluorescence detection for the determination of the
four main aflatoxins in nondairy plant-based milk products (oat, rice, coconut, almond,
and birdseed milk). Additionally, milk-based products enriched with nuts and cereals
(oats, almonds, and walnuts) have been analyzed in this study.
Materials and methods
Chemicals and reagents
Methanol, acetonitrile, formic acid, and chloroform (all LC-MS grade) were supplied by
VWR International Eurolab, S.L. (Barcelona, Spain). Magnesium sulfate, trisodium cit-
rate, and sodium chloride were purchased from Panreac Qu
ımica (Barcelona, Spain).
Potassium dihydrogen phosphate and disodium hydrogen citrate sesquihydrate were
supplied by Merck (Darmstadt, Germany).
Analytical standards of aflatoxins were supplied by Sigma-Aldrich (St. Louis, MO).
Individual stock standard solutions containing 20 mgL
1
for AFG
2
and AFB
2
and 2.5 mgL
1
for AFB
1
and AFG
1
were used by dissolving accurate volume in acetonitrile. Intermediate
working solutions were prepared in acetonitrile and stored at –20 C and used throughout
this work. Working standard solutions containing all the aflatoxins were daily prepared by
dilution of these solutions with methanol:water (1:1, v/v).
Ultrapure water (18.2 MX/cm, Milli-Q Plus system, Millipore Bedford, MA) was used
throughout all work. Nylon syringe filters, 0.22 mm25 mm (Agela Technologies, New
York) were used for filtration of samples before chromatographic analysis.
Instrumentation
Chromatographic separations were developed in a modular HPLC system that consisted
of a quaternary low pressure gradient pump (Model PU-2089, Jasco, Tokyo, Japan); an
autosampler with a 100-mL loop (Model AS-2055, Jasco); a column oven (X-LC-
3067CO), a ultraviolet derivatization module, consisting on a photochemical reactor
with a 254-nm lamp (LCTech, Dorfen, Germany) placed between the C18 Kinetex sep-
aration column (150 mm 4.6 mm, 2.6 mm from Phenomenex, Torrance, CA), and the
ANALYTICAL LETTERS 3
fluorescence detector (Model FP 2020, Jasco). ChromNAV software (1.18.03 version,
Jasco) was used for data acquisition and processing.
A Universal 320 R centrifuge (HettichZentrifugen, Tuttlingen, Germany), a bench
mixer multitube vortex agitator (model BV1010, Edison, NJ), and a nitrogen evaporator
(System EVA-EC from VLM GmbH, Bielefeld, Germany) were also used in this work.
Sample treatment
In order to select the best extraction methodologies, two approaches previously developed
in our laboratory for determination of mycotoxins (DLLME and QuEChERS) were tested.
DLLME method. A previously reported DLLME procedure for determination of aflatox-
ins in milk and yogurt was adapted (Campone et al. 2013; Hamed et al. 2017b). A 5-mL
sample was placed in a 15-mL falcon tube and 6mL of acetonitrile and 1.5g of NaCl
were added. The solution was vortexed for 30 s and centrifuged (5 min, 6000 rpm) allow-
ing protein precipitation. Then, the upper phase was quantitatively transferred (approxi-
mately 4mL) into a 10-mL vial. In order to carry out the DLLME, the organic phase
containing the extracted analytes and acting as disperser solvent and 1500μLofCHCl
3
(extractant solvent) was injected in 5mL of deionized water. This solution was strongly
shaken for 30 s, providing the formation of a stable cloudy solution. The mixture was
centrifuged (5 min, 6000 rpm) for phase separation and the organic phase was collected
and dried under a gentle nitrogen stream. The final residue was dissolved in 1000 μLof
methanol:water (1:1, v/v) and filtered before HPLC analysis.
QuEChERS method. For the QuEChERS-based procedure, a previously optimized
method for determination of Fusarium toxins in similar matrices was tested (Hamed
et al. 2017a). Briefly, 5 mL of sample and 5 mL of 50 mM potassium dihydrogen phos-
phate at pH 7.0 were placed into a 50-mL tube and vortexed for 10 s. Subsequently,
10 mL of acetonitrile containing 5% formic acid was added and vortexed for 2 min.
Then, 4 g MgSO
4
, 1 g NaCl, 1 g trisodium citrate, and 0.5 g disodium hydrogen citrate
sesquihydrate were added, shaken for 1 min, and centrifuged at 4500 rpm for 5 min.
Next, 2 mL of the upper acetonitrile layer was transferred to a glass vial, evaporated
to dryness under nitrogen, reconstituted with 500 mL of methanol:water (1:1, v/v), and
filtered prior to introduction into the HPLC system.
Chromatographic conditions
Separation was performed using HPLC photochemical derivatization in order to enhance
the native fluorescence of AFB
1
and AFG
1
using conditions described in the literature
(Arroyo-Manzanares et al. 2015). The derivatization reaction is based on the conversion
of AFB
1
and AFG
1
to AFB
2a
and AFG
2a
, respectively, using a photochemical reactor
with a 254 nm lamp. Briefly, a C18 Kinetex separation column (150 mm 4.6 mm,
2.6 mm) was used, while the mobile phase consisted on a mixture of water (eluent A),
acetonitrile (eluent B), and methanol (eluent C) at a flow rate of 0.9 mL min
1
, using a
gradient elution with constant composition of 27% B, 0% C (0.3min), 13% C (20 min)
and 68% C (2123 min), returning to the initial conditions using a 1 min linear gradi-
ent. The column oven was maintained at 30 C, and a volume of 50 mL was injected.
4A. M. HAMED ET AL.
The excitation and emission wavelengths for fluorescence measurements were 365 and
460 nm, respectively, with the detector operating at a gain 100.
Results and discussion
Optimization of the sample pretreatment
Two approaches were characterized for the extraction of aflatoxins from plant-based milks,
using rice milk as a representative matrix: a QuEChERS-based extraction and DLLME.
Theses sample treatments were selected as alternatives to standard methods for aflatoxins
determination in other matrices based on immunoaffinity columns. These columns contain
specific antibodies to the analytes, allowing excellent clean-up and sample purification.
However, this methodology presents some drawbacks such cost, complexity, inefficiency, and
high susceptibility to sample pH, therefore suffering from low recoveries for some aflatoxins.
In order to evaluate the extraction efficiency of both methods, the recovery values were
estimated. First, the QuEChERS-based extraction was tested, but this approach did not
provide good recoveries (lower than 54%). Alternatively, and considering the good results
previously reported for the determination of aflatoxins in yogurt using DLLME (Hamed
et al. 2017b), this sample treatment was tested. Cleaner extracts and high recoveries for all
of the analytes were provided without requiring any further optimization of the significant
variables affecting the extraction efficiency. A chromatogram corresponding to a rice milk
sample analyzed by the proposed DLLME method is shown in Figure 1. No interference
peaks co-eluted with the analytes. Thus, DLLME was selected for sample treatment.
Figure 1. Chromatograms of (a) a spiked rice milk sample at 2.5 mgL
1
for each aflatoxins and (b) a
blank sample. The column was aC18 Kinetex (150 mm 4.6 mm, 2.6 mm) using a mobile phase of
water (eluent A), acetonitrile (eluent B), and methanol (eluent C). The gradient was 27% B, 0% C
(0.3 min), 13% C (20 min), 68% C (21–23 min), 0% C (24 min) at a flow rate of 0.9 mL min
1
at 30 C.
The injection volume was 50 mL; the excitation wavelength was 365; the emission wavelength was
460 nm; and the gain was 100.
ANALYTICAL LETTERS 5
Method validation
The method was characterized in oat, rice, coconut, almond, and birdseed milk and
milk products enriched with oats, almonds, and walnuts. The linear dynamic ranges,
limits of quantification, precision, and trueness were evaluated for all of the
studied matrices.
Calibration curves. Spiked blank samples (previously analyzed to ensure that they
were free of aflatoxins) were used to establish the calibration curves at five concentration
levels (0.5, 1, 2.5, 5, and 10 mgL
1
of each aflatoxin). Each level was prepared and
injected in triplicate. The slopes, intercept, and coefficients of determination (R
2
) were
calculated by least-square regression. Table 1 summarizes the performance characteris-
tics of the method. Responses were linear with R
2
higher than 0.99 for all aflatoxins.
Limits of quantification were set as the lowest concentration level (0.5 mgL
1
), showing
the suitability of the method for the quantification of very low concentrations of aflatox-
ins in these matrices.
Precision. The precision was evaluated in terms of repeatability (intraday precision) and
intermediate precision (interday precision) by application of the DLLME method in the
different samples spiked at two concentration levels of aflatoxins (0.5 and 2.5 mgL
1
).
Repeatability was evaluated in one day by analyzing three samples, prepared and injected
Table 1. Statistical and performance characteristics of the method for each sample matrix.
Product Analyte
Linear range
(mgL
1
)
Coefficient of
determination Slope Intercept
Oat milk (14% oat) AFG
2
0.28–10 0.997 374661 172.83
AFG
1
0.18–10 0.997 183207 12654
AFB
2
0.22–10 0.997 241871 19662
AFB
1
0.18–10 0.997 205557 24872
Rice milk (15% rice) AFG
2
0.04–10 0.996 530816 83658
AFG
1
0.04–10 0.997 229517 22902
AFB
2
0.04–10 0.996 313917 50936
AFB
1
0.03–10 0.996 233732 47481
Coconut milk (5.9% coconut) AFG
2
0.12–10 0.997 566738 49141
AFG
1
0.21–10 0.997 247770 14270
AFB
2
0.10–10 0.996 342899 29909
AFB
1
0.11–10 0.997 246650 30222
Almond milk (2% almond) AFG
2
0.16–10 0.998 567068 6402.6
AFG
1
0.12–10 0.999 246899 4948.9
AFB
2
0.17–10 0.998 342759 6679.2
AFB
1
0.18–10 0.999 250773 7497.4
Birdseed milk (15% birdseed) AFG
2
0.26–10 0.999 551275 63621
AFG
1
0.48–10 0.998 242650 210143
AFB
2
0.12–10 0.999 332773 5634.4
AFB
1
0.32–10 0.999 249578 –15624
Milk-based product with oat (0.2% oat) AFG
2
0.17–10 0.998 356966 40305
AFG
1
0.25–10 0.994 169018 51365
AFB
2
0.14–10 0.997 225131 35373
AFB
1
0.21–10 0.996 187531 42413
Milk-based product with almond (0.2% almond) AFG
2
0.21–10 0.997 607015 132881
AFG
1
0.25–10 0.995 272321 25077
AFB
2
0.13–10 0.997 371034 44224
AFB
1
0.14–10 0.995 267662 22806
Milk-based product with walnut (0.2% walnut) AFG
2
0.21–10 0.997 374661 172.83
AFG
1
0.24–10 0.997 183207 –12654
AFB
2
0.24–10 0.997 241871 –19662
AFB
1
0.05–10 0.997 205557 –24872
6A. M. HAMED ET AL.
in triplicate under the same conditions. Intermediate precision was evaluated for 5 days
(one sample per day was prepared and injected in triplicate).
Trueness. Trueness was assessed by recovery experiments in the selected matrices. The
samples were spiked at two levels of each aflatoxins (0.5 and 2.5 mgL
1
). Each sample
was analyzed three times and injected in triplicate. Previously, a blank sample was ana-
lyzed to verify the absence of aflatoxins and co-eluting peaks.
Table 2 shows the results of the precision expressed as the relative standard deviation
of peak area and trueness. Good precision (relative standard deviation lower than 10%)
and recoveries between 82% and 104% were obtained in all cases, in compliance with
regulations for methods describing the official control of the levels of mycotoxins in
food (European Commission 2006a).
Analysis of commercial samples
Commercial samples of functional vegetable milks and milk-based products were pur-
chased at local stores from Granada, Spain. They comprise four oat milk products (14%
oat), five rice milk samples (15% rice), three coconut materials (5.9% coconut), two
almond milk products (2% almond), one birdseed milk sample (15% birdseed), and
Table 2. Recovery and precision as the relative standard deviation for the proposed DLLME-HPLC- fluorescence method.
Recovery % (n¼9) Intraday precision (n¼9) Interday precision (n¼15)
Product Analyte
Level 1
(0.5 mgL
1
)
Level 2
(2.5 mgL
1
)
Level 1
(0.5 mgL
1
)
Level 2
(2.5 mgL
1
)
Level 1
(0.5 mgL
1
)
Level 2
(2.5 mgL
1
)
Oat milk AFG
2
95 101 5.1 0.9 6.7 5.1
AFG
1
96 101 4.6 1.1 8.5 7.7
AFB
2
94 100 3.5 1.1 6.6 5.8
AFB
1
98 98 4.0 1.8 4.0 3.9
Rice milk AFG
2
97 97 5.6 4.4 9.7 6.2
AFG
1
95 98 6.0 4.0 6.9 6.8
AFB
2
98 100 4.9 4.8 7.7 6.9
AFB
1
104 104 5.2 4.8 7.5 4.6
Coco milk AFG
2
92 93 3.9 1.7 5.1 4.7
AFG
1
93 93 5.9 2.3 7.5 6.5
AFB
2
92 93 3.9 2.6 6.8 6.2
AFB
1
94 94 4.6 2.6 7.5 5.2
Almond milk AFG
2
91 94 5.6 4.7 6.6 6.1
AFG
1
93 93 7.4 0.2 7.9 7.8
AFB
2
87 87 6.6 2.5 7.7 6.8
AFB
1
91 95 4.8 0.6 6.8 5.6
Birdseed milk AFG
2
99 100 4.4 1.8 6.6 4.5
AFG
1
97 103 7.3 0.5 8.6 7.5
AFB
2
92 99 5.5 1.8 7.1 5.7
AFB
1
90 100 6.2 2.0 7.9 6.5
Milk-based
product
with oat
AFG
2
86 89 3.7 3.9 4.4 4.1
AFG
1
99 100 8.9 2.5 9.7 5.7
AFB
2
85 87 1.0 2.5 5.0 4.2
AFB
1
92 93 3.6 1.4 6.6 4.0
Milk-based
product
with
almond
AFG
2
92 92 4.1 1.8 9.1 7.4
AFG
1
91 93 4.4 2.0 7.9 4.7
AFB
2
87 91 2.6 2.2 5.4 4.8
AFB
1
91 91 4.1 2.3 5.4 4.8
Milk-based
product
with walnut
AFG
2
84 90 4.4 2.3 6.7 4.7
AFG
1
92 95 0.6 4.3 6.8 5.8
AFB
2
82 94 5.5 1.3 6.1 6.0
AFB
1
88 91 2.7 1.0 8.1 7.0
ANALYTICAL LETTERS 7
milk-based products: three enriched with oats (0.2%), three with almonds (0.2%), and
two with walnuts (0.2%). All of the milk samples were stored at 4 C in their original
1 L packaging prior to use. Fortunately, none of the studied aflatoxins were detected at
concentration higher than limits of quantification.
Conclusions
After characterization of QuEChERS and DLLME as possible alternative sample treat-
ments, the latter was applied for the quantification of AFB
1
, AFB
2
, AFG
1
, and AFG
2
in
plant-based beverages and enriched milk. Moreover, the use of photochemical derivati-
zation for enhancing the fluorescence emission coupled to HPLC avoids the use of deri-
vatization reagents and provides an easy and sensitive alternative to these hazardous
agents. The proposed method provided good results in terms of precision, recovery and
extract cleanliness, allowing the determination of these mycotoxins at very low concen-
trations in infrequently analyzed but increasingly consumed vegetable-based milk and
milk-based products.
Disclosure statement
The authors report no conflicts of interest with this study.
Funding
Financial support was provided from the Project Reference AGL2015-70708-R (MINECO/FEDER,
UE). AMH thanks the Erasmus Mundus–Al Idrisi II program for a predoctoral grant.
ORCID
Laura G
amiz-Gracia http://orcid.org/0000-0002-8880-5000
Ana M. Garc
ıa-Campa~
na http://orcid.org/0000-0002-3191-3350
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