Challenges in the determination of engineered nanomaterials in foods

ARTICLE IN PRESS Trends in Analytical Chemistry ■■ (2016) ■■–■■

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Trends in Analytical Chemistry j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / t r a c

Challenges in the determination of engineered nanomaterials in foods Yolanda Picó * Food and Environmental Safety Research Group (SAMA-UV), Desertification Research Centre (CIDE, UV-CSIC-GV) and Faculty of Pharmacy, University of Valencia, Av. Vicent Andrés Estellés s/n, Burjassot, Valencia, Spain

A R T I C L E

I N F O

Keywords: ENMs Nanoparticles Food Extraction Determination

A B S T R A C T

Detection, characterization, and quantification of engineering nanomaterials (ENMs) in foods is still a pending issue that needs to be tackle to protect consumers and to fix some related aspects (e.g. labelling or control). The global challenge for the analytical sciences is that ENMs are a new sort of analytes, involving both chemical (composition, mass and number concentration) and physical information (e.g. size, shape, aggregation). In this critical review, we evaluate and compare the procedures involved in the analytical methods and studies developed thus far for the identification and quantification of ENMs in food. We discuss advantages and limitation as well as prospects. We pointed out the main specific challenges that remain within this topic. Finally, we also envisaged future perspectives on the determination of ENMs. © 2016 Elsevier B.V. All rights reserved.

Contents 1. 2.

3. 4.

Introduction ............................................................................................................................................................................................................................................................. 1 Methods applied to detect, characterize and determine ENMs in food ............................................................................................................................................. 3 2.1. Sample preparation ................................................................................................................................................................................................................................. 3 2.2. Separation ................................................................................................................................................................................................................................................... 4 2.3. Detection, characterization and quantification .............................................................................................................................................................................. 8 Challenges ................................................................................................................................................................................................................................................................ 8 Conclusions and future prospects .................................................................................................................................................................................................................... 9 Acknowledgments ................................................................................................................................................................................................................................................. 9 References .............................................................................................................................................................................................................................................................. 10

1. Introduction Engineered nanomaterials (ENMs) have novel and useful properties to improve food characteristics, preservation and safety [1,2]. However, since years ago, nanotechnology has produced public and scientific concern as well as debate from the perspective of food safety [3]. This has resulted in the emergence of recommendations, guidelines, working groups and specific legislation [4–6]. As the Cockburn et al. review [4] highlighted, several bodies and organizations [e.g. European Food Safety Authority (EFSA), World Health Organization/Food and Agriculture Organization (FAO/ WHO), Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR)] have studied the terminology applicable to these materials for the purposes of evaluation from different perspectives. There is still on-going deliberation on working definitions

* Corresponding author. Tel.: +34 96 3543092; Fax: +34 96 3544954. E-mail address: [email protected].

to ensure consistency. Furthermore, a number of expert groups have been set up to develop practical guidance on how to approach the safety assessment of products of nanotechnology, aimed at scientists involved in the research and development of such products specifically for food applications [1,4,7,8]. The current regulatory approach for ENMs have been widely discussed in several reviews [9–11]. Among them, Aschberger et al. [6] performed a deep review of EU and non-EU legislation (to which the reader is refereed to gain inside into this topic) showing that the EU has incorporated in legislation for agri/feed/food nanospecific provisions while non-EU countries have mostly introduced non-mandatory frameworks. These countries consider that existing regulatory frameworks are able to adapt to and cover the particularities of ENMs (e.g. US, Australia and New Zealand, Canada). Interestingly, to gain more up-to date information, RIKILT and the Joint Research Centre (JRC) were commissioned by the EFSA to prepare an inventory of currently used and reasonably foreseen applications of NM in agriculture and food/feed production. Fig. 1 taken from this inventory illustrates the most frequent type of ENMs

http://dx.doi.org/10.1016/j.trac.2016.06.004 0165-9936/© 2016 Elsevier B.V. All rights reserved.

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Fig. 1. Overview of the main types of (A) ENMs and (B) applications mentioned in the Nano Inventory (including the percentage).

applied to food (nanocomposites and silver) and the regular types of application (food additives and food contact materials). Table 1, also compiling its data, outlines the ENMs currently in use in food industry and their applications (available on the market or under investigation). The inventory remarks that comparing the marketed applications to those in development, a trend from inorganic towards organic ENMs can be observed [12]. This should be keep in mind for further consideration. The most important physico-chemical characteristics for ENMs included in addition to chemical composition, size, size range or size distribution, others as shape, surface area, zeta potential, aggregation state, density and color. Table 2 shows the different analytical approaches described to characterize ENMs. These techniques work well when the bulk initial material is being characterized [13]. However, from an analytical point of view, the identification, quantification and characterization of NPs in food matrices poses significant challenges, because NPs are usually present at low concentration levels and the matrices, in which they are dispersed, are complexes and often incompatible with analytical instruments that

would be required for their detection and characterization. Furthermore, food is a matrix particularly complex because it contains a number of natural NMs, such as proteins, peptides and carbohydrates that could interfered with the analysis. Regarding the methods to assess the ENMs in foods. Tiede et al. [14] were the first that provided an overview of the different analytical techniques available for the detection as well as physical and chemical characterization of engineered nanoparticles (ENPs) in product formulations, environmental matrices and food materials. Since then, few reviews presented information on organic nanoparticles (NPs) intended for use in food and analytical methods that can potentially detect, identify and characterize these particles [15,16]. Detection and characterization of nanodelivery systems is an essential part to understanding the benefits as well as the potential toxicity of these systems in food. Few others covered detection, characterization and quantification of inorganic ENMs [17,18]. Different compilations showed the role that different analytical techniques could play in the characterization of pure ENMs and their prospects to be applied to food (e.g. Raman

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Table 1 ENMs currently used in food industry and their applications (source of data [12]) Applications

ENMs In the market

In development

Food contact materials

SiO2 (E551), TiO2 (E171), Fe2O3 (E172), Nisin (E234) • Gold, AgO • Nanoencapsulatesb (nano-sized silicon, gelatine based) • NPs: AgO, chitosan, ZnO, nisin • Nanocompositesa: nano plastic additives as impact modifier in rigid PVC and hexadecyl trimethyl ammonium bromide modified montmorillonite organoclay

Supplements

Nanoencapsulatesb (silica-mineral hydride complex)

Novel foods

Nanoencapsulatesb (liposomes involving phospholipid-based micelles) ——

Nanocompositesa, nanoencapsulatesb, chitosan Nanoencapsulatesb (liposomes involving phospholipid-based micelles) • Nanocompositesa: nano plastic additives to modify plastic characteristics (reducing the entry of O2 and other gases, thermalbuffering, active food packaging industry) • Natural biopolymer-based films • Smart Packaging systems • Carbon nanotubes Nanoencapsulatesb (liposomes involving phospholipid-based micelles, proteins and carbohydrates) Nanoencapsulatesb (liposomes involving phospholipid-based micelles, proteins and carbohydrates) • Nano encapsulatesb (vitamins and nutrients) • Nanonutrients (Se) • Antibacterials (AgO, polystyrene-based particles) • Antimycotoxins (AgO, montmorillonite based nanoclay) • Nanoemulsions (surfactant based) • Pesticides (β-cipermethrin) at nanoscale

Food additives Food ingredients

Feed additives

Pesticides and biocides

• •

Nano-encapsulates Nanoformulations with pesticides at nanoscale (carbofuran)

a Nanocomposites are multiphase or hybrid materials where one of the phases is a nanomaterial, which when combined together, display markedly different properties from the bulk components. These are thermoplastic polymers that have nanoscale inclusions, 2%–8% by weight. Nanoscale inclusions consist of nanoclays, carbon NPs, nanoscale metals and oxides, and polymeric resins. b Nano-encapsulation involves the incorporation, absorption or dispersion of bioactive compounds in, at or on small vesicles with nano (or submicron) diameters. The incorporated bioactive compounds are protected against degradation, have improved stability and solubility (e.g., solubilizing a hydrophilic compound in hydrophobic matrices and vice versa) and therefore might increase bioavailability and delivery to cells and tissues. Various types of organic nanomaterials are used for nano-encapsulation, which are based on lipids, proteins, polysaccharides, or combinations thereof.

spectroscopy [19], electron microscopy [20]). Several highlighted some current applications of nanomaterials in food, food additives and food-contact materials, and reviewed analytical approaches suitable to address food-safety issues related to nanotechnology [21–26]. These previous studies showed the difficulty of the analysis, the lack of proper methodologies and the need of different techniques’ combination as well as the rapid advances within this area. In this review, the different state-of-the-art methods traditionally used for the determination of ENMs in food are detailed. Then, using the data provided in the different studies, the analytical methods proposed to detect, characterize, size and quantify ENMs in food [i.e., electron microscopy, single-particle inductively coupled plasma mass spectrometry (spICP-MS)] are compared and evaluated. Finally, the remained challenges for future studies on the presence of ENMs in food are discussed, and the requirements and needs that should be tackled in this research field are envisaged. 2. Methods applied to detect, characterize and determine ENMs in food The detection, characterization and determination of ENMs in food is based on the same principles as any other chemical or physical analysis: extraction (and/or clean-up), separation and determination. Table 3 outlines the different methodologies reported in the last 5 years (from 2012 to 2016) to detect, characterize and quantify nanomaterials. 2.1. Sample preparation Sample preparation includes all techniques that involve handling the sample before analysis and/or detection. Some analytical techniques attain in situ detection of NPs. Others require extraction because ENMs needs to be isolated to eliminate food matrix interferences. As ENMs change structure and composition in response to their environment, results obtained for pre-treated or digested samples can often differ from the situation where the par-

ticles are characterized in situ. The sample preparation techniques can be classified depending whether the ENMs are going to be identified by electron microscopy (or other imaging techniques) or by spectrometry techniques. Specimens for electron microscopy are commonly prepared to preserve sample structure and components integrity in the highvacuum imaging environment. Dudkiewicz et al. [20] presented an overview of approaches used to sample preparation for determining ENMs by electron microscopy. Although written 5 years ago, it summarizes methods currently still in use. Sample preparation for electron microscopy incudes all methods of preparations from embedding, tissue processing, coating, immunogold labeling through ultrathin sectioning with ultramicrotomes, cryo-ultramicrotomy, cryosectioning, critical point drying, plunge freezing, freeze substitution, freeze fracturing, freeze drying, contrasting, cryofixation, high pressure freezing, cryo-transfer, freeze etching, freeze fracture to ion beam milling, ion beam etching, and target preparation – mechanical grinding and polishing. Electron microscopy sample treatment procedures are routine protocols and most times are not even described in the scientific articles as can be seen in Table 3. ENMs sample preparation procedures most commonly used to release inorganic ENMs from complex matrices are mainly based on wet digestion with a strong acid (nitric, perchloric, hydrogen peroxide etc. . .), even using microwave assisted digestion (MAD) [44]. This approach has been widely used to determine concentration of different metal oxides —TiO2, CeO2, ZnO, SiO2-, Ag and gold. However, in case of ENPs (e.g. Ag ENPs) which are not stable at acidic conditions acid digestion would not be a suitable separation method. Alternatively, colloidal extraction aims at separating ENPs and matrix components by physical separation e.g. by centrifugation or filtration. However, several studies showed that separation of SiO2ENPs from tomato soup using these colloidal extraction methods resulted in lower recoveries and incomplete separation of ENPs and matrix compared to MAD [44]. This instability of ENMs could be solved by stabilizing them after the acidic digestion by pH adjustment and probe sonication [41]. Other different protocol is macerating enzyme digestion using special

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Table 2 Physico-chemical parameters that should be determined to characterize an ENMs and applicable techniques Techniques

Physicochemical characteristics

Mass spectroscopy (MS)

Molecular weight Composition Structure Surface properties (secondary ion MS) Structure and conformation of bioconjugate Surface properties (ATR–FTIR)

Infrared spectroscopy (IR) Attenuated total reflection Fourier transform infrared (ATR–FTIR) Dynamic light scattering (DLS) Fluorescence correlation spectroscopy (FCS) Zeta potential Raman scattering (RS) Surface enhanced Raman (SERS) Tip-enhanced Raman spectroscopy (TERS) Near-field scanning optical microscopy (NSOM) Circular dichroism (CD) Scanning electron microscopy (SEM) Atmospheric SEM (ASEM)

Transmission electron microscopy (TEM)

Scanning tunneling microscopy (STM)

Atomic force microscopy (AFM)

Nuclear magnetic resonance (NMR)

X-ray diffraction (XRD) Small-angle X-ray scattering (SAXS)

macerating enzymes that released the NPs from plant (Macerozyme R-10) or animal (Proteinase K) tissues without changing the size distribution of the NPs [7,27,29–31,56]. A different procedure proposed to determine gold NPs in liver was the combination of a cationic surfactant with ionic liquids by a micro liquid–liquid extraction [46]. In this evolving context, a promising approach that recently raised is the so-called “third way” in analytical nanoscience and nanotechnology that involves the application of nanomaterials based sorbents or sensors to nanomaterials extraction [61]. In this sense, it is remarkable the development of a simple sustainable method for the extraction of AgNPs using a cationic surfactant in combination with sulfonated nanocellulose (s-NC) as dispersed extractant. The ease with which NC can be prepared and its excellent sorbent capabilities toward AgNPs in D-μSPE are demonstrated [35]. Methods for extraction and purification of organic NPs in food are scarcer. Extraction is commonly carried out with water miscible organic solvents, such as methanol, or dilution with buffers, or using acid or enzymatic digestion (to determine organic ENMs relatively stable). Some procedures involved complex schemes including purification by column chromatography (silica) with methanol: dichloromethane and finally dialysis to remove salts and other ions.

Hydrodynamic size distribution Hydrodynamic dimension Binding kinetics Stability Referring to surface charge Hydrodynamic size and size distribution (indirect analysis) Conformation change of protein–metallic NP conjugate Structural, chemical and electronic properties Size and shape of nanomaterials Structure and conformational change of biomolecules (e.g. protein and DNA) Thermal stability Size and size distribution Shape Aggregation Dispersion Size and size distribution Shape heterogeneity Aggregation Dispersion Size and size distribution Shape Structure Dispersion Aggregation Size and size distribution Shape Structure Sorption Dispersion Aggregation Surface properties (modified AFM) Size (indirect analysis) Structure Composition Purity Conformational change Size, shape and structure for crystalline materials Size/size distribution Shape Structure

This pointed out the most precarious stage of the organic NMs extraction and that some of the methods are not suitable for the routine determination of organic ENMs. 2.2. Separation Separation techniques are used to isolate NPs and to determine their size and size distribution. The best know techniques for separation of ENMs is field flow fractionation (FFF), which is a singlephase chromatography technique in which separation is achieved within a very thin channel, against a perpendicular force field is applied. One of the most common forms of FFF is asymmetricalflow FFF or (AF4) in which the field is generated by a cross-flow applied perpendicular to the channel. An analytical platform widely used to determine inorganic ENMs is coupling on-line AF4 with multiangle light scattering (MALS), and ICP-MS for separation and quantitative determination of size and mass concentration of ENMs [29,31,37,39,41,42]. However, there are other useful techniques as hydrodynamic chromatography (HDC), liquid chromatography (LC), capillary electrophoresis (CE), and ion mobility techniques that could be used to separate ENMs. Particularly suitable is HDC, which has been widely

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ENMs

Food

Sample preparation

Separation/ Determination

Remarks

Ref.

AgNPs

Plants (Arabidopsis taliana)

Enzymatic digestión (Macerozyme R-10)

spICP-MS

[27]

AgNPs

Spiked chicken meat

—-

AgNPs

Chicken meat

Enzimatic digestión (Proteinase K) at 37°C

AgNPs

Chiken meat

Enzimatic digestión (Proteinase K) at 37°C

TEM (particle size) spICP-MS (particle size) NAA (Ag mass fraction) AF4-ICP-MS AF4 and spICP-MS TEM spICP-MS

This procedure is employed to determine the size distribution and to quantify Ag NPs in tissues of the model plant. This approach is combined with TEM to localize the NPs Producing spiked reference matrix materials Differences in particle sizes between the spiked chicken samples and the original silver dispersions indicate relevant matrix effects spICP-MS and TEM characterize the number-based size distribution of AgNPs in the meat digestate. Recovery of AgNPs =80 %

[30]

AgNPs

Chicken meat

Enzimatic digestión (Proteinase K) at 37°C

AgNPs

Biological matrices (8 different foods)

Ag NPs

Water

AgNPs: No treatment Total Ag content: HNO3 digestion at 90°C IT-SPME

AgNPs

Chicken meat and other foods

Enzimatic digestión (Proteinase K) at 37°C

SEM, TEM, DLS spICP-MS, NTA, DCS, PIXE,

AgNPs

Fresh vegetables and river water

Dilution with HEPES pH 7.4

Biosensor MT-SPR

AgNPs

Orange juices and mussels

“The Third Way” cationic surfactant with s-NC as dispersant for D-μSPE

AgNPs

Pears

TiO2NPs

Food (sugar glass and coffee cream)

TEM: fixation (OsO4) SEM: dehydratation CO2 ICP-OES: Dry ashes MA-digestion

CE-DAD AFM UV-Vis spectra IR-spectra Detection: TEM, SEM Quantification: ICP-OES

TiO2NPs

Fish tissues

TiO2NPs (E-171)

27 foods

Validated for sizing and quantification The method was validated following the EU Commission Decision 2002/657/EC In-house validation using a certified silver standard, LODs 1.2 μg g−1, LOQs 3.6 μg g−1, recoveries 80 %, precision of AgNPs mass fraction <15 %, LODAgNPsize 20 nm. Lack of comparability TEM and AF4-ICP-MS results Uses the atomization delay of the respective GFAAS signal as significant indicator for AgNPs and thereby allows discrimination of AgNPs from ionic silver (Ag+) C18RP-LC can be used for predicting average sizes from estimated concentrations. Contrarily, in TEM, the concentrations are determine from the average sizes. Methods based on completely different physical principles can produce similar results for pure suspensions of metallic NPs. The organic matrix makes the detection and sizing of NPs more difficult, especially for microscopic techniques, while DLS and DCS detected multiple particle sizes. spICPMS and NTA showed accurate results results for mass concentrations in these complex matrices. Cross-reactivity towards Ag+ ions was reduced by increasing NaCl concentrations, but not eliminated, suggesting the need in a selective sample-prep for nanoform confirmation. D-μSPE method exhibited a linear response to AgNPs with a LOD of 20 μg/L. Recoveries of specifically recognize AgNPs of different sizes were 70.9–108.4%. The repeatability of the method at the LOQ level was 5.6%. Quantification results of Ag NPs in pear samples by ICP-OES demonstrate that there is a good linear relationship (R2 = 0.983) between the spiked values and recovered values. Two problems addressed: size distribution determination and element quantification of the NPs Size distribution validated by TEM TiO2NPs not detected in real samples Determination of TiO2NPs while simultaneously measuring other elements The number-based size distributions for TiO2 particles in the food showed that 5 − 10% of the particles in these products had sizes below 100 nm, comparable to that found in the E171 materials

TiO2NPs

Lettuce

Internalization and in situ-speciation of Ti were investigated by a combination of microscopic and spectroscopic techniques.

[40]

C18 RP-CLC

AF4-ICP-MS

ICP-OES SEM spICP-MS AF4-ICP-MS Ti distribution: TOF-SIMS, SR-μXRF, SEM, TEM, EDX Ti speciation: μXANES, ICP-MS, μ-PIXE

[29]

[31]

[32]

[33]

[7]

[34]

[35]

[36]

[37]

[38] [39]

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Dried overnight Digested with HNO3 Total Ti content: acidic digestion (HNO3 + H2O2 + HF) Quantification and size determination: boiling with H2O2 Microscopy: not specified SR-μXRF/μXANES: embedded in resin Others: No preparation

AF4-ICP-MS (size distrbution and quantification) TEM (size distribution) HR SC SS GFAAS

[28]

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Table 3 Selected applications to determine ENMs in food 2012–2016

5

6

ENMs

Food

Sample preparation

Separation/ Determination

Remarks

Ref.

SiO2NPs

Spiked tomato soup

Particle size: SEM and AF4-ICP-MS Quantification: ICP-OES

Reference materials for the detection and size determination Questions regarding the trueness of the results from EM and FFFICPMS procedures remain

[41]

SiO2NPs

Caffee creamer

SEM: embedded in gelatin AF4-ICP-MS: acid digestion and stabilization ICP-OES Digested by Wurzschmitt procedure Deffated with n-hexane and dilution with wáter

coffee with creamer, instant soup, pancake

In-vitro gastric digestion model

SiO2NPs

Tomato soup

Generic method: acid digestion or colloidal extraction Total Si mass content: MAD (HCl, HNO3, HF)

YtrONPs

Cabbage

Drying the plant and place directly in the detection system

SR-μXRF

AuNPs

Liver and water

UV/Vis Raman spectroscopy Confirmation by TEM

AuNPs

Tomato soup

Mix with TCA and EDTA and centrifuged. Upper sample was treated with a cation (CTAC) and an ionic liquid (BMIM PF6) 500 μL of sample+ 500 μL of dextran

The combination of FFF with offline fractionation by filtration, and with detection by online ICP-MS and offline TEM/EDAX, has proven essential to provide reliable information of nanoparticle size in food Additional experiments showed that the absence of nanosized silica in the gastric stage can be contributed to an effect of low pH combined with high electrolyte concentrations in the gastric digestion stage. Soup homogenization (step I) by heating (60 °C) and mechanical mixing. SiO2-ENP separation (step II) by MAD with HNO3,H2O2 Particle enrichment (step III) by centrifugation Particle stabilization (step IV) using an stabilizing agent (0.025% (v/v) FL-70™), pH to 8–9 and sonication for 90 s Synchrotron dual-energy X-ray micro-tomography is an effective method to observe yttria NPs inside the cabbage plants in both whole body and microscale level Thanks to the high affinity of the imidazolium group for the gold nanoparticle surface, it is possible to pre-concentrate the dispersed NPs in a low volume of ionic liquid.

[42]

SiO2NPs (E-551)

AF4-ICP-MS AF4-MALS TEM EDAX HDC-ICP-MS DLS SEM AF4-ICP-MS AF4-MALS Total Si mass content: ICP-OES

[48]

AuNPs

Drinking water samples

No sample preparation

HDC-spICP-MS

AuNRs

Polymeric films mimic food

No sample preparation

OCT

CeO2NPs/ ZnO NPs

Soybean (Glycine max)

Samples embedded in Tissue TEK

R-μXRF and μ-XANES

TiO2NPs ZnO NPs

Tomato (Solanum lycopersicum L.))

Total Ti and Zn: Acidic digestion (HNO3)

Total Ti and Zn: ICP-MS Size distribution: TEM

TiO2NPs ZnO NPs

Corn starch, yam starch, and wheat flour

Dry ashes at 750 °C for 16 h

CeO2NP SiO2NP and mix Metal oxide (CeO2, Fe3O4, SnO2, TiO2) or metallic (Ag, Co, Ni)

Sotbean porwders

No sample treatment

Tomate plants

Acid digestión: HNO3 and H2O2

Detection: SEM-EDX, TEM Quantification: ICP-OES TEM SEM EINAA Detection: FEG-ESEM SEM-EDX Quantification: ICP-OES

Food and complex matrices

4 mL of Tris Buffer, X-Triton and calcium Enzymatic digestion with Proteinkinase K

ASEM analysis was a complementary technique to existing methods that is able to visualize ENPs in complex liquid matrices and to provide size information Metal mass fraction, size, and number concentration. LODs for 60 nm Au NPs of approximately 2.2 ng Au L−1 or expressed in terms of NP number concentrations of 600 Au NPs mL−1 LOD for the setup and material was e 8 dB that corresponds to a ppm NP concentration well below the concentration used in food additive applications. The XANES data suggest that the Zn accumulated in the seeds of soybean plants is linked to O, resembling the form of Zn-citrate. There is a critical concentration of TiO2 and ZnO NPs up to which the plant’s growth and development are promoted; with no improvement beyond that The physical characteristics of NPs (size, shape, and others) were investigated using TEM and SEM-EDX. Quantification was by ICP-OES EINAA detects both NPs at 0.1 wt% in soybean powders. Recoveries were 86.2–104.7 % for CeO2, 85.7–95.2 % for SiO2 and 87.5–101.3 and 85.6–93.5 % for CeO2 and SiO2 mixtures The determination of metals in tomato by ICP-OES showed that the tomato plants exposed to Ag-, Co- and Ni-NPs have metal concentrations higher than the controls and that the fruits of plants treated with Ag-NPs were contaminated. For the quadrupole instrument the size detection limits were 20 nm (Au and Ag), 50 (TiO2) and 200 nm (SiO2). For the sector-field instrument size detection limits are lower, 10 nm (Au). LODs ranged from 1 ng L−1 for 60 nm Au NPs to 0.1 μg L−1 for 500 nm SiO2 particles.

spICP-MS

[44]

[45]

[46, 47]

[49]

[50]

[51] [52]

[53]

[54]

[55]

[56]

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AuNPs, AgNPs, SiO2NPs, TiO2NPs

Imaging ASEM Comparison to SEM, TEM and NTA

[43]

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Table 3 (continued)

ENMs

Food

Sample preparation

Separation/ Determination

Remarks

Ref.

c-MWCNTs

Water

No simple preparation

Luminescent CDs as nanosensor

[57]

Carbon NPs

Food caramels,

TEM, UV-Vis, fluorescence

Lipoome type-ENM

Beverages (orange juices)

Methanol extraction, concentration, clean-up by CC and dialysis Ultrafiltration

LOD and LOQ were 0.37 and 1.25 μg mL−1, respectively The formation of nanohybrids between c-MWCNTs and CDs make possible the determination of such water-soluble c-MWCNTs in aqueous solutions. The results clearly indicated that NPs were present in the dispersions extracted from bread, jaggery, caramel of sugar and other materials.

[58]

Cross-linked gelatin and/or polysorbate based NPs

Water and beverages (juices, aquarius drink and gelatin)

Validation of the analytical strategy revealed linearity (R2 > 0.99), repeatability (RSD < 10 %), and reproducibility (RSD < 10 %), recovery (61 + /- 5 %), and LOD (1 mg mL−1). The LOQ of organic ENPs was: (i) for cross-linked gelatine 1 mg/mL in beverages and 0.5 mg/mL in water and (ii) for polysorbate based ENPs 0.5 mg/mL in beverages and 0.1 mg/mL in water

Polysorbate 20 Polysorbate 80

Beverages and nutraceuticals

The LOQs of organic ENPs, based on polysorbate specific in-source fragments determination, are 0.5 μg/mL, and LOQ of tocopheryl acetate (active compound of organic ENPs) is 0.1 μg/mL.

[60]

Cross-linked gelatine Enzymatic digestion (trypsine) Polysorbates Filtration (0.45 μm) Direct injection

HDC (size sepration) and MALDITOF (chemical characterization) UHPLC-SEC-ELDS

AFM: atomic force microscopy. ASEM: atmospheric scanning electron microscope. AuNRs; gold nanorods. DCS: differential centrifugal sedimentation. DLS: dynamic light scattering. EDX: energy-dispersive X-ray spectroscopy. EINA: epithermal instrumental neutron activation analysis. ELDS: evaporative light scattering detector. FEG-ESEM: field emission gun-environmental scanning electron microscope. GFAAS: graphite furnace atomic absorption spectrometry. HDC: hydrodinamic chromatography. HEPES: 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid. HR-CS SS GFAAS: high resolution, continuum source solid sampling graphite furnace atomic absorption spectrometry. ICP: inductively coupled plasma. LOD: limit of detection. LOQ: limit of quantification. MAD: microwave assisted digestion. MALDI-TOF: matrix assisted lasser desorption ionization. μPIXE: micro particle-induced X-ray emission. μXANES: micro-X-ray absorption near-edge structure. MS: mass spectrometry. MT: human metallothionein. NPs: nanoparticles. NTA: nano tracking analysis. OCT: Optical Coherence Tomography. OES: optical emission spectrometry. PIXE: particle induced x-ray emission. SEC: size exclusion chromatography. SEM: scanning electron microscopy. s-NC: sulfonated nanocellulose. spICP-MS: single particle ICP-MS. SPR: surface plasmon resonance. SR-μXRF: synchrotron based micro X-ray fluorescenc. TEM: transmission electron microscopy. TOF-SIMS: time of flight secondary ion mass spectrometry. UHPLC: ultra-high pressure liquid chromatography.

[59]

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UHPLC-TOF-MS DART-TOF-MS DART-Orbitrap-MS In-source fragmentation

[17]

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Table 3 (continued)

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Fig. 2. Scanning electron microscopic images of a ZnO NPs in corn starch ashes and b TiO2 NPs in yam starch ashes with weight percentage of 0.5 %, respectively. Reproduced from [53] with permission of Springer.

applied to the separation of both organic and inorganic ENMs in food [43,49]. 2.3. Detection, characterization and quantification Electron microscopy is a recognized standard tool for nanomaterial characterization, recommended by the EFSA for the size measurement of nanomaterials in food [62]. As can be observed in Table 3, any type of study involves the use of electron microscopy, mostly transmission electron microscopy (TEM) or scanning electron microscopy (SEM), but also dynamic light scattering (DLS), and microscopy-related techniques [e.g., atomic force microscopy (AFM)] to localize ENMs [27,36] as well as establish particle size [28,29,41], and size distribution [7,31,39,40]. Fig. 2 illustrates an example of the images obtained using SEM in starches. The presence of Zn and Ti in all food samples were further confirmed using energy-dispersive X-ray spectroscopy (EDX). However, matrix constituents that were still present could complicate to obtain a proper image analysis of the particle sizes because of changes in the ENMs in a sample and introduction of analytical artefacts. To overcome these limitations, Luo et al. [48] explored the application of the atmospheric scanning electron microscope (ASEM), which allows the direct characterization of ENPs in liquid matrices. The obtained imaging results were compared to those obtained using conventional imaging by TEM and SEM and to size distribution data derived from nanoparticle tracking analysis (NTA) as well. ASEM analysis was a complementary technique to existing methods that is able to visualize ENPs in complex liquid matrices and to provide ENP size information without extensive sample preparation. In the same way Optical Coherence Tomography (OCT), an interferometric imaging technique, was applied to detect gold nanorods (AuNRs) embedded to act as ENPs in polymeric films that were produced to mimic complex food matrices [50]. The limit of detection was estimated to be 1 ppm of nanoparticles concentration. These alternative imaging techniques showed interesting prospects but their use is no as common as conventional SEM and TEM. Electron spectroscopies (X-ray photoelectron spectroscopy – XPS, X-ray absorption near edge structure —XANES, and ParticleInduced X-ray Emission-PIXE including the micro-version of the techniques), secondary ion mass spectroscopy – SIM, and AFM are some of the analysis techniques that provide information about topography, elemental composition, molecular and chemical state and structure [23]. Fig. 3 shows Ti localization and speciation in lettuce leaves exposed to paint leachate were studied by SR-μXRF and μXANES. Inductively coupled plasma mass spectrometry (ICP-MS) for analysis of ENMs in complicated biological tissue samples were recently

reviewed [63]. A serious drawback when operating the ICP-MS in its conventional mode is that it does not provide data regarding NP number concentrations and, thus, any information about the metal mass fraction of individual NPs. To address this limitation, spICPMS coupled online to HDC was developed as an analytical approach suitable for simultaneously determining NP size, NP number concentration, and NP metal content [49]. spICP-MS has proven to be a powerful tool to directly quantify single particle size, concentration, and size distribution. The spICPMS method utilizes a mass spectrometer to detect the pulse (noncontinuous) signals that are generated by each NP entering the plasma [27]. Mass spectrometry are emerging in the field of nanomaterials. However, they have demonstrated interesting prospects for the determination of organic NPs in food [58,60]. As an example, Fig. 4 shows the MALDI–TOF-MS analysis in positive mode of Coatsome A liposomes revealed major peaks at m/z 734.5, 756.6, 1468.1, and 1490.1 amu (atomic mass units) and smaller peaks at 991.6 and 1229.8. Ultimately, MS procedures should be validated for quality control of ENMs in food. Sporadically, other techniques as UV-Vis, fluorescence, Raman spectroscopy or even sensors were reported to determine ENMs. The future will fix their role in the determination of ENMs.

3. Challenges The analysis of ENMs in food is still complicated by 3 main reasons: (i) difficulty of the matrix, (ii) lack of standardized or reference materials, and, as a consequence (iii) lack of systematic validation procedures that establish the quality of the measurement. Regarding the difficulty of the matrix, there is still much complication in separating and analysing ENMs in (complex) food matrices, given the interactions between ENMs and a variety of substances in food that can alter ENM physico-chemical parameters. As can be deduced of the previous section, the method for inorganic ENMs are much more advanced than those for organic ones. Furthermore, there are no mention on how to distinguish ENMs of the natural ones present in the sample. Reference materials play a crucial role in the development and validation of analytical methods. The feasibility of producing colloidal AgNPs reference materials, and AgNPs spiked reference matrix materials to support the development of analytical methods for detecting and quantifying ENMs in food was successfully undertaken for chicken meat [28]. A set of four reference materials for the detection and quantification of SiO2 NPs in food was produced as a proof of principle exercise [41]. The study demonstrated that development and characterization of reference materials for the detection and quantification of SiO2NPs in liquid food is possible and that it should be feasible to assign values with acceptable uncertainties. A generic approach for the validation of methods for detection and quantification of ENMs in food samples, including identity, selectivity, precision, working range, limit of detection and robustness, was recently proposed [64]. The first international intercomparison of particle-size determination by spICP-MS was also reported [65]. Concentrated monodisperse AgNP suspensions with particle diameters of 20, 40 and 100 nm and a blank solution were sent to 23 laboratories in Europe, the USA and Canada. Laboratories prepared eight NP preparations in two food simulants (distilled water; 10 % ethanol) and reported median particle size, Ag particle mass concentration and Ag particle number concentrations. While further improvements of the method, especially with respect to software tools for evaluation, hardware options for shorter dwell times, calibration standards for determining nebuliser efficiency and further experience by

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Fig. 3. SR-μXRF maps and spectra for lettuce leaves exposed to 1250 nmol g−1 TiO2-NPs (A, B, C, H), to aged paint leachate (D, E, I) and leaves of control plants sprayed with ultrapure water (F, G, J) (st., stomata; ep., epidermis; p., parenchyma; v.b., vascular bundle). SR-μXRF maps are presented as bicolor maps with K in green and Ti in red (A,C, D, F) and as temperature maps for Ti fluorescence only (B, E, G). Total XRF spectra of maps A, D and F are shown in H–J, respectively. Arrows indicate spots analyzed by μXANES. (K) Light microscope picture presenting the localization of the analyzed area. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article). Reproduced from [40] with permission of Elsevier.

laboratories are certainly desirable, the results of this study demonstrate the suitability of spICP-MS for the detection and quantification of certain kinds of NPs. This information shows that although, slowly, there are significant progress in overcoming the challenges that are still pending in the analysis of ENMs in food. 4. Conclusions and future prospects Methods for the screening of ENMs in food are still under development. However, the overview presented in this review, if compared to the previous one, reveal technological developments of major importance for the detection, characterization, and quantification of these ENMs in food. It is clear that the analysis of ENMs is not question of a single analytical technique, but rather a combination of multiple sophisticated procedures and instrumentation. Detectors such as TOF and ICP-MS are being adapted to provide sensitive and specific detection of ENMs. X-ray–based techniques provide sensitivity and specificity. Traditional electron and optical microscopy based approaches are being augmented by minimally invasive techniques, such as ESEM, which are simpler to apply and less invasive. The availability of routine analytical methods that address these issues is already a key.

Despite not being completely resolved yet, there are already a few protocols established for the determination of some of them. For example, in the case of wet metals digestion followed by ICPMS and complemented by SEM or TEM to demonstrate that these metals were present as nanoforms. As mentioned, existing methods are not perfect and there is still much work to be done. The enormous diversity of ENMs with different sizes, shapes, compositions and coatings matches, and possibly exceeds that of conventional chemicals. More work should be done to produce standardized materials and to set-up methodologies to determine number-based size distributions and to get quantitative date about the NPs in such a complex matrices. Further development and application of these promising methods will provide research opportunities and challenges for the foreseeable future. Acknowledgments This work has been supported by the Spanish Ministry of Economy and Competitiveness and the ERDF (European Regional Development Fund) through the project GCL2015-64454-C2-1-R and the University of Valencia through the project (UV-INV-AE15348995).

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10

Intensity 5 x10Intens. x105 1.50 1.50

0_G23\1: +MS, Baseline subtracted(0.80)

DPPC

734.56 734.56

Coatsome A, positive mode

1.25 1.25

1.00 1.00 0.75 0.75 0.25 0.25 4 X100.00 x104 2.02.0

1468.08

756.64

0.50 0.50

1468.08

DPPC dimer

756.54

628.60

1229.86

628.60

1229.86 0_G19\1: +MS, Baseline subtracted(0.80)

734.55 734.55

Coatsome C, positive mode

1.51.5 991.65

1.01.0

1229.87 1229.87

991.65

1468.10 1468.10

0.50.5 848.88 848.88

0.0 5

5 X10x10

0_G23\1: -MS, Baseline subtracted(0.80)

DPPG

721.34 721.34

1.0

1.0

Coatsome A, negative mode

0.80.8 0.60.6 0.40.4 0.20.2

648.18

897.39 897.39 929.33

756.48

674.87

1067.40

929.33

756.48

648.18 674.87

1067.40

0.0

X103 6000 0.6

0_G18\1: -MS, Baseline subtracted(0.80)

Coatsome C, negative mode

648.16 648.16 886.43 886.43

4000 0.4

2000 0.2

673.30 673.30

0 600

600

718.37 718.37

700

700

836.35

776.69

926.34

836.35

776.69

800

800

926.34

900

900

1000

1100

1000

1100

1200

1200

1300

1300

1400

1400

m/z

m/z

Fig. 4. MALDI–TOF MS spectra of Coatsome A and Coatsome C liposomes, in both positive and negative modes. DPPC0L-(α)-dipalmitoyl phosphatidylcholine, DPPG0L-(α)dipalmitoylphosphatidylglycerol. R10R20CH3(CH2)14. Reproduced from [58] with permission of Springer.

References [1] H. Bouwmeester, P. Brandhoff, H.J.P. Marvin, S. Weigel, R.J.B. Peters, State of the safety assessment and current use of nanomaterials in food and food production, Trends Food Sci. Technol. 40 (2014) 200–210. [2] K. Pan, Q. Zhong, Organic nanoparticles in foods: fabrication, characterization, and utilization, in: M.P. Doyle, T.R. Klaenhammer (Editors), Annual Review of Food Science and Technology, vol. 72016, 2012, pp. 245–266. [3] A. Martirosyan, Y.-J. Schneider, Engineered nanomaterials in food: implications for food safety and consumer health, Int. J. Environ. Res. Public Health 11 (2014) 5720–5750. [4] A. Cockburn, R. Bradford, N. Buck, A. Constable, G. Edwards, B. Haber, et al., Approaches to the safety assessment of engineered nanomaterials (ENM) in food, Food Chem. Toxicol. 50 (2012) 2224–2242. [5] J.H.E. Arts, M. Hadi, M.-A. Irfan, A.M. Keene, R. Kreiling, D. Lyon, et al., A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping), Regul. Toxicol. Pharmacol. 71 (2015) S1–S27. [6] K. Aschberger, S. Gottardo, V. Amenta, M. Arena, F.B. Moniz, H. Bouwmeester, et al., Iop, Nanomaterials in Food – Current and Future Applications and Regulatory Aspects, 4th International Conference on Safe Production and Use of Nanomaterials, 2015. [7] R.J.B. Peters, Z.H. Rivera, H. Bouwmeester, S. Weigel, H.J.P. Marvin, Advanced analytical techniques for the measurement of nanomaterials in complex samples: a comparison, Qual. Assur. Safety Crops Foods 6 (2014) 281–290. [8] C.M. Sayes, A.B. Santamaria, Toxicological issues to consider when evaluating the safety of consumer products containing nanomaterials, Chapter 5, in: Nanotechnology Environmental Health and Safety, second ed., William Andrew Publishing, Oxford, 2014, pp. 77–115. [9] R. Gellert, E. Mantovani, P. De Hert, The EU regulation of nanomaterials: smoother or harder? The precautionary tool chest as the basis for better regulating nanomaterials A2, Chapter 2.7, in: P.I. Dolez (Editor), Nanoengineering, Elsevier, Amsterdam, 2015, pp. 339–373. [10] L.G. Garduno-Balderas, I.M. Urrutia-Ortega, E.I. Medina-Reyes, Y.I. Chirino, Difficulties in establishing regulations for engineered nanomaterials and considerations for policy makers: avoiding an unbalance between benefits and risks, J. Appl. Toxicol. 35 (2015) 1073–1085. [11] L.K. Breggin, R. Falkner, J. Pendergrass, R. Porter, N. Jaspers, Addressing the risks of nanomaterials under United States and European union regulatory

[12]

[13] [14]

[15]

[16]

[17]

[18]

[19] [20]

[21] [22]

[23]

frameworks for chemicals*,† A2, Chapter 8, in: R. Gurumurthy (Editor), Assessing Nanoparticle Risks to Human Health, second ed., William Andrew Publishing, Oxford, 2016, pp. 179–254. R.B. Peters, P. Weigel, S. Marvin, H. Bouwmeester, H. Aschberger, K. Rauscher, et al., A Inventory of Nanotechnology applications in the agricultural, feed and food sector, EFSA supporting publication 2014:EN-621. , 2014 (accessed 13.06.16). P.-C. Lin, S. Lin, P.C. Wang, R. Sridhar, Techniques for physicochemical characterization of nanomaterials, Biotechnol. Adv. 32 (2014) 711–726. K. Tiede, A.B.A. Boxall, S.P. Tear, J. Lewis, H. David, M. Hassellov, Detection and characterization of engineered nanoparticles in food and the environment, Food Addit. Contam. Part A Chem. Anal. Control Expo. Risk Assess. 25 (2008) 795–821. D.M.A.M. Luykx, R.J.B. Peters, S.M. van Ruth, H. Bouwmeester, A review of analytical methods for the identification and characterization of nano delivery systems in food, J. Agric. Food Chem. 56 (2008) 8231–8247. R. Peters, G. ten Dam, H. Bouwmeester, H. Helsper, G. Allmaier, F. vd Kammer, et al., Identification and characterization of organic nanoparticles in food, TrAC Trends Anal. Chem. 30 (2011) 100–112. J.-F. Liu, S.-J. Yu, Y.-G. Yin, J.-B. Chao, Methods for separation, identification, characterization and quantification of silver nanoparticles, TrAC Trends Anal. Chem. 33 (2012) 95–106. F. Laborda, E. Bolea, G. Cepriá, M.T. Gómez, M.S. Jiménez, J. Pérez-Arantegui, et al., Detection, characterization and quantification of inorganic engineered nanomaterials: a review of techniques and methodological approaches for the analysis of complex samples, Anal. Chim. Acta 904 (2016) 10– 32. Y.-S. Li, J.S. Church, Raman spectroscopy in the analysis of food and pharmaceutical nanomaterials, J. Food Drug Anal. 22 (2014) 29–48. A. Dudkiewicz, K. Tiede, K. Loeschner, L.H.S. Jensen, E. Jensen, R. Wierzbicki, et al., Characterization of nanomaterials in food by electron microscopy, TrAC Trends Anal. Chem. 30 (2011) 28–43. C. Blasco, Y. Picó, Determining nanomaterials in food, TrAC Trends Anal. Chem. 30 (2011) 84–99. Y. Picó, C. Blasco, Nanomaterials in food, which way forward?, Chapter 10, in: F. Marinella, B. Damià (Editors), Comprehensive Analytical Chemistry, Elsevier, 2012, pp. 305–353. C. Contado, Nanomaterials in consumer products: a challenging analytical problem, Front. Chem. 3 (2015) 48.

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[24] K.D. Grieger, J. Harrington, N. Mortensen, Prioritizing research needs for analytical techniques suited for engineered nanomaterials in food, Trends Food Sci. Technol. 50 (2016) 219–229. [25] A.I. Lopez Lorente, B.M. Simonet, M. Valcarce, Determination of nanoparticles in biological matrices, Front. Biosci. (Elite Ed.) 4 (2012) 1024–1042. [26] G. Singh, C. Stephan, P. Westerhoff, D. Carlander, T.V. Duncan, Measurement methods to detect, characterize, and quantify engineered nanomaterials in foods, Compr. Rev. Food Sci. Food Safety 13 (2014) 693–704. [27] D. Bao, Z.G. Oh, Z. Chen, Characterization of silver nanoparticles internalized by arabidopsis plants using single particle ICP-MS analysis, Front. Plant Sci. 7 (2016). [28] R. Grombe, G. Allmaier, J. Charoud-Got, A. Dudkiewicz, H. Emteborg, T. Hofmann, et al., Feasibility of the development of reference materials for the detection of Ag nanoparticles in food: neat dispersions and spiked chicken meat, Accredit. Qual. Assur. 20 (2015) 3–16. [29] K. Loeschner, J. Navratilova, C. Kobler, K. Molhave, S. Wagner, F. von der Kammer, et al., Detection and characterization of silver nanoparticles in chicken meat by asymmetric flow field flow fractionation with detection by conventional or single particle ICP-MS, Anal. Bioanal. Chem. 405 (2013) 8185–8195. [30] R.J.B. Peters, Z.H. Rivera, G. van Bemmel, H.J.P. Marvin, S. Weigel, H. Bouwmeester, Development and validation of single particle ICP-MS for sizing and quantitative determination of nano-silver in chicken meat, Anal. Bioanal. Chem. 406 (2014) 3875–3885. [31] K. Loeschner, J. Navratilova, R. Grombe, T.P.J. Linsinger, C. Købler, K. Mølhave, et al., In-house validation of a method for determination of silver nanoparticles in chicken meat based on asymmetric flow field-flow fractionation and inductively coupled plasma mass spectrometric detection, Food Chem. 181 (2015) 78–84. [32] N.S. Feichtmeier, N. Ruchter, S. Zimmermann, B. Sures, K. Leopold, A direct solid sampling analysis method for the detection of silver nanoparticles in biological matrices, Anal. Bioanal. Chem. 408 (2016) 295–305. [33] R.A. González-Fuenzalida, Y. Moliner-Martínez, C. Molins-Legua, V. Parada-Artigues, J. Verdú-Andrés, P. Campins-Falcó, New tools for characterizing metallic nanoparticles: AgNPs, a case study, Anal. Chem. 88 (2016) 1485–1493. [34] S.R. Raz, M. Leontaridou, M.G.E.G. Bremer, R. Peters, S. Weigel, Development of surface plasmon resonance-based sensor for detection of silver nanoparticles in food and the environment, Anal. Bioanal. Chem. 403 (2012) 2843–2850. [35] C. Ruiz-Palomero, M.L. Soriano, M. Valcárcel, Sulfonated nanocellulose for the efficient dispersive micro solid-phase extraction and determination of silver nanoparticles in food products, J. Chromatogr. A 1428 (2016) 352–358. [36] Z. Zhang, F. Kong, B. Vardhanabhuti, A. Mustapha, M. Lin, Detection of engineered silver nanoparticle contamination in pears, J. Agric. Food Chem. 60 (2012) 10762–10767. [37] I. López-Heras, Y. Madrid, C. Cámara, Prospects and difficulties in TiO2 nanoparticles analysis in cosmetic and food products using asymmetrical flow field-flow fractionation hyphenated to inductively coupled plasma mass spectrometry, Talanta 124 (2014) 71–78. [38] B.J. Shaw, C.S. Ramsden, A. Turner, R.D. Handy, A simplified method for determining titanium from TiO2 nanoparticles in fish tissue with a concomitant multi-element analysis, Chemosphere 92 (2013) 1136–1144. [39] R.J.B. Peters, G. van Bemmel, Z. Herrera-Rivera, H.P.F.G. Helsper, H.J.P. Marvin, S. Weigel, et al., Characterization of titanium dioxide nanoparticles in food products: analytical methods to define nanoparticles, J. Agric. Food Chem. 62 (2014) 6285–6293. [40] C. Larue, H. Castillo-Michel, S. Sobanska, N. Trcera, S. Sorieul, L. Cecillon, et al., Fate of pristine TiO2 nanoparticles and aged paint-containing TiO2 nanoparticles in lettuce crop after foliar exposure, J. Hazard. Mater. 273 (2014) 17–26. [41] R. Grombe, J. Charoud-Got, H. Emteborg, T.P.J. Linsinger, J. Seghers, S. Wagner, et al., Production of reference materials for the detection and size determination of silica nanoparticles in tomato soup, Anal. Bioanal. Chem. 406 (2014) 3895–3907. [42] J. Heroult, V. Nischwitz, D. Bartczak, H. Goenaga-Infante, The potential of asymmetric flow field-flow fractionation hyphenated to multiple detectors for the quantification and size estimation of silica nanoparticles in a food matrix, Anal. Bioanal. Chem. 406 (2014) 3919–3927. [43] R. Peters, E. Kramer, A.G. Oomen, Z.E.H. Rivera, G. Oegema, P.C. Tromp, et al., Presence of nano-sized silica during in vitro digestion of foods containing silica as a food additive, ACS Nano 6 (2012) 2441–2451. [44] S. Wagner, S. Legros, K. Loeschner, J. Liu, J. Navratilova, R. Grombe, et al., First steps towards a generic sample preparation scheme for inorganic engineered nanoparticles in a complex matrix for detection, characterization, and quantification by asymmetric flow-field flow fractionation coupled to multiangle light scattering and ICP-MS, J. Anal. At. Spectrom. 30 (2015) 1286–1296.

11

[45] Y. Chen, C. Sanchez, Y. Yue, M. de Almeida, J.M. Gonzalez, D.Y. Parkinson, et al., Observation of yttrium oxide nanoparticles in cabbage (Brassica oleracea) through dual energy K-edge subtraction imaging, J. Nanobiotechnology 14 (2016) 23. [46] A.I. Lopez-Lorente, B.M. Simonet, M. Valcarcel, Rapid analysis of gold nanoparticles in liver and river water samples, Analyst 137 (2012) 3528–3534. [47] A.I. López-Lorente, M. Valcárcel, Determination of gold nanoparticles in biological, environmental, and agrifood samples, Chapter 10, in: V. Miguel, I.L.-L. Ángela (Editors), Comprehensive Analytical Chemistry, Elsevier, 2014, pp. 395–426. [48] P. Luo, I. Morrison, A. Dudkiewicz, K. Tiede, E. Boyes, P. O’Toole, et al., Visualization and characterization of engineered nanoparticles in complex environmental and food matrices using atmospheric scanning electron microscopy, J. Microsc. 250 (2013) 32–41. [49] S.A. Pergantis, T.L. Jones-Lepp, E.M. Heithmar, Hydrodynamic chromatography online with single particle-inductively coupled plasma mass spectrometry for ultratrace detection of metal-containing nanoparticles, Anal. Chem. 84 (2012) 6454–6462. [50] R. Grombe, L. Kirsten, M. Mehner, T.P.J. Linsinger, H. Emons, E. Koch, Feasibility of non-invasive detection of engineered nanoparticles in food mimicking matrices by Optical Coherence Tomography, Food Chem. 153 (2014) 444–449. [51] J.A. Hernandez-Viezcas, H. Castillo-Michel, J.C. Andrews, M. Cotte, C. Rico, J.R. Peralta-Videa, et al., In situ synchrotron x-ray fluorescence mapping and speciation of CeO2 and ZnO nanoparticles in soil cultivated soybean (glycine max), ACS Nano 7 (2013) 1415–1423. [52] R. Raliya, R. Nair, S. Chavalmane, W.-N. Wang, P. Biswas, Mechanistic evaluation of translocation and physiological impact of titanium dioxide and zinc oxide nanoparticles on the tomato (Solanum lycopersicum L.) plant, Metallomics 7 (2015) 1584–1594. [53] X. Song, R. Li, H. Li, Z. Hu, A. Mustapha, M. Lin, Characterization and quantification of zinc oxide and titanium dioxide nanoparticles in foods, Food Bioprocess Technol. 7 (2014) 456–462. [54] X. Song, H. Li, Z. Hu, A. Mustapha, M. Lin, Characterization and quantification of engineered nanoparticles in food by epithermal instrumental neutron activation analysis and electron microscopy, J. Food Measur. Charact. 8 (2014) 207–212. [55] L.V. Antisari, S. Carbone, A. Gatti, G. Vianello, P. Nannipieri, Uptake and translocation of metals and nutrients in tomato grown in soil polluted with metal oxide (CeO2, Fe3O4, SnO2, TiO2) or metallic (Ag, Co, Ni) engineered nanoparticles, Environ. Sci. Pollut. Res. Int. 22 (2015) 1841–1853. [56] R. Peters, Z. Herrera-Rivera, A. Undas, M. van der Lee, H. Marvin, H. Bouwmeester, et al., Single particle ICP-MS combined with a data evaluation tool as a routine technique for the analysis of nanoparticles in complex matrices, J. Anal. At. Spectrom. 30 (2015) 1274–1285. [57] A. Cayuela, M. Laura Soriano, M. Valcarcel, Photoluminescent carbon dot sensor for carboxylated multiwalled carbon nanotube detection in river water, Sens. Actuators B Chem. 207 (2015) 596–601. [58] J.P.F.G. Helsper, R.J.B. Peters, L. Brouwer, S. Weigel, Characterisation and quantification of liposome-type nanoparticles in a beverage matrix using hydrodynamic chromatography and MALDI-TOF mass spectrometry, Anal. Bioanal. Chem. 405 (2013) 1181–1189. [59] V. Schulzova, V. Krtkova, M. Tomaniova, J. Hajslova, T. Ltd, Using of ELSD for determination of organic engineered nanoparticles, Nanocon 2012, 4th International Conference, 2012, 370–375. [60] V. Krtkova, O. Lacina, V. Schulzova, M. Tomaniova, J. Hajslova, T. Ltd, Determination of organic engineered nanoparticles in beverages and nutraceuticals, Nanocon 2012, 4th International Conference, 2012, 504–509. [61] A.I. López-Lorente, M. Valcárcel, The third way in analytical nanoscience and nanotechnology: involvement of nanotools and nanoanalytes in the same analytical process, TrAC Trends Anal. Chem. 75 (2016) 1–9. [62] A. Dudkiewicz, A.B.A. Boxall, Q. Chaudhry, K. Molhave, K. Tiede, P. Hofmann, et al., Uncertainties of size measurements in electron microscopy characterization of nanomaterials in foods, Food Chem. 176 (2015) 472–479. [63] C.K. Su, Y.C. Sun, Considerations of inductively coupled plasma mass spectrometry techniques for characterizing the dissolution of metal-based nanomaterials in biological tissues, J. Anal. At. Spectrom. 30 (2015) 1689– 1705. [64] T.P.J. Linsinger, Q. Chaudhry, V. Dehalu, P. Delahaut, A. Dudkiewicz, R. Grombe, et al., Validation of methods for the detection and quantification of engineered nanoparticles in food, Food Chem. 138 (2013) 1959–1966. [65] T.P.J. Linsinger, R. Peters, S. Weigel, International interlaboratory study for sizing and quantification of Ag nanoparticles in food simulants by single-particle ICPMS, Anal. Bioanal. Chem. 406 (2014) 3835–3843.

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