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Trends in Food Science & Technology 65 (2017) 10e22

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Review

Ensuring food safety: Quality monitoring using microfluidics

Xuan Weng, Suresh Neethirajan*

BioNano Laboratory, School of Engineering, University of Guelph, Guelph, N1G 2W1, Canada

a r t i c l e i n f o

Article history:Received 11 November 2016Received in revised form23 April 2017Accepted 30 April 2017Available online 8 May 2017

Keywords:Food analysisMicrofluidicsBiosensorPoint-of-careFood safety

* Corresponding author.E-mail address: sneethir@uoguelph.ca (S. Neethira

http://dx.doi.org/10.1016/j.tifs.2017.04.0150924-2244/© 2017 Elsevier Ltd. All rights reserved.

a b s t r a c t

Background: Food safety, which is the primary goal of food analysis, is a worldwide health concern toboth humans and animals. Thus, this topic is of substantial interest to food science researchers. Thedevelopment of analytical methods and techniques to ensure food safety is thriving, particularly asconsumers have increasing concerns regarding the content and safety of their food supply. Conventionalmethods of food analysis, including mass spectroscopy (MS), high-performance liquid chromatography(HPLC), enzyme-linked immunosorbent assay (ELISA), gas chromatography (GC), and capillary electro-phoresis (CE), are time-consuming, labor intensive, and require skilled technicians. Therefore, there is anurgent need to develop sustainable, high-efficiency, reliable, and cost-effective methods for rapidanalysis and safety inspections of food products.Scope and approach: This review describes the latest developments in the field of food safety monitoringusing microfluidic methods. Challenges and future perspectives of microfluidics are also discussed.Key findings and conclusions: Microfluidics and microfluidic analytical devices blaze a new way for rapidand efficient detection of foodborne pathogens, allergens, toxins, heavy metals, pesticide residue, ad-ditives, and other chemical and physical contaminants. Portability, miniaturization, and a significantlyreduced sample/reagent volume make microfluidic technology an ideal choice for field use, particularlyin resource-limited areas.

© 2017 Elsevier Ltd. All rights reserved.

1. Introduction

Food safety is of increasing public health concern worldwide,resulting in substantial costs to both individual consumers and thefood industry. With an increased enforcement of regulations andgrowing consumer awareness, both the food industry and pro-ducers have been subjected to evermore stringent scrutiny in orderto ensure food quality and safety. Personnel working in the field offood safety are most concerned about foodborne illness by micro-biological pathogens such as bacteria, parasites, and viruses.However, factors impacting food safety include not only foodbornepathogens, but also allergens, toxins, heavy metals, pesticide res-idue, additives, and other chemical and physical contaminants thathave been introduced via agricultural and industrial processes(Busa et al., 2016; Sasaki et al., 2002).

Numerous analytical methods have been developed and arecurrently employed to evaluate the quality and safety of food.Among these methods, HPLC, GC, ELISA, and PCR are the most

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common and preferred methods. Although these laboratory-basedmethodologies have high sensitivity, most of these are also time-consuming and expensive. Generally, samples must be deliveredto a centralized laboratory, where the time to obtain results canrange from several hours to several days, which may result in adelay in report generation. Consumers have a need to know thecontent and safety of their food. Thus, there is an urgent need todevelop simpler, rapid, accurate, field-deployable, and sensitivedevices to detect substances (pathogens, allergens, biotoxins, etc.)in food, with the goal to efficiently prevent foodborne illnesses.

Microfluidics refers to the science of studying the behavior ofminute amounts of fluid inside micrometer-sized channels, as wellas manufacturing microfluidics devices (“lab-on-a-chip”) forvarious applications (Whitesides, 2006). Microfluidic devices haveenormous potential in miniaturizing and improving conventionalmethods for specific target separation, detection, and analysis dueto the unique characteristics of the small dimensions of micro-fluidics resulting in high surface area-to-volume ratio, strongersurface tension, laminar flow, and enhanced capillary effects (Yageret al., 2006). Other advantages include minimal handling andconsumption of hazardous materials, high throughput sampledetection, portability, and diverse designs for varying functional

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e22 11

modules (Gao, Li, & Pappas, 2013; Kumar et al., 2013; Mehling &Tay, 2014; Shields IV, Reyes, & L�opez, 2015). By implementingmicrofluidic technology, laboratory testing can be performed in asignificantly reduced time, ranging from hours to minutes, whilethe reagents can be reduced to microliters or nanoliters. Foodanalysis can benefit from the advantages of microfluidics, not onlyshort analysis time and extremely low sample/reagent consump-tion, but also portability, low-cost, disposability and high capacityformultiplexing assay. All of these advances inmicrofluidic systemsfacilitate the development of portable devices for on-site foodanalysis (Escarpa, 2014; García-Ca~nas, Sim�o, Herrero, Ib�a~nez, &Cifuentes, 2012; Kim, Lim, & Mo, 2016; L�opez, Moreno-Guzman,Jurado, & Escarpa, 2016; Vilela, Martín, Gonz�alez, & Escarpa,2014; Xu, 2014).

This review will focus on recent progress (from 2012 toSeptember 2016) and applications of microfluidic analytical tech-niques as they relate to monitoring various target compounds ofsignificance to food safety. Wewill specifically turn our attention tothe detection of foodborne pathogens, allergens, toxins, heavymetals, as well as microfluidic analytical platforms in food pro-cessing. In addition, common challenges whenmicrofluidics is usedin food safety applications will also be discussed.

2. Microfluidics and food safety

Many microfluidic devices have been developed that focus onthe determination of foodborne pathogens (microorganisms), foodallergens, biotoxins, heavy metal ions, and other chemical compo-nents that may be in food (Busa et al., 2016; Escarpa, 2014; L�opezet al., 2016).Table 1 summarizes representative microfluidic de-vices that are used to ensure food safety.

2.1. Foodborne pathogens

Foodborne illness caused by microbial pathogens affects thehealth and safety of humans and animals all over the world, and isthe primary concern of those who are in the field of food safety(Zhao, Lin, Wang, & Oh, 2014). The major foodborne pathogenicbacteria Salmonella Spp., Listeria monocytogenes, Escherichia coli(E. coli) O157:H7, Campylobacter Spp., Clostridium perfringens, andStaphylococcus aureus are responsible for the majority of foodborneillness outbreaks (CDC, 2016). Currently, ELISA and PCR are the twomost commonly used methods by clinical and food industriesdetect foodborne pathogens (Law, Ab Mutalib, Chan, & Lee, 2015;Zhao et al., 2014). These methods usually require bacterial culti-vation in highly specialised laboratories, and tedious and laboriousassay procedures, resulting in time-consuming and expensiveprocedures. A delayed delivery of food samples to the laboratorymay result in loss of viability of microorganisms, resulting in falsenegatives and delayed reports. Using the powerful tools of micro-fluidic methods to detect foodborne pathogens may overcomethese drawbacks.

Sun et al. (2015) developed an 8-chamber lab-on-chip systemfor rapid and quantitative detection of Salmonella Spp. in foodsamples. This platform was able to perform the on-chip samplepreparation by using magnetic beads followed by loop-mediatedisothermal amplification (LAMP) for bacteria detection. The sys-tem was capable of analyzing eight Salmonella-spiked bufferedpeptone water (BPW) enriched pork meat samples within 40 minwith a limit of detection (LOD) as low as 50 cells per test.

Immunomagnetic separation (IMS) technique was developed ina microfluidic nano-biosensor for pathogenic Salmonella detection(Kim, Moon, Moh, & Lim, 2015) by using magnetic beads andquantum dots (QDs) as a fluorescent label, as shown in Fig. 1. This

microfluidic chip consisted of two inlets, one outlet, and a detectionwell was located near the outlet. The portable fluorometer includedan LED unit providing the excitation light source, a silicon photo-multiplier tube (PMT) for fluorescence signal detection, a samplingunit containing a tray for microfluidic chip mounting, and housingto block ambient light. An assay could be finished within 30 minwith a detection limit of 103 CFU/mL, and good differentiation bythe microfluidic biosensor between S. typhimurium and E. coli.

In recent years, nanotechnology provides a significantenhancement of the biosensor performances for food applications(Arduini, Cinti, Scognamiglio, & Moscone, 2016). A PDMS/paper/glass hybrid microfluidic biochip was demonstrated to perform aone-step ‘turn on’ homogenous assay (Zuo, Li, Dominguez, & Ye,2013) for multiplexed pathogen detection using aptamer-functionalized graphene oxide, as shown in Fig. 2. The aptamer-functionalized graphene oxide interacted with the pathogen,resulting in changes in fluorescence due to quenching and recoveryproperties of GO and by adsorption and desorption of the Cy3 dyelabel on the aptamer. The concentration of pathogens could bedetermined by analysis of the fluorescence intensity. For an assay,30 mL of the sample solution was loaded into the ready-to-usemicrofluidic chip and incubated for 8 min at room temperatureand followed by fluorescence images capturing and intensitiesanalysis. Spiked L. acidophilus, S. aureus, and S. enterica sampleswere detected by thismethodwith a percent recovery ranging from92.9 to 107.8%. This test demonstrated the accuracy of the method;though no food samples were tested using this method. A singleassay could be completed in 10 min with a detection limit of11.0 CFU/mL. Compared to the previous methods, coupling ofnanotechnology presented higher sensitivity and less assay time.

Generally, detection of pathogens in food or biological samplesrequires sample preparation prior to loading on microfluidic de-vices for analysis. Clime et al. (2015) first introduced a microfluidicchip for sample preparation, filtration, and extraction of pathogens.The microfluidic chip utilized hydrodynamic focusing and inertiallateral migration effects for membrane-free removal of debris frombiological samples. They demonstrated that the microfluidicfiltration and extraction chip could remove over 50% of the debris in(pre-filtered) ground beef samples while retaining up to 70% of theinitial pathogenic organisms at the device outlet. As seen thattedious sample preparation for complex food matrix requires theintegration of more functional units in the microfluidic chip.Although microfluidics has such capability, the fabrication andoperation complexity and cost will be significantly increased.Fronczek, You, and Yoon (2013) developed a handheld microfluidicdevice for detection of Salmonella typhimurium on poultry packageswithout sample preparation, such as filtration, culturing, or isola-tion required. These multi-layer microfluidic chips were fabricatedusing polycarbonate, and consisted of a channel cut-out, bottomcasing, and top casing. The Mie scatter signals in the microfluidicchannels were generated from immuno-agglutination betweenSalmonella and carboxylated polystyrene microparticles, and con-jugated anti-Salmonellawere then read using a handheld device. Atotal assay time of 10 min and a detection limit of 10 CFU/mL wereachieved in all matrices, demonstrating that this method is verysuitable for field assays.

Centrifugal microfluidic devices are one of the most powerfulplatforms in the field of microfluidics (Kwok et al., 2016;Strohmeier et al., 2015). A series of microfluidic unit operationscan be performed on these devices, including liquid valving,pumping, mixing, separation, and others (Gorkin et al., 2010).Centrifugal microfluidic devices have been reported to be used forfoodborne pathogen detection in many studies (Sayad et al., 2016;Strohmeier et al., 2014). For example, Sayad et al. (2016) developed

Table 1Microfluidic devices for food safety.

Target analyte/sample Characteristic of the microfluidic deviceand the analysis

Real sample Reference

Pathogen

S. Typhimurium Peristaltic pump, immunomagnetic separation (IMS),LOD: 103 CFU/mL,Assay time: 30 min (no sample preparation)

chicken extract Kim et al., 2015

Salmonella micro-LAMP system, pumpLOD:10 cells/mLAssay time: 40 min

Salmonella spiked BPW(buffered peptone water)enriched pork meat

Sun et al., 2015

Salmonella live cell mPAD, ATP quantification,LOD: 2.6 � 107 CFU/mL,

——— Jin, Guo, Zuo, & Ye,2015

Salmonella Lab-on-a-disc, centrifugal force, LAMP,LOD: 5 � 10�3 ng/mLAssay time: 70 min

Tomatoes spiked withSalmonella

Sayad et al., 2016

L. acidophilus, S. aureus and S. enterica PDMS/paper/glass hybrid microfluidic biochip, capillary force, aptamer-functionalized graphene oxideLOD: 11.0 CFU/mL for L. acidophilus

——— Zuo et al., 2013

Salmonella,Shigella, V. cholera and C. jejuni

Microfluidic array of 15 reaction wells, and microchannel for sampledistribution, hydrophobic air vents, microvalves, LAMP.LOD: 10e100 gene copies per mL

——— Tourlousse et al., 2012

E. coli O157:H7 and S. aureus Non-biofouling polyethylene glycol (PEG) based microfluidic chip,electrochemical detection.Linear detection range: 102 CFU/mL to 105 CFU/mL LOD: 102 CFU/mL

——— Tian, Lyu, Shi, Tan, &Yang, 2016

Cronobacter sakazakii Real-time PCR-based microfluidics platformLOD: 103 and 104 CFU/mLAssay time: 50 min

Reconstituted skim milk El-Sharoud, Darwish,&Batt, 2013

G. duodenalis cysts Inertial microfluidic separation,LOD: 38 cysts

Lettuce Ganz et al., 2015

Salmonella Centrifugal microfluidic device, fully automated fashion,LOD: 10 cfu/mL and 102 cfu/mL in PBS and milkAssay time: 30 min

Milk Kim et al., 2015

Listeria monocytogenes Inertial microfluidic devices, microfluidic filtration and extraction;removing more than 50% of the debris in (pre-filtered) ground beefsamples whilemaintaining up to 70% recovery of initial pathogenic content

Ground beef samples Clime et al., 2015

Listeria monocytogenes, Salmonellatyphimurium, EHEC, Staphylococcusaureus, Citrobacter

freundii and Campylobacter jejuni

Centrifugal microfluidic device, PCR, sequential aliquoting,LOD: 189 and 141 DNA copies for L. monocytogenes and S. typhimurium

——— Strohmeier et al., 2014

E. coli,S. tymphirium, S. enteritis, P. aeruginosa

BK-76,L. monocytogenes 1892, L. innocua,

MRSA 35, and MRSA 86

SERS microfluidic device,LOD: 28 and 7 CFU/mL for MRSA 86 and S. typhimurium

——— Mungroo, Oliveira, &Neethirajan, 2016

Salmonella Single-pipetting microfluidic assay device,LOD: 10 CFU/mLAssay time: 10min

Poultry packages Fronczek et al., 2013

AllergenAra h 1 Biofunctionalized digital microfluidic chip, magnetic detection Peanut P�erez-Ruiz et al., 2012Hazelnut (Corylus avellana L.), peanut

(Arachis hypogaea), and soybean(Glycine max)

Digital versatile disk (DVD), imaging,LOD: 1 mg/g

Jam, frozen ready meal Tortajada-Genaroet al., 2011

Casein ELISA-based colorimetric detection,Linear range: 100 ng/mL to 1 mg/mLLOD: 100 ng/mLAssay time:15 min

Milk Zhang et al., 2013

DNP-BSA Cell electrochemical microfluidic chip, food allergen-induced cellmorphological changes

e Jiang et al., 2016

Ara h 1gluten

Microfluidics ELISA-based optical sensor,Linear response region: 6.25 ng/mL to 50 ng/mL for gluten; 6 ng/mL to1000 ng/mL for Ara h 1.LOD: 4.77 ng/mL (Ara h 1) and 15.2 ng/mL (gluten)

Chocolate bar, peanut butter,biscuit,gluten free flour

Weng et al., 2016

Ara h 1 Microfluidic biosensor using graphene oxide and aptamer-functionalizedquantum dotsLinear range: 200e2000 ng/mL.LOD: 56 ng/mLAssay time: 10 min

Biscuit Weng & Neethirajan,2016

BiotoxinAflatoxins Microfluidic chip-based nano liquid chromatograph (LC), triple quadrupole

MS systemLinear range: 0.048e16 ng/g,LOD: 0.004e0.008 ng/g;Recovery: 90.8%e100.4%.

Peanutpeanut powder,peanut butter

Liu et al., 2013

Aflatoxins Microfluidic smectite-polymer nanocomposite stripwith fluorometeric quantification by a hand-held ultraviolet lampLinear range: 5e80 ppb

Corn Hu et al., 2013

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Table 1 (continued )

Target analyte/sample Characteristic of the microfluidic deviceand the analysis

Real sample Reference

Pathogen

LOD: 6.09 ppbAssay time: 10 min

Aflatoxins Microfluidic chip integrated with automated MiSens electrochemicalbiosensor device, competition immunoassayLinear range: 5.7e8.1 g/gLOD: 0.08e0.65 ppbRecovery: 85.1%e100.8%.

Wheat, fig Uludag et al., 2016

Aflatoxins Distance-readout microfluidic chip using a target-responsive hydrogelLinear range: 0.25e40 mMLOD: 1.77 nMAssay time: 90 min

Beer Ma et al., 2016

Botulinum neurotoxin Centrifugal microfluidic immunoassay platform, Sample volume: 2-mLLOD: 0.09 pg/mLAssay time: 30 min

Salad dressing,whole milk,canned meat,peanut butter

Koh et al., 2015

Ochratoxin A PDMS microfluidics with integrated microfabricated hydrogenatedamorphous siliconphotodiodes, two-channel U-shaped microfluidic device,chemiluminescence detectionLOD: 0.85 ng/mLAssay time: ~50 min

Wine and beer Novo et al., 2013

Ochratoxin A Microfluidic chip embedded with surface-enhanced Raman spectroscopy(SERS) detection

—— Galarreta et al., 2013

Deoxynivalenol (DON) Microfluidics based Real-time electrochemical immunoassay detectionLinear range: 6.25e250 ng/mLLOD: 6.25 ng/mLAssay time: 15 min

Wheat grain Olcer et al., 2014

Botulinum Microfluidic device integrated with polystyrene microbeads by FRETdetection of enzymatic reaction

—— Bae et al., 2015

Botulinum neurotoxin (BoNT) Centrifugal microfluidic LabDisk platform, luciferase reporter assayLinear range: 8 p.m.-6 nMLOD: 6e14 pMAssay time: 30 min

Whole milk van Oordt et al., 2013

Okadaic acid PDMS microfluidic chip coupled with Love Wave biosensorLinear range: 0e200 mg/L

—— Zhang et al., 2015

Ricin Microfluidic passive pumping arrayLOD: 2 pM for orange juice and 170 pM for diet sodaAssay time: 35 min

Milk, orange juice, diet soda Khnouf, Chapman, Jin,Beebe, & Fan, 2015

Heavy metalMercury (II) ion (Hg2þ) and silver(I)

ion (Agþ)Paper-based microfluidic device, fluorescence labeled single-strandedDNA (ssDNA) functionalized graphene oxide sensorLOD: 121 nM (Hg2þ); 47 nM (Agþ)Assay time: ~10 minRecovery: 87.5%e116% (Hg2þ); 91%e126% (Agþ)

—— Zhang et al., 2015

Copper (Cu2þ) ions Paper-based microfluidic deviceLOD: 1.0 ng/mLAssay time: 2 min

Tomoto, rice Chaiyo et al., 2015

Copper (Cu2þ) ions Paper-based microfluidic chiplinear range: 0.01e1 ppmLOD: 0.018 ppm

—— Thao, 2013

Mercury ion (Hg2þ) Optical microfluidic systemLOD: 11 ppb

—— G�omez-de Pedro et al.,2014

Cadmium (Ca2þ) Y-shape PMDS microfluidic device, fluorimetric detection,Linear range: 0e1 mMLOD: 0.45 mg/L

—— Zhang et al., 2013

Other componentsNeomycin Paper-based microfluidic device. Fluorescence labeled single-stranded

DNA (ssDNA) functionalized graphene oxide sensorLOD: 153 nMAssay time: ~10 minRecovery: 95%e101%

—— Zhang et al., 2015

Dichlorvos molecularly imprinted polymer (MIP) based lab-on-paper device,chemiluminescence(CL) detectionLinear range: 3.0 ng/mL-1.0 mg/mLLOD: 0.8 ng/mLAssay time: ~20 min

Cabbage leaves,tomato skin

Liu et al., 2015

Nitrite Microfluidic paper-based analytical devices, colorimetric determinationthrough the modified Griess reactionLOD: 5.6 mMAssay time: ~25 min

Ham, sausage Cardoso et al., 2015

Dichlorvos Cabbage, cucumber, tomato Liu et al., 2014

(continued on next page)

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e22 13

Table 1 (continued )

Target analyte/sample Characteristic of the microfluidic deviceand the analysis

Real sample Reference

Pathogen

Microfluidic paper-based devices, chemiluminescence (CL) detectionLinear range: 10.0 ng/mL-1.0 mg/mLLOD: 3.6 ng/mL

Organophosphate (OP) Paper-based device coated with nanoceria, enzyme inhibition assay,LOD: 18.3 ng/mL (methyl-paraoxon); 5.3 ng/mL (chlorpyrifos-oxon)Assay time: ~50 minRecovery: ~95%

Cabbage, dried green mussel Nouanthavong,Nacapricha, Henry, &Sameenoi, 2016

Chlorpyrifos PDMS microfluidic immunosensor chip, impedance detection,Linear range: 10e105 ng/mLLOD: 1 ng/mLAssay time: ~20 minRecovery: 88.6%-102.5

Leek, lettuce and cabbage Guo et al., 2015

Fig. 1. Schematic of the layout of the PDMS microfluidic chip and the portable fluorometer for Salmonella detection by Kim et al. (2015).

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e2214

a LAMP-based microfluidic lab-on-a-disc for automatic Salmonelladetection by integrating sample preparation, LAMP reagent mixingand metering, sealing, amplification, and detection on a single disc.Centrifugal force was applied to dispense liquid on to the disc. Atomato spiked with Salmonella DNAwas assayed using this methodand results were obtained in approximately 70 min with a limit ofdetection of 5 � 10�3 ng DNA/mL, which is a much shorter time-frame than the conventional method that usually requires 3e4 h.Usually, liquid transport is obtained by the centrifugal forcegenerated from spinning motors, ome other liquid pumping ap-proaches include thermal expansion, electrolytic gas generation orexpansion (Strohmeier et al., 2014). Therefore, mechanic or heatingelements will be used, which dose not facilitate the miniaturization

of the system.

2.2. Food allergens

A food allergy is an abnormal immune-mediated response tocertain foods. Food allergies have become a critical food safety andpublic health issue due to the dangers of allergic reactions and thelegal regulations imposed on the food industry. Eight types of foodare responsible for the majority of allergic reactions: peanuts, treenuts, milk, eggs, wheat, soy, fish, and shellfish (FARE, 2016).Monitoring of food allergens is critically important to both the foodindustry and to susceptible individuals. There is no cure for foodallergies and the only way for sensitive individuals to protect

Fig. 2. Schematic of the (a) PDMS/paper hybrid microfluidic system integrated with aptamer-functionalized GO biosensors for multiplexed pathogen detection (not drawn to scale).(b) The system consisted of three layers: bottom glass slide, middle PDMS layer bearing four 3 � 8 microwell array with a piece of chromatography paper in each well for reactionand incubation, top PDMS layer for delivery of reagents. (c) Principle of ‘turn on’ homogenous assay based on graphene oxide, aptamer labeled with Cy3 and pathogens (Zuo et al.,2013).

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e22 15

themselves against an allergenic reaction is strict avoidance of foodcontaining the offending component(s). The increase in allergenregulations and awareness highlight the need for accurate, on-site,sensitive, and rapid assays to detect potential allergens in food.

Clinical diagnosis of patients suffering from food allergies isusually performed by immunochemical methods such as RAST(radio-allergosorbent) or EAST (enzyme-allergosorbent) assayswhich are based on the use of IgE isolated from the serum of in-dividuals who are allergic to certain foods (Andjelkovic, Martinovic,& Josic, 2015). One limitation of using IgE for clinical diagnosis offood allergies is that serum samples are required from allergic in-dividuals, which creates a potential biological hazard risk. Inaddition, standardization and false positives are the other twochallenges in developing microfluidics as a tool for rapid allergendetection (Andjelkovic et al., 2015). Thus, in this review, we focuson the direct detection and measurement of allergens in foodsamples.

Electrochemical microfluidic chip is a powerful tool to performfood analysis which benefits from the advantages of electro-chemical methods including high sensitivity, simplicity of opera-tion, and good temporal and spatial control (Hao & Wang, 2016;Martin, V�azquez, & Escarpa, 2016). Jiang et al. (2016) designed acell-to-cell electrochemical microfluidic chip for food allergendetection via measurement of food allergen-induced cell morpho-logical changes, as shown in Fig. 3. ANA-1 macrophages and RBL-2H3 mast cells were seeded at a density of 106 cells/mL andcultured in parallel channels, followed by injecting 0.1 ng/mLdinitrophenylated bovine serum albumin (DNP-BSA) of allergensolution to stimulate macrophage cells and mast cells. Metabolitedetection was performed on an electrochemical workstation viareal-time monitoring and analysis of impedance signal changes inthe microfluidic chip. The electrochemical microfluidic chip accu-rately monitored real-time allergenic responses in the cell andprovided a general platform for food allergen detection.

As the exploration and combinations of materials, fluid handlingand detection techniques in microdevices, immunosassays can beperformed. Zhang et al. (2013) developed a microfluidic ELISA fordetection of allergens in the food system. A T-shaped PDMS/glasschip was fabricated and a peristaltic pump was used to deliversample, wash buffer, and other reagents. The casein in a milksample was measured and the performance was compared with acommercial 96-well assay. The on-chip assay had a superior 7-logdetection range (100 g/mL~1 mg/mL) with a low limit of detec-tion of 100 ng/mL, compared to a 2-log detection range (50 ng/mL~1 mg/mL) of a conventional 96-well assay. The on-chip methodalso had a decreased analysis time from 45 min to 15 min. TheBionano group at the University of Guelph (Weng, Gaur, &Neethirajan, 2016) developed a microfluidic ELISA chip for wheatgluten and Ara h 1 protein determination via colorimetric detectionusing a miniaturized optical detector. The wheat gluten and Ara h 1proteins in biscuits, gluten-free flour, chocolate bars and peanutbutter were successfully analyzed. The sensitivity of this on-chipmethod and commercial ELISA kits were comparable while thetotal assay time was reduced from 4 h to 20 min. Microfluidic ELISAsubstantially reduces the time and reagent consumption comparedto the standard lab ELISA, which may extend the range of its ap-plications. More recently, our group (Weng & Neethirajan, 2016)developed another microfluidic biosensor by utilizing quantumdots (QD)-aptamer-graphene oxide (GO) complexes as probes thatundergo conformational change upon interaction with food aller-gens. These interactions resulted in fluorescence changes due tofluorescence quenching and recovery properties of GO by adsorp-tion and desorption of aptamer-conjugated QDs. The concentrationof proteinwas determined by recovered fluorescence intensity. Thisone-step ‘turn on’ homogenous assay in a ready-to-use microfluidicchip required ~10 min to quantitatively detect Ara h 1, one of themajor allergens in peanuts, at a detection limit of 56 ng/mL. Using ahomemade miniaturized optical detector, our methods pave the

Fig. 3. (a) and (b) The two-layer cell-to-cell electrochemical microfluidic chip for food allergen investigation, which consisted of PDMS flow channels (top) and electric platingelectrodes glass wafer (bottom). (c) Schematic of the bioreactor on the microfluidic device. (e) Layout of the PDMS chip. (e) Electrodes in microfluidic chip (mm) and (f) assemblyschematic of the microfluidic chip (Jiang et al., 2016).

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e2216

way for a rapid, sensitive, and cost-effective on-site determinationof food allergens in a complex biological system. The microfluidicbiosensor simplified the procedures significantly but had compa-rable or even superior sensitivity than the microfluidic ELISAapproach.

2.3. Biotoxins

Biotoxins refer to toxic substances produced by a living organ-ism that may seriously threaten the health or life of humans andlivestock if they exist in raw or processed foods (Dong, Xu, Yong,Chu, & Wang, 2014). The poisonous effects of biotoxins (i.e. myco-toxin, marine toxin, phytotoxin, and animal toxin) (Zhang et al.,2014) can be acute even at a very low intake dosage. Therefore,government agencies and food administration institutes have setextremely strict maximum residue limits on biotoxins in food.Microfluidic chips are capable of conducting both analyte trans-portation and sensing, its rapid sensing time, low sample con-sumption and high compatibility make them widely used inbiotoxin determination. Recently, due to the requirement for highvolume and high-throughput on-site detection, numerous rapidsensing methods have been developed. Microfluidics-based plat-forms present significant advantages in homemade portable micro-instrument development of rapid and high-sensitivity biotoxindetermination. Recently, Guo, Feng, Fang, Xu, & Lu (2015) sum-marized the application of microfluidics to the detection of myco-toxins in agricultural and food products.

Olcer et al. (2014) developed a real-time microfluidic electro-chemical profiling method for on-site detection of deoxynivalenol(DON) in wheat. Two sets of electrode arrays were fabricated on asilicon dioxide wafer and cut to 10 � 20 mm2 to form the sensor

chips. A poly(methyl-methacrylate) (PMMA) sensor cassette wasthen fixed to the sensor chip by means of double-sided sticky tapeto form amicrofluidic channel. An assaywas performed by applying0.1 V potential to the electrode array followed by continuous cur-rent measurement. Samples of wheat spiked with DON wereassayed by microfluidic electrochemical profiling as well as con-ventional ELISA. Good correlation between these two methods wasobtained with an R2 value of 0.97.

Aflatoxins are a secondary metabolite of molds, and pose aserious threat to humans and animals when consumed throughanimal sources or crop-based food products (Eaton & Groopman,2013; Grace et al., 2015; Kabak, 2016). Liu, Lin, Chan, Lin, and Fuh(2013) reported a microfluidic chip-based nano LC coupled to atriple quadrupole mass spectrometer (QqQ-MS) system for quan-titatively determining aflatoxins in peanut butter, peanut powder,and peanut samples. Spiked samples (8 mL total volume) wereassayed in a single test and good linearity ranging from 0.048 to16.00 ng/g with a regression coefficient of 0.996 was achieved. Hu,Deng, and Zou (2013) developed a microfluidic smectite-polymernanocomposite sensor for aflatoxin detection as well. By intro-ducingmicrofluidic channels, the flow of the aflatoxinwas confinedto a narrow zone of the smectite-polymer nanocomposite surface;hence the diffusion time and traveling distance of the aflatoxinmolecules prior to adsorptionwas reduced. In addition, rather thanutilizing a sophisticated spectrofluorometer, the oblique-incidentwas employed to generate fluorescence excitation modulation forquantitative determination of aflatoxin. Aflatoxin B1-spiked cornextraction solutionwas tested on this chip and a single test could becompleted in 10 min. A dynamic detection range of 5e80 ppb wasachieved with a detection limit of 6.09 ppb. More recently, Uludaget al. (2016) developed a miniaturized automated system for

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e22 17

aflatoxin detection by coupling microfluidic electrochemical chips(based on theMiSens biosensor) and HPLC. The biochip consisted of6 working electrodes with shared reference and counter electrodes.When spiked wheat samples were assayed, a great correlationbetween this method and conventional ELISAwas obtained with anR2 value of 0.96. In addition, this method had a very high recoveryand a limit of detection as low as 0.08e0.65 ppb. Based on theaforementioned studies, these electrochemical methods havehigher sensitivity compared to the colorimetric methods.

Marine toxins produced by microscopic algae may causeneurological and gastrointestinal illnesses in humans when theyconsume toxins that have accumulated in filter-feeding shellfishesand fishes (McPartlin, Lochhead, Connell, Doucette, & O'Kennedy,2016; Shen et al., 2013; Zhang et al., 2012). As shown in Fig. 4,Zhang et al. (2015) developed a PDMS microfluidic chip integratedwith a real-time Love Wave biosensor for marine toxin detection.The PDMS chip consisted of 4 air cavities and 2 liquid storagecavities which were used as the cell culturing chamber. The LoveWave biosensor (Fig. 5c) consisted of a piezoelectric quartz sub-strate and Ti/Au interdigitated transducers (IDTs) guided with a3 mm SiO2 film. In this method, HepG2 cells were cultured in the 8-channel LoveWave biosensor array for the detection of okadaic acid(OA) by measuring the amplitude and phase signals. Real-timeresponse of the biosensors to different concentrations of OA wassuccessfully tested and a good linear correlation (R2 ¼ 0.9698) wasobtained.

A microfluidic ELISA method for detecting ochratoxin A in wineand beer using chemiluminescence was demonstrated by Novo,

Fig. 4. Schematic (a) and real picture (b) of the developed PDMS based microfluidic chip intbiosensor and the detection device (Zhang et al., 2015).

Moulas, Prazeres, Chu, and Conde (2013). The microfluidic devicecontained a U-shaped channel which was able to perform simul-taneous analysis of a reference solution and of a sample solution.The integrated microfluidic system required 10 mL of sample and45 min to complete the assay with LODs on the order of 0.1 and2 ng/mL for beer and red wine extracts, respectively. Botulinum, themain toxin responsible for food-borne botulism, was also detectedon a F€orster resonance energy transfer (FRET)-based microfluidicdevice (Bae, Jin, Kim, & Shin, 2015). Babrak, Lin, Stanker, McGarvey,and Hnasko (2016) also developed a 96-well microfluidic immu-noassay plate device with a tapered spiral microchannel in eachwell for the detection of botulinum toxin.

As mentioned above, centrifugal microfluidic platforms areoutstanding tools in the microfluidic field, as well as in determi-nation of biotoxins in food. van Oordt, Stevens, Vashist, Zengerle,and von Stetten (2013) and Koh et al. (2015) utilized centrifugalmicrofluidic platforms to automatically detect botulinum toxin. Thecentrifugal microfluidic immunoassay platform (SpinDx) devel-oped by Koh et al. (2015) could serve as a general-purpose immu-noassay platform to analyze multiple sample types, including food,without any sample preparation. A sample-to-result assay could beachieved within 30 min using 2-mL of unprocessed sample with100-fold improvement in sensitivity compared to the gold-standard mouse bioassay.

2.4. Heavy metal ions

Heavy metal contamination of food, as exemplified by arsenic,

egrated with the Love Wave biosensor. Schematic (c) and picture (d) of the Love Wave

Fig. 5. (a) Schematic of the colorimetric microdevice based on plug-based microfluidics for the detection of organophosphate pesticides (OPs). (b) The real size of the chip, planardimensions are 30 mm � 11 mm (Wang et al., 2014).

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mercury, copper and lead, poses a risk to human health, and hasproven to be a substantial food safety threat. Long-term exposure toheavy metals from the diet may cause cancer or other associateddiseases (Dong et al., 2014); thus, the importance of developingmethods for rapid, reliable detection of heavy metals cannot beunderestimated. Conventional lab methodologies for heavy metalincludes the atomic absorption spectrometry (AAS) and theinductively coupled plasma mass spectroscopy (ICP-MS), which arelimited in their use for in situ screening andmonitoring due to theirsize, cost, and analysis time. However, microfluidicmethods has thepotential to achieve the in situ measurement of heavy metal ions.

Chaiyo, Siangproh, Apilux, and Chailapakul (2015) used amicrofluidic paper-based analytical device for determination oftrace amounts of copper (Cu2þ) ions by colorimetric analysis via thecatalytic etching of modified AgNPs by thiosulfate. The deviceconsisted of 8 detection zones and was fabricated by awax printingmethod. A linear range from 0.5 to 200 ng/mL, with a LOD of0.35 ng/mL was obtained when determining the Cu2þ in real foodsamples, including tomato and rice. Marine microalgae are theprimary producers at the base of the marine food chain. Zheng,Wang, and Qin (2012) developed a microfluidic chip to estimatethe toxicity of heavy metals in marine organisms. The microfluidicchip consisted of a toxicant concentration gradient generator and amicroalgal chemostatic module. The toxicity of heavy metals wasassessed by testing the motility of the microalgae. The toxicity ofCu2þ and Cd2þwas investigated and they determined that Cu2þ hada more toxic effect than Cd2þ. G�omez-de Pedro et al. (2014)developed an optical microfluidic system for monitoring Hg (II)by using modified gold nanoparticles. Their method showed greatpotential for developing automatic, low-cost instruments for in-field measurements of Hg(II). Zhang et al. (2015) utilized a papermicrofluidic device integrated with single-stranded DNA (ssDNA)and a functionalized graphene oxide sensor to simultaneouslydetect heavy metal mercury (II) ions (Hg2þ), silver (I) ions (Agþ),and aminoglycoside antibiotic residue in food.

2.5. Other food concerns

Other concerns in food safety include pesticides, dyes and fun-gicides, antibiotics, persistent organic pollutants, and additives.

Wang, Suzuki, and Satake (2014) developed a colorimetricmicro-device using plug-based microfluidics for the determinationof organophosphate pesticides (OPs). As shown in Fig. 5, the

microfluidic chip consisted of a main flow channel and an auxiliaryflow including an array of rhombus structures for using surfacetension to precisely measure solution volumes. The volume andposition of the liquid plugs (substrate and a solution containingenzymes and OPs) were formed at the T-junction by applyingappropriate positive or negative pressure to the end of the flowchannels. The two plugs merged in the main flow channel and thenflowed into the detection chamber. This method provided a novelcolorimetric technique by using plugs of small volumes andmicrofluidics, thus minimizing the consumption of expensive re-agents, while also improving reproducibility and precision. Usingthis method, the lower limit of detection (LOD) was 33 nM formalathion and 90 nM for acephate, MEP, and diazinon wasachieved.

Cardoso, Garcia, and Coltro (2015) reported a paper microfluidicdevice to determine nitrite levels in ham, sausage, and preservativewater samples via colorimetric detection. The paper microfluidicdevice was fabricated using a stamping-based method. Thismethod required a sample volume of 0.4 mL, and of the LOD was5.6 mM. Liu, Kou, Xing, and Li (2014) developed a chromatographicchemiluminescence microfluidic chip for determination ofdichlorvos in fruits and vegetables. A linear relationship between10.0 ng/mL and 1.0 mg/mL with a detection limit of 3.6 ng/mL wasobtained. Guo, Liu, Sun, Cao, & Wang (2015) used a PDMS micro-fluidic impedance immunosensor to measure pesticide residue invegetables. The PDMS microfluidic chip consisted of a mainmicrochannel, a detection microchamber of6 mm � 0.5 mm � 0.02 mm, an inlet and outlet, and an interdigi-tated array microelectrode (IDAM) in the microchannel. Comparedto other methods, such as immunochromatography and AChE-[BMIM] [BF4]a- MWCNT/CPb, the microfluidic impedance immu-nosensor had a broader linear range of 10e105 ng/mL with a LOD of1 ng/mL in the determination of chlorpyrifos.

Dietary nutrition is important in maintaining health, andmonitoring nutrient content in the diet and in micronutrient sup-plements is an important part of a food-based strategy in the fightagainst global malnutrition. Microfluidics has also been used inmonitoring nutrient content in a range of applications. Ramadanet al. (2013) developed an integrated microfluidic platform calledNutriChip to mimic the in vivo environment of the human gastro-intestinal tract (GIT) to investigate the immuno-modulatory func-tion of dairy products. The NutriChip consisted of a monolayer ofconfluent epithelial cells separated from a co-culture of immune

Fig. 6. (a) Schematic of the NutriChip forming the miniaturized GIT. (d) A top view of a single apical fluidic chamber with small perfusion channels. (e) The miniaturized GITinserted in a prototype microfluidic interface unit (Ramadan et al., 2013).

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cells by a permeable membrane, as shown in Fig. 6. By monitoringthe expression of relevant immune cell biomarkers, the NutriChipplatform provided an option with which to evaluate the impact offood quality on health.

2.6. Food processing

Use of microfluidics allows for streamlining workflow and otherprocesses in the food and health sciences (Lin & Lee, 2010).Microfluidic technology has been applied to online process moni-toring and process efficiency improvement in fermentation pro-cesses in the food and beverage industry (Schemberg, Grodrian,R€omer, Gastrock, & Lemke, 2010).

Hypochlorous acid (chlorine) is a widely-used sanitizer forwashing fresh produce. When developing science-based foodsafety regulations and practices, minimum free chlorine concen-tration needs to be strictly monitored and controlled in order toprevent pathogen cross-contamination. Zhang et al. (2015) utilizeda mixer-based approach for free chlorine concentration determi-nation using the inactivation kinetics of E. coli O157:H7. Themicromixer was composed of three mixers (Y-injection mixer,Dean's vortex mixer, and chaotic mixer), three inlets for dispensing

bacterial, chlorine, and dechlorinating solutions, and one outlet.Pathogen inactivation kinetics, time and dose-dependent re-sponses of pathogen inactivation using free chlorine were assessedby the micromixer. The researchers found that E. coli O157:H7inactivation was significantly affected by the free chlorine con-centration and a 5-log10 reduction in viable bacterial cells could beobtained by exposing the culture to a solution of 1.0 mg/L freechlorine for at least one second. This method provides an efficientway to determine the minimum free chlorine concentrationrequired to prevent pathogen survival during fresh producewashing operations. Due to the comparable size of microfluidics tothe structural elements of foods, microfluidic devices are suitablefor developing novel food macrostructures (Kim et al., 2016).Emulsions are one of the most common components in processedfood products, and the control of features such as the texture andinterfaces within the food is critical to design innovative micro-structures and to obtain awider variety of functional characteristicsof food products (Maan, Nazir, Khan, Boom, & Schro€en, 2015).Although microfluidic emulsification has been extensively investi-gated in research laboratories, commercialization is difficult due tochallenges in scaling up for larger throughput (Maan et al., 2015).

Microstructural element formations, such as bubbles, fibers, and

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strips, are important in food engineering and industry. Calciumalginate foams have been reported to be produced by microfluidics(Ahmad, Stride, & Edirisinghe, 2012; Cuadros, Skurtys, & Aguilera,2012). A microfluidic device was employed (Cuadros et al. (2012))to produce calcium alginate fibers with uniform dimensions. Themicrofluidic device was co-axially assembled using transparentpolycarbonate capillary tubes, and a metal needle was designed togenerate coaxial flow. A CaCl2 solution was injected into the outercapillary tubes and mixed with the alginate solution from the innercapillary tubes to form the polymerized calcium alginate fibers.Laporte, Montillet, Della Valle, Loisel, and Riaublanc (2016) usedtwo PMMA micro-devices placed crosswise to produce food foamsto obtain desired void fractions [0.55e0.72] and flow rates viaviscous shear thinning fluidics in microchannels. This microfluidicmethod was able to produce stable foams at the lowest void frac-tions due to the higher flow velocities generated in themicrochannels.

In summary, by miniaturizing the analytical system, the afore-mentioned glass, silicon, and polymer-based microfluidic devicescan significantly reduce sample and reagent consumption whenmeasuring foodborne pathogens, allergens, biotoxins, and othercomponents. Compared to conventional lab methods, thesemicrofluidic devices demonstrated superior or comparable sensi-tivity, selectivity, and LOD while significantly reducing the assaytime due to the shorter diffusion distances and higher surface-to-volume ratio. By introducing microfluidics, handheld device forrapid in situ screening and on-site detection can be achieved.However, some of the shortcoming of microfluidics including theexpense of substrate materials, requirements for a power supply,and mechanical components for fluidic transport (Busa et al., 2016)are presented. Although paper-based microfluidic devices are moreeconomical and results can be obtained rapidly they can providequalitative or semi-quantitative results only; thus, there are limi-tations on selectivity and sensitivity. A major challenge in using themicrofluidic paper based analytical methods in food safety is the“off-chip” handling and pre-treatment of samples prior to detec-tion, which can be difficult to integrate into the microfluidic de-vices. Centrifugal microfluidic devices facilitate multiplex parallelanalyses and versatile operations, some of which are capable of an“on-chip” sample preparation. However, the disc fabrication isrelatively complicated. In addition, a spinning motor is required fordisc rotation leading to vibration issues, and the use of bulky me-chanical components is not desired when developing handheldsystems to be used in the field.

3. Conclusions and future perspectives

Food analysis for safety and quality control requires the devel-opment of portable, rapid, cost-effective, and highly sensitiveanalytical devices to meet both regulatory and consumer demands.Microfluidics analytical systems have become a powerful tool as analternative to conventional lab technologies due to their potentialfor high performance analysis in the food safety and food qualitysectors. Some of the improvements that microfluidics offers in-cludes a reduction in detection time and cost, a decrease indetection limits, and increased portability. However, currentmicrofluidics applications for food analysis have been utilized lesswhen compared to other fields, such as clinical and environmentaltesting (Escarpa, 2014). The tedious sample preparation due to thediverse nature of complex food matrix could be the main reason,because it requires more functional units integrated in the micro-fluidic chip hence increasing the complexity and cost. To simplifythe sample preparation techniques, separation and concentrationfor example, by leveraging the physical properties according to thespecific testing targets could be an effective solution. Although on-

chip extraction, filtration and centrifugation can be achieved,additional andmore complex fabrication steps are usually required.Therefore, more effort must be expended to develop diversemicrofluidic platforms for real food sample analysis by not onlyintegrating multiple functional units, but also improving themicrofluidic transport, by microfluidic electrokinetics, inertialfocusing, etc. In this article, we have summarized the most recentadvances in microfluidic methods for the detection of foodbornepathogens, allergens, biotoxins, heavy metals, and other food safetyrelated components.

Point-of-care testing devices should be portable in size tosimplify sample preparation and to lower the analysis time, whilealso providing comparable sensitivity and selectivity at a lower costcompared to centralized lab technologies. Microfluidics facilitatesthe miniaturization of the analytical device due to its small-scalesize. Computer numerical simulation technology has beenemployed to study the flow field and transportation of fluids inmicrochannels to aid in the design and to optimize the microfluidicdevice parameters. In addition, the miniaturization of the systemcould also be limited to the detector and food sample preparation.By using microfluidics, sample preparation can be performed in themicrochannel. Adami, Mortari, Morganti, and Lorenzelli (2016)demonstrated a microfluidic method to separate the fat and pro-tein components in milk. Optical detection with the aid of smartphone cameras (Coskun et al., 2013) or miniaturized optical/elec-trochemical sensors (Weng & Neethirajan, 2016) are promisingdevelopments that would make the device truly portable, person-alized, and easy-to-use in homes, schools, restaurants, and otherpublic venues. More recently, nanotechnology/nanomaterials havebeen coupled with microfluidics integrated biosensors, it not onlyfacilitate the miniaturization of the microfluidic system but also isan effective strategy to simplify sample preparation while signifi-cantly enhancing sensitivity and selectivity (Arduini et al., 2016).The development of novel microfluidic bio-sensing strategies pro-vides a promising way to integrate sample preparation operationsonto a chip resulting in simplification of a complex operation. Forexample, integration of bio-molecules into microfluidic systems,such as food proteins or DNA, is a powerful tool to improve samplepreparation as well as detection strategy. Aptamers, peptide se-quences, or single-stranded oligonucleotides are emerging as novelmolecular recognition probes in the biomedical field offering highaffinity and specificity towards various classes of target molecules.Aptamers, when used as an alternative to natural antibodies, areless expensive but more stable while still having high affinity andbinding specificity to their target molecules. A considerable varietyof aptamer-based assays have been employed in food analysis,including detection of foodborne pathogens, allergens, and bio-toxins, demonstrating outstanding performance (Amaya-Gonz�alez,de-los-Santos-�Alvarez, Miranda-Ordieres, & Lobo-Casta~n�on, 2013;Lin et al., 2014). However, the literature regarding the developmentof aptamer-based microfluidic platforms is very limited as this is anarea of recent growth. Surface enhanced Raman scattering (SERS)has also become a frontline tool for chemical or molecular analysis,sensing, detection, and identification (Aroca, 2006; West, Becker,Tombrink, & Manz, 2008). The distinct advantages of SERS, suchas a high degree of control of the surface functionalization,providing precise structural information in a few seconds, and theeasewith which SERS can be integrated into complex devices, makeit suitable for molecular recognition. Galarreta, Tabatabaei, Guieu,Peyrin, and Lagugn�e-Labarthet (2013) reported that theyembedded a SERS platform in a microchannel and achievedaptamer detection of ochratoxin A. By taking advantage of theoptical properties of the target, SERS-based microfluidic platformscan be used for food analysis. These platforms offer significantlyhigh sensitivity without sample preparation, particularly in the

X. Weng, S. Neethirajan / Trends in Food Science & Technology 65 (2017) 10e22 21

detection of toxins, pesticides, or heavy metal ions at lowconcentrations.

In the future, microfluidic analytical systems in combinationwith nanomaterials and novel bio-molecules for bio-sensing will becapable of offering simple, rapid, powerful, cost-effective, andhighly-sensitive analytical food analysis devices with a high degreeof portability, automation, and multiplexing capabilities.

Acknowledgments

The authors are grateful to the Natural Sciences and EngineeringResearch Council of Canada (400705), the Ontario Ministry ofResearch and Innovation (300181), and the Ontario Ministry ofAgriculture, Food and Rural Affairs (053142) for funding this study.

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