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The Use of Electrochemical Biosensors in Food Analysis

John Bunney, Shae Williamson, Dianne Atkin, Maryn Jeanneret, Daniel Cozzolino*, James Chapman, Aoife Power and Shaneel Chandra

Agri-Chemistry Group, School of Health, Medical and Applied Sciences Central Queensland University, Rockhampton North, QLD 4702, Australia.

Corresponding Author Email: d.cozzolino@cqu.edu.au

DOI : https://dx.doi.org/10.12944/CRNFSJ.5.3.02

Article Publishing History

Published Online: 25-10-2017

Plagiarism Check: Yes

Reviewed by: Dr. Dilek DÜLGER ALTINER (Turkey)

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Abstract:

Rapid and accurate analysis of food produce is essential to screen for species that may cause significant health risks like bacteria, pesticides and other toxins. Considerable developments in analytical techniques and instrumentation, for example chromatography, have enabled the analyses and quantitation of these contaminants. However, these traditional technologies are constrained by high cost, delayed analysis times, expensive and laborious sample preparation stages and the need for highly-trained personnel. Therefore, emerging, alternative technologies, for example biosensors may provide viable alternatives. Rapid advances in electrochemical biosensors have enabled significant gains in quantitative detection and screening and show incredible potential as a means of countering such limitations. Apart from demonstrating high specificity towards the analyte, these biosensors also address the challenge of the multifactorial food industry of providing high analytical accuracy amidst complex food matrices, while also overcoming differing densities, pH and temperatures. This (public and Industry) demand for faster, reliable and cost-efficient analysis of food samples, has driven investment into biosensor design. Here, we discuss some of the recent work in this area and critique the role and contributions biosensors play in the food industry. We also appraise the challenges we believe biosensors need to overcome to become the industry standard.

Keywords:

Biosensors, Food analysis; Rapid analysis; Selectivity; Sensitivity

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Bunney J, Williamson S, Atkin D, Jeanneret M, Cozzolino D, Chapman J, Power A, Chandra S. The Use of Electrochemical Biosensors in Food Analysis. Curr Res Nutr Food Sci 2017;5(3). doi : http://dx.doi.org/10.12944/CRNFSJ.5.3.02


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Bunney J, Williamson S, Atkin D, Jeanneret M, Cozzolino D, Chapman J, Power A, Chandra S. The Use of Electrochemical Biosensors in Food Analysis. Curr Res Nutr Food Sci 2017;5(3). http://www.foodandnutritionjournal.org/?p=4090


Introduction

Food safety

The issue of food safety has emerged as increasingly significant public concerns worldwide due to sub-quality foods being linked to increased morbidity, mortality, human suffering, and economic burden.1 Accordingly, in an information-age society where consumer awareness and expectations of safety are high, food manufacturers have to meet the need of modern consumers to make informed purchase decisions and their preference for food products with high quality and affordable price, and at the same time, must maintain high-quality standards and assurance of product safety.2

Matching the end-user compliance with regulatory guidelines on food quality, the instrumentation and scientific industries have responded with continuous improvement and development of analytical methodologies. Of many analytical methods, liquid chromatography has acquired a role of great importance in a majority of food analysis, as witnessed by the wide range of applications that can be found throughout the whole literature.3-5 However, choromatographic analysis is constrained by the rigors of often elaborate sample preparation, and homogenization, clean up and then the analytical component of the test to determine a viable concentration.4 Consequently, the process often must  be repeated multiple times, as many samples are needed to give an accurate result due to the number of  interferences in the matrix extracts, which can result in inaccurate identification and false positives.6 Additionally, the extensive set-up and extraction / clean-up processes required for HPLC analysis can cause prolonged delays in contaminant identification.This hefty time requirement makes HPLC methods unsuitable for “fresh foods” which are typically consumed in a short period, given short shelf lives. It is possible that by the time a contaminant is detected, multiple individuals may have been exposed to it, increasing likelihood of contamination.8,9

The need for selective measurement of analytes in food is paramount.10 Here, “younger” technologies like those on an electrochemical platform may present viable alternatives. Biosensors are an examples of new, innovative methods to tacking old but important problems in a quality-conscious society and have become powerful instruments in clinical, environmental and especially, food analyses.11

Therefore, in this review, we appraise biosensors applied to food analysis. We will examine the attributes of biosensors that present attractive alternatives to traditional technologies and instrumentation, briefly explore recent advances in biosensor technologies and also critique their limitations. We conclude the review by proposing future directions and challenges that the biosensor research arena has to overcome to establish as the new order in food analysis and safety.

Biosensor attributes

A biosensor can be defined as an analytical device that combines a biologically sensitive recognition element (such as antibodies, nucleic acids, enzymes, organelles, whole cells and aptamers) immobilized on a physicochemical transducer, and connected to a detector to identify the presence of one or more specific analytes, their concentrations, and kinetics in a sample.12 Electrochemical biosensors use an electrode transducer to detect electrons released by the reaction of the bioreceptor and analyte to obtain a measurable analysis of the contaminant.13 Figure 1 shows the general scheme of a biosensor.

Fig. 1: A simplified, general scheme of a biosensor depicating the three electrode system, direction of electron transfer on the working electrode and a close-up of the working electrode interface with the recognition entity. Reproduced with permission from Ref.14 Figure 1: A simplified, general scheme of a biosensor depicting the three-electrode system, direction of electron transfer on the working electrode and a close-up of the working electrode interface with the recognition entity. Reproduced with permission from Ref14.

Click here to View figure

 

Key to the operative success of biosensors is their biological recognition elements which imparts a superior level of specificity and binding affinity with the target molecule.  Such binding is termed specific binding or coupling and determines if an interaction occurs, which creates the electrical signal that is recorded and amplified.15 Because of the particularity of the recognition entity toward the analyte, a high level of selectivity is achieved which results in signals generated solely from such precise interactions, irrespective of the matrix complexity.16 This is terrifically illustrated by, commercially available, glucose meters that exploit a working electrode modified with glucose oxidase ensuring that a response is solely derived by glucose.17

The demand for high-speed, accurate and selective identification of analytes present within food produce, such as pathogenic bacteria,18 pesticides19 and toxins,20 has facilitated rapid advances in biosensor development and enabled quantitative detection and screening.  Apart from their inherent specificity, these biosensors help address the multifactorial food industry challenge of high analytical accuracy in the midst of the complex food matrices, overcoming differing densities, pH and temperature.21 It has been argued that for biosensor use to become widespread, they need to offer further substantial benefits over existing methods.22 One such advance is the potential for sensor miniaturization, which results in the sensor requiring greatly reduced sample sizes or volumes. However, sensor miniaturization   has only partially been achieved to date23 due to limitations in the structural integrity of very fine electrode tips associated with microelectrodes.24,25

The recent development of novel bio-recognition molecules, such as synthetic aptamers, DNA, proteins and viruses has enabled considerable selectivity in analysis.26,27 Furthermore, parallel improvements in the immobilization of bio-recognition molecules28 through robust attachment methods like electrodeposition29,30 and nanoparticle-bound entities at the working electrode interface is a significant step in the increased application of biosensors in food analysis. This is due in no small part to their greater specificity, selectivity and affinity for their target analytes.26,27

New leaps in biosensing

The field of biosensors has certainly witnessed astonishing growth in recent times.  Over the last three decades, the number of papers published on the subject each year has increased/risen approximately 4000%.31 Biosensor development and construction has focused predominantly on clinical research, continuing on the pioneering efforts of Clarke in 1950’s and 60’s.32,33  Yet, a shift in biosensor focus towards food analysis has grown in the last decade due to the improved accuracy in target pursuit, intensifying demands about quality from stakeholders, such as safety regulators, traders and consumers as well as significant reduction in analysis times associated with electrochemical detection.34

In the agriculture and food industries, early detection and sensitive analysis of potential contaminants and toxins is crucial35 and driven by a multiplicity of factors, such as the short shelf life of many fresh food products,36 increasing consumer preferences for chemical free and unprocessed foods,37 minimization of waste/reduction of costs in processing operations,38 and the need for detection in very low quantities, and removal of pathogens from the supply chain that may cause serious illness to the consumer.39

These pressures are exacerbated by  the inherent limitations of traditional food analysis methods that involve expensive, cumbersome instrumentation40 and as a result, have helped shape biosensor development relating to food analysis.41  Naturally, researchers have recognized the need for inexpensive, portable sensors that can perform rapidly and accurately with great sensitivity.42

Food analysis challenges

Biosensors address three broad categories of food analysis expectations: safety, quality and authenticity.43  Food safety screening focuses on the detection of undesirable  contaminants in food, such as pesticide and antibiotic residues,44,45 allergens,46 biological toxins47 and pathogenic microbes.48 Similar analysis is also used to establish or confirm the nutritional value of a food product.49 Authenticity analysis seeks to confirm the origin and/or production process of a food stuff, while also providing information about the adulteration or counterfeiting of food.49,50 The literature indicates that presently, electrochemical biosensors are primarily being utilized in food safety rather than quality and authenticity analysis.51,52

Traditional analysis methods for detecting harmful microorganisms, such as pathogenic Escherichia and Salmonella,53 aflatoxins54 and pesticides such as organophosphates and carbamates55 could only be conducted post-production.  This limitation is easily overcome by the use of biosensors which allows food items to be tested at all phases of production53 from raw materials screening to the product on shelf, resulting in more efficient means of ensuring of food safety and outbreak prevention.56

Timeliness and costs

Improved analysis times is another benefit to biosensor application in food analysis.  Using an array of biosensors on a microfluidic or lab-on-a-chip platform, low volume samples can be analyzed directly, thus eliminating the need for laborious and costly sample preparation stages.57  This is a particularly attractive feature of biosensors, where toxin accumulation often correlates with time,58 for example, mycotoxins are harmful carcinogenic metabolites produced by mold which affects many food products, including but not limited to; bread, cereals, dried fruit, wine and meat products.7

Biosensors present an attractive alternative as their capability of being used ­in situ allows reduced detection times, from several days to hours, or even minutes59-61 as illustrated in Figure 2. Other advantages stemming from in-situ determination capabilities include minimized sampling protocols, reduced storage requirements and the removal of often elaborate sample preparation procedures.62 Furthermore, in-situ detection capabilities allow for the improved portability of analysis tools such as handheld detection devices which generally require minimal training to operate63 and can facilitate the integration of real time analysis in food processing work centers/systems.64 Improved timeliness within food processing systems can also reduce spoilage, particularly in fresh produce, such as seafood, this was illustrated by the development of for the rapid detection of Vibrio parahaemolyticus65 – a leading global cause of bacterial gastroenteritis. Whilst bacteriophages have been successfully used to remove antibiotic strains of V. parahaemolyticus from seafood,66 the method lengthens the time between catch and plate, thus reducing the seafood’s freshness and ultimately its value.67

Figure 2: A flowchart elucidating the processing steps involved and relative time taken in detecting a pathogen in a food sample.  Reproduced under license from Ref67. Figure 2: A flowchart elucidating the processing steps involved and relative time taken in detecting a pathogen in a food sample.  Reproduced under license from Ref67.

Click here to View figure

 

The cost effectiveness of biosensors cannot be overstated. The rapid analysis rendered from biosensing allows significant gains through cost mitigation normally reserved for sample preparation methods and the need for expensive laboratories with highly trained staff,69 and the additional possibility of automated on-line analysis in food processing plants70 which will further reduce cost. Moreover, the ability of biosensors to detect contaminants in raw foods in real-time with high specificity and very low concentrations reduces waste56 and the economic costs associated with health issues and product recalls.68

Losses due to sample preparation

A fundamental prerequisite to using traditional methodologies in food analysis is the sample homogenization process, which can be problematic because of the organic acids and antimicrobial compounds present in many fruits and vegetables.71 The release of these compounds during sample preparation can inhibit the detection of certain contaminants, potentially having detrimental impacts on product consumers, a problem not encountered by biosensors as they require little or no sample preparation.8  Methods commonly used for detecting pathogenic bacteria detection in foods, such as enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR) or cell culture72 are incredibly time consuming.  The identification of certain pathogens may take days as they have lengthy sample preparation times coupled with low sensitivity, which can often result in false positives: ELISA requires a 24-48 hr period to successfully detect harmful pathogens such as Escherichia coli, a leading cause of death in children under five.73  Target-induced aptamer displacement strategies can overcome the time and sensitivity barriers by completing the test within 3.5 hours at a sensitivity of 112 CFUmL-1 in a phosphate buffer saline and 305 CFUmL-1 in a milk solution.74 This far exceeds the sensitivity of ELISA for E. coli detection.

Biosensor detection prowess

Despite the ubiquity of microbes, their detection in food is difficult75 and  further complicated by the fact that only some strains are pathogenic.76 Therefore, screening for the presence of bacteria alone is insufficient for food safety analysis and ideally, only the pathogenic strains, such as E. coli is one of two pathogenic strains responsible for 5 food poisoning deaths in Japan in 2011, should be identified.77 Here, biosensors present notable advances compared to traditional analysis methods in targeting only the analyte, such as the enterohaemorrhagic Escherichia coli strain O111.74

It should be noted that the specificity of biosensors is not limited to the detection of a singular analyte. Several biosensors have been developed to detect minute levels of multiple pesticide residues in foods based on the biochemical pathways the pesticides act upon, such as acetylcholinesterase (AChE) inhibitors. This means biosensor usefulness can extend to an entire class of pesticides.78 Similarly biosensors have been designed to detect certain compounds or toxin vectors, because of their inherent potential for inducing acute toxicity.  Screening for these is critically important to food safety as such contaminants may have devastating effects even in very low concentrations. For example as few as ~10 bacteria can cause infection67; carbamate pesticides which, despite having a low bioaccumulation potential are considered carcinogenic,79 and antibiotic residues in animal-derived foods can cause allergic reactions and even secondary infections.80 Biosensors can also detect traditionally challenging ‘viable but not culturable’ (VBNC) bacteria, differentiating dangerous pathogens that are in a state of dormancy from non-living, non-threatening bacteria.81

Current innovations in biosensor design

While enzymatic biosensors were recognized as a leap into elevated or ultimate selectivity, the next stage in biosensor design includes gene based sensors involving DNA; as the recognition or coupling entity (via hybridization), antibody or antigen based biosensors; and whole cell sensors.82 Within the agri-food industry, pathogen detection trends have focused on the utilization of single sensor platform for detection of multiple pathogens/toxins.83 More recently, biotechnology has shifted into ever smaller systems to allow for portability, cost reduction, analysis time reduction and commercial viability.84  Improvements in microfabrication systems have similarly aided in advancing biosensor technology and utility.85  Emerging nanomaterials, such as nanoparticles and nanofibers have featured in these, paving the way for this miniaturization trend.86

Such functional nanomaterials enhance electrochemical biosensors in two ways: refining the response features of the electrode by increasing its surface area for instance and assisting in robust attachment of the bioreceptor/recognition entity.  With greater surface to area volume ratios, nanomaterials lend greater catalytic prowess, ensure biocompatibility and achieve lower mass transfer resistance. This translates to improved selectivity, sensitivity, time efficiency and cost effectiveness for the biosensor.87-89 Similarly, the increase in transducer surface area delivers greater conductivity and sensitivity, promotes greater interaction capacity90 and lowers detection limits.91 These are all ideal features of a biosensing interface.  An excellent example of a nano-biosensor, capable of pesticide residue detection in concentrations as low as 0.4 pM, has been reported in by Verma et al.86 Furthermore, the inclusion of other nanomaterials at the transducer level, for example carbon nanotubes,92 can increase electron transfer and increase the transducer activity.93 Evidence of these improvements is in the slow but gradual replacement of traditional enzyme-substrate biosensors by nano-biosensor technology.94 Nano-biosensors have been developed for the agriculture and food processing industries to identify and quantify pesticides, herbicides, pathogenic microorganisms and other microbial contamination such as viruses and bacteria, hormones, glucose, as well as the presence of insects or fungus.95-97

Another medium of interest is microfluidics which provides throughput processing, reduces sample and reagents volume (down to the nanolitre),56 increases sensitivity, and employs a single platform for both sample preparation and detection.98 Microfluidics are portable, disposable, offer real-time detection, and simultaneous analysis of different analytes in a single device with exceptional accuracy.99,100 For example, microfluidic nano-biosensor for the detection of pathogenic species like Salmonella have already been proposed recently.101

It is envisaged that the ever improving analytical properties of electrochemical transducers will even allow for the detection of multiple analytes simultaneously.102 However, despite these promising advances and the potential of nanomaterial-based biosensors, realistically their application within food matrices is still in the very early stages of development.103 Compared with other biosensing forays, for example in medicinal biosensor technology through favored point of care and home diagnostics for pregnancy, glucose content, biosensing in food production and processing or screening has not been embraced as readily.104-106

Concluding remarks and future directions

Although biosensors display clear advantages over traditional methods, the perfect biosensor does not as yet exist107 and there are many obstacles in its development to be overcome.108 Presently, many biosensors are not easily implementable, if only because so few are currently available commercially.108

Nonetheless, it is almost inevitable that the future of biosensors will involve partnership with information communications technology to assist food producers, retailers, authorities and even consumers, in their  decision making109 by equipping them with the necessary tools and data to improve their decision-making process. This will ultimately, enable greater management of the natural resources.110-113 Moreover, inspired by mammalian sensory networks, new sensor systems being developed have the potential to revolutionize food analysis.114,115 Biomimetic sensors, such as electronic tongues and electronic noses are based on biosensor technologies116 and we expect that their exploitation of arrays of low specificity sensors capable of detecting multiple signals will allows a more complete analysis of food quality.  Inspiration for these developments and applications comes from the electronic tongues that form the basis for food authenticity and safety sensor systems,117,118 or similarly, electronic noses that can detect unique volatile compounds within the tea, wine, coffee, and spice industries.119-121

The combination of different types of biosensors has great promise: the fusion of electronic tongues with electronic noses and may further increase the identification capabilities of such a biomimetic system, as precisely as it does within the biological system,122 The advantage of real time monitoring in food manufacture, especially of dairy products123 and brewed products124, further enhances the usefulness of biosensors and drives the push for their  commercially availability to general public.125 The inherent specificity, sensitivity, and adaptability of biosensors make them the ideal candidate for use as a safety net throughout the food industry improving product quality with minimal investment,125 both now and for the foreseeable future. The opportunity afforded through biosensing, particularly in situ and safety analysis at all levels of the supply chain, as well as authenticity and quality analysis by the consumers themselves, make biosensors food productions tool of the future.

References

  1. Wu, M.Y.-C.; Hsu, M.-Y.; Chen, S.-J.; Hwang, D.-K.; Yen, T.-H.; Cheng, C.-M. Point-of-care detection devices for food safety monitoring: Proactive disease prevention. Trends in Biotechnology. 2017;35(4):288-300.
    CrossRef
  2. Baiano, A. Applications of hyperspectral imaging for quality assessment of liquid based and semi-liquid food products: A review. Journal of Food Engineering; 214(Supplement C). 2017;10-15.
    CrossRef
  3. Cacciola, F.; Dugo, P.; Mondello, L. Multidimensional liquid chromatography in food analysis. TRAC Trends in Analytical Chemistry. 2017
  4. Sun, H.; Ge, X.; Lv, Y.; Wang, A. Application of accelerated solvent extraction in the analysis of organic contaminants, bioactive and nutritional compounds in food and feed. Journal of Chromatography A. 2012;12371-23.
    CrossRef
  5. Verdu, C.F.; Gatto, J.; Freuze, I.; Richomme, P.; Laurens, F.; Guilet, D. Comparison of two methods, uhplc-uv and uhplc-ms/ms, for the quantification of polyphenols in cider apple juices. Molecules (Basel, Switzerland). 2013;18(9):10213-10227.
    CrossRef
  6. Frenich, A.G.; Vidal, J.L.M.; López, T.L.; Aguado, S.C.; Salvador, I.M. Monitoring multi-class pesticide residues in fresh fruits and vegetables by liquid chromatography with tandem mass spectrometry. Journal of Chromatography A. 2004;1048(2):199-206.
    CrossRef
  7. Alshannaq, A.; Yu, J.H. Occurrence, toxicity, and analysis of major mycotoxins in food. Int J Environ Res Public Health. 2017;14(6)
    CrossRef
  8. Yeni, F.; Acar, S.; Polat, Ö.G.; Soyer, Y.; Alpas, H. Rapid and standardized methods for detection of foodborne pathogens and mycotoxins on fresh produce. Food Control. 2014;40359-367.
    CrossRef
  9. Välimaa, A.-L.; Tilsala-Timisjärvi, A.; Virtanen, E. Rapid detection and identification methods for listeria monocytogenes in the food chain – a review. Food Control. 2015;55103-114.
    CrossRef
  10. Vasilescu, A.; Marty, J.-L. Electrochemical aptasensors for the assessment of food quality and safety. TRAC Trends in Analytical Chemistry. 2016;7960-70.
  11. Bahadır, E.B.; Sezgintürk, M.K. Applications of commercial biosensors in clinical, food, environmental, and biothreat/biowarfare analyses. Analytical Biochemistry. 2015;478107-120.
    CrossRef
  12. Perumal, V.; Hashim, U. Advances in biosensors: Principle, architecture and applications. Journal of Applied Biomedicine. 2014;12(1): 1-15.
    CrossRef
  13. Thévenot, D.R.; Toth, K.; Durst, R.A.; Wilson, G.S. Electrochemical biosensors: Recommended definitions and classification1international union of pure and applied chemistry: Physical chemistry division, commission i.7 (biophysical chemistry); analytical chemistry division, commission v.5 (electroanalytical chemistry).1. Biosensors and Bioelectronics. 2001;16(1):121-131.
    CrossRef
  14. Chapman, J.; Power, A.; Kiran, K.; Chandra, S. New twists in the plot: Recent 385 advances in electrochemical genosensors for disease screening. Journal of the 386 Electrochemical Society. 2017;164(13):B665-B673.
  15. Sharma, A.; Goud, K.Y.; Hayat, A.; Bhand, S.; Marty, J.L. Recent advances in electrochemical-based sensing platforms for aflatoxins detection. Chemosensors. 2017;5(1).
  16. Idili, A.; Amodio, A.; Vidonis, M.; Feinberg-Somerson, J.; Castronovo, M.; Ricci, F. Folding-upon-binding and signal-on electrochemical DNA sensor with high affinity and specificity. Analytical Chemistry. 2014;86(18):9013-9019.
    CrossRef
  17. Yoo, E.-H.; Lee, S.-Y. Glucose biosensors: An overview of use in clinical practice. Sensors (Basel, Switzerland). 2010;10(5):4558-4576.
    CrossRef
  18. Arora, P.; Sindhu, A.; Kaur, H.; Dilbaghi, N.; Chaudhury, A. An overview of transducers as platform for the rapid detection of foodborne pathogens. Applied Microbiology and Biotechnology. 2013;97(5):1829-1840
    CrossRef
  19. Arduini, F.; Cinti, S.; Scognamiglio, V.; Moscone, D. Nanomaterials in electrochemical biosensors for pesticide detection: Advances and challenges in food analysis. Microchimica Acta. 2016;183(7):2063-2083.
    CrossRef
  20. Bazin, I.; Tria, S.A.; Hayat, A.; Marty, J.-L. New biorecognition molecules in biosensors for the detection of toxins. Biosensors and Bioelectronics. 2017;87285-298.
    CrossRef
  21. Gaudin, V. Advances in biosensor development for the screening of antibiotic residues in food products of animal origin – a comprehensive review. Biosensors and Bioelectronics. 2017;90363-377.
    CrossRef
  22. Velusamy, V.; Arshak, K.; Korostynska, O.; Oliwa, K.; Adley, C. An overview of foodborne pathogen detection: In the perspective of biosensors. Biotechnology Advances. 2010;28(2):232-254.
    CrossRef
  23. Bettazzi, F.; Marrazza, G.; Minunni, M.; Palchetti, I.; Scarano, S. Biosensors and related bioanalytical tools. Comprehensive Analytical Chemistry. 2017;771-33.
    CrossRef
  24. Chandra, S.; Miller, A.D.; Wong, D.K.Y. Evaluation of physically small p-phenylacetate-modified carbon electrodes against fouling during dopamine detection in vivo. Electrochimica Acta. 2013;101225-231.
    CrossRef
  25. Chandra, S.; Miller, A.D.; Bendavid, A.; Martin, P.J.; Wong, D.K.Y. Minimizing fouling at hydrogenated conical-tip carbon electrodes during dopamine detection in vivo. Analytical Chemistry. 2014;86(5):2443-2450.
    CrossRef
  26. Chandra, S.; Siraj, S.; Wong, D.K.Y. Recent advances in biosensing for neurotransmitters and disease biomarkers using microelectrodes. ChemElectroChem. 2017;4(4):822-833.
    CrossRef
  27. Ali, J.; Najeeb, J.; Ali, M.A.; Aslam, M.F.; Raza, A. Biosensors: Their fundamentals, designs, types and most recent impactful applications: A review. Journal of Biosensors & Bioelectronics. 2017;8(1).
    CrossRef
  28. Putzbach, W.; Ronkainen, J.N. Immobilization techniques in the fabrication of nanomaterial-based electrochemical biosensors: A review. Sensors. 2013;13(4).
    CrossRef
  29. Srivastava, S.; Kumar, V.; Ali, M.A.; Solanki, P.R.; Srivastava, A.; Sumana, G.; Saxena, P.S.; Joshi, A.G.; Malhotra, B.D. Electrophoretically deposited reduced graphene oxide platform for food toxin detection. Nanoscale. 2013;5(7):3043-3051.
    CrossRef
  30. Devi, R.; Yadav, S.; Nehra, R.; Yadav, S.; Pundir, C.S. Electrochemical biosensor based on gold coated iron nanoparticles/chitosan composite bound xanthine oxidase for detection of xanthine in fish meat. Journal of Food Engineering. 2013;115(2):207-214.
    CrossRef
  31. Turner, A.P.F. Biosensors: Sense and sensibility. Chemical Society Reviews. 2013;42(8).
    CrossRef
  32. Harper, A.; Anderson, M.R. Electrochemical glucose sensors—developments using electrostatic assembly and carbon nanotubes for biosensor construction. Sensors. 2010;10(9).
    CrossRef
  33. Bhalla, N.; Jolly, P.; Formisano, N.; Estrela, P. Introduction to biosensors. Essays in Biochemistry. 2016;60(1):1-8.
    CrossRef
  34. Kim, K.-P.; Singh, A.; Bai, X.; Leprun, L.; Bhunia, A. Erratum: Kim, k.-p.; singh, a.K.; bai, x.; leprun, l.; bhunia, a.K. Novel pcr assays complement laser biosensor-based method and facilitate listeria species detection from food. Sensors 2015, 15, 22672–22691. Sensors. 2017;17(5):945-945.
    CrossRef
  35. Sharma, H.; Mutharasan, R. Review of biosensors for foodborne pathogens and toxins. Sensors and Actuators B: Chemical. 2013;183535-549.
    CrossRef
  36. Biji, K.B.; Ravishankar, C.N.; Mohan, C.O.; Srinivasa Gopal, T.K. Smart packaging systems for food applications: A review. Journal of Food Science and Technology. 2015;52(10):6125-6135
    CrossRef
  37. Law, J.W.-F.; Ab Mutalib, N.-S.; Chan, K.-G.; Lee, L.-H. Rapid methods for the detection of foodborne bacterial pathogens: Principles, applications, advantages and limitations. 2014;5.
  38. Nychas, G.-J.E.; Panagou, E.Z.; Mohareb, F. Novel approaches for food safety management and communication. Current Opinion in Food Science. 2016;1213-20.
  39. Vidal, J.C.; Bonel, L.; Ezquerra, A.; Hernández, S.; Bertolín, J.R.; Cubel, C.; Castillo, J.R. Electrochemical affinity biosensors for detection of mycotoxins: A review. Biosensors and Bioelectronics. 2013;49146-158.
    CrossRef
  40. McGrath, T.F.; Elliott, C.T.; Fodey, T.L. Biosensors for the analysis of microbiological and chemical contaminants in food. Analytical and Bioanalytical Chemistry. 2012;403(1):75-92.
    CrossRef
  41. Korotkaya, E. Biosensors: Design, classification, and applications in the food industry. Foods and Raw Materials. 2014;2(2).
  42. Justino, C.I.L.; Freitas, A.C.; Pereira, R.; Duarte, A.C.; Rocha Santos, T.A.P. Recent developments in recognition elements for chemical sensors and biosensors. TRAC Trends in Analytical Chemistry. 2015;682-17
  43. Rotariu, L.; Lagarde, F.; Jaffrezic-Renault, N.; Bala, C. Electrochemical biosensors for fast detection of food contaminants – trends and perspective. TRAC Trends in Analytical Chemistry. 2016; 7980-87.
  44. Ye, W.; Guo, J.; Bao, X.; Chen, T.; Weng, W.; Chen, S.; Yang, M. Rapid and sensitive detection of bacteria response to antibiotics using nanoporous membrane and graphene quantum dot (gqds)-based electrochemical biosensors. Materials. 2017;10(6):603
    CrossRef
  45. Ribeiro, F.W.P.; Barroso, M.F.; Morais, S.; Viswanathan, S.; de Lima-Neto, P.; Correia, A.N.; Oliveira, M.B.P.P.; Delerue-Matos, C. Simple laccase-based biosensor for formetanate hydrochloride quantification in fruits. Bioelectrochemistry. 2014;957-14.
    CrossRef
  46. Andjelković, U.; Gavrović-Jankulović, M.; Martinović, T.; Josić, D. Omics methods as a tool for investigation of food allergies. TRAC Trends in Analytical Chemistry. 2017.
  47. Malhotra, B.D.; Srivastava, S.; Ali, M.A.; Singh, C. Nanomaterial-based biosensors for food toxin detection. Applied Biochemistry and Biotechnology. 2014;174(3):880-896.
    CrossRef
  48. Singh, R.; Mukherjee, M.D.; Sumana, G.; Gupta, R.K.; Sood, S.; Malhotra, B.D. Biosensors for pathogen detection: A smart approach towards clinical diagnosis. Sensors and Actuators B: Chemical. 2014;197385-404.
    CrossRef
  49. Cao, M.; Li, Z.; Wang, J.; Ge, W.; Yue, T.; Li, R.; Colvin, V.L.; Yu, W.W. Food related applications of magnetic iron oxide nanoparticles: Enzyme immobilization, protein purification, and food analysis. Trends in Food Science & Technology. 2012;27(1):47-56.
    CrossRef
  50. Inbaraj, B.S.; Chen, B.H. Nanomaterial-based sensors for detection of foodborne bacterial pathogens and toxins as well as pork adulteration in meat products. Journal of Food and Drug Analysis. 2016;24(1):15-28.
    CrossRef
  51. Mehrotra, P. Biosensors and their applications – a review. 2016;6.
  52. Lavecchia, T.; Tibuzzi, A.; Giardi, M.T. Biosensors for functional food safety and analysis. Giardi, M.T.; Rea, G.; Berra, B., Eds. Springer US: Boston, MA, 2010; pp 267-281.
  53. Adley, C.C. Past, present and future of sensors in food production. Foods. 2014;3(3):491-510.
    CrossRef
  54. Castillo, G.; Spinella, K.; Poturnayová, A.; Šnejdárková, M.; Mosiello, L.; Hianik, T. Detection of aflatoxin b1 by aptamer-based biosensor using pamam dendrimers as immobilization platform. Food Control. 2015;529-18.
  55. Cesarino, I.; Moraes, F.C.; Lanza, M.R.V.; Machado, S.A.S. Electrochemical detection of carbamate pesticides in fruit and vegetables with a biosensor based on acetylcholinesterase immobilised on a composite of polyaniline–carbon nanotubes. Food Chemistry. 2012;135(3):873-879.
    CrossRef
  56. Jayas, D.S. The role of sensors and bio-imaging in monitoring food quality. Resource Magazine. 2017;12.
  57. Weng, X.; Neethirajan, S. Ensuring food safety: Quality monitoring using microfluidics. Trends in Food Science & Technology. 2017;6510-22.
    CrossRef
  58. Moreb, N.A.; Priyadarshini, A.; Jaiswal, A.K. Knowledge of food safety and food handling practices amongst food handlers in the republic of ireland. Food Control. 2017;80341-349.
    CrossRef
  59. Ruiz-Valdepeñas Montiel, V.; Gutiérrez, M.L.; Torrente-Rodríguez, R.M.; Povedano, E.; Vargas, E.; Reviejo, Á.J.; Linacero, R.; Gallego, F.J.; Campuzano, S.; Pingarrón, J.M. Disposable amperometric polymerase chain reaction-free biosensor for direct detection of adulteration with horsemeat in raw lysates targeting mitochondrial DNA. Analytical Chemistry. 2017;89(17):9474-9482.
    CrossRef
  60. Ahmed, A.; Rushworth, J.V.; Hirst, N.A.; Millner, P.A. Biosensors for whole-cell bacterial detection. 2014;27:631-646.
  61. Thakur, M.S.; Ragavan, K.V. Biosensors in food processing. Journal of Food Science and Technology. 2013;50(4):625-641.
    CrossRef
  62. Bülbül, G.; Hayat, A.; Andreescu, S. Portable nanoparticle-based sensors for food safety assessment. Sensors. 2015;15(12).
    CrossRef
  63. Garg, M.; Mehrotra, S. Biosensors. In Principles and applications of environmental biotechnology for a sustainable future, Singh, R.L., Ed. Springer Singapore: Singapore. 2017;341-363.
    CrossRef
  64. Alves, R.C.; Barroso, M.F.; González-García, M.B.; Oliveira, M.B.P.P.; Delerue-Matos, C. New trends in food allergens detection: Toward biosensing strategies. Critical Reviews in Food Science and Nutrition. 2016;56(14):2304-2319.
    CrossRef
  65. Nordin, N.; Yusof, N.A.; Abdullah, J.; Radu, S.; Hushiarian, R. A simple, portable, electrochemical biosensor to screen shellfish for vibrio parahaemolyticus. AMB Express. 2017;7(1):41.
    CrossRef
  66. Jun, J.W.; Kim, H.J.; Yun, S.K.; Chai, J.Y.; Park, S.C. Eating oysters without risk of vibriosis: Application of a bacteriophage against vibrio parahaemolyticus in oysters. International Journal of Food Microbiology. 2014;18831-35.
    CrossRef
  67. Castro-Ibáñez, I.; López-Gálvez, F.; Gil, M.I.; Allende, A. Identification of sampling points suitable for the detection of microbial contamination in fresh-cut processing lines. Food Control. 2016; 59841-848.
  68. Singh, A.; Poshtiban, S.; Evoy, S. Recent advances in bacteriophage based biosensors for food-borne pathogen detection. Sensors (Basel). 2013;13(2):1763-1786.
    CrossRef
  69. Wang, Y.; Salazar, J.K. Culture-independent rapid detection methods for bacterial pathogens and toxins in food matrices. Comprehensive Reviews in Food Science and Food Safety. 2016;15(1): 183-205.
    CrossRef
  70. Zeng, Y.; Zhu, Z.; Du, D.; Lin, Y. Nanomaterial-based electrochemical biosensors for food safety. Journal of Electroanalytical Chemistry. 2016;781147-154.
    CrossRef
  71. Farahi, R.H.; Passian, A.; Tetard, L.; Thundat, T. Critical issues in sensor science to aid food and water safety. ACS Nano. 2012;6(6):4548-4556.
    CrossRef
  72. Ligaj, M.; Tichoniuk, M.; Gwiazdowska, D.; Filipiak, M. Electrochemical DNA biosensor for the detection of pathogenic bacteria aeromonas hydrophila. Electrochimica Acta. 2014;12867-74.
    CrossRef
  73. Poltronieri, P.; Mezzolla, V.; Primiceri, E.; Maruccio, G. Biosensors for the detection of food pathogens. Foods. 2014;3(3):511-526.
    CrossRef
  74. Luo, C.; Lei, Y.; Yan, L.; Yu, T.; Li, Q.; Zhang, D.; Ding, S.; Ju, H. A rapid and sensitive aptamer-based electrochemical biosensor for direct detection of escherichia coli o111. Electroanalysis. 2012;24(5):1186-1191.
    CrossRef
  75. Zwietering, M.H.; den Besten, H.M.W. Microbial testing in food safety: Effect of specificity and sensitivity on sampling plans—how does the oc curve move. Current Opinion in Food Science. 2016;1242-51.
  76. Ma, X.; Jiang, Y.; Jia, F.; Yu, Y.; Chen, J.; Wang, Z. An aptamer-based electrochemical biosensor for the detection of salmonella. Journal of Microbiological Methods. 2014;9894-98.
    CrossRef
  77. Idil, N.; Mattiasson, B. Imprinting of microorganisms for biosensor applications. Sensors (Basel, Switzerland). 2017;17(4).
    CrossRef
  78. Raghu, P.; Madhusudana Reddy, T.; Reddaiah, K.; Kumara Swamy, B.E.; Sreedhar, M. Acetylcholinesterase based biosensor for monitoring of malathion and acephate in food samples: A voltammetric study. Food Chemistry. 2014;142188-196.
    CrossRef
  79. Oliveira, T.M.B.F.; Fátima Barroso, M.; Morais, S.; de Lima-Neto, P.; Correia, A.N.; Oliveira, M.B.P.P.; Delerue-Matos, C. Biosensor based on multi-walled carbon nanotubes paste electrode modified with laccase for pirimicarb pesticide quantification. Talanta. 2013;106137-143.
    CrossRef
  80. Chen, T.; Cheng, G.; Ahmed, S.; Wang, Y.; Wang, X.; Hao, H.; Yuan, Z. New methodologies in screening of antibiotic residues in animal-derived foods: Biosensors. Talanta. 2017;175435-442.
    CrossRef
  81. Ayrapetyan, M.; Oliver, J.D. The viable but non-culturable state and its relevance in food safety. Current Opinion in Food Science. 2016;8127-133.
  82. Yang, T.; Huang, H.; Zhu, F.; Lin, Q.; Zhang, L.; Liu, J. Recent progresses in nanobiosensing for food safety analysis. Sensors. 2016;16(7)
    CrossRef
  83. Cho, I.-H.; Radadia, A.D.; Farrokhzad, K.; Ximenes, E.; Bae, E.; Singh, A.K.; Oliver, H.; Ladisch, M.; Bhunia, A.; Applegate, B., et al. Nano/micro and spectroscopic approaches to food pathogen detection. Annual Review of Analytical Chemistry. 2014;7(1):65-88.
    CrossRef
  84. Warriner, K.; Reddy, S.M.; Namvar, A.; Neethirajan, S. Developments in nanoparticles for use in biosensors to assess food safety and quality. Trends in Food Science & Technology. 2014;40(2): 183-199.
    CrossRef
  85. Derkus, B. Applying the miniaturization technologies for biosensor design. Biosensors and Bioelectronics. 2016;79901-913.
    CrossRef
  86. Shruthi, G.S.; Amitha, C.V.; Blessy Baby, M. Biosensors: A modern day achievement. Journal of Instrumentation Technology. 2014;2(1):26-39.
  87. Verma, M.L. Nanobiotechnology advances in enzymatic biosensors for the agri-food industry. Environmental Chemistry Letters. 2017;1-6.
    CrossRef
  88. Zhu, C.; Yang, G.; Li, H.; Du, D.; Lin, Y. Electrochemical sensors and biosensors based on nanomaterials and nanostructures. Analytical Chemistry. 2015;87(1):230-249.
    CrossRef
  89. Anu Bhushani, J.; Anandharamakrishnan, C. Electrospinning and electrospraying techniques: Potential food based applications. Trends in Food Science & Technology. 2014;38(1):21-33.
    CrossRef
  90. Eivazzadeh-Keihan, R.; Pashazadeh, P.; Hejazi, M.; de la Guardia, M.; Mokhtarzadeh, A. Recent advances in nanomaterial-mediated bio and immune sensors for detection of aflatoxin in food products. TRAC Trends in Analytical Chemistry. 2017;87112-128.
  91. Rai, M.; Jogee, P.S.; Ingle, A.P. Emerging nanotechnology for detection of mycotoxins in food and feed. International Journal of Food Sciences and Nutrition. 2015;66(4):p.363-370; 66(4):363-370.
  92. Barsan, M.M.; Ghica, M.E.; Brett, C.M.A. Electrochemical sensors and biosensors based on redox polymer/carbon nanotube modified electrodes: A review. Analytica Chimica Acta. 2015;8811-23:
    CrossRef
  93. Yang, N.; Chen, X.; Ren, T.; Zhang, P.; Yang, D. Carbon nanotube based biosensors. Sensors and Actuators B: Chemical. 2015;207690-715.
    CrossRef
  94. Sharma, T.K.; Ramanathan, R.; Rakwal, R.; Agrawal, G.K.; Bansal, V. Moving forward in plant food safety and security through nanobiosensors: Adopt or adapt biomedical technologies? PROTEOMICS. 2015;15(10):1680-1692.
    CrossRef
  95. Sekhon, B.S. Nanotechnology in agri-food production: An overview. Nanotechnology, Science and Applications. 2014;7.
    CrossRef
  96. Pashazadeh, P.; Mokhtarzadeh, A.; Hasanzadeh, M.; Hejazi, M.; Hashemi, M.; de La Guardia, M. Nano-materials for use in sensing of salmonella infections: Recent advances. Biosensors and Bioelectronics. 2017;871050-1064
    CrossRef
  97. Sharma, R.; Ragavan, K.V.; Thakur, M.S.; Raghavarao, K.S.M.S. Recent advances in nanoparticle based aptasensors for food contaminants. Biosensors and Bioelectronics. 2015;74612-627.
    CrossRef
  98. Luka, G.; Ahmadi, A.; Najjaran, H.; Alocilja, E.; DeRosa, M.; Wolthers, K.; Malki, A.; Aziz, H.; Althani, A.; Hoorfar, M. Microfluidics integrated biosensors: A leading technology towards lab-on-a-chip and sensing applications. Sensors. 2015;15(12).
    CrossRef
  99. Rackus, D.G.; Shamsi, M.H.; Wheeler, A.R. Electrochemistry, biosensors and microfluidics: A convergence of fields. Chemical Society Reviews. 2015;44(15):5320-5340.
    CrossRef
  100. Huang, Y.; Shi, Y.; Yang, H.Y.; Ai, Y. A novel single-layered mos2 nanosheet based microfluidic biosensor for ultrasensitive detection of DNA. Nanoscale. 2015;7(6):2245-2249.
    CrossRef
  101. Kim, G.; Moon, J.-H.; Moh, C.-Y.; Lim, J.-g. A microfluidic nano-biosensor for the detection of pathogenic salmonella. Biosensors and Bioelectronics. 2015;67(Supplement C):243-247.
    CrossRef
  102. Vigneshvar, S.; Sudhakumari, C.C.; Senthilkumaran, B.; Prakash, H. Recent advances in biosensor technology for potential applications – an overview. Frontiers in Bioengineering and Biotechnology.2016;411.
    CrossRef
  103. Pilolli, R.; Monaci, L.; Visconti, A. Advances in biosensor development based on integrating nanotechnology and applied to food-allergen management. TRAC Trends in Analytical Chemistry. 2013;4712-26.
  104. Qin, C.; Tao, L.; Phang, Y.H.; Zhang, C.; Chen, S.Y.; Zhang, P.; Tan, Y.; Jiang, Y.Y.; Chen, Y.Z. The assessment of the readiness of molecular biomarker-based mobile health technologies for healthcare applications. Scientific Reports. 2015;17854-17854.
  105. Narsaiah, K.; Jha, S.N.; Bhardwaj, R.; Sharma, R.; Kumar, R. Optical biosensors for food quality and safety assurance—a review. Journal of Food Science and Technology. 2012;49(4):383-406
    CrossRef
  106. Quesada-González, D.; Merkoçi, A. Mobile phone-based biosensing: An emerging “diagnostic and communication” technology. Biosensors and Bioelectronics. 2017;92:549-562.
  107. Templier, V.; Roux, A.; Roupioz, Y.; Livache, T. Ligands for label-free detection of whole bacteria on biosensors: A review. TRAC Trends in Analytical Chemistry. 2016;7971-79.
  108. Valderrama, W.B.; Dudley, E.G.; Doores, S.; Cutter, C.N. Commercially available rapid methods for detection of selected food-borne pathogens. Critical Reviews in Food Science and Nutrition. 2016;56(9):1519-1531.
    CrossRef
  109. Zhang, D.; Liu, Q. Biosensors and bioelectronics on smartphone for portable biochemical detection. Biosensors and Bioelectronics. 2016;75273-284.
    CrossRef
  110. Seo, S.-M.; Kim, S.-W.; Jeon, J.-W.; Kim, J.-H.; Kim, H.-S.; Cho, J.-H.; Lee, W.-H.; Paek, S.-H. Food contamination monitoring via internet of things, exemplified by using pocket-sized immunosensor as terminal unit. Sensors and Actuators B: Chemical. 2016;233148-156.
    CrossRef
  111. Liu, Y.; Han, W.; Zhang, Y.; Li, L.; Wang, J.; Zheng, L. An internet-of-things solution for food safety and quality control: A pilot project in china. Journal of Industrial Information Integration. 2016;31-7.
  112. Parastar, H.; Shaye, H. Mvc app: A smartphone application for performing chemometric methods. Chemometrics and Intelligent Laboratory Systems. 2015;147105-110.
    CrossRef
  113. Qian, J.-P.; Yang, X.-T.; Wu, X.-M.; Zhao, L.; Fan, B.-L.; Xing, B. A traceability system incorporating 2d barcode and rfid technology for wheat flour mills. Computers and Electronics in Agriculture. 2012;8976-85.
    CrossRef
  114. Lu, L.; Hu, X.; Zhu, Z. Biomimetic sensors and biosensors for qualitative and quantitative analyses of five basic tastes. TRAC Trends in Analytical Chemistry. 2017;8758-70.
  115. Śliwińska, M.; Wiśniewska, P.; Dymerski, T.; Namieśnik, J.; Wardencki, W. Food analysis using artificial senses. Journal of Agricultural and Food Chemistry. 2014;62(7):1423-1448.
    CrossRef
  116. Cetó, X.; Voelcker, N.H.; Prieto-Simón, B. Bioelectronic tongues: New trends and applications in water and food analysis. Biosensors and Bioelectronics. 2016;79608-626.
    CrossRef
  117. Peris, M.; Escuder-Gilabert, L. Electronic noses and tongues to assess food authenticity and adulteration. Trends in Food Science & Technology. 2016;5840-54.
    CrossRef
  118. Facure, M.H.M.; Mercante, L.A.; Mattoso, L.H.C.; Correa, D.S. Detection of trace levels of organophosphate pesticides using an electronic tongue based on graphene hybrid nanocomposites. Talanta. 2017;16759-66.
    CrossRef
  119. Dong, Q.; Du, L.; Zhuang, L.; Li, R.; Liu, Q.; Wang, P. A novel bioelectronic nose based on brain–machine interface using implanted electrode recording in vivo in olfactory bulb. Biosensors and Bioelectronics. 2013;49263-269.
    CrossRef
  120. Glass, J.B.; Chen, S.; Dawson, K.S.; Horton, D.R.; Vogt, S.; Ingall, E.D.; Twining, B.S.; Orphan, V.J. Trace metal imaging of sulfate-reducing bacteria and methanogenic archaea at single-cell resolution by synchrotron x-ray fluorescence imaging. Geomicrobiology Journal. 2017;1-9.
  121. Zhou, H.; Luo, D.; GholamHosseini, H.; Li, Z.; He, J. Identification of chinese herbal medicines with electronic nose technology: Applications and challenges. Sensors. 2017;17(5):1073-1073.
    CrossRef
  122. Di Rosa, A.R.; Leone, F.; Cheli, F.; Chiofalo, V. Fusion of electronic nose, electronic tongue and computer vision for animal source food authentication and quality assessment – a review. Journal of Food Engineering. 2017;21062-75.
    CrossRef
  123. Nguyen-Boisse, T.T.; Saulnier, J.; Jaffrezic-Renault, N.; Lagarde, F. Highly sensitive conductometric biosensors for total lactate, d- and l-lactate determination in dairy products. Sensors and Actuators B: Chemical. 2013;179232-239.
    CrossRef
  124. Vargas, E.; Conzuelo, F.; Ruiz, A.M.; Campuzano, S.; Ruiz-Valdepeñas Montiel, V.; González de Rivera, G.; López-Colino, F.; Reviejo, J.Á.; Pingarrón, M.J. Automated bioanalyzer based on amperometric enzymatic biosensors for the determination of ethanol in low-alcohol beers. Beverages. 2017;3(2).
  125. Scognamiglio, V.; Arduini, F.; Palleschi, G.; Rea, G. Biosensing technology for sustainable food safety. TRAC Trends in Analytical Chemistry. 2014;621-10.


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