Recent advancements in sensing techniques based on functional materials for organophosphate pesticides

Biosensors and Bioelectronics 70 (2015) 469–481

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Biosensors and Bioelectronics

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Recent advancements in sensing techniques based on functional ma-terials for organophosphate pesticides

Pawan Kumar a, Ki-Hyun Kim a,n, Akash Deep b

a Department of Civil & Environmental Engineering, Hanyang University, 222 Wangsimni-Ro, Seoul 133-791, Republic of Koreab Academy of Scientific and Innovative Research, CSIR-CSIO, Sector 30C, Chandigarh 160030, India

a r t i c l e i n f o

Article history:Received 10 February 2015Received in revised form24 March 2015Accepted 25 March 2015Available online 27 March 2015

Keywords:OrganophosphatePesticidesHealth issuesSensingMonitoring techniques

x.doi.org/10.1016/j.bios.2015.03.06663/& 2015 Elsevier B.V. All rights reserved.

esponding author at: Department of Civil &g University, 222 Wangsimni-Ro, Seoul 12 2 2220 1945.ail address: [email protected] (K.-H. Kim

a b s t r a c t

The use of organophosphate pesticides (OPs) for pest control in agriculture has caused serious en-vironmental problems throughout the world. OPs are highly toxic with the potential to cause neurolo-gical disorders in humans. As the application of OPs has greatly increased in various agriculture activities,it has become imperative to accurately monitor their concentration levels for the protection of ecologicalsystems and food supplies. Although there are many conventional methods available for the detection ofOPs, the development of portable sensors is necessary to facilitate routine analysis with more con-venience. Some of these potent alternative techniques based on functional materials include fluorescencenanomaterials based sensors, molecular imprinted (MIP) sensors, electrochemical sensors, and bio-sensors. This review explores the basic features of these sensing approaches through evaluation of theirperformance. The discussion is extended further to describe the challenges and opportunities for theseunique sensing techniques.

& 2015 Elsevier B.V. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4692. Organophosphate pesticides: toxicity and its mechanism with poisoning symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 470

2.1. Toxicity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4702.2. Mechanisms of toxicity and symptoms of OP poisoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471

3. Functional materials based different sensing techniques for OPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4714. Performance of diverse sensing approaches established on functional materials for OP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472

4.1. Biosensors for OPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4724.2. Optical sensors for OPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4764.3. Electrochemical sensors for OPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4774.4. Molecularly imprinted polymer sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479

5. Comparison between different functional materials for sensing OPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4806. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481

1. Introduction

Productivity in agricultural activities has been greatly improved

Environmental Engineering,33-791, Republic of Korea.

).

via expansion of cultivation areas and techniques, development ofbetter seeds and better water management, and employment ofeffective pesticides (Eddleston et al., 2008; Soltaninejad and Ab-dollahi, 2009; Bassi et al., 2009). It is estimated that the use ofpesticides helps in securing almost one-third of crop productionglobally (Eddleston et al., 2008). The application of pesticides hasbeen accounted as a major factor for the high growth of wheat andcorn production in the UK and USA, respectively (Liu et al., 2008).

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481470

Likewise, it has helped China and India to register their cropproduction at 126 and 95 million tons, respectively in 2012 (UNFood & Agriculture Organization Report, 2013; September 04,2014, WHO Report).

Pollution due to the uncontrolled use of pesticides has becomeone of the most alarming challenges when pursuing sustainabledevelopment. Although pesticides are directly applied in plantsand soils, only 1% of pesticide sprayed is delivered to the intendedtarget. Accidental release of pesticides due to spills, leaking pipes,underground storage tanks, waste dumps, and ground water maylead to their persistence in the environment for a long time (due tolong half-lives) (Smith and Gangolli, 2002; Knapton et al., 2006).

For proper management of pesticides, one needs to accuratelyassess the status of their contamination in air, soil, and water(Smith and Gangolli, 2002; Knapton et al., 2006). Thus, the de-mand for rapid and reliable quantitation of pesticides in the en-vironment has become critical to attain the protection and securityof public health. Enzymatic biosensors and immunosensors are thetwo main classes of sensors feasible for the detection of organo-phosphate pesticides (OPs) in environmental samples. The adventof advanced functional materials in the past few decades such ascarbon nanotubes (CNTs), graphene, molecularly imprinted poly-mers (MIPs), and quantum dots (QDs) has allowed researchers todevelop and/or to improve sensor systems in parallel with con-ventional analytical instrumentation. These alternative, simple,fast, and portable sensors helped in providing much needed so-lutions to widen the scope and applicability of pesticide detectionsystems that could be achieved with conventional systems such asgas chromatography (GC) and high-performance liquid chroma-tography (HPLC) (Smith and Gangolli, 2002; Tahara et al., 2005;Tang et al., 2005; Knapton et al., 2006; Zhang et al., 2014).

The versatile applicability of advanced functional materials inenergy or sensing volatile organics has been reviewed in a numberof our recent publications (e.g., Kumar et al., 2015a, 2015b). In thisreview paper, we expanded the coverage to discuss recent devel-opments in sensor technology based on advanced functional ma-terials by specifically focusing on organophosphate pesticides(OPs). The first section describes the fundamental characteristicsof OPs, e.g. their categorization, general properties, applications,and sign/symptoms of poisoning. Discussions on the differentdetection techniques for OPs are surveyed with emphasis onelectrochemical, molecular imprinted, and fluorescent chemo-/bio-sensors. In addition, the applications of various advancedfunctional materials are reviewed. The advantages and dis-advantages of different approaches and/or advanced functionalmaterials are also evaluated to assess the usability and reliabilityof the different sensing techniques. Finally, the article discusses

Fig. 1. (a) Different classes and subclasses of pesticides used in agricultural land and (b) Pet al. (2010) by permission of MDP1.

the present challenges and opportunities vis-à-vis different de-tection techniques for OPs.

2. Organophosphate pesticides: toxicity and its mechanismwith poisoning symptoms

According to the US Environmental Protection Agency (EPA), apesticide is any substance or mixture of substances intended forpreventing, destroying, repelling, or mitigating pests. Pesticidescan be classified on the basis of target organism, origin, and che-mical structure. These can be inorganic, synthetic, or biological(biopesticides) compounds. Pesticides are broadly classified intothree main classes as shown in Fig. 1 (Obare et al., 2010).

Organophosphates pesticides are widely used in agriculturalindustries around the world. Hexaethyl tetra phosphate (HETP)was the first invented OP (in 1942) for use as an agricultural in-secticide (Hayes and Laws, 1991; Kwong, 2002; Tahara et al.,2005). Presently, a large number of organophosphorus compoundsare commercially available as insecticides, fungicides, and herbi-cides (Fig. 1) (Obare et al., 2010). Amongst the various classes ofOPs, the nitro-group containing compounds are widely used pro-ducts in agriculture as well as in many other areas includingchemical weapons. Some of the main examples of these OPs canbe listed as parathion, paraoxon, malathion, monocrotophos,coumaphos, and chloropyrifos.

2.1. Toxicity

Organophosphates pesticides are known as neurotoxic com-pounds that are structurally similar to well-known nerve gaseslike soman and sarin (Kwong, 2002). The chemical structure of OPis illustrated in Fig. 2 (Obare et al., 2010). OPs are synthetic organicchemicals that typically include esters/amides/thiol derivatives ofphosphoric/phosphonic/phosphorothioic/phosphonothioic acids(Fukuto, 1990a, 1990b); Costa, 2006; Jurewicz and Hanke, 2008;Aktar et al., 2009). All OPs have a central phosphorus atom witheither double bonded oxygen (P¼O) (oxon derivatives) or a doublebonded sulfur atom (P¼S) (thion derivatives) (Fig. 2) (Obare et al.,2010). Around one-hundred OPs are commercially available withdifferent physical, chemical, and biological properties. Most ofthem share some common physical and chemical properties suchas partial solubility in water, a high oil–water partition coefficient,low vapor pressure, and low volatility (except dichlorvos) (Zhaoand Hwang, 2009).

In an open environment, OPs undergo hydrolysis to yield wa-ter-soluble end products (Amaya-Chavez et al., 2006; Kazemi et al.,

ossible routes of pesticide contamination in the food-chain. Reproduced from Obare

Fig. 2. General chemical formulas and different examples of organophosphate pesticides. Reproduced from Obare et al. (2010) by permission of MDP1.

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481 471

2012). Parathion is one of the most toxic and widely used in-secticides. Once it is converted into paraoxon, the residues onplant surfaces persist in the environment (Kojima et al., 2010). Thepresence of such residues can become a significant problem,especially in hot and dry agricultural areas where agriculturalproducts are not properly washed before consumption or storage.Toxicity due to parathion is known to affect animal life with manytypes of illnesses and sometimes death. Another OP, fenitrothion,also constitutes a broad spectrum of insecticides used for pestcontrol in rice, vegetables, wheat, cereals, and cotton. Althoughfenitrothion has relatively low toxicity to mammals, it is known todisrupt the endocrine system (Amaya-Chavez et al., 2006; Kazemiet al., 2012).

Health risk analysis of OPs has been carried out in terms of the“No Observed Adverse Effect Level” (NOAEL). The nature and ex-tent of related toxic effects were studied in this model, and thedose levels were recorded at which no adverse effects were ob-served (Amaya-Chavez et al., 2006; Kazemi et al., 2012). The ac-ceptable daily tolerance values of OPs in different samples are alsocalculated using the NOAEL model. The relative hazard of a pes-ticide is dependent upon the combined effects of its toxicity, dosereceived, and length of exposure time. Another useful term “LD50”(lethal-dose 50) is the concentration of pesticide that is lethal to50% of a population of test subjects for a specific exposure time.The typical LD50 valves of various OPs are given in Fig. 2 (Obareet al., 2010). In certain cases, OP poisoning has been linked withadverse effects in the neurological and behavioral development ofthe fetus and newborn children (Obare et al., 2010). Because evena very low level of exposure from OPs may cause severe healthrelated problems, governments all over the world have laid downstringent regulations on the maximum permissible concentrationsof OPs in food samples, potable and drinking water, soil, andgeneral environmental media (Mulchandani et al., 2001; Wata-nabe et al., 2002; Zhang et al., 2014).

2.2. Mechanisms of toxicity and symptoms of OP poisoning

The toxicity of OPs depends upon a number of factors includingtheir chemical structure, mode of entry into organisms,

metabolism in the target organism, total applied dose, mode ofapplication, and degree of decomposition (Fukuto, 1990a, 1990b;Gong et al., 2011; Liu et al., 2013; Gong et al., 2014). In humans,OPs cause acute poisoning by primarily targeting the Acet-ylcholinesterase (AchE) enzyme which is found at neuromuscularjunctions and cholinergic brain synapses (Watanabe et al., 2002).This enzyme is essential for functioning of the central nervoussystem and plays an important role in the transmission of stimu-lation between the nerves. Poisoning by OPs may irreversibly in-hibit the above enzyme which, in turn, inactivates the main neu-rotransmitter “acetylcholine” (Watanabe et al., 2002). The poi-soning ultimately affects vital organs and disturbs muscular re-sponses. Damage to organs through OP poisoning makes themvulnerable to different crude diseases such as cancer, neurologicaldisorders, and reproductive disorders. At times, it may also lead todeath from mild poisoning from the pesticides or OPs associatedwith typical symptoms of fatigue, headache, dizziness, numbnessin the arms or legs, nausea and vomiting, excessive sweating,salivation, abdominal cramps (or diarrhea), inability to walk,generalized weakness, difficulty in talking, muscular twitches,contraction of the eye pupil, and unconsciousness. Higher levels ofpoisoning show more severe symptoms such as cardiac attack,high and low blood pressure, and stroke. Recent studies havehighlighted that children exposed to OPs are more likely to bediagnosed with attention deficit hyperactivity disorder (ADHD),pancreatitis, hypo- or hyperglycemia, and acute renal failure (Fu-kuto, 1990a, 1990b; Gong et al., 2011; Liu et al., 2013; Gong et al.,2014).

3. Functional materials based different sensing techniques forOPs

Environmental concerns related to OPs have risen to criticallevels due to excessive use of OPs in agriculture. Over the years,technicians and researchers have relied upon conventional ana-lytical techniques, like GC and HPLC for the desired detection ofOPs and their residues in the environment (Fig. 3). However, it isnot always convenient to employ such detection tools due to their

Fig. 3. Classification of the available sensing techniques for OP detection.

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high-cost, long analysis duration, and requirement of skilled labor.Fortunately, the need for simplified and portable detection tech-niques for OPs can be met through the use of biosensors, im-munosensors, chemosensors, or electrochemical sensors (Table 1).These technologies have undergone remarkable development.Some of the essential requirements for a viable sensing systemshould include (1) broadening of the detection spectrum vis-à-visthe specificity, sensitivity, temperature, pH, sample type, and ro-bustness, (2) fast response time, (3) field deployability, (4) bothqualitative and quantitative analysis, (5) cost-effectiveness, and(6) acquisition of additional modes for signal transduction. Focus isalso required for developing miniaturized sensors that integrateboth biosensing and chemosensing approaches to minimize oreliminate false-positives (Vadgama and Crump, 1992; Hu et al.,2003; Dhull et al., 2014; Ge et al., 2014; Wang et al., 2014; Xu et al.,2014).

Application of novel nano and hybrid advanced functionalmaterial (e.g. quantum dots, carbon nanotubes, graphene, andmetal organic frameworks) is another key to develop next-gen-eration sensor systems (Dhull et al., 2014; Ge et al., 2014; Wanget al., 2014). With great advancements in nanotechnology, differ-ent nanomaterials with unique chemical and physical propertieshave been widely employed to develop nanosensors for OPs. Metaloxide nanoparticles, quantum dots, graphene, nanocrystal co-ordination polymers and other functionalized/non-functionalizedfunctional materials/nanomaterials generally offer rapid, sensitive,and user friendly solutions. These materials bear high mechanicalstrength and have a large surface area to offer development ofextremely miniaturized sensors employing both optical and elec-trochemical transduction approaches (Barreto et al., 2010; Wenet al., 2010a, 2010b). Some of the above advanced materials, suchas metal organic frameworks (MOFs), can selectivitely interactwith OPs to yield measurable signals on the basis of the electrontransfer reaction involved. As such, there are a number of factorsto positively consider the feasibility of MOFs such as availability ofa stable framework structure, ultra-high porosity, a high internalsurface area, pore volume, thermal/chemical stability, selectivity,and their non-toxic nature. Consequently, the use of MOFs isprojected to be expanded in the construction of next-generation

pesticide sensors. MOFs are also reported as effective sorbents forOPs. In some other cases, applications for OP detection are alsomade after tagging with biomolecules.

4. Performance of diverse sensing approaches established onfunctional materials for OP

In a broad sense, OPs sensing approaches can be divided by thefact – whether to use biomolecules or not. These two approachescan be further divided into four major sub-classes: (1) biosensors,(2) optical sensors, (3) molecularly imprinted (MIP) sensors, and(4) electrochemical sensors (Table 1). In Table 1, a summary of thedifferent sensing functional materials/nanomaterials is providedwith information to allow a comparison between the reporteddetection limits therein. Table 2 highlights the advantages anddisadvantages of different detection methods. According to thisclassification, it can be assessed that the electrochemical detectionmethod is probably one of the most widely advocated techniquesfor OPs.

A large number of studies have been devoted to the develop-ment of detection methods for nitro OPs. It is interesting to notethat, except for paraoxon, the sensing of metabolites/residues is byfar considered to be an unexplored area. Most of the above men-tioned sensing techniques for OPs are reported to be sensitive;however, there is still a high demand for converting them intoportable alternatives with high accuracy levels. The stability andregeneration of tagged biomolecules (antibodies and enzymes) areanother critical factor that may influence the ultimate sensitivityand selectivity of OP detection. In some indirect immunoassays,the requirement of lengthy labeling steps is seen as a major de-terrent in extending their applications to practical levels.

4.1. Biosensors for OPs

A biosensor basically consists of two major integrated ele-ments, namely the transducer and the recognition element (Sas-solas et al., 2012; Goel, 2013). Recognition elements such as en-zymes, antibodies, and nucleic acids interact with the analyte to

Table 1List of materials used for the development of sensing systems for the detection of OPs.

Sr. no. Target analyte Detection limit (DL) Reconginationelement

Substrate type /assay

Materials Reference

Name Chemical formula CAS no. MW (g/Mol) Raw data DL (nM)

A. Biosensors1 Atrazine C8H14ClN5 1912-24-9 215.68 1 ng/mL 4.64 mAb ELISA NA Kaur et al. (2007)2 1 mg/mL 4636.50 mAb ELISA NA Salmain et al.

(2008)3 Chlorpyrifos C9H11Cl3NO3PS 2921-88-2 350.59 0.22 mg /L1 6.27 mAb ELISA NA Sullivan et al.

(2007)4 0.1 ppb 0.29 pAb ELISA NA Cho et al. (2002)5 0.3 ng/mL 0.86 pAb ELISA NA Brun et al. (2005)6 DDT C14H9Cl5 50-29-3 354.49 27 ng/mL 76.17 mAb ELISA NA Lisa et al. (2009)7 Deltamethrin C22H19Br2NO3 52918-63-5 505.20 1.2 ng/mL 2.38 mAb ELISA NA Kong et al. (2010)8 2,4-dichlorophenoxyacetic

acidC8H6Cl2O3 94-75-7 221.04 3 ng/mL 13.57 pAb ELISA NA Boro et al. (2011)

9 Enrofloxacin C19H22FN3O3 93106-60-6 359.4 1 ppb 2.78 mAb ELISA NA Watanabe et al.(2002)

10 EPN C14H14NO4PS 2104-64-5 323.3 0.09 ng/mL 0.28 pAb ELISA NA Shim et al. (2010)11 Imidacloprid C9H10ClN5O2 138261-41-3 255.66 0.03 ng/mL 0.13 pAb ELISA NA Wang et al. (2012)12 Metyl parathion C8H10NO5PS 298-00-0 263.21 50 ppt 1.90 mAb ELISA NA Kumar et al.

(2006)13 Parathion C10H14NO5PS 56-38-2 291.26 5 ng/mL, 10 ng/mL 1.71,3.42 mAb ELISA NA Liu et al. (2009)14 Sarin C4H10FO2P 107-44-8 140.09 25 mmol 25000 mAb ELISA NA Simonian et al.

(2001)15 Soman C7H16FO2P 96-64-0 182.17 25 mmol 25000 mAb ELISA NA Simonian et al.

(2001)16 Triazophos C12H16N3O3PS 24017-47-8 313.3 0.063 ng/mL 0.19 pAb ELISA NA Jin et al. (2012)

B. Optical sensors AChE17 All nitro OPs Applicable on fenitrithion, methyl parathion, para-

thion, and paraoxan5 ppb 15.76 NA MOF-5 Simonian et al.

(2001)18 1 ppb 3.15 NA NMOF1 Kumar et al.

(2014)Carbamate C3H7NO2 51-79-6 89.09 0.1 mM 100000 AChE Quartz fiber FITC Roger et al. (1991)

19 Endosulfan C9H6Cl6O3S 115-29-7 406.93 5.5 ppb 5 NA CdTe QDs Zhang et al. (2010)20 Herbicides and pesticides NA NA NA 2 ppm NA NA Cyclodextrin Delattre et al.

(2009)21 Metyl parathion C8H10NO5PS 298-00-0 263.21 15 ppb 63.50 AChE FITC Kolosova et al.

200322 5 ppb 19.00 OPH Pyranine Thakur et al.

(2013)24 Malathion C10H19O6PS2 121-75-5 330.35 2 ppb 7.60 OPH Pyranine Thakur et al.

(2013)25 Methyl-Azinphos C10H14NO5PS 56-38-2 291.26 1.96 ppm 673.01 AChE FITC Tang et al. 200826 10 nM 10 OPH (CdSe)ZnS Ji et al. (2005)27 Paraoxan C10H14NO6P 311-45-5 275.195 0.1 mM 100000 AChE Quartz fiber FITC Roger et al. (1991)28 Parathion C10H14NO5PS 86-50-0 317.32 1.96ppm 617.81 AChE FITC Tang et al. 200829 4 ppb 12.71 OPH Ag NPs Thakur et al.

(2012)30 NA NA NA platinum 1,2-

enedithiolateVan Houten et al.,1998

C. Electrochemical sensors31 Chlorpyrifos C9H11Cl3NO3PS 2921-88-2 350.59 NA NA NA Glassy carbon CNT Deo et al. (2005)

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Table 1 (continued )

Sr. no. Target analyte Detection limit (DL) Reconginationelement

Substrate type /assay

Materials Reference

Name Chemical formula CAS no. MW (g/Mol) Raw data DL (nM)

electrode32 NA NA NA Glassy carbon

electrodeAuNPs Xie et al. (2010)

33 0.1 nM, in nM AChE Gold electrode Fe2O4/c-MWNT Chauhan andPundir (2]011)

34 Malathion C10H19O6PS2 121-75-5 330.35 0.1 nM in nM AChE Gold electrode Fe2O4/c-MWNT Chauhan andPundir (2011)

35 Methyl parathion C8H10NO5PS 298-00-0 263.21 0.08 μg /mL 300 AChE Glassy carbonelectrode

MOF Wen et al. (2010a,2010b)

36 Carbon electrode CNT Wang et al. (2010)37 0.5 ng mL�1 0.2 Glassy carbon

electrodepRGO Li et al., (2013)

38 0.02 mg/ml 70 AChE Glassy carbonelectrode

Graphene–Nafion Xue et al., (2013)

39 0.82 ng/mL 3 NA Au electrode GN-AuNRs Zhu et al. (2014)40 0.15 ng/mL 0.5 NA Gold electrode Fe2O4/Au Wang et al.,

2008a, 2008b41 3 ppb 3 NA ZrO2 Liu and Lin (2005)42 Mecoprob C10H11ClO3 93-65-2 214.65 5 ppb 4 NA Glassy carbon

electrodeZIF-8 Kumar et al.

(2012)43 Malathion C10H19O6PS2 121-75-5 330.35 0.3 nM 0.3 NA Silicon wafer CuO NWs–SWCNTs Wu et al. (2011)44 Parathion C10H14NO5PS 56-38-2 291.26 0.01 ppb 0.001 Anti-parathion Glassy carbon

electrodeNMOF1 Kumar et al.

(2014)45 3 ng/ml 10 NA Gold electrode ZrO2/Au Wang et al.,

2008a, 2008b46 Paraoxan C10H14NO6P 311-45-5 275.195 0.4 pM 0.0004 AChE CNT,Au/cr-GS Liu and Lin (2006)47 8.0 pM 0.0008 NA Glassy carbon

electrodeCdTe QDs/Au/ MWNT Yang et al. (2012)

D. Molecularly imprinted sensing techniques AChE48 Chlorpyrifos C9H11Cl3NO3PS 2921-88-2 350.59 1.0�10�11 mol/L. 0.01 AChE Chlorpyrifos (CPF)

imprintingTiO2 Wu et al. (2011)

49 Diazinon C12H21N2O3PS 333-41-5 304.35 50 ng/mL 164 AChE Molecularly Im-printed Polymers

QDs@MIPnanosphere

Zhao et al., (2011)

50 Monocrotophos C7H14NO5P 6923-22-4 223.2 0.4 pM 0.0004 AChE CNT-modifiedelectrode

CNT Liu and Lin (2006)

51 NA AChE CdTe QDs/AuNPs. Du et al. (2008)52 Methyl parathion C8H10NO5PS 298-00-0 263.21 0.03 nM 0.03 BChE Glassy carbon

electrodeCdSe-QD

53 Parathion C10H14NO5PS 56-38-2 291.26 0.01 nM 0.01 BChE Glassy carbonelectrode

Fe3O4@TiO2 Zhang et al. (2013)

54 Paraoxan C10H14NO6P 311-45-5 275.195 0.1 pM 0.0001 AChE cr-Gs sheets AuNPs/cr-Gs Wang et al. (2011)

aRaw detection limit values reported in the original literature were converted to allow comparison of data using the same criterion.

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Table 2Advantages and disadvantages of different OP sensing techniques.

Sr. no. Sensing techniques type Handling Detection setup

Analysis cost Sensitivity Selectivity Reliablilty Reproducibility Real worldapplication

1 Chromatography/spectroscopytechniques

Skilled Large Very high Excellent Excellent Excellent Excellent Good

2 Biosensors Fair Small Low Excellent Excellent Fair Fair No3 Optical sensors Easy Very small Very low Excellent Excellent Fair Fair No4 Electrochemical sensors Easy Small Low Excellent Excellent Excellent Good Fair5 Molecularly imprinted sensors Easy Very small Very low Excellent Excellent Fair Good Fair

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produce measurable electrical or fluorescence signals for detec-tion. Biosensing probes have attained considerable sophisticationwith the aid of fusion technologies, such as microelectronics andbiotechnology. Biosensors have become a popular tool for detect-ing a wide spectrum of chemical analytes, including gases, ions,organic compounds, pesticides, and bacteria. Several types ofbiosensors for pesticides have been reported over the years (Sas-solas et al., 2012; Goel, 2013). Enzymatic biosensors are amongstthe most popular tools during the last few decades as they providea viable, handy, and potentially portable alternative. However, ef-forts are still continuing to optimize their sensitivity and accuracy.In these types of biosensors, the enzymes of choice include acet-ylcholinesterase (AChE), butyryl cholinesterase (BChE), organo-phosphorus acid anhydrolase (OPAA), organophosphorus hydro-lase (OPH), choline oxidase (ChOx), and tyrosine (Simonian et al.,2001; Cho et al., 2002). The mechanism of detection for theseenzymes is shown in Table 3. Biosensors based on AChE/BChEinhibition or organophosphate hydrolase (OPH) induced hydro-lysis have allowed fairly sensitive monitoring of OPs (EPA, 2014a,2014b). Cholinesterases, urease, and GOx based techniques are fastand sensitive but are susceptible to poor specificity, longer in-cubation times, and interference from other substances, such asheavy metals and Carbamates (Cho et al., 2002). The OPAA enzymeis capable of effectively hydrolyzing the P–F bond (G agents) of OPs(such as sarin and soman), thus providing a pathway for theirdetection. This enzyme also provides specificity towards G agents.OPH is capable of hydrolyzing the P–O, P–F, P-CN, and P–S bondsof organophosphate and offers the detection of a large class of OPs.As such, OPPA appears to be the most attractive alternative in thecatalytic sensing of OPs. In an interesting study, Simonian et al.(2001) reported the use of OPAA for the detection of fluorinecontaining organophosphates pesticides (sarin GB and soman GD).The detection mechanismwas based on hydrolysis of the P–F bondin fluorine containing OPs. The method was specific and did notrespond to non-fluorine OPs.

As shown in Table 1, the enzyme-linked immunosorbent assay(ELISA) has taken on new importance for pesticides analysis over

Table 3Commonly used enzymes for the detection of OPs using different sensing techniques.

Sr. no. Enzyme Biological source

1 Acetyl cholinesterase (AChE) Drosophila melanogaster, Electriceel, Bovineor Human erythrocytes, Horse serum andHuman blood etc.

2 Butyryl cholinesterase (BChE) Bovine or Human erythrocytes, Horse serumand Human blood etc.

3 Organophosphorus acid anhy-drolase (OPAA)

Alteromonas Strain 6.0 & 6.5, E.coil etc.

4 Organophosphorus hydrolase(OPH)

Pseudomonas diminuta MG, Flavobacteriumsp.etc.

5 Choline oxidase (ChOx) Acinetobacter baumannii CI796 Tyrosine Bovine or Human erythrocytes, Horse serum

and Human blood etc.

the past decades. ELISA techniques offer remarkable advantagesover chromatographic techniques, mainly in terms of fast re-sponse, specificity, low detection limits, and most attractively,cost-effectiveness (Sassolas et al., 2012; Goel, 2013). Watanabeet al. (2002) reported direct and indirect competitive enzyme as-say based detection of enrofloxacin in real samples includingchicken liver, muscle, and cattle milk. The achieved limit of de-tection was in the range of 1 ppb. Cho et al. (2002) reported foursynthesized haptens for the detection of chlorpyrifos with a de-tection limit of 0.1 ppb using ELISA. These synthesized haptensshowed negligible cross-reactivity with other organophosphoruspesticides except for the insecticides chlorpyrifos-methyl andbromophos-ethyl, which make these assays suitable for theselective detection of chlorpyrifos. Similarly, Brun et al. (2005)investigated cross-reactivity during the testing of chlorpyrifoswith respect to chlorpyrifos-methyl, bromophos-methyl, andfenchlorphos using ELISA. They reported specific detection ofthe pesticide with a detection limit of 0.3 ng/mL. In anotherreport, Liu et al. (2009) found competitive indirect ELISA basedon optimal immunogen ‘5-(ethoxy(4-nitrophenoxy) phosphor-othioylaminopentanoic acid’ for the detection of parathion. Theimmunoassay was successfully applied to achieve 5 ng/mL of de-tection limit in water and soil samples, while 10 ng/mL of detec-tion limit was observed in cucumber, rice, and corn samples.

In another variant of ELISA based OP sensing, flow injectionanalysis (FIA) was introduced. For example, Kumar et al. (2006)employed ELISA with the FIA technique to quantify methyl para-thion in water using sample volumes of less than 100 ml. The assaywas sensitive in the detection range of 50 ppt–500 ppb with therequired analysis time of around 45 min. These authors claimedthat such a system had many uses including monitoring pesticidesin industrial waste, agriculture, water resources, and food samples.In another report, Sullivan et al. (2007) used a commercial mag-netic particle-based ELISA kit for the detection of chlorpyrifos. Thecross-reactivity from the chlorpyrifos-methyl was estimated to be37% while it was in the range of 1.6–10.7% in the case of otherpesticides. The reported detection range of this chlorpyrifos kit

Common OP sensing mechanism Reference

Hydrolyzes of the acetyl esters such as acetylcholine Sassolas et al.(2012)

Hydrolyses of butyrlchloine Campanella et al.(1991)

Detoxifying of P–F bonds Hoskin et al. (1993)

Hydrolyses of the OPs and release of p-nitrophenol Defrank and Cheng,1991

Oxidation of the choline to betaine Mulbry et al. (1986)Oxidizes monophenols in two steps: (1) catalyzes theo-hydroxylation of monophenol to o-diphenol (2) Oxi-dized to its corresponding o-quinone

Thakur et al. (2012)

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481476

was 0.22–3.50 mg L�1 in the agricultural run-off water. A gold/se-lenium-nanoparticle based competitive dipstick immunoassay wasdeveloped for atrazine, DDT, and 2,4-dichlorophenoxyacetic acidpesticides (Kaur et al., 2007; Sullivan et al., 2007). Detection limitsof 1, 3 and 27 ng/mL were reported for atrazine, 2,4-di-chlorophenoxyacetic acid, and DDT, respectively (Sullivan et al.,2007; Kaur et al., 2007). In a further development, Salmain et al.(2008) also investigated the competitive ELISA analysis of a fewpesticides using the above type of antibody–antigen and goldnanoparticle based immunosensor, and they reported almost si-milar detection limits in the case of the different pesticides tested.Likewise, the topic of the immunoassay of pesticides has beendealt with by many authors (Salmain et al., 2008; Kong et al., 2010;Shim et al., 2010; Jin et al., 2012; Wang et al., 2012).

In the case of biosensors for Ops, enzymes such as OPAA, OPH,ChOx, and tyrosine have been recognized as potential recognitionelements for OP detection. Major limitations of the enzymaticbiosensors can be listed as their solution instability and shortstorage time. The construction of biosensors involves the in-tegration of biomolecules such as enzymes (e.g., AChE, BChE,OPAA, OPH, ChOD, and tyrosine), antibodies, and aptamers withtransducing elements that may include dyes, nanoparticles,quantum dots, carbon nanotubes graphene, and nanocrystallinecoordination polymers (Barreto et al., 2010; Wen et al., 2010a,2010b). On the basis of these sensor transducers and their signaltypes, biosensors can be classified into two major classes: opticalsensors and electrochemical sensors. These two types of sensorsystems are thus discussed below based on functional materials/nanomaterials with a focus on recent reports.

4.2. Optical sensors for OPs

Optical signals from nanomaterials have been explored as apotent detection option for OPs (Kolosova et al., 2003; Ma et al.,2004; Dale and Rebek, 2006; Burn worth et al., 2007; De Marcoset al. 2014). Optical signal based sensors fall into two categories

Fig. 4. (a) Structure of fluorescein isothiocyanate (FITC) at different pH and (b) its relativpermission of Elsevier Science Ltd., UK.

based on: (a) the use of biomolecules and (b) direct chemical in-teractions. Several reports are available in the literature on bothtypes of these optical sensors (Dale and Rebek, 2006; Burn worthet al., 2007; Barreto et al., 2010; Wen et al., 2010a, 2010b; Lianget al., 2014; Baker et al., 2014). In the case of optical biosensors,there is an important paper describing an AChE-based fiber-opticdetection system with the aid of a pH-sensitive compound, fluor-escein isothiocyanate (FITC) (Ma et al., 2004). The AChE-dye ad-duct was immobilized on a quartz fiber that was directly attachedto a photolumisence spectrophotometer. A change in the fluores-cence intensity was recorded, and such a signal was attributed tohydrolysis of acetylcholine. The reaction produced one proton persubstrate molecule, which resulted in an increase in the acidity ofthe solution. The reduction of the fluorescence intensity inducedby the variation in the solution acidity can be explained as theinterruption of the fluorophore’s conjugation upon protonation(Fig. 4) (Ma et al., 2004). Further development of this technology isdesirable to expand the utility of the fluorescence polarizationimmunoassay (Kolosova et al., 2003; Ma et al., 2004; Dale andRebek, 2006; Tang et al., 2008).

Over the past decades, the use of functional materials/nano-materials in conjunction with monitoring biomolecules (such asenzymes and antibodies) has been recommended for sensitive andselective detection of OPs. In this respect, organophosphate hy-drolase (OPH) has a great potential for catalytic biosensing of OPs.To date, a number of OPH based modified fluorescent biosensorshave been developed. The special advantage of these sensors liesin the fact that OPH can hydrolyze a wide range of OPs containingP–O, P–F, P–S, or P–CN bonds (Cao et al., 2004; Ji et al., 2005;Thakur et al., 2012; Thakur et al., 2013). However, specificity for aparticular OP is hard to achieve. Cao et al. (2004) reported thetagging of OPH with FITC dye. The resulting complex was im-mobilized on silanized quartz slides using the Langmuir–Blodgetttechnique, which produced monolayers of the enzyme-basedfluorescent sensor. This fluorescent sensor showed enhancedsensitivity to detect the OPs at nanomolar concentrations. Ji et al.

e fluorescence intensity at selected pH values. Reproduced from Liu et al. (2013) by

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481 477

(2005) reported a novel biosensor for the detection of paraoxanbased on the conjugation of (CdSe)ZnS core–shell QDs with OPHthrough electrostatic interactions between the negatively-chargedQD surfaces and the positively-charged side-chain end groups(NH2) of the enzyme. The fluorescence intensity of the QD-OPHbioconjugates were quenched in the presence of paraoxan due toconformational changes. The limit of detection for paraoxon was10 nM.

In a recent study, pyranine dye (8-hydroxypyrene-1, 3, 6-tri-sulfonic acid trisodium salt) was conjugated with OPH for thedetection of OPs (Thakur et al., 2012). The pH sensitive bioconju-gates were used for OP sensing in different molar ratios. The lowerlimit of the detections for malathion and metyl parathion were 2–5 ppb under optimized conditions (55–60 °C). Thakur et al. (2013)have also reported the use of silver nanoparticle conjugated OPHfor the detection of methyl parathion. In this case, the detection ofthe OPs was achieved as low as 4 ppb. Despite their broad ap-plicability, these enzyme based techniques are not free from cer-tain limitations such as (a) the enzymes easily lose activity underharsh environmental conditions (e.g. high temperature and harshpH conditions), (b) lengthy incubation times are required for en-zyme–analyte interaction, (c) regeneration of enzyme activity maynot be precise, and (d) the lifetime of the enzyme based sensor isshort.

Apart from biomolecule-based fluorescence sensing, opticalchemosensing techniques based on functional materials/nanoma-terials have also been proposed as a potential alternative for thedetection of pesticides. As the first example, a series of non-emissive platinum 1,2-enedithiolate complexes with an appendedprimary alcohol was explored for the detection of OPs (Van Hou-ten et al., 1998). The process was conducted in the absence ofoxygen because its presence could quench the fluorescence. De-lattre et al. (2009) reported a fluorescent sensor for the detectionof OPs in water by using cyclodextrin (CD) molecules. Cyclodextrinhas D-glucopyranose units in the form of truncated cone-shapedmolecules with a hydrophobic cavity, which can induce inclusionphenomena for guest molecules (Delattre et al., 2009). The dipolesare generated upon the entry of the guest molecules in the CDsystem, and the resulting variation in the optical signal is corre-lated with the concentration of the analyte (guest) molecules. Thisapproach was used for the analysis of pesticides such as parathion,malathion, atrazine, linadane, imidacloprid, and simazine (Delattreet al., 2009). Recently, a number of authors have advocated the useof fluorescent chemosensors for toxic OPs. Use of nanomaterialswith dual transduction properties (e.g. fluorescence/electricalconductance) has been proposed to drive the next generation ofOP chemosensors, as such systems may help in minimizing false-positives and provide in situ cross validation of the obtained re-sults (Kumar et al. 2014a, 2014b). In this series, nano-metal organicframeworks such as NMOF1 and MOF-5 have been reported to beuseful for the direct sensing of OPs. Detection limits of 1–5 ppb forsome nitro OPs (parathion, metyl parathion, paraoxan, and feni-trothion) have been reported using chemosensing with NMOF1and MOF-5 (Kumar et al. 2014a, 2014b).

4.3. Electrochemical sensors for OPs

The mechanism and other important aspects of the electro-chemical sensing of OPs have been reviewed by many researchers(Liu and Lin, 2006) Grieshaber et al., 2008; Palchetti et al., 2009;Trojanowicz, 2014). Hence, in this review, we mainly focused onrecent case studies to understand and evaluate state of the art ofthe subject. The biorecognition element is an important compo-nent in electrochemical sensors as it determines the selectivity.The electrochemical properties of the transducer nanomaterials(e.g. CNTs, conducting polymers, nanoparticles, and graphene) are

important to attain improved detection limits. The conductivityproperties of the material used have been reported to be the de-termining factor for the sensitivity of the electrochemical sensors.The electrochemical technique has a number of advantages, in-cluding low cost and short analysis time (Liu and Lin, 2005; Deoet al., 2005; Wang et al., 2008a, 2008b; Du et al., 2008; Wang et al.,2008a, 2008b; Chauhan and Pundir, 2011; Wang et al., 2011; Liet al., 2013; Xue et al., 2013; Zhao et al., 2013; Wen et al., 2010a,2010b; Huo et al., 2014; Deep et al., 2015).

In recent years, the application of relatively new functionalmaterials/nanomaterials, e.g. graphene, gold nanoparticles, QDs,CNT, MOFs, and nanocomposites has offered a great chance toextend the applicability of electrochemical sensing techniques tounprecedented low detection limits. Liu and Lin (2006) reported aself-assembled AChE/ CNT-modified electrode to achieve the de-tection of parathion at 0.4 pM level. (The linearity of their detec-tion method was up to 1.6 mM.) In another report, a composite ofthe Fe3O4 nanoparticles with carboxylated multi-walled carbonnanotubes (MWCNTs) was tagged with AChE (Fig. 5) (Liu and Lin,2006). This composite was immobilized on a gold electrode andused for the sensing of OPs. The AChE/Fe3O4/c-MWCNT/Au elec-trode biosensor was shown to be synergistic to provide excellentelectrocatalytic activity at low potential (þ0.4 V). The inhibitionrates of OPs were proportional to certain concentration ranges(0.1–40 nM for malathion, 0.1–50 nM for chlorpyrifos, 1–50 nM formonocrotophos, and 10–100 nM for endosulfan). The detectionlimits of the AChE/Fe3O4/c-MWCNT/Au biosensor were 0.1 nM formalathion and chlorpyrifos, 1 nM for monocrotophos, and 10 nMfor endosulfan. Interestingly, the sensor was reported to be reu-sable for more than 50 cycles while maintaining sufficiently highstability. The applicability of such a sensor was highlighted in theanalysis of milk and water samples (Liu and Lin, 2006).

Wang et al. (2011) reported the synthesis of an AChE/AuNPs/cr-Gs nanohybrid (acetylecholine esterase/gold nanoparticales/che-mically reduced graphene-oxide nanosheets). This nanohybridwas reported for ultrasensitive (0.1 pM) detection of paraoxan(Fig. 6) (Wang et al., 2011). The nanosize effect of gold nano-particales (AuNPs) scattered on cr-Gs sheets led to greatly im-proved electrochemical detection. Du et al. (2008) reported aglassy-carbon electrode (GCE) surface modified with CdTe QDs/AuNPs for the electrochemical detection of monocrotophos. Inanother report, a carbon nanotube modified screen printed carbonelectrode (SPE) was tagged with AChE to develop an electro-chemical sensor for OP (Wang et al., 2008a, 2008b). The calibrationcurve was linear over a wide range of OP concentrations (5 pM–

0.5 nM) with an observed detection limit of 2 pM. Li et al. (2013)reported the sensitive amperometric biosensing of OPs using AChEmodifying glassy carbon/reduced graphene oxide electrode. Thiselectrochemical biosensor displayed a detection limit of0.5 ng mL�1 with good reproducibility and stability. Xue et al.(2013) also reported a graphene–nafion matrix modified glassycarbon electrode (Graphene–Nafion/GCE) for the determination ofOPs. Methyl parathion was detected over a concentration range of0.02–20 mg/ml in vegetable samples. Likewise, Zhao et al. (2013)introduced the use of methyl parathion hydrolase loaded(MPH)Fe3O4@Au nanocomposite for the analysis of methyl para-thion. Cysteamine (SH–NH2) was used as a linker for decoratingthe AuNPs on the Fe3O4 core. The positively-charged methylparathion hydrolase (MPH) was quickly and strongly adsorbedonto the negatively-charged Fe3O4@Au nanocomposite (Fig. 7)(Zhao et al., 2013).

Electrochemical detection of OPs with an MOF-based enrich-ment-detection platform has also been proposed (Wen et al.,2010a, 2010b). A stripping voltammetric analysis technique wasemployed to quantify the methyl parathion samples. The entireprocess involved two main steps: (i) the sorption of metyl

Fig. 5. (a) AChE/Fe3O4/c-MWCNT/Au electrode amperometric biosensor based on acetylcholinesterase immobilized in which iron oxide nanoparticles/multi-walled carbonnanotubes modified gold electrode for sensing of malathion and chlorpyrifos in milk and water and (b) Electrochemical impedance Nyquist plot for OP sensing and insertshowing the equivalent circuit for mixed kinetic and diffusion control for amperometric biosensor. Reproduced from Chauhan and Pundir (2011) by permission of ElsevierScience Ltd., UK.

Fig. 6. Gold nanoparticle and chemically reduced graphene oxide nanosheet (AuNP/cr-Gs) hybrid synthesis and acetylcholinesterase/AuNP/cr-Gs (AChE/AuNP/cr-Gs) na-noassembly generation using poly(diallyldimethylammonium chloride) (PDDA). Negatively-charged AChE was immobilized on the positively-charged AuNP/cr-Gs stronglythrough electrostatic interactions, which prevented the aggregation of AChE. Reproduced from Wang et al. (2011) by permission of Royal Chemical Society, UK.

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481478

Fig. 7. Fe3O4@Au nanocomposite biosensor for the detection of methyl parathionwith the use of cysteamine (SH–NH2) as a linker for decorating AuNPs on the Fe3O4

core. The positively-charged methyl parathion hydrolase (MPH) was quickly andstrongly adsorbed onto the negatively-charged Fe3O4@Au nanocomposites. Re-produced from Zhao et al. (2013) by permission of Royal Chemical Society, UK.

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481 479

parathion on the MOF-glassy carbon electrode substrate and (ii)electrochemical analysis. The observed detection limit was0.08 μg/mL (Wen et al., 2010a, 2010b). Recently, an NMOF1 basedelectrochemical sensing technique for parathion was proposed byDeep et al. (2015). NMOF1 was assembled on a conducting indiumtin oxide substrate and the terminal –NH2 groups of the NMOF1were exploited to attach an anti-parathion antibody. Using theelectrochemical impedance signal, a detection limit of 0.1 ng/mLwas reported, and the detection of parathion was also specific inthe presence of several other pesticides as shown in Fig. 8 (Deepet al., 2015).

Electrochemical methods of quantitative analysis have alsobeen explored for direct sensing based on the functional materials/nanomaterials of OPs without requiring any biomolecule in theprocess. In these cases, the CNTs, nanoparticles, and MOFs havealso been the main transducer elements. Liu and Lin (2005)

Fig. 8. (a) Surface Assembly of anti-parathion/NMOF/2-ABA/ITO for impedimetric sensin(0.1–20 ng/mL) of parathion. Reproduced from Deep et al. (2015) by permission of Elsev

reported the use of electrodynamically deposited zirconia (ZrO2)nanoparticles/polycrystalline gold electrode for the detection ofmethyl parathion via a stripping voltammetric response. In thisstudy, the reported linear range of detection was 5–100 ng/mLwith a detection limit of 3 ng/mL. In another report, ZrO2 nano-particle decorated graphene was used for the analysis of methylparathion without enzymes by using the square-wave voltam-metry technique. The detection limit for methyl parathion wasdetermined to be 0.6 ng/mL. Xie et al. (2010) reported electro-polymerized polyaminothiophenol (PATP)/gold nanoparticles/glassy carbon (GC) based membranes for the electrochemical de-tection of chlorpyrifos (CPF). The cyclic voltammetric response ofthe imprinted PATP-AuNP-GC sensor was about 3.2-fold higherthan the imprinted PATP-Au sensor. The detection limit for CPFwas also improved (almost two times) relative to the imprintedPATP-Au sensor alone (Xie et al., 2010). A proton doped zinc imi-dazolate MOF thin film has also been proposed for the directsensing of the herbicide, mecopropo using the surface con-ductance property (Kumar et al., 2012). A detection limit of 50 ppbwas achieved using this direct method. Recently, Huo et al. (2014)reported CuO-SWNT (copper oxide nanowires-single-walled car-bon nanotubes) hybrid nanocomposite for malathion detection.The nanocomposite showed a wide dynamic detection range. Thedetection limit was observed to be 0.1 ppb, and the methodshowed a good selectivity against some other common pesticides,inorganic ions, and sugars. Some other prominent examples of thedirect electrochemical sensing approach for OPs are highlighted inTable 1 (Deo et al., 2005; Wang et al., 2008a, 2008b; Yang et al.,2012; Zhu et al., 2014).

4.4. Molecularly imprinted polymer sensors

Molecularly imprinted polymer (MIP) sensors consist of highly

g of parathion and (b) EIS response of the platform toward varying concentrationsier Science Ltd., UK.

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481480

cross-linked polymers with shared advantages of synthetic re-cognition platforms and biological recognition elements (Wanget al., 2011, 2008b, 2014).

MIP sensors display excellent mechanical, chemical, and ther-mal stability, and they can also be tailored to meet specificity. Thebasic design, preparation, characterization, and applications of MIPsensors for pesticides have been evaluated in past articles (Alex-ander et al., 2006; Vasapollo et al.,2011; Philip and Mosha, 2012).However, MIP sensors may suffer from some disadvantages, e.g. alack of stability and poor signal transduction. To overcome theseshortcomings of MIPs, some authors have suggested attachingthem with other molecules so as to improve the chemical affinityand to obtain a specific signal (Alexander et al., 2006; Vasapollo etal.,2011; Philip and Mosha, 2012; Diaz-Diaz et al., 2009).

The synthesis of MIPs is largely based on the use of diversefunctional materials such as polypyrrole, over-oxidized poly-pyrrole, polyaniline polyphony-lendiamines, polyphenol, and re-dox polymers (e.g. metallo-porphyrins) (Choong et al.,2009). Wuet al. (2011) proposed the use of polymer membranes imprinted atthe surface of TiO2 nanoparticles for chemiluminescence signalbased (CL) detection of chlorpyrifos (CPF). The use of TiO2 en-hanced the chemiluminescence of the luminol–H2O2 system. Theresponse of the above MIP was linear over a chlorpyrifos con-centration range of 1.0�10�10 to 5.0�10�7 mol/L with a limit ofdetection of 1.0�10�11 mol/L. Zhao et al. (2011) reported theencapsulation of QDs in a MIP nanosphere for specific recognitionof diazinon in water. Direct fluorescence quantification analysisoffered detection of 50 ng/mL of the pesticide above.

5. Comparison between different functional materials forsensing OPs

In recent years, the need for convenient and efficient detectiontools for OPs has become more urgent due to ever-increasingcontamination of water bodies, soil, dairy products, foodstuffs, andgrains, etc. In addition, it has also become important for manu-facturing industries to comply with standards in line with inter-national regulations. The conventional instrumentation (e.g., GC,HPLC, and MS) and the newly evolved detection techniques (asdiscussed in Section 4) have many advantages and disadvantages.Under such circumstances, the availability of diverse detectiontechniques for OPs, e.g, immunosensors, biosensors, and chemo-sensors, offers a lucrative alternative for time-consuming andcostly conventional instrumentation. However, a number of lim-itations remain. Reproduction of the same sensor material is ahuge challenge, and the resulting output can vary between dif-ferent batches.

Researchers are putting great efforts to widen the scope ofroutine monitoring and detection of pesticides in real samples forpractical applications. Advanced functional materials/nanomater-ials such as MOFs, QDs, and graphene are reported with muchdesired success in terms of sensitivity and signal stability. Sensorregeneration is also another facet that researchers are trying topay attention to. In an overall scenario, electrochemical sensingtechniques seem to be edging out other techniques for achievingreliable and convenient sensor design. The feasibility of the elec-trochemical sensing of OPs has indeed been demonstrated with arange of advanced nanomaterials.

Development of reliable portable devices for the detection ofOPs in real samples is yet confronted with formidable challenges.Some disposal sensors and test strips have been proposed over thepast years. In these cases, the electrochemical approach has alsobeen the mode of choice. For example, anti-BChE antibodies con-jugated CdSe-QD were proposed for the electrochemical im-munosensing of methyl parathion (Zhang et al., 2013a, 2013b).

Samples of methyl parathion containing 0.1–30 nM levels wereanalyzed with a detection limit of 0.03 nM. In some cases, the useof optical signal based techniques has been proposed for the de-velopment of disposable sensing strips for OPs. As one such ex-ample, an anti-BChE antibody conjugated Fe3O4@TiO2 was re-ported for the sandwich immunoassay of OPs (Zhang et al., 2013a,2013b). This disposable sensor offered a linear response over abroad concentration range (0.02–10 nM) with a detection limit of0.01 nM. An immune-chromatographic test strip for an OP meta-bolite was reported by using a CdS@ZnS–TCP (3,5,6-tri-chloropyridinol) conjugate. Competitive immunoreaction underoptimal conditions helped in the visual detection of 1.0 ng/mL TCPin 15 min (Zhang et al., 2013a, 2013b). Based on the available in-formation, is expected that some realistic kits for the quick, easy,and accurate detection of OPs will soon be commercialized.

As far as future research endeavors are concerned, we predictthat the development of sensor systems based on diverse func-tional materials/nanomaterials with an integrated sorbent section(for easy enrichment) will further lead to enhanced and re-producible sensitivities. MOFs and porous nanoparticles are po-tential candidates for this. Current trends indicate that the ex-ploration of advanced materials/composites with dual transduc-tion properties (electrochemicalþoptical) may play an importantrole in devising tools that will enable the cross-validation of thedata with minimization of false positives.

6. Conclusion

It can be concluded that the development of novel detectionsystems for the routine and convenient monitoring of OPs is animportant area for continuing research efforts to meet ever-growing market and social requirements. Although current sen-sing techniques have brought many important advantages in themonitoring of OPs, there is an urgent need to develop field-de-ployable devices at low cost and portability. In this sense, use offunctional materials/nanomaterials may facilitate the develop-ment of accurate and precise sensing techniques in the near futureto encounter the present challenges. In addition, applications ofnanomaterials would be helpful in achieving enhanced robustnessand high sensitivity of the sensing tools. Furthermore, paper basedsimple bio- or chemo-sensors integrated into lateral flow test-strips (LFTSs) or microfluidic channels might prove to be excellentanalytical tools to meet the common demand for routine andrandom quality checks. However, researchers need to extend theirtheories and laboratory scale demonstrations in order to bringthem better and more reliable levels of technology. Functionalmaterials/nanomaterials based LFTS sensing techniques are in thestarting stage of development. In the near future, nanomaterials-based paper sensing will also be available and employed for OPsensing. The use of integrated sample preparation and enrichmentcolumns will further add to the market acceptability of the sensingdevices for the OPs. Lastly, it is anticipated that futuristic sensorsfor OPs will be the focus to ensure low-cost, portable, rapid de-tection, sensitive measurement, and real-time sensing with wire-less networking using miniaturized designs.

Acknowledgements

This study was supported by a grant from the National Re-search Foundation of Korea (NRF) funded by the Ministry of Edu-cation, Science, and Technology (MEST) (No. 2009-0093848). Thethird author acknowledges a financial grant from CSIR Indiathrough project OMEGA/PSC0202/2.2.5. We are thankful to the

P. Kumar et al. / Biosensors and Bioelectronics 70 (2015) 469–481 481

Director of the CSIR-CSIO, Chandigarh, India.

References

Aktar, M.W., Sengupta, D., Chowdhury, A., 2009. Interdiscip. Toxicol. 2 (1), 1–12.Alexander, C., Andersson, H.K.S., Andersson, L.I., Ansell, R.J., Kirsch, N., Nicholls, I.A.,

O’Mahony, Whitcombe, M.J., 2006. J. Mol. Recognit. 19 (2), 106.Amaya-Chavez, A., Martanez-Tabche, L., Lopez-Lopez, E., 2006. Chemosphere 63 (7), 1124.Bassi, A.S., Flickinger, M.C., 2009. “Biosensors, Environmental,” Encyclopedia of Industrial

Biotechnology. John Wiley & Sons, Inc..Barreto, A.S., Silva, R.L.D., Silva, S.C., 2010. J. Sep. Sci. 33 (23-24), 3811–3816.Baker, P.A., Goltz, M.N., Schrand, A.M., Yoon do, Y., Kim, D.S., 2014. Biosens. Bioelectron.

61 (2014), 119–123.Brun, E.M., Garces-Garcia, M., Puchades, R., Maquieira, A., 2005. J. Agric. Food Chem. 53,

9352–9360.Boro, R.C., Kaushal, J., Nangia, Y., Wangoo, N., Bhasin, A., Suri, C.R., 2011. Analyst 136,

2125–2130.Burn worth, M., Rowan, S.J., Weder, C., 2007. Chemistry 13 (28), 7828–7836.Cao, X., Mello, S.V., Leblanc, R.M., Rastogi, V.K., Cheng, T.C., DeFrank, J.J., 2004. Colloids

Surf. A 250, 349–356.Campanella, L., Achilli, M., Sammartino, P.M., Tomassetti, M., 1991. Bioelectrochem.

Bioenerg. 26, 237–249.Choong, C.L., Bendall, J.S., Milne, W.I., 2009. Biosens. Bioelectron. 25 (3), 652–656.Cho, Y.A., Lee, V., Park, E.Y., Lee, Y.T., Bruce, D.H., Chang, A.K., Jae, K.L., 2002. Bull. Korean

Chem. Soc. 23, 481–487.Costa, L.G., 2006. Clin. Chim. Acta 366 (1-2), 1–13.Chauhan, N., Pundir, C.S., 2011. Anal. Chim. Acta 701, 66.Defrank, J.J., Cheng, T.C., 1991. J. Bacteriol., 1938–1943.Dale, T.J., Rebek, J., 2006. J. Am. Chem. Soc. 128 (14), 4500–4501.De Marcos, S., Callizo, E., Mateos, E., Galban, J., 2014. Talanta 122, 251–256.Delattre, F., Cazier, F., Cazier, F., Tine, A., 2009. Curr. Anal. Chem. 5, 48–52.Deep, A., Bhardwaj, S.K., Paul, A.K., Kim, K.H., Kumar, P., 2015. Biosens. Bioelectron. 65,

226–231.Deo, R.P., Wang, J., Block, I., Mulchandanic, A., Joshi, K.A., Trojanowicz, M., Scholz, F., Chen,

W., Lin, Y., 2005. Anal. Chim. Acta 530 (2), 185–189.Diaz-Diaz, G., Blanco-Lopez, M.C., Lopo-Orddieres, M.J., Tunon-Blanco, P., 2009. Electro-

analysis, 1348–1353.Du, D., Chen, S., Song, D., Li, H., Chen, X., 2008. Biosens. Bioelectron. 24, 475–479.Dhull, V., Dilbaghi, N., Hooda, V., 2014. Int. J. Pharm. Pharm. Sci.Eddleston, M., Buckley, N.A., Eyer, P., Dawson, A.H., 2008. Lancet 37, 597–607.Fukuto, T.R., 1990a. Environ. Health Perspect. 87, 245–254.Fukuto, T.R., 1990b. Environ. Health Perspect. 87, 245.Ge, X., Asiri, A.M., Du, D., Wen, W., Wang, S., Lin, Y., 2014. Trac-Trend Anal. Chem. 58, 31.Gong, J., Miao, X., Zhou, T., Zhou, T., Zhang, L., 2011. Talanta 85 (3), 1344–1349.Gong, J., Miao, X., Wan, H., Song, D., 2014. Sens. Actuat B-Chem. 162 (1), 341–347.Goel, P., 2013. Afr. J. Biotechnol. Special Rev. Issue 12 (52), 7158–7167.Grieshaber, D., MacKenzie, R., Varas, J., Reimhult, E., 2008. Sensors 8 (3), 1400.Hayes, W.J., Laws, E.R., 1991. In Handbook of Pesticide Toxicology. Academic Press, Inc,

San Diego.Hoskin, G.C.F., Rajan, S.K., David, R., Walker, E.J., 1993. Chem. Biol. Interact. 87 (1–3),

109–116.Huo, D., Li, Q., Zhang, Y., Hou, C., Le, Y., 2014. Sens. Actuat B-Chem. 199 (2014), 410–417.Hu, S.Q., Xie, J.W., Xu, Q.H., Rong, K.T., Shen, G.L., Yu, R.Q., 2003. Talanta 61 (6), 769–777.Jurewicz, J., Hanke, W., 2008. Int. J. Occup. Med. Environ. Health 21 (2), 121.Jin, M., Shao, H., Jin, F., Gui, W., Shi, X., Wang, J., Zhu, G., 2012. J. Food Sci. 77, T99–T104.Ji, X., Zheng, J., Xu, J., Xu, J., Rastogi, V.K., Cheng, T.C., DeFrank, J.J., Leblanc, R.M., 2005. J.

Phys. Chem. B 109 (9), 3793–3799.Kaur, J., Singh, V.K., Boro, R., Thampi, R.K., Raje, M., Varshney, G.C., Suri, C.R., 2007. En-

viron. Sci. Technol. 41, 5028–5036.Kazemi, M., Tahmasbi, A.M., Valizadeh, 2012. R. Agric. Sci. Res. J. 2, 512–522.Kojima, H., Takeuchi, S., Nagai, T., 2010. J. Health Sci. 56 (4), 374–386.Knapton, D., Burnworth, M., Rowan, S.J., 2006. Angew. Chem. Int. Edit. 45 (35),

5825–5829 2006.Kumar, P., Deep, A., Kim, H.K., Brown, C.J.R., 2015a. Prog. Poly. Sci . http://dx.doi.org/

10.1016/j.progpolymsci.2015.01.002.Kumar, P., Bansal, V., Deep, A., Kim, H.K., 2015b. J. Por. Mater. . http://dx.doi.org/10.1007/

s10934-015-9910-3Kumar, P., Paul, A.K., Deep, A., 2014a. Anal. Methods 6, 1094095.Kumar, P., Paul, A.K., Deep, A., 2014b. Micropor. Mesopor. Mater. 195, 60–66.Kumar, P., Kumar, P., Deep, A., Bharadwaj, L.M., 2012. Adv. Mat. 488, 1543–1546.Kumar, M.A., Chouhan, R.S., Thakur, M.S., Amita Rani, B.E., Karanth., N.G., 2006. Anal.

Chim. Acta 560 (1-2), 30–34.Kolosova, A.Y., Park, J.H., Eremin, S.A., Kang, S.J., Chung, D., 2003. J. Agric. Food Chem. 51,

1107–1114.Kong, Y., Zhang, Q., Zhang, W., Gee, S.J., Li, P., 2010. J. Agric. Food Chem. 58, 8189–8195.Kwong, T.C., 2002. Ther. Drug Monit. 24 (1), 144–149.

Liang, H., Song, D., Gong, J., 2014. Biosens. Bioelectron. 53, 363–369.Li, Y., Bai, Y., Han, G., Li, M., 2013. Sens. Actuat B-Chem. 185, 706–712.Lisa, M., Chouhan, R.S., Vinayaka, A.C., Manonmani, H.K., Thakur, M.S., 2009. Biosens.

Bioelectron. 25, 224–227.Liu, G., Song, D., Chen, F., 2013. Talanta 104, 103–108.Liu, G., Lin, Y., 2006. Anal. Chem. 78, 835–843.Liu, S., Yuan, L., Yue, X., Zheng, Z., Tang, Z., 2008. Adv. Powder Technol. 19, 419–441.Liu, Y., Wang, C., Gui, W., Bi, J., Jin, M., Zhu, G., 2009. Ecotoxicol. Environ. Saf 72,

1673–1679.Liu, G., Lin, Y., 2005. Anal. Chem. 77, 5894–5901.Ma, L.Y., Wang, H.Y., Xie, H., Xu, L.X., 2004. Spectrochim. Acta A Mol. Biomol. Spectrosc.

60, 1865.Mulchandani, A., Chen, W., Mulchandani, P., Wang, J., Rogers, K.R., 2001. Biosens. Bioe-

lectron. 16 (4-5), 225–230.Mulbry, W.W., Karns, S.J., Kearney, C.P., Nelson, O.J., Mcdaniel, S.C., Wild, R.J., 1986. Appl.

Environ. Microbiol. 51, 926–930.Obare, S.O., De, C., Guo, W., Haywood, T.L., Samuels, T.A., Adams, C.P., Masika, N.O.,

Murray, D.H., Jaffrezic-Renault, N., 2010. Sensors 1 (2), 60–74.Palchetti, I., Laschi, S., Mascini, M., 2009. Biosensors and Biodetection, 504. Humana

Press, p. 115.Philip, J.Y.N., Mosha, D.M.S., 2012. Tanzan. J. Sci. 38 (3), 72–83.Roger, K.R., Cao, C.J., Valdes, J.J., Eldedri, M.E., 1991. Appl. Toxcol. 16, 810–820.Sassolas, A., Simon, B.P., Marty, J.L., 2012. Am. J. Anal. Chem. 3, 210–232.Simonian, A.L., Grimsley, J.K., Flounders, A.W., Schoeniger, J.S., Cheng, T.C., DeFrank, J.J.,

Wild, J.R., 2001. Analytica Chimica Acta 442 (1), 15–23.Sullivan, J.J., Chen, Y.G., Goh, K.S., 2007. J. Agric. Food Chem 55 (16), 6407–6416.Salmain, M., Fischer-Durand, N., Pradier, C.M., 2008. Anal. Biochem. 373 (2008), 61–70.Shim, J.Y., Kim, Y.A., Lee, Y.T., Hammock, B.D., Lee, H.S., 2010. J. Agric. Food Chem. 58,

5241–5247.Soltaninejad, K., Abdollahi, M., 2009. Med. Sci. Monit. 15 (3), RA75.Smith, A.G., Gangolli, S.D., 2002. Food Chem. Toxicol 40 (6), 767–779.Tang, S.J., Zhang, M., Cheng, C.G., Lu, Y.T., 2008. J. Immuno. Immunochem. 29, 356–369.Tang, B., Zhang, J.E., Zang, L.G., Zhang, Y.Z., Li, X.Y., Zhou, L., 2005. J. Chromatogr. Sci. 43

(7), 337–341.Tahara, M., Kubota, R., Nakazawa, H., 2005. Water Res. 39 (20), 5112–5118.Thakur, S., Venkateswar Reddy, M., Siddavattam, D., Paul, A.K., 2012. Sens. Actuat

B-Chem. 163 (1), 153–158.Thakur, S., Kumar, P., Venkateswar Reddy, M., Siddavattamc, D., Paul, A.K., 2013. Sens.

Actuat B-Chem. 178, 458–464.Trojanowicz, M., 2014. Electrochem. Commun. 38, 47–52.U.S.EPA Policy for Managing Risk to Workers from Organophosphate Pesticides (OPs)

⟨http://www.epa.gov/opp00001/factsheets/opworkers.htm⟩ (accessed on December30, 2014a).

U.S.EPA Revised OP Cumulative Risk Assessment ⟨http://www.epa.gov/ opp00001/cumulative/rra-op/pr.htm⟩ (accessed on December 30, 2014b).

Vasapollo, G., Sole, R.D., Mergola, L., Lazzoi, M.R., Scardino, A., Scorrano, S., Mele, G., 2011.Int. J. Mol. Sci. 12 (9), 5908.

Van Houten, K.A., Heath, D.C., Pilato, R.S., 1998. J. Am. Chem. Soc. 120, 12359–12360.Vadgama, P., Crump, P.W., 1992. Analyst 117 (11), 1657–1670.Wang, R., Wang, Z., Yang, H., Wang, Y., 2012. J. Sci. Food Agric. 92, 1253–1260.Wang, J., Timchalk, C., Lin, Y., 2008a. Environ. Sci. Technol. 42 (7), 2688–2693.Wang, Y., Zhang, S., Du, D., Shao, Y., Li, Z., Wang, J., Engelhard, M.H., Li, J., Lin, Y., 2011. J.

Mater. Chem. 21, 5319–5325.Wang, J., Timchalk, C., Lin, Y., 2008b. Environ. Sci. Technol 42, 2688–2693.Wang, X., Lu, X., Chen, J., 2014. Trac-Trend Anal. Chem. 2, 25–32.Watanabe, H., Satake, A., Kido, Y., Tsuji, A., 2002. Analyst 127 (1), 98–103.Wen, L.L., Wang, F., Leng, X.K., Wang, C.G., Wang, L.Y., Gong, J.M., Li, D.F., 2010a. Cryst.

Growth Des. 10 (7), 2835.Wen, L.L., Wang, F., Leng, X.K., Wang, F., Leng, X.K., Wang, C.G., Wang, L.Y., Gong, J.M., Li,

D.F., 2010b. Cryst. Growth Des. 10 (7), 2835.Wu, J., Fu, X., Xie, C., Fang, W., Gao, S., 2011. Sens. Actuat B-Chem. 160 (1), 511–516.Xue, R., Kang, T.F., Lu, L.P., Cheng, S.Y., 2013. Anal. Lett. 46 (1), 131–141.Xie, C., Gao, S., Guo, Q., Xu, K., 2010. Microchim. Acta 169 (1-2), 145–152.Xu, M.-L., Liu, J.-B., Lu, J., 2014. Appl. Spectrosc. Rev. 49 (2), 97–120.Yang, Y., Tu, H., Zhang, A., Du, D., Lin, Y., 2012. J. Mater. Chem. 22, 4977–4981.Zhao, Y., Zhang, W., Lin, Y., Du, D., 2013. Nanoscale 5, 1121–1126.Zhao, Y., Ma, Y., Li, H., Wang, L., 2011. Anal. Chem. 84 (1), 386–395.Zhao, X., Hwang, H.M., 2009. Arch. Environ. Contam. Toxicol. 56 (4), 646–653.Zhang, K., Qingsong, M., Guan, G., Liu, B., Wang, S., Zhang, Z., 2010. Anal. Chem. 82 (22),

9579–9586.Zhang, W., Tang, Y., Du, D., Smith, J., Timchalk, C., Liu, D., Lin, Y., 2013a. Talanta 114,

261–267.Zhang, X., Wang, H., Yang, C., Du, D., Lin, Y., 2013b. Biosens. Bioelectron. 41, 669–674.Zhang, W., Asiri, A.M., Liu, D., Du, D., Lin, Y., 2014. TrAC Trends Anal. Chem. 54, 1–10.Zhu, W., Liu, W., Li, T., Yue, X., Liu, T., Zhang, W., Yu, S., Zhang, D., Wang, 2014. J. Elec-

trochim. Acta 146, 419–428.