Skip to main content

The application of rapid test paper technology for pesticide detection in horticulture crops: a comprehensive review

Abstract

Background

The ever increasing pests and diseases occurring during vegetable crop production is a challenge for agronomists and farmers. One of the practices to avoid or control the attack of the causal agents is the use of pesticides, including herbicides, insecticides nematicides, and molluscicides. However, the use of these products can result in the presence of harmful residues in horticultural crops, which cause several human diseases such as weakened immunity, splenomegaly, renal failure, hepatitis, respiratory diseases, and cancer. Therefore, it was necessary to find safe and effective techniques to detect these residues in horticultural crops and to monitor food security.

Main body

The review discusses the use of conventional methods to detect pesticide residues on horticultural crops, explain the sensitivity of nanoparticle markers to detect a variety of pesticides, discuss the different methods of rapid test paper technology and highlight recent research on rapid test paper detection of pesticides.

Conclusions

The methodologies discussed in the current review can be used in a certain situation, and the variety of methods enable detection of different types of pesticides in the environment. Notably, the highly sensitive immunoassay, which offers the advantages of being low cost, highly specific and sensitive, allows it to be integrated into many detection fields to accurately detect pesticides.

Background

Pesticides are commonly employed in modern agriculture to control weeds and pests, regulate and promote plant growth, and enhance food production [90]. Crop disease management is applied to avoid destructive losses in agriculture and subsequently to satisfy the demands of a growing world population [155]. Raw and processed horticultural crops such as fruits and vegetables enrich nutritional intake and human health [20, 22, 131]. However, pesticide residues on fruit and vegetables hold serious health implications.

According to a report published in 2009, pathogens, insects, and weeds cause crop (losses of 13, 14, and 13%, respectively [143]). Regarding crop management worldwide, herbicides are used mostly (44%), followed by fungicides and bactericides (27%), insecticides (22%), and various others (7%) [113]. Excessive use or abuse of pesticides results in residues in food, which can threaten human health [66, 128, 65]. Pesticide residues contain hazardous compounds that even at extremely low concentrations have negative effects on human health and the environment. As a result, effective residue detection methods were designed for food security monitoring and public health safeguards [19, 25].

Instrumental detection techniques, which include high-performance liquid chromatography (HPLC), gas chromatography (GC), and chromatographic methods linked with mass spectrometry (MS) detectors, are commonly used to determine pesticide residues [6]. These techniques give precise qualitative and quantitative information about the residues. However, extensive sample pre-treatment limits the use of these techniques, because highly trained technicians and expensive equipment are needed [17]. Rapid approaches to determine pesticides are comparatively simple and include electrochemical techniques, spectroscopic analyses, and immunoassays. Although rapid methods lack the accuracy and precision of traditional analytical techniques, they can be employed as supplementary pre-screening procedures. Novel analytic methods for the quick, low cost, reliable, and selective detection of pesticides are therefore in demand [140].

The application of chemical agents not only increased agricultural productivity in short period, but also increased chemical toxicity in the air, water, and soil over time [112]. If chemicals are applied at incorrect times and products are harvested before the end of the pre-harvest interval, large concentrations of pesticides will remain in the product, which is dangerous to human health [159]. Residues on products must not exceed international regulatory maximum residue limits (MRLs) [180]. The concentration of pesticides in crops must be taken into account to maintain public health and protect the environment.

Developing and implementing pesticide alternatives must be cost-effective, environmentally safe, and produce rapid results. Thus, this review focuses on nanomaterials that are used as agricultural promoters and highlights the importance of nanomaterials in detecting pesticide residues [152]. Nanotechnology has many advantages over traditional methods, including high sensitivity and reducing energy consumption [47, 48]. Many nanomaterials such as nanoparticles, nanotubes, and nanocomposites can be utilized for the detection, degradation, and removal of pesticides [1]. This review discusses methods to detect pesticide residues on horticultural crops, explaining their advantages and disadvantages, including conventional, rapid test paper and immunoassay methods.

Main text

Conventional methods in pesticide detection

Hercegová et al. [77] demonstrated that there are several traditional analytical techniques for analysing pesticides and their products. These comprise flame ionization detection, diode array, electrochemical detection, gas chromatography (GC) with electron capture detection, fluorescence, and ultraviolet liquid chromatography (LC), all of which lack selectivity. The most common techniques are mass spectrometry (MS) merged with gas and/or liquid chromatography. At low detection limits, these methods have high sensitivity and selectivity, but are limited because they use sophisticated, time-consuming, and expensive equipment, which require skill to operate [155].

Gas Chromatography

Gas chromatography is one of the main analytical strategies utilized in food analysis to identify and quantify pesticide residues in complex matrices. Petsas and Vagı [142] demonstrated that GC differentiates between the pesticides based on their volatilities and thermal stability [45]. Gas chromatography can be combined with different detection methods and depends on the category of pesticides being quantified [100]. For example, methods such as mass selective detection (MSD), flame ionization detection (FID), nitrogen–phosphorous detection (NPD), and flame photometric detection (FPD) are used to determine pesticide residues in cereal samples [69]. The detectors provide selectivity and sensitivity for a particular pesticide. Electron capture detectors (ECDs) are notably used to for halogenated compounds such as organochlorine pesticides [14, 105]. The NPD is sensitive for organophosphate and nitrogenous pesticides ([105]), and the FPD for sulphur and phosphorus pesticides [14, 71]. The techniques are limited for pesticides such as N-methyl carbamate, because they are either maintained on the chromatographic column or decomposed to their phenols. Furthermore, derivatization methods can limit sensitivity and applicability of fragrant carbamates ECD, which include initial hydrolysis to the equivalent phenols or amines and reaction with halogen-rich reagents [130].

Liquid chromatography

Liquid chromatography (LC) is used to detect pesticide residues for limited categories of compounds or single compounds and for which there were no appropriate GC conditions. Esquinas-Requena et al. [55] demonstrated that the original detectors used for LC methods were the UV or diode array detectors (DAD). These methods are generally accurate and effective, but necessitate the use of costly instruments, specialized staff, and have lengthy procedures [61]. To develop both selectivity and sensitivity, effective coupling between LC separation can be done with MS (LC-MS and LC-MS/MS) to improve the determination pesticide residues and their transformation products in complex matrices such as food [161]. Currently, high-resolution MS (HRMS) and tandem MS (MS/MS) are widely used. Celeiro et al. [34] showed that the usual MS analysers used in food analysis are quadrupole(Q), triple quadrupole (QqQ), time of flight (TOF), hybrid quadrupole ion trap (QTrap), and Orbitrap [34, 70].

High-performance LC (HPLC)

High-performance LC is widely utilized and can be combined with many detectors. It can be used with DAD and/or UV to determine organophosphorus and triazines in various matrices. The HPLC uses a pump to promote the movement of the mobile phase (s) and analyte across the column and includes a detector to allow keeping time for the analyte [175]. Many factors affect the analyte keeping time and depends on the extent to which it interacts with the stationary, the solvent composition, and the mobile phase flow rate. Reversed-phase liquid chromatography (RPLC) is a type of HPLC that is most approved, due to its capability to perform successful separation of polar to apolar pesticides with good performance and detection that cannot be directly applied to GC [79]. Table 1 summarizes conventional methods such as GC, HPLC, infrared spectroscopy, MS, and spectrophotometry, which are expensive and time-consuming, and indicates the need to develop simple and rapid methods.

Table 1 Conventional methods to detect pesticides

Detection of pesticide residues through multivariate analysis and VIS /NIR spectroscopy

Using chromatographic methods has several disadvantages such as a complex evaluation procedure, long detection cycle, and lagged nature of detection results. So, it is important to develop fast, reliable techniques [53, 138, 139]. Near-infrared (NIR) spectroscopy is a convenient technique used in quantitative and qualitative analysis in fields such as medicine, agriculture, and chemistry. Ultraviolet visible–NIR spectroscopy can be used to predict soil composition and pesticide absorption [88, 103]. Near-infrared spectroscopy (12900–4000 cm−1) is categorized within NIR reflectance spectroscopy and NIR transmission spectroscopy. The NIR can be non-dispersive (filter-based instrumentation) and dispersive and can use Fourier transform-based instrumentation. This method is cheap, safe, simple, environmentally friendly, avoids using organic solvents, and does not need sample preparation as does chromatographic methods [87, 156]. Models and regressions (partial least squares discriminant analysis (PLS-DA)) and models (partial least squares (PLS)) are used for quantitative determination of total nitrogen (TN) and organic carbon (OC) in soil [162]. Table 2 lists some NIR spectroscopic techniques appropriate for pesticide calculation.

Table 2 Near-infrared (NIR) spectroscopy applications for the determination of pesticides

Rapid detection technology of pesticides

Paper chromatography

Paper chromatography refers to an analytical approach that separates coloured chemicals or substances on chromatographic paper. This technique is extensively implemented to separate complex mixtures of carbohydrates, steroids, amino acids, peptides, amino acids, purines, simple organic compounds, and inorganic ions [41, 89]. It was the only technique available for the isolation and detection of pesticide residues before the development of GC and thin-layer chromatography (TLC) [58]. Currently, GC is used, because of its sensitivity and simultaneous quantitative estimation capabilities. However, paper chromatography is still implemented to validate non-specific gas chromatographic results [69]. However, TLC is increasingly replacing paper chromatography in pesticide residue research due to its enhanced resolution and shorter development time [158].

Paper chromatography in pesticide detection

Yang et al. [189] and Getz [189, 64] extensively explored various applications of paper chromatography for pesticide identification. Pesticide isolation, detection, and identification from cleaned tissue extracts have been the primary applications of paper chromatography. Pesticide residue separation depends on paper chromatography, especially insect tissue extracts to separate insecticides from their metabolites, and organophosphate residues from their lipid content. Paper chromatography has also been used to separate pesticides from plant waxes. Pesticide residues were quantified by measuring the spot size on a paper chromatogram [91].

Paper chromatography techniques

Paper chromatography cannot be applied to water-insoluble materials such as chlorinated hydrocarbons and organophosphate-based pesticides, which limits its scope [123, 164]. Zweig and Archer used paper chromatography to isolate and detect sevin and 1-naphthol in wine [120], and the same method has also been used to detect herbicides. For example, Mitchell used the method to determine monuron and 3-amino-1,2,4-triazole [126, 127], and Anliker et al. separated phosphamidon and its metabolites [195]. In pesticide residue studies, the most common method is reverse-phase chromatography where the paper only supports the immobile solvent. The compounds of interest are separated through the partition between the immobile solvent and the mobile solvent, which passes through it. Stationary phases are usually made of vegetable or mineral oils, silicone, propylene glycol, and dimethylformamide. This method is suitable for isolating compounds with a very low water solubility, such as chlorinated hydrocarbons and organophosphorus (OP) pesticides [28, 179]. Paper chromatography is used to separate pesticide residues without chemically altering the chromatographic paper. However, fibreglass papers have been used for reverse-phase chromatography of OP compounds [91]. McKinley, Colovic and their colleagues have also used acetylated papers to separate organophosphorus pesticides in reverse-phase chromatography [42].

Advantages of paper chromatography

The ease of the procedure, low cost, and the ease of altering conditions are all advantages of paper chromatography. In paper chromatography, many characteristics, including the paper, immobile phase, developing solvents, development direction, duration, and detection method, can be changed quickly and effortlessly [24]. This aspect is vital when developing procedures for samples under specific circumstances. If the sample is processed after chromatographic separation, but before quantitative analysis, then paper chromatography has a significant advantage over TLC, because the paper can be processed along with the sample [24]. It is occasionally necessary to elute the separate parts from the thin-layer chromatogram in TLC before processing. As paper chromatography has been used in pesticide studies for several years, it is more familiar than newer chromatographic techniques. Due to this familiarity, interpreting paper chromatographic findings is more straightforward and done with more confidence [24, 43].

Mechanism of rapid test paper technology in pesticide detection

An enzyme inhibitor is a molecule that binds to an enzyme’s active site, thereby reducing its activity and preventing the substrate from binding. This prevents the development of enzyme–substrate complexes, the catalysis of reactions and reduces product formation. Enzyme inhibition-based methods have been used to detect organophosphates and carbamates [21, 32]. Guo et al. created a rapid test strip for visual pesticide identification by inactivating the enzyme, its substrate, and a chromogenic agent on a paper matrix [73]. This method is portable, fast, easy to use, and inexpensive. It has a shelf life of 2 months when stored at four degrees Celsius; however, the enzyme activity is lower if stored at room temperature for 2 months [73]. Increasing colour resolution improves visual pesticide residue identification accuracy, because human optic cells are especially sensitive to wavelengths on the blue-green spectrum. Sun et al. [169] developed a dual-film screening strip made of fibreglass and polyester fibre-containing acetylcholinesterase (AChE) and indoxyl acetate. The strip was able to soak up and liberate all of the AChE or indoxyl acetate (Fig. 1).

Fig. 1
figure 1

Schematic illustration of the dual-film visual screening card: A panorama, B decomposition schematic, and C longitudinal section

Colorimetric analysis

Colorimetric analysis is a commonly used technique in paper-based analysis. Colorimetric analysis has several advantages, including high effectivity, operation ease, and increased stability [149]. Screening tools that are rapid, simple, inexpensive, and detectable by the naked eye are designed for the high-throughput screening of pesticides [39]. In colorimetric analysis, the sample solution is inserted into a test zone via capillary action. The sample then reacts with a colour reagent, and the colour changes. The colour formation or colour change is used to perform qualitative and quantitative studies of the pesticide from the test result [149].

Colour signals

Colour signals can be collected in two ways: (1) Smartphones, single-lens reflex cameras, and inexpensive desktop scanners can be used to directly image the result, after which quantitative analysis can be performed by specific software. (2) A spectrophotometer can be used to measure the absorbance at a specific wavelength, giving an accurate quantitative result [149].

A paper-based microfluidic chip can measure de-oxy-nivalenol (DON-Chip) in animal feed and food rapidly and at a low cost. The DON-Chip combines a colorimetric immunoassay with gold nanoparticles (AuNPs) and a paper microfluidic apparatus. The AuNPs act as signal indicators. As shown in Fig. 2, a new ratiometric analysis technique proposed for the analysis of DON performed well and successfully detected compounds in 12 minutes [149].

Fig. 2
figure 2

Schematic illustration of DON-Chip production and operation

Surface-enhanced Raman spectroscopy (SERS) swabs to detect pesticides in vegetables and fruits on-site

The feasibility of using silver nanoparticles–graphene oxide (Ag NP/GO) surface-enhanced Raman spectroscopy (SERS) swabs was tested on-site in fruits and vegetables with and without spiked pesticide [112]. The peels of vegetables and fruits were cut into 1 cm2 squares. Following this, 10 mL of pesticide solutions of varying concentrations was added to the peels [112]. Ten mL ethanol was added onto the AgNP/GO paper before applying Raman measurements to improve contact with the area of analysis and pesticide adsorption [112]. The square-shaped peel was blotted with the paper for 3 seconds. The Ag NP/GO paper was placed on a glass slide for SERS analysis after the strips dried out [112] (Fig. 3).

Fig. 3
figure 3

Illustration of the screen-printing production process for SERS swabs its application to detect pesticides in fruits and vegetables

Examples of rapid paper use in pesticide detection

Blažková et al. developed a strip-based immunoassay that quickly detects thiabendazole in fruit juice. The immunoassay depends on the interactions between thiabendazole–ovalbumin and thiabendazole. C-nanoparticles are combined with anti-thiabendazole to create a detection complex after which thiabendazole can be visualized [27]. If thiabendazole is absent, the detection complex will bind to thiabendazole–ovalbumin to produce a black band [27]. If thiabendazole is present, a portion of the detection complex will be neutralized. The test line’s colour intensity is inversely correlated with the thiabendazole concentration [27]. There is a similar test card similar, which can detect carbaryl [80]. The test card relies on the capture of carbon NPs by inactivated antibodies on the test zone, giving a black band.

Free carbaryl binds to immobilized antibodies, which stops the interaction of carbon NPs with the inactivated antibodies. The colour intensity of the test band is inversely proportional to the sample’s carbaryl concentration [80]. A competitive immunoassay dipstick based on AuNPs was developed as a rapid test for dichlorodiphenyltrichloroethane (DDT). The DDT pesticide is harmful, because it does not break down easily in the environment, and causes nervous system damage and complications in animal reproduction [106]. The gold nanoparticles are coupled with anti-DDT antibodies, after that the immune-complex solution is added to nitrocellulose membrane cards, which contain free DDT and the antigen. The free DDT then competitively inhibits the antigen at the AuNPs binding site. In the absence of free DDT, the card will show the red colour of the AuNPs. The red colour intensity decreases with an increase in free DDT concentration [106].

A Highly sensitive immunoassay of pesticide

The previous methods have disadvantages such as costly apparatuses needed, the long time needed for analysis, and the necessity of professional staff and not being safe to the environment. As a result, using of immunoassay-based antigen-antibody is widely used. [44] demonstrated that the immunoassay is an analytical method for detecting different substances using antigen-antibody specific binding reactions. There are two types of immunoassay: (i) labelled immunoassays and (ii) unlabelled immunoassays. For example, labelled immunoassays involve the bio-barcode immunoassay, enzyme-linked immunoassay (ELISA), fluorescence immunoassay (FIA), etc., while unlabelled immunoassays comprise immunoelectrophoresis and immunodiffusion. Advantages of immunoassay include simplicity, low cost, high sensitivity, and its ability to identify multiple types of pesticides (veterinary drugs, bio-toxins, heavy metals, etc.) or different types of small molecules at the same time. Cui et al. [44] demonstrated the main method of multiple residual detections which includes bio-barcode assay immunoassay, ELISA, FIA, etc. There are pesticides such as fenpropathrin, decamethrin, λ-cyhalothrin parathion, methyl parathion, fenitrothion organothiophosphate pesticides, organophosphate pesticides, and chlorpyrifos fenthion analysed and detected by ELISA and CLIA [44], 170.

Types of test paper technology utilized in rapid detection of pesticides

Nanoparticle markers

Nanoparticle markers have recently been developed and are known as ultrafine particles or nano-dust. The particles have a diameter of less than one nanometre (typically between 1 and 100 nm) [47]. Concerning light, heat, and susceptibility to magnetic fields, the particles are different from ordinary particles and have a broad specific surface region [23]. Nanoparticles are analytically important with various applications [47, 48]. Chemical nanoparticles, colloidal gold, lanthanides, quantum dots, magnetic nanoparticles, and carbon nanotubes are only a few of the nanoparticle markers that have been included in test strip processes [194].

Organic nanoparticles with strong optical properties, such as fluorescein isothiocyanate (FITC) nanoparticles, were one of the first to be used in the test strip process [8]. The primary amines of proteins are provided by the FITC nanoparticles, resulting in the ideal dye-protein conjugate [121]. The addition of fluorescein in the compound can be used to determine the presence of proteins. However, this approach has low sensitivity and photochemical stability since it relies too heavily on the chemiluminescent properties and lacks the effect of inorganic nanoparticles, which may regulate wavelength. As a result, new markers are increasingly being developed.

Colloidal gold, called a gold sol, is a multiphase uneven system created by the electrostatic repulsion between gold particles in water [118]. A system will ingest biological macromolecules without disrupting biological function and emit colours varying from green to red to purple. This allows for use as markers to differentiate between macromolecules such as proteins, polysaccharides, nucleic acids, and hormones. The test strip colloidal gold marker is the oldest and most thoroughly researched technique [140]. It has been used to test for aflatoxins in food. Many compounds such as the gold marker test strips, which are used for the identification of veterinary drug residues and pesticides, have been commercialized and include vibrio parahaemolyticus, Sudan red, and MicroRNA [182]. The gold colloidal-based immuno-dip strip was used to detect Sudan red I residue in tomato sauce and chilli powder samples quickly, with a limit of detection of 10 ng/g [72].

Lanthanide elements are a group of intermediate elements with atomic numbers ranging from 57 to 71 in the periodic table. A group of fluorescent up-conversion phosphor particles are produced by combining two related lanthanide ions as “light absorber” and “emitter” and incorporating them into ceramic particles that serve as “primary substrates”. Hong et al. [81] produced a strip that is stable for 10 days at 37 degrees Celsius with 10.3 per cent using up-conversion phosphor particles as markers. Its sensitivity and quantitative findings are equivalent to those of a traditional immunology assay. The traditional enzyme-linked immunosorbent assay (ELISA) is used for antibody detection with a linearity fitting coefficient of determination (R2) between 0.93 and 0.99. As a result, using lanthanide elements in test strips provides ideal detection limit and stability [81], resulting in rapid application development.

Quantum dots, also classified as fluorescence semiconductor nanoparticles, have compounds and nanoparticles of Si and related elements, as well as primary groups II-IV (e.g. CdSe) and III-V (e.g. InP). Particle diameters range from 1 to 10 nanometres. Since they mimic tiny dots, they are named after quantum dot. A core–shell standardized quantum dot is currently the most widely used since it not only has strong photochemical stability, but also a high luminescence quantum yield (30–50%). Quantum dot application in test strip markers is still under investigation, but its viability has been documented. With a minimal test line of 1–2 nm, Petryayeva and Algar [141] were able to complete the quantitative detection of protease in 5 minutes.

Nano-magnetic particles, also known as super-paramagnetic particles, are a relatively new kind of nanomaterial. Their super-paramagnetic feature, large specific surface area, and compact particle size incorporate the aspects of magnetic particles and nanomaterials. Magnetic materials (e.g. iron oxide) that act as a stable phase carrier are common markers. When active groups are added to the layers of magnetic substances, a coupled reaction between the magnetic materials and biological molecules including enzymes and antibodies occurs. The research material can be detected easily and quantitatively in this manner [63]. Fisher et al. [57] developed an immunomagnetic lateral flow system that allowed the identification of Bacillus anthracis spores in 10 mL dairy samples (n = 38) at a concentration of 5 × 105 CFU mL¯1, resulting in a 60-fold increase in sensitivity over standard strip methods. However, since magnetic particles are vulnerable to aggregation during the chromatographic process, few records of nano-magnetic particles used in test strip markers exist.

Carbon nanotubes, called buckytubes, are quantum substances with a topological shape resembling a twisted hexagonal grid structure of graphite. Carbon nanotubes have quantum effects similar to ordinary nanoparticles, have a large surface area, and have high conductivity and high mechanical power. Its distinct black colour makes it easier to identify qualitatively or semi-quantitatively with the naked eye. A nucleic material lateral flow method was defined for detecting listeria infection [136], with a low visual level of 0.1 ng of the labelled amplicon. The PCR solution is specifically applied to the strip, and the presence of clear amplicons is shown by the appearance of a grey/black line mediated by carbon nanoparticles (maximum time of 15 min). However, removing the carbon graphite and amorphous carbon debris mixed in the carbon nanotubes is technically challenging.

Paper in microfluidics

As described by Whiteside in 2006 [26], microfluidics is the modern science of devices that manage and control small quantities of fluid (10−9 L). Fluidic channels of hundreds to tens of micrometres in diameter are used. Because of variation in length, use of small amounts of samples and reagents, and rapid isolation and detection with high resolution and sensitivity [2], microfluidics experienced exponential growth with significant impacts in analytical chemistry. Glass, silicon, and polymers such as polydimethylsiloxane (PDMS) were used in early microfluidic studies. Even though microfluidic systems miniaturize traditional approaches for precise isolation and identification, they have disadvantages such as the cost of substrate materials and the need for power and fluid transfer instruments [157].

Paper is an attractive substrate medium to synthesize microfluidic devices [122]. Paper has many benefits as a low-cost diagnostic tool, which has been extensively explored: It can be printed quickly, coated, and impregnated; the cellulose structure is consistent with proteins and biomolecules, widely available and environmentally friendly since it can be disposed of by incineration [99]. The cellulose membrane network of microfluidic paper-based analytical devices (µPADs) uses paper as the primary substrate to provide instrument-free liquid transport through capillary action. Paper has a large surface area, a volume ratio that improves detection limits for colorimetric assays, and has the capacity to store chemical components in their active state within the paper fibre network. While µPADs lack the high resolution and sensitivity of silicon, glass, or plastic-based instruments, their implementation is suitable for point-of-need monitoring. The µPADs can be used in inexpensive research for constant testing, especially in less developed countries where complex instrumentation, analytical laboratories, and experts are scarce. As a result, µPADs have emerged as an appealing alternative to highly sophisticated instrumentation in analytical applications for food and water monitoring [137]. Much research studies have been conducted on the construction and deployment of µPADs for water and food protection and quality control and include fabrication techniques of µPADs and appropriate detection methods for quantitative and qualitative analyses [137].

Molecular imprinted polymer grafted paper-based multi-disc micro-disc plate (MIP method)

Pesticides have been used in agriculture for many years and have made a major contribution to food safety and productivity. However, these compounds harm human well-being [33]. Wang et al. [183] created a paper-based molecular imprinted polymer-grafted multi-disc micro-disc plate (MIP) for 2,4-dichlorophenoxyacetic acid CL detection (2,4-D).The MIP method had been considered as an option for immunoassay, which depends on antibodies. There are, however, significant disadvantages such as antibody hydrolysis and instability during manufacture and transport.

Tobacco peroxidase (TOP)-labelled 2,4-D molecularly imprinted on a polymer-grafted unit was used in an indirect comparative assay. The luminol–TOP–H2O2 CL system produced enzyme-catalysed chemiluminescence emission with a limit of detection of 1.0 pM [182, 183]. Liu et al. [111] created a simple paper-based luminol–H2O2 chemiluminescence for the identification of dichlorvos (DDV). Gilbert-López et al. [67] formalized a µPAD chemiluminescence assay to detect DDV in fruits and vegetables using paper chromatography, and the separation was completed in 12 minutes using 100 mL of developing reagent. The technique was successfully applied to identify trace DDV on cucumber, onion, and cabbage using a spiking method (3.6 ng mL−1 detection maximum). Liu et al. [111] proposed another MIP method for chemiluminescence detection of DDV using a paper-based instrument with a molecularly imprinted polymer. The detection limit was 0.8 ng mL−1, and the procedure worked well on cucumber and tomato. A paper-based colorimetric technique for identifying organophosphate and carbamate pollutants has also been demonstrated. Wang et al. [183] created a system based on the inhibition of organophosphate (methomyl) and carbamate (profenophos) pesticides and used acetylcholinesterase (AChE) to degrade acetylcholine molecules into choline and acetic acid. The degree of AChE inhibition suggested pesticide toxicity, making AChE a typical bioevaluator for the presence of organophosphates and carbamates [111].

Smartphone-based detection

The use of smartphones is growing, along with the number of µPAD techniques that combine tablets or smartphones for measurements [166]. Chaiyo et al. [35] established a µPAD sensor and a mobile application for on-site colorimetric identification of organophosphate pesticides (paraoxon and malathion) based on the pesticides' inhibition of immobilized AChE. The enzyme AChE hydrolyses the substrate in the absence of pesticides, and the colourless indoxyl acetate substrate is converted to an indigo-coloured substance. The colour strength decreases with rising pesticide concentration due to AChE inhibition. The colour intensity is evaluated using an image analysis algorithm on a smartphone, resulting in real-time monitoring and mapping of water quality. The tool can detect pesticide concentrations as low as 10 nM, as demonstrated by a colour shift in the µPAD [134]. Zhang et al. [191] focused on the use of nanoceria-coated µPAD for colorimetric organophosphate pesticide detection using enzyme inhibition assay with AChE and choline oxidase. In the existence of pesticides, AChE activity is prevented, resulting in no or limited H2O2 production and, as a result, less yellow colour formation of the nanoceria. (The colour production process is depicted in Fig. 4.) The assay could detect methyl-paraoxon and chlorpyrifos-oxon with detection limits of 18 ng mL−1 and 5.3 ng mL−1, respectively. The procedure was applied successfully for methyl-paraoxon identification on spiked cabbage and dried green mussel, with 95% recovery values for both samples.

Fig. 4
figure 4

The colour production process in nanoceria-coated µPAD colorimetric organophosphate pesticide detection

Paper-based visual detection

The design of a mobile (CdTe) paper-based sensor for identifying carbamate pesticides was continued. The nano-ZnTPyP concentration on the paper chip was increased to ensure the high sensitivity of the sensor. The same concentration (10 g L−1) of metolcarb was tested using a CdTe-based paper sensor with different concentrations of nano-ZnTPyP (17.04, 17.85, 18.75, 19.73, and 20.83 mol L−1). A low concentration of nano-ZnTPyP was not beneficial to visual identification, whereas a high concentration of nano-ZnTPyP was detrimental to eventual fluorescence recovery. The nano-ZnTPyP concentration of 17.85 mol L−1 had the most noticeable variations in colour change between quenching and regeneration, which was useful for visual recognition. As a result, the nano-ZnTPyP concentration for the paper-based sensor was determined to be 17.85 mol/L. The paper chips were then used thereafter to identify carbamate pesticides. As shown in Fig. 5, various concentrations of metolcarb (1–20 g L−1) were applied to the paper chips. As the metolcarb concentrations rose, the colour of the paper changed from dark green to yellow-green, then to pale green, and eventually to green, allowing for the quick visual identification of pesticides. Images were taken with a camera under 365 nm ultraviolet analyser, and the colour RGB values were collected and simulated by a computer programme, revealing the same pattern of colour shifts on the paper. Carbofuran and carbaryl were detected visually and quantitatively by the paper-based sensor under the same conditions. It was stated that the production of a novel nano-zinc 5, 10, 15, 20-tetra(4-pyridyl)-21H-23H-porphine (nano-ZnTPyP)-CdTe-based paper sensor could successfully detect carbamate pesticides in a quick, highly sensitive, highly precise, and on-site manner [148].

Fig. 5
figure 5

Change in paper colour with rising of the metolcarb concentrations using a CdTe-nano-ZnTPyP-based paper sensor

Recent studies in rapid test paper technology

Pesticide enzymatic and immunoassay test kits have been produced. Enzyme-based test kits can indicate organophosphate (OP) and carbamate (CM) pesticides in water, ground, vegetables, fruits, and other ecological samples. Also, to evaluate enzyme activity before and after pesticide exposure, techniques such as fluorimetry, amperometry, spectrophotometry, potentiometry, and thermometry are used [96]. There are several recent studies in rapid test paper technology, as summarized in Table 3.

Table 3 Advantages and disadvantages of the techniques used for pesticide detection in horticulture crops

Conclusions

The usage of pesticides can lead to toxic residues in horticulture crops, which, if consumed, can lead to decreased immunity, splenomegaly, renal failure, hepatitis, respiratory disorders, and cancer in humans. As a result, safe and practical strategies for detecting these residues in horticultural crops and monitoring food security is essential. Each of the discussed methods can be used in a certain situation, and the variety of methods enable detection of different types of pesticides in the environment. For instance, conventional methods, such as ECDs, are effective for organochlorine pesticides detection, while NPD, LC, HPLC, and NIR are suitable for organophosphate and nitrogenous pesticides, single compounds, organophosphates/triazines, and prediction of soil composition/pesticide absorption, respectively. Recently, rapid detection technologies have proved a great success, such as TLC that has enhanced resolution and shorter development time. Paper chromatography has a significant advantage over TLC, because the paper can be processed along with the sample. Colorimetric analysis and SERS that combine nano-markers, tablets, or smartphones for measurements are more effective to detect pesticides on horticulture crops on-site. Interestingly, the highly sensitive immunoassay, which offers the advantages of being low cost, specific, and sensitive, allows it to be integrated into many detection fields to accurately detect pesticides (Table 4).

Table 4 Summary of recent studies in rapid test paper technology

Availability of data and materials

Not applicable.

Abbreviations

AChE:

Acetylcholinesterase

AgNP/GO:

Silver nanoparticles–graphene oxide

CM:

Carbamate

DAD:

Diode array detectors

DDT:

Dichlorodiphenyltrichloroethane

DON-Chip:

De-oxy-nivalenol

ECD:

Electron capture detectors

ELISA:

Enzyme-linked immunoassay

FIA:

Fluorescence immunoassay

FID:

Flame ionization detection

FITC:

Fluorescein isothiocyanate

FPD:

Flame photometric detection

GC:

Gas chromatography

HPLC:

High-performance liquid chromatography

HRMS:

High-resolution MS

LC:

Liquid chromatography

MRLs:

Maximum residue limits

MS:

Mass spectrometry

MSD:

Mass selective detection

NPD:

Nitrogen–phosphorous detection

OC:

Organic carbon

OP:

Organophosphate

OP:

Organophosphorus

PCR:

Polymerase chain reaction

PDMS:

Polydimethylsiloxane

PLS:

Partial least squares

PLS-DA:

Partial least squares discriminant analysis

Q:

Quadrupole

QqQ:

Triple quadrupole

QTrap:

Hybrid quadrupole ion trap

RPLC:

Reversed-phase liquid chromatography

SERS:

Surface-enhanced Raman spectroscopy

TLC:

Thin-layer chromatography

TN:

Total nitrogen

TOF:

Time of flight

References

  1. Abd Elkodous M, El-Husseiny HM, El-Sayyad GS, Hashem AH, Doghish AS, Elfadil D, Radwan Y, El-Zeiny HM, Bedair H, Ikhdair OA, Hashim H, Salama AM, Alshater H, Ahmed AA, Elsayed MG, Nagy M, Ali NY, Elahmady M, Kamel AM et al (2021) Recent advances in waste-recycled nanomaterials for biomedical applications: waste-to-wealth. Nanotechnol Rev 10(1):1662–1739

    Article  CAS  Google Scholar 

  2. Abera A, Choi JW (2010) Quantitative lateral flow immunosensor using carbon nanotubes as label. Anal Methods 2(11):1819–1822

    Article  CAS  Google Scholar 

  3. Agrawal O, Gupta VK (1999) Sub-parts-per-million spectrophotometric determination of phenol and related pesticides using diazotizedpaminoacetophenone. Microchem J 62(1):147–153

    Article  CAS  Google Scholar 

  4. Akash MSH, Rehman K (2020) Gas chromatography. Essentials of pharmaceutical analysis. Springer, Singapore, pp 185–193

    Chapter  Google Scholar 

  5. Akkad R, Schwack W (2010) Multi-enzyme inhibition assay for the detection of insecticidal organophosphates and carbamates by high-performance thin-layer chromatography applied to determine enzyme inhibition factors and residues in juice and water samples. J Chromatogr B 878(17–18):1337–1345

    Article  CAS  Google Scholar 

  6. Alcántara-Durán J, Moreno-González D, Gilbert-López B, Molina-Díaz A, García-Reyes JF (2018) Matrix-effect free multi-residue analysis of veterinary drugs in food samples of animal origin by nanoflow liquid chromatography high resolution mass spectrometry. Food Chem 245:29–38

    Article  PubMed  CAS  Google Scholar 

  7. Alder L, Greulich K, Kempe G, Vieth B (2006) Residue analysis of 500 high priority pesticides: better by GC–MS or LC–MS/MS? Mass Spectrosc R 25(6):838–865

    Article  CAS  Google Scholar 

  8. Alsolmy E, Abdelwahab WM, Patonay G (2018) A comparative study of fluorescein isothiocyanate-encapsulated silica nanoparticles prepared in seven different routes for developing fingerprints on non-porous surfaces. J Fluoresc 28(5):1049–1058

  9. Amvrazi EG, Martini MA, Tsiropoulos NG (2012) Headspace single-drop microextraction of common pesticide contaminants in honey–method development and comparison with other extraction methods. Inter J Environ Anal Chem 92(4):450–465

    Article  CAS  Google Scholar 

  10. Andrews R (1992) Immunoassay advances as tool for environmental testing. The scientist (USA)

  11. Arena K, Mandolfino F, Cacciola F, Dugo P, Mondello L (2021) Multidimensional liquid chromatography approaches for analysis of food contaminants. J Sep Sci 44(1):17–34

    Article  CAS  PubMed  Google Scholar 

  12. Aretz I, Meierhofer D (2016) Advantages and pitfalls of mass spectrometry based metabolome profiling in systems biology. Int J Mol Sci 17(5):632

    Article  PubMed Central  CAS  Google Scholar 

  13. Armenta S, Garrigues S, de la Guardia M (2007) Partial least squares-near infrared determination of pesticides in commercial formulations. Vibr Spectrosc 44(2):273–278

    Article  CAS  Google Scholar 

  14. Aruna G, Baskaran V (2010) Comparative study on the levels of carotenoids lutein, zeaxanthin and β-carotene in Indian spices of nutritional and medicinal importance. Food Chem 123(2):404–409

    Article  CAS  Google Scholar 

  15. Bacigalupo MA, Ius A, Longhi R, Meroni G (2003) Homogeneous immunoassay of atrazine in water by terbium-entrapping liposomes as fluorescent markers. Talanta 61(4):539–545

    Article  CAS  PubMed  Google Scholar 

  16. Badawy ME, El-Aswad AF (2014) Bioactive paper sensor based on the acetylcholinesterase for the rapid detection of organophosphate and carbamate pesticides. Inter J Anal Chem. https://doi.org/10.1155/2014/536823

    Article  Google Scholar 

  17. Baghani A, Mesdaghinia A, Rafieiyan M, Soltan Dallal MM, Douraghi M (2019) Tetracycline and ciprofloxacin multiresidues in beef and chicken meat samples using indirect competitive ELISA. J Immuno Immunochem 40(3):328–342

    Article  CAS  Google Scholar 

  18. Bai W, Zhu C, Liu J, Yan M, Yang S, Chen A (2015) Gold nanoparticle–based colourimetric aptasensor for rapid detection of six organophosphorous pesticides. Environ Toxicol Chem 34(10):2244–2249

    Article  CAS  PubMed  Google Scholar 

  19. Baynes RE, Dedonder K, Kissell L, Mzyk D, Marmulak T, Smith G, Riviere JE (2016) Health concerns and management of select veterinary drug residues. Food Chem Toxicol 88:112–122

    Article  CAS  PubMed  Google Scholar 

  20. Bedair H (2020) Composition and pattern of wild trees and shrubs in the Egyptian flora. M. Sc. Thesis. Botany Department, Faculty of Science, Tanta University, Tanta, Egypt.

  21. Bedair H, Rady HA, Hussien AM, Pandey M, Apollon W, AlKafaas SS, Ghosh S (2022) Pesticide detection in vegetable crops using enzyme inhibition methods: a comprehensive review. Food Anal Methods. https://doi.org/10.1007/s12161-022-02254-x

    Article  Google Scholar 

  22. Bedair H, Shaltout K, Ahmed D, Sharaf El-Din A, El-Fahhar R (2020) Characterization of the wild trees and shrubs in the Egyptian Flora. Egypt J Bot 60(1):147–168

    Google Scholar 

  23. Bera H, Abosheasha MA, Ito Y, Ueda M (2021) Etherified pullulan-polyethylenimine based nanoscaffolds improved chemosensitivity of erlotinib on hypoxic cancer cells. Carbohydrate Polymers 271:118441

  24. Biedermann M, Grob K (2019) Advantages of comprehensive two-dimensional gas chromatography for comprehensive analysis of potential migrants from food contact materials. Anal Chim Acta 1057:11–17

    CAS  PubMed  Google Scholar 

  25. Biros FJ (1971) Pesticides identification at the residue level—a symposium sponsored by the Division of Pesticide Chemistry of the American Chemical Society at the Joint Conference of the Chemical Society of Canada and the American Chemical Society at Toronto, Ont. Canada, May 26–27, 1970.

  26. Blažková M, Koets M, Rauch P, Van Amerongen A (2009) Development of a nucleic acid lateral flow immunoassay for simultaneous detection of Listeria spp. and Listeria monocytogenes in food. Euro Food Res Technol 229(6):867–874

    Article  CAS  Google Scholar 

  27. Blažková M, Rauch P, Fukal L (2010) Strip-based immunoassay for rapid detection of thiabendazole. Biosens Bioelectron 25(9):2122–2128

    Article  PubMed  CAS  Google Scholar 

  28. Boyle WJ, van der Geer P, Hunter T (1991) Phosphopeptide mapping and phosphoamino acid analysis by two-dimensional separation on thin-layer cellulose plates. Methods in enzymology, vol 201. Elsevier, New York, pp 110–149

    Google Scholar 

  29. Brody SS, Chaney JE (1966) Flame photometric detector: the application of a specific detector for phosphorus and for sulfur compounds—sensitive to subnanogram quantities. J Chromatogr Sci 4(2):42–46

    Article  CAS  Google Scholar 

  30. Bunert E, Kirk AT, Oermann J, Zimmermann S (2017) Electron capture detector with non-radioactive electron source. Multidiscipl Digit Publ Inst Proc 1(4):443

    Google Scholar 

  31. Brunet D, Woignier T, Lesueur-Jannoyer M, Achard R, Rangon L, Barthes BG (2009) Determination of soil content in chlordecone (organochlorine pesticide) using near infrared reflectance spectroscopy (NIRS). Enviro Pollut 157(11):3120–3125

    Article  CAS  Google Scholar 

  32. Cao J, Wang M, Yu H, She Y, Cao Z, Ye J, Lao S (2020) An overview on the mechanisms and applications of enzyme inhibition-based methods for determination of organophosphate and carbamate pesticides. J Agric Food Chem 68(28):7298–7315

    Article  CAS  PubMed  Google Scholar 

  33. Cardoso TM, Garcia PT, Coltro WK (2015) Colourimetric determination of nitrite in clinical, food and environmental samples using microfluidic devices stamped in paper platforms. Anal Methods 7(17):7311–7317

    Article  CAS  Google Scholar 

  34. Celeiro M, Llompart M, Lamas JP, Lores M, Garcia-Jares C, Dagnac T (2014) Determination of fungicides in white grape bagasse by pressurized liquid extraction and gas chromatography tandem mass spectrometry. J Chromatogr A 1343:18–25

    Article  CAS  PubMed  Google Scholar 

  35. Chaiyo S, Siangproh W, Apilux A, Chailapakul O (2015) Highly selective and sensitive paper-based colourimetric sensor using thiosulfate catalytic etching of silver nanoplates for trace determination of copper ions. Anal Chim Acta 866:75–83

    Article  CAS  PubMed  Google Scholar 

  36. Chang C, Luo J, Chen M, Wu K, Dong T, He X, Xia Y (2016) Determination of twenty organophosphorus pesticides in blood serum by gas chromatography-tandem mass spectrometry. Analy Methods 8(22):4487–4496

    Article  CAS  Google Scholar 

  37. Chawla P, Kaushik R, Swaraj VS, Kumar N (2018) Organophosphorus pesticides residues in food and their colourimetric detection. Environ Nano Technol Monit Manag 10:292–307

    Google Scholar 

  38. Chen Y, Ren HL, Liu N, Sai N, Liu X, Liu Z, Ning BA (2010) A fluoroimmunoassay based on quantum do—streptavidin conjugate for the detection of chlorpyrifos. J Agric Food Chem 58(16):8895–8903

    Article  CAS  PubMed  Google Scholar 

  39. Chiou J, Leung AHH, Lee HW, Wong W-t (2015) Rapid testing methods for food contaminants and toxicants. J Integr Agric 14:2243–2264

    Article  CAS  Google Scholar 

  40. Christopher FC, Kumar PS, Christopher FJ, Joshiba GJ, Madhesh P (2020) Recent advancements in rapid analysis of pesticides using nano biosensors: a present and future perspective. J Cleaner Prod 269:122356

  41. Coskun O (2016) Separation techniques: chromatography. Northern Clin Istanbul 3(2):156

    Google Scholar 

  42. Colovic MB, Krstic DZ, Lazarevic-Pasti TD, Bondzic AM, Vasic VM (2013) Acetylcholinesterase inhibitors: pharmacology and toxicology. Curr Neuropharmacol 11(3):315–335

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Coffin DE (1966) Paper chromatography in pesticide residue analysis. J Assoc Offic Anal Chem 49(3):638–643

    CAS  Google Scholar 

  44. Cui X, Jin M, Du P, Chen G, Zhang C, Zhang Y, Wang J (2018) Development of immunoassays for multi-residue detection of small molecule compounds. Food Agric Immunol 29(1):638–652

    Article  CAS  Google Scholar 

  45. de Mirandaa JAT, de CarvalhoaL MJ, de Castrob IM, dos Anjosb MR, de Carvalhob LV,de Macêdo Vieiraa AC (2020) Heating, identification, and determination of pesticides residues in black bean samples. Chem Eng, pp. 80.‏

  46. de Villiers A, Lestremau F, Szucs R, Gélébart S, David F, Sandra P (2006) Evaluation of ultra-performance liquid chromatography: Part I. Possibilities and limitations. J Chromatogr A 1127(1–2):60–69

    Article  PubMed  CAS  Google Scholar 

  47. Diab T, Alkafaas SS, Shalaby TI, Hessien M (2020) Paclitaxel nanoparticles induce apoptosis and regulate txr1, cyp3a4 and cyp2c8 in breast cancer and hepatoma cells. Anti-Cancer Agents Med Chem (Formerly Current Medicinal Chemistry-Anti-Cancer Agents) 20 (13):1582–1591

  48. Diab T, AlKafaas SS, Shalaby TI, Hessien M (2020) Dexamethasone simulates the anticancer effect of nano-formulated paclitaxel in breast cancer cells. Bioorg Chem 99:103792

  49. Dkhar DS, Kumari R, Mahapatra S, Kumar R, Chandra P (2022) Ultrasensitive aptasensors for the detection of viruses based on opto-electrochemical readout systems. Biosensors 12(2):81

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Dong M (2013) The essence of modern HPLC: advantages, limitations, fundamentals, and opportunities. LCGC North Am 31(6):472–479

    CAS  Google Scholar 

  51. Dong J, Pan YX, Lv JX, Sun J, Gong XM (2011) Multiresidue method for the determination of pesticides in fruits and vegetables using gas chromatography-negative chemical ionization-triple quadrupole tandem mass spectrometry. Chromatogr 74(1):109–119

    Article  CAS  Google Scholar 

  52. El Alami A, Lagarde F, Huo Q, Zheng T, Baitoul M, Daniel P (2020) Acetylcholine and acetylcholinesterase inhibitors detection using gold nanoparticles coupled with dynamic light scattering. Sens Intern 1:100007

    Article  Google Scholar 

  53. ElMasry G, Wang N, ElSayed A, Ngadi M (2007) Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry. J Food Eng 81(1):98–107

    Article  CAS  Google Scholar 

  54. Ercegovich C (1971) Analysis of pesticide residues: immunological techniques. ACS Publications

  55. Esquinas-Requena JL, Lozoya-Moreno S, García-Nogueras I, Atienzar-Núñez P, Sánchez-Jurado PM, Abizanda P (2020) La anemia aumenta el riesgo de mortalidad debido a fragilidad y discapacidad en mayores: Estudio FRADEA. Aten Prim 52(7):452–461

    Article  Google Scholar 

  56. Fernández-Ramos MD, Ogunneye AL, Babarinde NA, Erenas MM, Capitán-Vallvey LF (2020) Bioactive microfluidic paper device for pesticide determination in waters. Talanta 218:121108

    Article  PubMed  CAS  Google Scholar 

  57. Fisher M, Atiya-Nasagi Y, Simon I, Gordin M, Mechaly A, Yitzhaki S (2009) A combined immunomagnetic separation and lateral flow method for a sensitive on-site detection of Bacillus anthracis spores–assessment in water and dairy products. Lett Appl Microbiol 48:413–418

    Article  CAS  PubMed  Google Scholar 

  58. Fodor-Csorba K (1992) Chromatographic methods for the determination of pesticides in foods. J Chromatogr A 624(1–2):353–367

    Article  CAS  Google Scholar 

  59. François I, De Villiers A, Sandra P (2006) Considerations on the possibilities and limitations of comprehensive normal phase–reversed phase liquid chromatography (NPLC×RPLC). J Sep Sci 29(4):492–498

    Article  PubMed  CAS  Google Scholar 

  60. Fu G, Chen W, Yue X, Jiang X (2013) Highly sensitive colourimetric detection of organophosphate pesticides using copper catalyzed click chemistry. Talan 103:110–115

    Article  CAS  Google Scholar 

  61. Fuyal M, Giri B (2020) A combined system of paper device and portable spectrometer for the detection of pesticide residues. Food Anal Methods 13:1492–1502

    Article  Google Scholar 

  62. Gabaldon JA, Cascales JM, Morias S, Maquieira A, Puchades R (2003) Determination of atrazine and carbaryl pesticide residues in vegetable samples using a multianalyte dipstick immunoassay format. Food Addit Contam 20(8):707–715

    Article  CAS  PubMed  Google Scholar 

  63. Gao X, Xu H, Baloda M, Gurung AS, Xu LP, Wang T, Liu G (2014) Visual detection of microRNA with lateral flow nucleic acid biosensor. Biosens Bioelectron 54:578–584

    Article  CAS  PubMed  Google Scholar 

  64. Getz ME (1963) The determination of organophosphate pesticides and their residues by paper chromatography. In: Residue Reviews/Rückstands-Berichte. Springer, pp 9–25

  65. Ghosh SK (2020) Evaluation of safe insecticides against sucking pests, jassid (Amrasca bigutula bigutula Ishida) and aphid (Aphis gossypii Glov.) infesting chilli (Capsicum annum L.) crop. J Entomol Zool Stud 8:1428–1433

  66. Ghosh S, Falyouna O, Malloum A, Othmani A, Bornman C, Bedair H, Onyeaka H, Al-Sharify ZT, Jacob AO, Miri T, Osagie C, Ahmadi S (2021) A general review on the use of advance oxidation and adsorption processes for the removal of furfural from industrial effluents. Microporous Mesoporous Mater. https://doi.org/10.1016/j.micromeso.2021.111638

    Article  Google Scholar 

  67. Gilbert-López B, García-Reyes JF, Molina-Díaz A (2009) Sample treatment and determination of pesticide residues in fatty vegetable matrices: a review. Talanta 79(2):109–128

    Article  PubMed  CAS  Google Scholar 

  68. Gobo AB, Kurz MH, Pizzutti IR, Adaime MB, Zanella R (2004) Development and validation of methodology for the determination of residues of organophosphorus pesticides in tomatoes. J Braz Chem Soc 15:945–950

  69. Grimalt S, Dehouck P (2016) Review of analytical methods for the determination of pesticide residues in grapes. J Chromatogr A 1433:1–23

    Article  CAS  PubMed  Google Scholar 

  70. Guan SX, Yu ZG, Yu HN, Song CH, Song ZQ, Qin Z (2011) Multi-walled carbon nanotubes as matrix solid-phase dispersion extraction adsorbent for simultaneous analysis of residues of nine organophosphorus pesticides in fruit and vegetables by rapid resolution LC–MS–MS. Chromatography 73(1):33–41

    Article  CAS  Google Scholar 

  71. Guerrero ED, Marín RN, Mejías RC, Barroso CG (2009) Traceability of phytosanitary products in the production of a Sherry wine vinegar. J Agric Food Chem 57(6):2193–2199

    Article  CAS  Google Scholar 

  72. Guo A, Sheng H, Zhang M, WuR XJ (2012) Development and evaluation of a colloidal gold immunochromatography strip for rapid detection of V ibrio parahaemolyticus in food. J Food Qual 35(5):366–371

    Article  CAS  Google Scholar 

  73. Guo X, Zhang X, Cai Q, Shen T, Zhu S (2013) Developing a novel sensitive visual screening card for rapid detection of pesticide residues in food. Food Cont 30(1):15–23

    Article  CAS  Google Scholar 

  74. Gupta M, Kapoor B, Gupta R (2018) Paper chromaography: a review. JETIR 5(10):442–448

    Google Scholar 

  75. Hage DS (2018) Chromatography. Principles and applications of clinical mass spectrometry: small molecules, peptides, and pathogens. Elsevier, Amsterdam, pp 1–32

    Google Scholar 

  76. Hall RC (1978) The nitrogen detector in gas chromatography. Crit Rev Anal Chem 7(4):323–380

    Article  CAS  Google Scholar 

  77. Hercegová A, Dömötörová M, Matisova E (2007) Sample preparation methods in the analysis of pesticide residues in baby food with subsequent chromatographic determination. J Chromatogr A 1153(1–2):54–73

    Article  PubMed  CAS  Google Scholar 

  78. Hernández F, Cervera MI, Portolés T, Beltrán J, Pitarch E (2013) The role of GC-MS/MS with triple quadrupole in pesticide residue analysis in food and the environment. Anal Methods 5(21):5875–5894

    Article  CAS  Google Scholar 

  79. Hogendoorn EA (2006) High-performance liquid chromatography methods in pesticide residue analysis. Encycl Anal Chem Appl Theory Instrum. https://doi.org/10.1002/9780470027318.a1712

    Article  Google Scholar 

  80. Holubová-Mičková B, Blažková M, Fukal L, Rauch P (2010) Development of colloidal carbon-based immunochromatographic strip for rapid detection of carbaryl in fruit juices. Euro Food Rese Technol 231(3):467–473

    Article  CAS  Google Scholar 

  81. Hong W, Huang L, Wang H, Qu J, Guo Z, Xie C, Zhou L (2010) Development of an up-converting phosphor technology-based 10-channel lateral flow assay for profiling antibodies against Yersinia pestis. J Micro Methods 83(2):133–140

    Article  CAS  Google Scholar 

  82. Hosseini S, Vázquez-Villegas P, Rito-Palomares M, Martínez-Chapa SO (2018) Advantages, disadvantages and modifications of conventional ELISA. Enzyme-linked immunosorbent assay (ELISA). Springer Briefs in Applied Sciences and Technology. Springer, Singapore, pp 67–115

    Google Scholar 

  83. Hu T, Xu J, Ye Y, Han Y, Li X, Wang Z, Ni Z (2019) Visual detection of mixed organophosphorous pesticide using QD-AChE aerogel based microfluidic arrays sensor. Biosen Bioelectron 136:112–117

    Article  CAS  Google Scholar 

  84. Islam S, Hossain MS, Nahar N, Mosihuzzaman M, Mamun MIR (2009) Application of high performance liquid chromatography to the analysis of pesticide residues in eggplants. J Appl Sci 9(5):973–977

    Article  CAS  Google Scholar 

  85. Jain M, Yadav P, Joshi B, Joshi A, Kodgire P (2021) A novel biosensor for the detection of organophosphorus (OP)-based pesticides using organophosphorus acid anhydrolase (OPAA)-FL variant. Appl Micro Biotechnol 105(1):389–400

    Article  CAS  Google Scholar 

  86. Jallow MF, Awadh DG, Albaho MS, Devi VY, Ahmad N (2017) Monitoring of pesticide residues in commonly used fruits and vegetables in Kuwait. Inter J Environ Res Pub Heal 14(8):833

    Article  CAS  Google Scholar 

  87. Jamshidi B (2017) Non-destructive safety assessment of agricultural products using Vis/NIR spectroscopy. NIR News 28(1):4–8

    Article  Google Scholar 

  88. Jamshidi B, Mohajerani E, Jamshidi J (2016) Developing a Vis/NIR spectroscopic system for fast and non-destructive pesticide residue monitoring in agricultural product. Measurements 89:1–6

    CAS  Google Scholar 

  89. Ji QI, Xin-Xia FA, DE Dong-Mei N, Hai-Bo HE, Li-Qiang LU (2020) Progress in rapid detection techniques using paper-based platforms for food safety. Chin J Anal Chem 48(12):1616–1624

    Article  Google Scholar 

  90. Jia M, Zhai F, Bing X (2020) Rapid multi-residue detection methods for pesticides and veterinary drugs. Molecules 25(16):3590

    Article  CAS  PubMed Central  Google Scholar 

  91. Joint F (2005) Validation of thin-layer chromatographic methods for pesticide residue analysis. Results of the coordinated research projects 1996–2002.

  92. Khanmohammadi M, Armenta S, Garrigues S, de la Guardia M (2008) Mid-and near-infrared determination of metribuzin in agrochemicals. Vibra Spectrosc 46(2):82–88

    Article  CAS  Google Scholar 

  93. Khetagoudar MC, Chetti MB, Bilehal DC (2019) Gas chromatographic-mass spectrometric detection of pesticide residues in grapes. Gas chromatography-derivatization, sample preparation, application. IntechOpen, London, pp 97–130

    Google Scholar 

  94. Kibelka GP, Short RT, Toler SK, Edkins JE, Byrne RH (2004) Field-deployed underwater mass spectrometers for investigations of transient chemical systems. Talanta 64(4):961–969

    Article  CAS  PubMed  Google Scholar 

  95. Kim G, Kim J, Kim SM, Kato T, Yoon J, Noh S, Park EY, Park C, Lee T, Choi JW (2022) Fabrication of MERS-nanovesicle biosensor composed of multi-functional DNA aptamer/graphene-MoS2 nanocomposite based on electrochemical and surface enhanced Raman spectroscopy. Sens Actuat B Chem 352:131060

    Article  CAS  Google Scholar 

  96. Kumar M, Munoz-Arriola F, Furumai H, Chaminda T (2020) Resilience, Resp, and Ris in Wat Syst. Springer, Singapore, pp 1–399

    Google Scholar 

  97. Lan M, Guo Y, Zhao Y, Liu Y, Gui W, Zhu G (2016) Multi-residue detection of pesticides using a sensitive immunochip assay based on nanogold enhancement. Anal Chim Acta 938:146–155

    Article  CAS  PubMed  Google Scholar 

  98. Langford JB, Lurie IS (2021) Use of micro, capillary, and nano liquid chromatography for forensic analysis. J Sep Sci 45(1):38–50

    Article  PubMed  CAS  Google Scholar 

  99. Leclerc E, Sakai Y, Fujii T (2004) Microfluidic PDMS (polydimethylsiloxane) bioreactor for large-scale culture of hepatocytes. Biotechno Progr 20(3):750–755

    Article  CAS  Google Scholar 

  100. LeDoux M (2011) Analytical methods applied to the determination of pesticide residues in foods of animal origin. A review of the past two decades. J Chromatogr A 1218(8):1021–1036

    Article  CAS  PubMed  Google Scholar 

  101. Lee MG, Patil V, Na YC, Lee DS, Lim SH, Yi GR (2018) Highly stable, rapid colourimetric detection of carbaryl pesticides by azo coupling reaction with chemical pre-treatment. Sens Actuat B Chem 261:489–496

    Article  CAS  Google Scholar 

  102. Lehotay SJ, Hajšlová J (2002) Application of gas chromatography in food analysis. TrAC Trends Anal Chem 21(9–10):686–697

    Article  CAS  Google Scholar 

  103. Levasseur-Garcia C (2018) Updated overview of infrared spectroscopy methods for detecting mycotoxins on cereals (corn, wheat, and barley). Toxins 10(1):38

    Article  PubMed Central  CAS  Google Scholar 

  104. Li X, Cui H, Zeng Z (2018) A simple colourimetric and fluorescent sensor to detect organophosphate pesticides based on adenosine triphosphate-modified gold nanoparticles. Sensors 18(12):4302

    Article  PubMed Central  CAS  Google Scholar 

  105. Lian YJ, Pang GF, Shu HR, Fan CL, Liu YM, Feng J, Chang QY (2010) Simultaneous determination of 346 multiresidue pesticides in grapes by PSA-MSPD and GC-MS-SIM. J Agric Food Chem 58(17):9428–9453

    Article  CAS  PubMed  Google Scholar 

  106. Lisa M, Chouhan RS, Vinayaka AC, Manonmani HK, Thakur MS (2009) Gold nanoparticles based dipstick immunoassay for the rapid detection of dichlorodiphenyltrichloroethane: an organochlorine pesticide. Biosens Bioelectron 25(1):224–227

    Article  CAS  PubMed  Google Scholar 

  107. Liu B, Zhuang J, Wei G (2020) Recent advances in the design of colorimetric sensors for environmental monitoring. Environ Sci Nano 7(8):2195–2213

    Article  CAS  Google Scholar 

  108. Liu D-M, Xu B, Dong C (2021) Recent advances in colorimetric strategies for acetylcholinesterase assay and their applications. TrAC Trends Anal Chem 142:116320

    Article  CAS  Google Scholar 

  109. Liu D, Chen W, Wei J, Li X, Wang Z, Jiang X (2012) A highly sensitive, dual-readout assay based on gold nanoparticles for organophosphorus and carbamate pesticides. Anal Chem 84(9):4185–4191

    Article  CAS  PubMed  Google Scholar 

  110. Liu S, Zheng Z, Li X (2013) Advances in pesticide biosensors: current status, challenges, and future perspectives. Anal Bioanal Chem 405(1):63–90

    Article  CAS  PubMed  Google Scholar 

  111. Liu W, Kou J, Xing H, Li B (2014) based chromatographic chemiluminescence chip for the detection of dichlorvos in vegetables. Biosens Bioelectron 52:76–81

    Article  CAS  PubMed  Google Scholar 

  112. Ma Y, Wang Y, Luo Y, Duan H, Li D, Xu H, Fodjo EK (2018) Rapid and sensitive on-site detection of pesticide residues in fruits and vegetables using screen-printed paper-based SERS swabs. Anal Meth 10(38):4655–4664

    Article  CAS  Google Scholar 

  113. Mahapatro G, Rajna S (2020) Insecticide toxicity and pesticide residues in horticultural crops. In: Innovative pest management approaches for the 21st century. Springer, pp 377–390

  114. Majima K, Fukui T, Yuan J, Wang G, Matsumoto K (2002) Quantitative measurement of 17β-estradiol and estriol in river water by time-resolved fluoroimmunoassay. Anal Sci 18(8):869–874

    Article  CAS  PubMed  Google Scholar 

  115. ‏ Makio T, Hiroaki I, Tomohiro T, Hisaya Y, Kumiko N, Nobuaki T (2007). Classification of pesticide residues in the agricultural products based on diffuse reflectance IR spectroscopy. In: SICE annual conference 2007 IEEE, pp. 216–219.‏

  116. Malhat F, Boulangé J, Abdelraheem E, Abd Allah O, Abd El-Hamid R, Abd El-Salam S (2017) Validation of QuEChERS based method for determination of fenitrothion residues in tomatoes by gas chromatography–flame photometric detector: decline pattern and risk assessment. Food Chem 229:814–819

    Article  CAS  PubMed  Google Scholar 

  117. Manley M (2014) Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials. Chem Soc Rev 43(24):8200–8214

    Article  CAS  PubMed  Google Scholar 

  118. Masinde LA, Sheng W, Xu X, Zhang Y, Yuan M, Kennedy IR, Wang S (2013) Colloidal gold based immunochromatographic strip for the simple and sensitive determination of aflatoxin B1 and B2 in corn and rice. Micro Acta 180(9–10):921–928

    Article  CAS  Google Scholar 

  119. Mathivanan S (2021) Perspectives of nano-materials and nanobiosensors in food safety and agriculture. Novel Nanomaterials. InTech, London, p 197

    Google Scholar 

  120. Matros A, Peukert M, Lahnstein J, Seiffert U, Burton R (2019) Determination of fructans in plants: current analytical means for extraction, detection, and quantification. Annual Plant Rev Online 2:1–39

    Google Scholar 

  121. Mayhew TM, Mühlfeld C, Vanhecke D, Ochs M (2009) A review of recent methods for efficiently quantifying immunogold and other nanoparticles using TEM sections through cells, tissues and organs. Ann Anato-Anatomis Anzeiger 191(2):153–170

    Article  CAS  Google Scholar 

  122. McDonald JC, Whitesides GM (2002) Poly (dimethylsiloxane) as a material for fabricating microfluidic devices. Acc Chem Resea 35(7):491–499

    Article  CAS  Google Scholar 

  123. Mdeni NL, Adeniji AO, Okoh AI, Okoh OO (2022) Analytical evaluation of carbamate and organophosphate pesticides in human and environmental matrices: a review. Molecules 27(3):618

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Melo LF, Collins CH, Jardim IC (2005) High-performance liquid chromatographic determination of pesticides in tomatoes using laboratory-made NH2 and C18 solid-phase extraction materials. J Chromatogr A 1073(1–2):75–81

    Article  CAS  PubMed  Google Scholar 

  125. Melo MG, Carqueijo A, Freitas A, Barbosa J, Silva AS (2020) Modified QuEChERS extraction and HPLC-MS/MS for simultaneous determination of 155 pesticide residues in rice (Oryza sativa L.). Foods 9(1):18

    Article  CAS  Google Scholar 

  126. Mitchel LC (1966) Separation and identification of substituted urea herbicides by paper chromatography. J Assoc Off Analy Chem 49(6):1163–1166

    Google Scholar 

  127. Mitchell LC (1960) Paper chromatography of 3-amino1, 2, 4-triazole. J Assoc Off Agri Chem 43(1):87–88

    CAS  Google Scholar 

  128. Mostafalou S, Abdollahi M (2017) Pesticides: an update of human exposure and toxicity. Archiv of Toxico 91(2):549–599

    Article  CAS  Google Scholar 

  129. Motaharian A, Motaharian F, Abnous K, Hosseini MR, Hassanzadeh-Khayyat M (2016) Molecularly imprinted polymer nanoparticles-based electrochemical sensor for determination of diazinon pesticide in well water and apple fruit samples. Analy and Bioanaly Chem 408(24):6769–6779

    Article  CAS  Google Scholar 

  130. Munir MA, Badri KH (2020) The importance of derivatizing reagent in chromatography applications for biogenic amine detection in food and beverages. J Anal Methods Chem, 1–15.

  131. Mushtaq W, Bedair H, Shakeel A (2020) Halophytes: a phytoremediation tool for salt-affected soils with special reference to indian subcontinent. Handbook of halophytes: from molecules to ecosystems towards biosaline agriculture, pp. 1–16.‏

  132. Nasiri A, Amirahmadi M, Mousavi Z, Shoeibi S, Khajeamiri A, Kobarfard F (2016) A multi residue GC-MS method for determination of 12 pesticides in cucumber. Irani J Pharma Res IJPR 15(4):809

    CAS  Google Scholar 

  133. Ng WF, Teo MJ, Lakso HÅ (1999) Determination of organophosphorus pesticides in soil by headspace solid-phase microextraction. Fresen ’ J Analy Chem 363(7):673–679

    Article  CAS  Google Scholar 

  134. Nouanthavong S, Nacapricha D, Henry CS, Sameenoi Y (2016) Pesticide analysis using nanoceria-coated paper-based devices as a detection platform. Analyst 141(5):1837–1846

    Article  CAS  PubMed  Google Scholar 

  135. Pang B, Zhu Y, Lu L, Gu F, Chen H (2016) The applications and features of liquid chromatography-mass spectrometry in the analysis of traditional chinese medicine. Evid Based Complement Alternat Med 2016:7. https://doi.org/10.1155/2016/3837270

    Article  Google Scholar 

  136. Parolo C, Medina-Sánchez M, De La Escosura-Muñiz A, Merkoçi A (2013) Simple paper architecture modifications lead to enhanced sensitivity in nanoparticle based lateral flow immunoassays. Lab Chip 13(3):386–390

    Article  CAS  PubMed  Google Scholar 

  137. Pelton R (2009) Bioactive paper provides a low-cost platform for diagnostics. TrAC Trends in Analy Chem 28(8):925–942

    Article  CAS  Google Scholar 

  138. Peng Y, Wu J (2008) Hyperspectral scattering profiles for prediction of beef tenderness. In ASABE Annual Intern Meet, pp. 080004.‏

  139. Peng Y, Zhang J, Wu J, Hang H (2009) Hyperspectral scattering profiles for prediction of the microbial spoilage of beef. Sens Agric Food Qual Saf Intern Soc Opt Photon 7315:73150

    Google Scholar 

  140. Pérez-Fernández B, Mercader JV, Abad-Fuentes A, Checa-Orrego BI, Costa-García A, de la Escosura-Muñiz A (2020) Direct competitive immunosensor for Imidacloprid pesticide detection on gold nanoparticle-modified electrodes. Talanta 209:120465

    Article  PubMed  CAS  Google Scholar 

  141. Petryayeva E, Algar WR (2013) Proteolytic assays on quantum-dot-modified paper substrates using simple optical readout platforms. Analy Chem 85(18):8817–8825

    Article  CAS  Google Scholar 

  142. Petsas AS, Vagı MC (2017) Determination of pesticides residues in food of vegetal origin: Sample preparation, chromato-graphic techniques and applications. In 15th international conference on environmental science and technology rhodes, Greece, pp. 1–5.

  143. Pimentel D (2009) Pesticides and pest control. In: Integrated pest management: innovation-development process. Springer, pp 83–87

  144. Pirogov AV, Shpigun OA (2020) Application of microemulsions in liquid chromatography and electrokinetic methods of analysis: advantages and disadvantages of the approach. J Anal Chem 75:139–147

    Article  CAS  Google Scholar 

  145. Poole CF (2004) Gas chromatography—detectors. Encyclopedia of analytical science, 2nd edn. Elsevier Inc, New York, pp 95–105

    Google Scholar 

  146. Płaza G, Ulfig K, Tien AJ (2000) Immunoassays and environmental studies. Pol J Environ Studies 9:231–236

    Google Scholar 

  147. Podhorniak LV, Negron JF, Griffith FD (2001) Gas chromatography with pulsed flame photometric detection multiresidue method for organophosphate pesticide and metabolite residues at the parts-per-billion level in representative commodities of fruit and vegetable crop groups. J of AOAC Intern 84(3):873–890

    Article  CAS  Google Scholar 

  148. Pundir CS, Chauhan N (2012) Acetylcholinesterase inhibition-based biosensors for pesticide determination: a review. Anal Bioch 429(1):19–31

    Article  CAS  Google Scholar 

  149. Qi Y, Chen Y, Xiu F-R, Hou J (2020) An aptamer-based colorimetric sensing of acetamiprid in environmental samples: Convenience, sensitivity and practicability. Sens Actuators B: Chem 304:127359

  150. Quintás G, Armenta S, Garrigues S, de la Guardia M (2008) Towards minimization of chlorinated solvents consume in Fourier transform infrared spectroscopy determination of Propamocarb in pesticide formulations. Talanta 75(2):339–343

    Article  PubMed  CAS  Google Scholar 

  151. Raja PMV, Barron AR (2021) Principles of gas chromatography. Rice University. https://chem.libretexts.org/@go/page/55860

  152. Rawtani D, Khatri N, Tyagi S, Pandey G (2018) Nanotechnology-based recent approaches for sensing and remediation of pesticides. J of Enviro Manag 206:749–762

    Article  CAS  Google Scholar 

  153. Sakamoto S, Putalun W, Vimolmangkang S, Phoolcharoen W, Shoyama Y, Tanaka H, Morimoto S (2018) Enzyme-linked immunosorbent assay for the quantitative/qualitative analysis of plant secondary metabolites. J Nat Med 72(1):32–42

    Article  CAS  PubMed  Google Scholar 

  154. Sarrut M, Corgier A, Crétier G, Le Masle A, Dubant S, Heinisch S (2015) Potential and limitations of on-line comprehensive reversed phase liquid chromatography×supercritical fluid chromatography for the separation of neutral compounds: an approach to separate an aqueous extract of bio-oil. J Chromatogr A 1402:124–133

    Article  CAS  PubMed  Google Scholar 

  155. Samsidar A, Siddiquee S, Shaarani SM (2018) A review of extraction, analytical and advanced methods for determination of pesticides in environment and foodstuffs. Trends in Food Sci Technol 71:188–201

    Article  CAS  Google Scholar 

  156. Sánchez MT, Flores-Rojas K, Guerrero JE, Garrido-Varo A, Pérez-Marín D (2010) Measurement of pesticide residues in peppers by near-infrared reflectance spectroscopy. Pest Manag Sci Form Pesti Sci 66(6):580–586

    Article  CAS  Google Scholar 

  157. Sanjoh A, Tsukihara T (1999) Spatiotemporal protein crystal growth studies using microfluidic silicon devices. J Cryst Grow 196(2–4):691–702

    Article  CAS  Google Scholar 

  158. Santiago M, Strobel S (2013) Thin layer chromatography. Methods Enzy 533(303):324

    Google Scholar 

  159. Saranwong I, Kawano S (2005) Rapid determination of fungicide contaminated on tomato surfaces using the DESIR-NIR: a system for ppm-order concentration. J Near Infrared Spectrosc 13(3):169–175

    Article  CAS  Google Scholar 

  160. Sato-Berrú RY, Medina-Valtierra J, Medina-Gutiérrez C, Frausto-Reyes C (2004) Quantitative NIR–Raman analysis of methyl-parathion pesticide microdroplets on aluminum substrates. Spectrochim Acta Part A Mol Biomol Spectrosc 60(10):2231–2234

    Article  CAS  Google Scholar 

  161. Savant RH, Banerjee K, Utture SC, Patil SH, Dasgupta S, Ghaste MS, Adsule PG (2010) Multiresidue analysis of 50 pesticides in grape, pomegranate, and mango by gas chromatography—ion trap mass spectrometry. J Agric Food Chem 58(3):1447–1454

    Article  CAS  PubMed  Google Scholar 

  162. Shan R, ChenY ML, Li H, Zhao Z, Gao M, Sun X (2020) Rapid prediction of atrazine sorption in soil using visible near-infrared spectroscopy. Spectrosc Acta Part A Mol Biomol Spect 224:117455

    Article  CAS  Google Scholar 

  163. Shen F, Yan ZK, Ye ZZ, Ying YB (2009) Application of Near-infrared spectroscopy to detection of pesticide phoxim residues. Spect Spectral Anal 29(9):2421–2424

    CAS  Google Scholar 

  164. Sherma J (1971) Paper chromatography. Paper chromatography and electrophoresis. Elsevier, New York, pp 90–109

    Chapter  Google Scholar 

  165. Si F, Zou R, Jiao S, Qiao X, Guo Y, Zhu G (2018) Inner filter effect-based homogeneous immunoassay for rapid detection of imidacloprid residue in environmental and food samples. Ecotoxicol Environ Safe 148:862–868

    Article  CAS  Google Scholar 

  166. Sicard C, Glen C, Aubie B, Wallace D, Jahanshahi-Anbuhi S, Pennings K, Filipe CD (2015) Tools for water quality monitoring and mapping using paper-based sensors and cell phones. Water Resear 70:360–369

    Article  CAS  Google Scholar 

  167. Stanczyk FZ, Clarke NJ (2010) Advantages and challenges of mass spectrometry assays for steroid hormones. J Steroid Biochem Mol Biol 121(3–5):491–495

    Article  CAS  PubMed  Google Scholar 

  168. Sun X, Xia K, Liu B (2008) Design of fluorescent self-assembled multilayers and interfacial sensing for organophosphorus pesticides. Talanta 76(4):747–751

    Article  CAS  PubMed  Google Scholar 

  169. Sun Z, Tian L, Guo M, Xu X, Li Q, Weng H (2017) A double-film screening card for rapid detection of organophosphate and carbamate pesticide residues by one step in vegetables and fruits. Food Control 81:23–29

    Article  CAS  Google Scholar 

  170. Taheri N, Lan M, Wei P, Liu R, Gui W, Guo Y, Zhu G (2016) Chemiluminescent enzyme immunoassay for rapid detection of three α-cyano pyrethroid residues in agricultural products. Food Anal Methods 9(10):2896–2905

    Article  Google Scholar 

  171. Thomas MR, Hutton S (2000) Guidelines for the collection of statistics on the usage of plant protection products within agriculture and horticulture. Ministry of Agriculture, Fisheries and Food, Central Science Laboratory, Sand Hutton York, UK. YO4 1LZ. On Behalf of The Eurostat Pestic Statist Task Force, pp. 1–38

  172. Thurman EM, Goolsby DA, Meyer MT, Mills MS, Pomes ML, Kolpin DW (1992) A reconnaissance study of herbicides and their metabolites in surface water of the midwestern United States using immunoassay and gas chromatography/mass spectrometry. Environ Sci Technol 26(12):2440–2447

    Article  CAS  Google Scholar 

  173. Timchenko YV (2021) Advantages and disadvantages of high-performance liquid chromatography (HPCL). J Environ Anal Chem 8(10):335

    Google Scholar 

  174. Tsagkaris AS, Pulkrabova J, Hajslova J (2021) Optical screening methods for pesticide residue detection in food matrices: advances and emerging analy trends. Foods 10(1):88

    Article  CAS  PubMed Central  Google Scholar 

  175. Velkoska-Markovska L, Petanovska-Ilievska B, Markovski A (2018) Application of high performance liquid chromatography to the analysis of pesticide residues in apple juice. Contemp Agric. https://doi.org/10.2478/contagri-2018-0014

    Article  Google Scholar 

  176. Visentainer JV, Claus T, Santos O Jr, Chiavelli LU, Maruyama SA (2014) Analytical aspects of the flame ionization detection in comparison with mass spectrometry with emphasis on fatty acids and their esters. InTech, London, pp 39–56

    Google Scholar 

  177. Walorczyk S, Drożdżyński D (2012) Improvement and extension to new analytes of a multi-residue method for the determination of pesticides in cereals and dry animal feed using gas chromatography–tandem quadrupole mass spectrometry revisited. J Chromatogr A 1251:219–231

    Article  CAS  PubMed  Google Scholar 

  178. Walorczyk S, Kopeć I, Szpyrka E (2016) Pesticide residue determination by gas chromatography-tandem mass spectrometry as applied to food safety assessment on the example of some fruiting vegetables. Food Anal Methods 9(5):1155–1172

    Article  Google Scholar 

  179. Wall PE (2007) Thin-layer chromatography: a modern practical approach. Royal Society of Chemistry

    Google Scholar 

  180. Wang J, Leung D (2009) Applications of ultra-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry on analysis of 138 pesticides in fruit-and vegetable-based infant foods. J Agric Food Chem 57(6):2162–2173

    Article  CAS  PubMed  Google Scholar 

  181. Wang Y, Li-Ying J (2014) When does inward technology licensing facilitate firms' NPD performance? A contingency perspective. Technovation 34(1):44–53

  182. Wang J, Wang Z, Liu J, Li H, Li QX, Li J, Xu T (2013a) Nanocolloidal gold-based immuno-dip strip assay for rapid detection of Sudan red I in food samples. Food Chem 136(3–4):1478–1483

    Article  CAS  PubMed  Google Scholar 

  183. Wang S, Ge L, Li L, Yan M, Ge S, Yu J (2013b) Molecularly imprinted polymer grafted paper-based multi-disk micro-disk plate for chemiluminescence detection of pesticide. Biosens Bioelectron 50:262–268

    Article  CAS  PubMed  Google Scholar 

  184. Wang K, Huang M, Chen J, Lin L, Kong L, Liu X, Lin M (2018) A “drop-wipe-test” SERS method for rapid detection of pesticide residues in fruits. J Raman Spectrosc 49(3):493–498

    Article  CAS  Google Scholar 

  185. Wang L, Chen W, Xu D, Shim BS, Zhu Y, Sun F, Kotov NA (2009) Simple, rapid, sensitive, and versatile SWNT− paper sensor for environmental toxin detection competitive with ELISA. Nano Lett 9(12):4147–4152

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. Wang L, Ma W, Xu L, Chen W, Zhu Y, Xu C, Kotov NA (2010) Nanoparticle-based environmental sensors. Mater Sci Eng R Rep 70(3–6):265–274

    Article  CAS  Google Scholar 

  187. Willner MR, Vikesland PJ (2018) Nanomaterial enabled sensors for environmental contaminants. J of Nanobiotechn 16(1):1–16

    Article  CAS  Google Scholar 

  188. Xu F, Yu JY, Wang QS, Fu Y, Zhang H, Wu YL (2019) Simultaneous determination of 25 pesticides in Zizania latifolia by dispersive solid-phase extraction and liquid chromatography-tandem mass spectrometry. Sci Rep 9(1):1–8

    Google Scholar 

  189. Yang N, Wang P, Xue CY, Sun J, Mao HP, Oppong PK (2018) A portable detection method for organophosphorus and carbamates pesticide residues based on multilayer paper chip. J Food Process Eng 41(8):e12867

    Article  CAS  Google Scholar 

  190. Zamora-Sequeira R, Starbird-Pérez R, Rojas-Carillo O, Vargas-Villalobos S (2019) What are the main sensor methods for quantifying pesticides in agricultural activities? A review. Molecules 24(14):2659

    Article  CAS  PubMed Central  Google Scholar 

  191. Zhang Y, Zuo P, Ye B-C (2015) A low-cost and simple paper-based microfluidic device for simultaneous multiplex determination of different types of chemical contaminants in food. Biosens Bioelectron 68:14–19

    Article  CAS  PubMed  Google Scholar 

  192. Zhang Z, Li P, Hu X, Zhang Q, Ding X, Zhang W (2012) Microarray technology for major chemical contaminants analysis in food: Current status and prospects. Sensors 12(7):9234–9252

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  193. Zhang Z, Liu JF, Shao B, Jiang GB (2010) Time-resolved fluoroimmunoassay as an advantageous approach for highly efficient determination of sulfonamides in environmental waters. Environ Sci Technol 44(3):1030–1035

    Article  CAS  PubMed  Google Scholar 

  194. Zhou W, Gao X, Liu D, Chen X (2015) Gold nanoparticles for in vitro diagnostics. Chem Rev 115(19):10575–10636

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Zweig G (2013) Insecticides: analytical methods for pesticides, plant growth regulators, and food additives, vol 2. Academic Press, Cambridge

    Google Scholar 

Download references

Acknowledgements

The authors are grateful and thankful to the University of the Free State, South Africa, Tanta University, Egypt, Universidad Autónoma de Nuevo León, Mexico, and Alexandria University, Egypt, for the completion of this project.

Funding

The authors declare that there is no funding involved in this project.

Author information

Authors and Affiliations

Authors

Contributions

SG contributed to conceptualization, data curation, investigation, methodology, writing—original draft, writing—review and editing, supervision, and validation. SSA helped in data curation, writing—original draft, writing—review and editing, and validation. CB and WA performed visualization and writing—review and editing. AMH was involved in writing—original draft and writing—review and editing. AEB, MHA, MBK, and EAM contributed to writing—review and editing. HB performed conceptualization, writing—original draft, and writing—review and editing.

Corresponding author

Correspondence to Soumya Ghosh.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that there are no competing interests involved in this project.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ghosh, S., AlKafaas, S.S., Bornman, C. et al. The application of rapid test paper technology for pesticide detection in horticulture crops: a comprehensive review. Beni-Suef Univ J Basic Appl Sci 11, 73 (2022). https://doi.org/10.1186/s43088-022-00248-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43088-022-00248-6

Keywords

  • Rapid detection
  • Nano-particle
  • Pesticide residue