Next Article in Journal
Possibility of Human Gender Recognition Using Raman Spectra of Teeth
Previous Article in Journal
Protein Denaturation Through the Use of Magnetic Molecularly Imprinted Polymer Nanoparticles
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

The Existing Methods and Novel Approaches in Mycotoxins’ Detection

Biohazard Prevention Centre, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland
Military Institute of Armament Technology, Prymasa Stefana Wyszyńskiego 7, 05-220 Zielonka, Poland
CBRN Reconnaissance and Decontamination Department, Military Institute of Chemistry and Radiometry, Antoniego Chrusciela “Montera” 105, 00-910 Warsaw, Poland
Author to whom correspondence should be addressed.
Molecules 2021, 26(13), 3981;
Submission received: 22 May 2021 / Revised: 23 June 2021 / Accepted: 28 June 2021 / Published: 29 June 2021


Mycotoxins represent a wide range of secondary, naturally occurring and practically unavoidable fungal metabolites. They contaminate various agricultural commodities like cereals, maize, peanuts, fruits, and feed at any stage in pre- or post-harvest conditions. Consumption of mycotoxin-contaminated food and feed can cause acute or chronic toxicity in human and animals. The risk that is posed to public health have prompted the need to develop methods of analysis and detection of mycotoxins in food products. Mycotoxins wide range of structural diversity, high chemical stability, and low concentrations in tested samples require robust, effective, and comprehensible detection methods. This review summarizes current methods, such as chromatographic and immunochemical techniques, as well as novel, alternative approaches like biosensors, electronic noses, or molecularly imprinted polymers that have been successfully applied in detection and identification of various mycotoxins in food commodities. In order to highlight the significance of sampling and sample treatment in the analytical process, these steps have been comprehensively described.

1. Introduction

Mycotoxins are low molecular mass (MW ~700 Da) secondary metabolites of filamentous fungi which are harmful to human and animal health [1]. More than 400 different mycotoxins with various chemical structures and properties produced by a wide variety of fungal species, have been identified [2]. The main genera of mycotoxigenic fungi are: Aspergillus, Fusarium, Penicillium, Alternaria, Claviceps, and Stachybotrys [3]. Among the mycotoxins, aflatoxins (AFs), ochratoxin A (OTA), zearalenone (ZEA), patulin (PAT), fumonisins (FUMs), and trichothecenes (TCs) like deoxynivalenol (DON) and T-2 toxin (T-2) are the most concerning [4,5]. Many agricultural commodities such as wheat, barley, maize, oat, rice [2], vegetables, fruits [6] are contaminated with mycotoxins. Mycotoxins can also contaminate herbs [7,8], spices [9,10], and beverages like: wine, fruit juices, beer [11], and milk [12,13]. Different factors can influence processes of growth and production of mycotoxins in various fungi species. These include environment, temperature, humidity, water activity (aw), pH, nutrients, substrate nature, level of inoculation, physiological state, and microbial interactions [14]. Toxin formation can occur on the field, during processing, packaging, distribution, and storage of agricultural commodities or food processing [15]. The occurrence of mycotoxin contamination is more frequent in food and feed produced in developing countries due to their climate, poor production technologies, and crops storage conditions [16]. A large number of mycotoxins are chemically and thermally stable during food processing, including milling, boiling, baking, roasting, frying, and pasteurization [17]. Mycotoxins are characterized by a wide range of toxic properties. Depending on the dose or exposure duration, severe immediate reactions or long-term effects may occur [3]. Mycotoxins are associated with toxicities, such as hepatotoxicity [18], nephrotoxicity [19], genotoxicity [20], neurotoxicity, and immunosuppression [21]. Moreover, the International Agency for Research on Cancer (IARC) classified aflatoxin B1 (AFB1) in Group 1 (carcinogenic to humans), and OTA in Group 2B (possibly carcinogenic to humans) [22]. Due to these facts, their presence in food can pose a risk to human health and life. However mycotoxins are natural contaminants and their presence in food are unavoidable [23].
National and international institutions and organizations, like the US Food and Drug Administration (FDA), the European Commission (EC), the Food and Agriculture Organization of the United Nations (FAO), and the World Health Organization (WHO), have identified potential health hazards to humans and animals associated with food- or feed-borne mycotoxin intoxication and tackled this problem by developing regulatory limits for main mycotoxin classes and selected individual mycotoxins [24]. The FDA has prepared guidance documents [25] and booklet lists [26] for mycotoxins such as DON and AFs in food and feed. The EC has compiled comprehensive regulations regarding the maximum level for mycotoxins in different foodstuff [27]. The FAO has developed extensive worldwide regulations for mycotoxins in food and feed [28]. Additionally, in the eighty-third report of the Joint FAO/WHO Expert Committee on Food Additives fumonisins and AFs as food contaminants have been widely evaluated in terms of their toxicology, exposure, and daily limits [29].
All of these efforts to establish mycotoxins limits and standards have induced the development of various analysis methods for the identification and quantification of mycotoxins in food samples [24]. Methods that have been validated and applied in the analysis of mycotoxins in agricultural commodities include: chromatographic techniques, immunoassay-based methods, or rapid strip screening tests [30]. Although great progress has been made in this area, there are still significant challenges and disadvantages to these analytical methods that should be addressed. The chemical diversity and co-occurrence of mycotoxins, their different concentrations in agricultural products and complex food matrices with mycotoxin contamination require special extraction, clean-up, and detection methods [31]. Continuous improvements in mycotoxin analytical methodology are needed to comply with mycotoxin legislation, restrictions, and to protect consumer health and support the agriculture [32].
This review summarizes the used methods and novel innovative techniques applied for mycotoxins detection and analysis in a variety of foods. In addition, a brief presentation of extraction methodologies and clean-up procedures are included.

2. Food Sampling and Sample Preparation

The determination of mycotoxins in food samples is preceded by several different steps such as sampling and sample preparation. Sample preparation includes extraction and clean-up. Both are crucial and cannot be separated from each other. Appropriate performance of all these steps enables a proper mycotoxins ascertainment [33].

2.1. Sampling

Sampling is significant in determination of mycotoxin levels because mycotoxigenic fungi do not grow even on the substrate and it is difficult to obtain a representative bulk sample. Moreover, the existing mycotoxin contaminations in natural samples are not homogeneous [30]. Therefore, apart from liquid food samples such as milk or certain highly processed foods like peanut butter, traditional food sampling methods are usually not suitable for mycotoxin analysis [34]. In order to standardize the sampling procedures for mycotoxin analysis, Commission Regulation (EC) No. 401/2006 [35] specified the sampling and analysis methods for the official control of the mycotoxins levels in foodstuffs [36]. The example is the cereals and cereal products sampling method for lots <50 tons, where sampling plan shall be used with 10 to 100 incremental samples, depending on the weight, resulting in an aggregate sample of 1 to 10 kg [35]. Inadequate sampling is associated with errors in the evaluation of the mycotoxin level of the lot could easily occur, usually leading to an underestimation. If sampling is performed for monitoring/surveillance purposes, poor sampling could give false information for risk assessors/managers. For inspection purposes, incorrect sampling can cause problems in litigations [37].

2.2. Grinding and Mixing

In order to accelerate the chemical reaction process of extraction and to increase the chances to detect the mycotoxins, the sample should be ground to the final particle size of approximately 500 µm opening size and homogenized to whole wheat flour or powder-like consistency [35,38]. Once homogeneity is obtained, the sample should be mixed. According to the conducted research and techniques comparison, the slurry mixing process appears to be a good option. This process resulted in very small particles size and consequently homogeneous samples with the lowest variation ratio [39].

2.3. Extraction and Purification

Extraction from contaminated food and feed samples aims to remove mycotoxins from the sample using appropriate solvents. It is the first step of sample preparation. QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method was initially developed for pesticide analysis, but it facilitates a simultaneous detection of different groups of mycotoxins in various matrices [40]. This method firstly requires an extraction with acetonitrile water, followed by liquid–liquid partitioning induced by the addition of inorganic salts. As a consequence, some polar components of the matrix remain in the aqueous layer, while mycotoxins are moved into the organic phase. Next, a dispersive solid phase extraction is applied to reduce other matrix compounds from the organic phase [41]. QuEChERS has been used for the analysis of different mycotoxins in numerous food matrices such as OTA, AFs, and citrinin in eggs [42], OTA and AFs in cereals [43], and in berries-derived jam and juice [44]. Next extraction method is liquid–liquid extraction (LLE) that is based on the different toxin solubility in aqueous phase and in immiscible organic phase. The compound extraction is placed into one solvent leaving the remainder of the matrix in the other [45]. LLE has been applied for the simultaneous analysis of AFs and OTA in breast milk [46]. Liquid–solid extraction (SLE) is a simple method for the mycotoxin’s extraction from solid matrices of various consistency. The extraction is based on the weighing of homogenized sample, and adding the extraction solvent, followed by agitating it in a shaker [47]. It has been confirmed that this method can be used to extract various mycotoxins from cereals [48]. Pressurized Liquid Extraction (PLE), also known as accelerated solvent extraction (ASE), is the same method as SLE but performed under increased pressure and temperature in a pressure-resistant vessel [49,50]. In these methods, conventional solvents at high temperatures (100–180 °C) and pressures (1500–2000 psi) are used to improve the extraction of analytes from the matrix [51]. PLE has been used to detect mycotoxins produced by Alternaria alternata in a tomato sample [50]. The next method is the Supercritical Fluid Extraction (SFE). SFE can minimize and eliminate the use of organic solvents by application of supercritical CO2. The SFE procedure is mostly used for the extraction of non-polar organic molecules [47] and has been carried in ZEA detection in maize flour [52]. All extraction methods, solvents, advantages, and disadvantages are summarized in Table 1.
Table 1. Extraction methods, solvent, advantages, and disadvantages.
Table 1. Extraction methods, solvent, advantages, and disadvantages.
QuEChERSAcetonitrile, acetonitrile/acetic acid, acetonitrile/citric acid, acetonitrile/formic acidFast, simple, economical, reproducibility and applicabilityLow enrichment factor in extracts of lipophilic compounds and the need for original modifications of the procedure[53,54,55]
LLEHexane, cyclohexaneEffective for small-scale preparationsDoes not provide a sufficiently clean analyte in all cases, time-consuming, possible loss of sample by adsorption onto the glassware[45,49,56]
SLEAcetonitrile/water, methanol/waterSmaller volumes of solventSLE alone can be not satisfactory to extract some mycotoxins without interference and additional purification steps are usually needed[47,49]
Extraction process can be automated, higher extraction efficiency in shorter time, lower amount of extraction solventHigh instrument price[47,49,57]
SFEsupercritical CO2 fluid, acetonitrileFast, small solvent volumes, extraction of temperature sensible analytesLow recoveries, high concentrations of co-extracts, high costs[45,49]
Extraction is required to release the mycotoxins from the matrix. Clean-up of the extract is crucial to reduce matrix effects and eliminate substances, which can interfere with the next mycotoxin detection. Purification of the extract increases specificity and sensitivity, resulting in improvement of quantification accuracy and precision. The most commonly used methods for mycotoxins clean-up are solid phase extraction (SPE) and immunoaffinity columns (IAC), because they are rapid, efficient, and reproducible with a wide range of selectivity [34,51]. The SPE method involves the solid absorbents (where the mycotoxins are absorbed), which are usually packed in cartridges and rinsed in order to remove contaminants and capture the mycotoxins [58]. SPE is a rapid, efficient, and reproducible technique, but it presents some limitations, like the inability to use a single cartridge for all mycotoxins detection. Moreover, efficiency can be affected by several conditions, such as: the type of solvent, or the pH and ionic strength of the sample [59]. For commercial SPE, octadecylsilyl (C18), hydrophilic–lipophilic balance (HLB), amino-propyl (NH2) and silica gel can be used as adsorbent, but the majority of the commercial cartridges are not appropriate for high-throughput screening for multiclass mycotoxins [60,61]. Recently, carbon nanomaterial and magnetic carbon nanomaterial have been applied as alternative sorbent due to their strong absorption capacities. Among them, multi-walled carbon nanotubes (MWCNTs) were used for simultaneous determination of type A trichothecenes in rice, maize, and wheat [62]. What is more, multi-walled carbon nanotube-magnetic nanoparticles (MWCNT-MNPs) were introduced as sorbents for purification of ZEA in maize [63] and type A trichothecenes in coix [64].
In the case of IAC, monoclonal antibodies are used for certain mycotoxins detection. The target mycotoxin in the extract is bound by specific antibodies on the column during the sample flow through the column. At the same time, water-soluble impurities are removed during column washing and the mycotoxins are eluted from the IAC with pure methanol or acetonitrile for the following detection. IACs are very sensitive, selective, and can serve as universal and valid purification tool for tracing the mycotoxins. Furthermore, it is a user-friendly and solvent-saving method because of the antibodies’ specificity [65]. However, some limitations are linked with this technique. Columns have a limited ability to absorb mycotoxins and if the contents of mycotoxins in the sample exceed the column binding capacity, the mycotoxin is not effectively capture and bound, resulting in unreliable results. What is more, the numerous components in the matrix can interfere with the antibodies [66]. Other disadvantages include organic solvents, which can denature or devitalize the antibodies leading to difficulties in the reuse of IACs. Moreover, the operating costs of this method are substantially high [65]. IAC has been successfully applied in simultaneous analysis of OTA, ZEA, and AFs in wheat bran [67], OTA, AFs, and Fusarium toxins in maize [68] and cereals [69].

3. Techniques Used in Detection and Analysis of Mycotoxins

Since the discovery of the first mycotoxins, many different methods have been tested and used to analyze mycotoxins presence in food and feed [70]. The dominance of chromatographic techniques is observed, mainly due to the use of many different types of chromatography: thin layer chromatography (TLC) and high performance liquid chromatography (HPLC) in combination with various detectors such as diode array, fluorescence, and UV. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS) have been also widely applied in mycotoxin detection [30,71]. When rapid mycotoxin analysis is required, immunoassay methods such as enzyme-linked immunosorbent assay (ELISA) [72,73] and lateral flow immunoassay (LFIA) [74,75] are also important. Biosensors also appear to be a useful tool for identifying mycotoxins in food [76,77].

3.1. Chromatography Techniques

3.1.1. TLC

A popular method of mycotoxin detection is TLC, which offers the possibility of economical screening of a large numbers of samples [78]. TLC is comprised of a stationary phase made of either alumina, silica, or cellulose, immobilized on an inert material like plastic or glass, which serves as a matrix. The mobile phase consists of methanol, acetonitrile, and water mixtures, that carry the sample in the solid stationary phase [79]. This method is effective for mycotoxins detection and some examples are listed in Table 2. Due to low costs, simplicity and fluorescent spots under UV light, it plays an important role in the analysis of many mycotoxins. This technique was developed for mycotoxin qualitative [80,81] and quantitative analysis [82,83,84]. However, TLC has low sensitivity and poor accuracy, which makes quantification very demanding [85]. Moreover, one of the main requirements is the sample preparation and the type of clean-up procedure, which strongly depends on the properties and the type of a mycotoxin [78].

3.1.2. Liquid Chromatography (LC)

In order to overcome the limitations of the TLC technique, like limited plate height or humidity and temperature effects, the LC methods have been developed [85]. LC enables the simultaneous determination of several mycotoxins, regardless of their chemical structure and biological activity. An analytical column and a mobile phase are used for separation between analytes and the matrix components. What is more, it is applied as a separation and determination technique for high polarity, non-volatile, and thermally labile mycotoxins [53].
Mycotoxin analysis heavily relies on HPLC with different adsorbents, depending on the mycotoxin physical and chemical structure. Majority of the protocols used in mycotoxins detection are very similar. The most common detectors used in HPLC are the UV-visible (UV) or fluorescent (FLD) ones, which rely on the presence of a chromophore in the molecules but also on MS (single mass spectrometry, and tandem MS (MS/MS)) [45]. Some toxins already have a natural fluorescence (e.g., AFs, OTA) and can be detected directly in HPLC-FLD. HPLC-FLD is most commonly used for the detection of OTA in various matrices e.g., rice [86]. For other types of mycotoxins, such as fumonisin B1 (FB1), which do not possess chromophores in their structure, derivatization is necessary [30]. Derivatization is used to add chromophores or fluorescent moieties to the analyte. The process can be performed either before the chromatographic analysis (precolumn derivatization) or after the column separation and before detection (post column derivatization) [87]. The main limitations of HPLC technique are portability and practical issues based on the matrix effect, sample type and preparation, and also calibration [85]. The use of HPLC in mycotoxin analysis has been described in many publications, which is summarized in Table 2.
The use of LC-MS/MS for the determination of low molecular weight contaminants and residues at trace levels has increased significantly over the past two decades. MS/MS in combination with LC provides better sensitivity and reliability. Therefore, LC-MS/MS is a good standard tool to deal with the analytical challenges, which exist in food and feed safety chemical analysis, both in research and in commercial investigation [88]. LC-MS/MS provides high selectivity and sensitivity, greater certainty of analytes identification and a wider range of matrices compared to traditional methods using conventional detectors [89]. Majority of mycotoxigenic fungi can produce several distinct mycotoxins simultaneously. Therefore, agricultural commodities can be simultaneously contaminated by different mycotoxins [90,91]. Studies have confirmed that, the LC-MS/MS provides one of the most reliable and sensitive results for simultaneous determination of multi-mycotoxins analysis [92,93,94,95]. The examples are summarized in Table 2.

3.1.3. Gas Chromatography (GC)

GC depends on differential partitioning of analytes between the two phases of GC column. The various chemical components in the sample distribute themselves between the stationary and mobile phases. After the separation process, volatile products are detected using a mass spectrometer, an electron capture detector (ECD) or flame ionization detector (FID) [85]. GC is rarely used in the mycotoxins’ analysis due to the low volatility and high polarity of analytes. Furthermore, the derivatization step is required for their conversion in volatile derivatives [34]. However, the GC-MS/MS method has been used for mycotoxins detection in milled grain-based products [96] and wheat semolina [97]. The examples are also listed in Table 2. The technique is highly sensitive and specific to mycotoxins and can be derivatized to a compound, which is sufficiently volatile for use in gas chromatography. The major problems in mycotoxin GC analysis are: column blockage, drifting responses, cross contamination from earlier samples and nonlinearity of calibration curves in some types of detectors [85].
Table 2. Chromatography techniques used in mycotoxin detection.
Table 2. Chromatography techniques used in mycotoxin detection.
TechniqueMycotoxinFood CommodityLODLOQReferences
TLCPATApple juice14 µg/L-[98]
TLCAFB1Herbs0.01 µg /mL-[99]
TLCAFsBrazil nuts-2000 µg/kg[83]
HPLCDONWheat bran12.58 µg/kg-[67]
HPLCOTAWheat bran0.40 µg/kg-[67]
HPLCOTAWine0.09 μg/L-[100]
HPLCZEAWheat bran6.74 µg/kg-[67]
HPLCAFB1Peanut0.10 µg/kg-[101]
HPLCZEAWheat flour0.10 µg/kg-[101]
LC-MS/MSAFsWalnut kernel0.004–0.013 µg/kg-[102]
LC-MS/MSAFB1Animal feed0.72 µg/kg-[94]
LC-MS/MSFB1Maize1 µg/kg-[94]
LC-MS/MST-2Beer0.001 µg/mL-[95]
LC-MS/MSDONRed wine0.001 µg/mL-[95]
LC-MS/MSAFB1Cow milk0.00002 µg/mL-[93]
LC-MS/MSZEACow milk0.00051 µg/mL-[93]
GC-MS/MST-2Wheat-based cereals-5 µg/kg[96]
GC-MS/MSPATRice-based cereals-10 µg/kg[96]
GC-MS/MSZEAMaize-based cereals-10 µg/kg[96]
GC-MS/MSDONWheat semolina-1.25 µg/kg[97]
GC-MS/MSDASWheat semolina-5 µg/kg[97]

3.2. Rapid Technologies

3.2.1. ELISA

In addition to the sensitive but complex and costly chromatographic techniques, immunochemical methods such as ELISA are fast and simple screening techniques for on-site mycotoxin analysis [16,103]. ELISA is simple in design, enables simultaneous testing of multiple samples and its detection is precise [72,104]. It is a high-throughput assay with low sample volume requirements and less clean-up procedures compared to chromatographic methods such as HPLC or TLC [85]. The test is based on the interaction of the antigen-antibody complex with the presence of chromogenic substrates. The measurable result is obtained by spectrophotometric assessment [105]. ELISA technique has been widely used in mycotoxins detection in various types of food, as summarized in Table 3. Solcan et al., have also used ELISA to determine residues of AFB1 from chicken liver samples [106]. However, this technique has some disadvantages. Compounds with similar chemical groups can interact with the antibodies. The result of matrix effect or matrix interference that occurs in ELISA method may lead to under- or overestimation of mycotoxin concentrations in tested samples [107]. Moreover, inadequate ELISA validation, limits the technique to the matrices for which they have been validated [108]. Therefore, a comprehensive study of ELISA accuracy is needed for a wide range of food commodities [109].
Table 3. ELISA method used in the detection and of mycotoxins in various types of food.
Table 3. ELISA method used in the detection and of mycotoxins in various types of food.
Type of ELISAMycotoxinFood CommoditiesLODReferences
Direct ELISAAFB1Wheat0.05 µg/kg[108]
AFB20.04 µg/kg
AFG10.06 µg/kg
AFG20.07 µg/kg
Competitive ELISAOTAWhite tea3.7 µg/kg[110]
Red tea3.7 µg/kg
Spearmint1.1 µg/kg
ZEAWhite tea8.3 µg/kg
Red tea4.5 µg/kg
Spearmint2.1 µg/kg
Competitive ELISAFUMsMaize30 µg/kg[111]
DON70 µg/kg
Green ELISA based on the SSB-assisted aptamerAFB1Corn0.112 µg/L[112]
OTA0.319 µg/L
ZEA0.377 µg/L
Competitive ELISAOTACorn1.9 ppb[113]
Barley2.8 ppb
Wheat3.5 ppb
Green coffee3.3 ppb
Soybeans2.5 ppb

3.2.2. Lateral Flow Immunoassay (LFIA)

LFIA, also called immunochromatographic strip test is a membrane-based immunoassay and works as a competitive method, using a labeled antibody as a signal reagent [114]. In the test, capillary beds, like pieces of porous paper drive the analyte and specific recognition elements bind moieties immobilized on the membrane surface [115]. The accuracy of LFIA mostly depends on signal labels. Traditionally, gold nanoparticles (GNPs) are the most widely used label to generate visual signals [116]. Besides nanoparticles, other materials such as magnetic nanoparticles (MNPs) [117], carbon nanoparticles (CNPs) [118], gold nanoparticles (AuNPs) [119], or quantum dots (QDs) [120] have been used as labels. Examples of different labels used for mycotoxins detection are presented in Table 4.
Table 4. Different labels used in mycotoxins detection and their sensitivity.
Table 4. Different labels used in mycotoxins detection and their sensitivity.
LabelMycotoxinFood CommoditySensitivityReferences
1 μg/kg
2.5 μg/kg
GNPsDASRice50 µg/kg[121]
GNPsFB1Cereals5 µg/L[122]
Maize1 µg/kg
13 µg/kg
20 µg/kg
CdSe/ZnS QDs + GNPsFUMsMaize62.5 µg/kg[120]
CdSe/CdS/ZnS QDsFB1+ FB2Maize2.8 µg/L[123]
LFIA has many advantages, such as simplicity, fast results, and low cost, and is suitable for large-scale on-site screening. Moreover, sample clean-up can be omitted [124]. The main limitations of LFD are the interferences that may occur. What is more, it is a complicated matrix for the determination of trace analytes [125].

3.2.3. Biosensors

In general, biosensors contain biological or biologically derived sensing element to detect specific bio-analytes integrated with a transducer in order to convert biological signal into an electrical signal [126]. Different types of transducers can be used for mycotoxin detection, including electrochemical (potentiometric, amperometric, and impedimetric), optical (surface plasmon resonance-SPR and fluorescence) and piezoelectric (quartz crystal microbalance-QCM) [127]. Commonly recognized materials are nucleic acids, peptides, enzymes, antibodies and cells, but other bioinspired elements like recombinant antibodies, aptamers, and molecularly imprinted polymers (MIPs) can also be used [128,129]. Furthermore, to improve the biosensors sensitivity, a wide variety of metal nanoparticles, carbon nanotubes (CNTs), nanofibers, and QDs are used due to their biocompatibility, physicochemical properties, and high surface volume ratio [130,131]. Various biosensors have been developed for different mycotoxins’ detection and are listed in Table 5.
The electrochemical biosensors are based on potentiometric, amperometric, and impedimetric detection methodologies [132]. The potentiometric sensor requires two (working and reference) or three (working, reference, and counter) electrode systems, and recognition event is provided by the changes in the circuit potential between working and reference electrodes [126,133]. The amperometric sensor, similarly to potentiometric requires two- or three-electrode system. The identification of an analyte by amperometric transducer is provided by the calculation of current data generated after the reduction and oxidation of electroactive species immobilized on the working surface after setting an appropriate potential [127]. Electrochemical impedance spectroscopy (EIS) method monitors the alterations that occur in the interface between electrode surface, modified by a nanostructured platform in contact with redox probe [134].
High sensitivity and real-time analysis are the main advantages of optical biosensors [135]. SPR and fluorescence approaches like fluorescence resonance energy transfer (FRET), are the main methods used [127]. The SPR system utilizes a thin metal (silver or gold) film between two transparent media with different refractive indices, like glass prism and sample solution. The SPR method detects alterations in the surface layer refractive index in contact with the sensor chip [136]. In the FRET system, the energy is transferred from excited donor fluorophore to nearby acceptor species [137]. The acceptor and donor in the FRET can be designed in biunique or one-to-multiple manners, ensuring the simultaneous application of multiple mycotoxin detection [127].
The QCM transducer consists of thin gold-plated crystal quartz, where electrodes are placed. A molecular recognition and binding event in the electrode surface lead to mass alteration and specific vibrations, when electric signal is sent by the quartz, which results in inducing alterations in the resonant frequency [127,138].
Table 5. Examples of biosensors used in different mycotoxin detection.
Table 5. Examples of biosensors used in different mycotoxin detection.
Recognition ElementTransducer/TechniqueMycotoxinFood CommodityDetection LimitReferences
AntibodyPiezoelectric/QCMAFB1Peanut 0.83 ng/kg [139]
AntibodyPiezoelectric/QCMOTARed wine 0.16 ng/mL [140]
AntibodyImpedimetric/EISAFB1Corn 0.05 ng/mL [141]
AntibodyOptical/SPROTACoffee 0.05 ng/mL [142]
AptamerImpedimetric/EISPATApple juice 2.8 ng/L [143]
AptamerOptical/FRETT-2Wheat, maize 0.00093 ng/mL [144]
AntibodyAmperometric/CV/DPVZEAMaize 0.00017 ng/mL [145]
AptamerImpedimetric/EISFB1Maize 2 pM [146]
Black phosphorenePotentiometric/DPVOTAGrape juice, red wine 180 ng/mL [147]
Rapid mycotoxin analysis share many common advantages, including speed, low costs, simplicity, and easy to use [109]. Important aspects include portability and multi-toxin detection. Mobility is also significant in face of the growing demand for on-site testing, which can take place, for example, on site of the food production process. The results are obtained relatively quickly, as the samples do not need to be shipped and analyzed at laboratories. It also prevents slowing down the food production process. Multi-toxin detection eliminates the need to perform multiple single-toxin tests for one sample batch [148]. The main limitations of these methods are matrix interference, antibody cross-reactivity, and the necessity of matrices’ validation [85].

3.3. Novel Technologies of Mycotoxins Analysis and Detection

In addition to the standard methods described above, there are several other methods that have been developed and may be useful in mycotoxin detection. Nevertheless, these methods have limited applicability and have not been widely used outside the research areas. Moreover, they require further verification and validation by recognized organizations such as the Association of Official Analytical Chemists (AOAC), International Organization for Standardization (ISO), or the European Standardization Committee (CEN) [34].

3.3.1. Electronic Nose

An electronic nose (e-nose) consists of a range of nonspecific chemical detectors, which capture different volatile organic compounds (VOCs) and detects qualitative volatile fingerprints of toxigenic fungi. After achieving a fingerprint, detection of the odor gives preliminary information about the category of the produced metabolites by a pattern recognition system [149]. E-nose technology for the fungal infection detection is based on identifying specific VOCs related to the growth of fungi on cereal grains. The growth and biochemical pattern of mycotoxigenic fungi species cause chemical changes in the VOCs’ composition and a correlation between VOCs and mycotoxin concentration in food can be observed [150]. The e-nose has been successfully used for detection of OTA in dry-cured meat [151], AFs and fumonisins in maize [150] and DON in wheat bran [152] and in durum wheat [153]. In order to achieve wide usage of e-nose in the detection of mycotoxins, optimization for the quantification of low levels of mycotoxins in food samples is necessary. Moreover, the majority of mycotoxins are non-volatile organic compounds that pose a problem for e-nose detection [34].

3.3.2. Fluorescent Polarization

Fluorescent polarization (FP) immunoassay is a method based on the competition between the analyte and the tracer (fluorophore labeled analyte) for specific antibody-binding sites. The binding of the tracer to the antibody has an impact on the rotation of the tracer molecule, increasing the fluorescence polarization value (Figure 1). The amount of bound tracer is inversely proportional to the amount of free analyte in the sample, resulting in the polarization value inversely proportional to the concentration of the analyte [154].
Some immunoassay methods like ELISA require steps like washing multiple times or the separation of free from antibody-bound analyte. In FP technique, the time-consuming pre-analytical steps are not necessary [155]. FP immunoassay has been applied in determinations of various mycotoxins in food commodities, such as ZEA in maize [156], DON in wheat-based products [157], AFB1 in maize [158], and OTA in rice [155]. However, FP method has limited sensitivity and accuracy compared to HPLC. This is likely due to the cross-reactivity of antibodies towards other fungal metabolites and food matrix component [34].

3.3.3. The Aggregation-Induced Emission

The aggregation-induced emission (AIE) is a photophysical phenomenon, in which a group of fluorescent dyes glows faintly in the dilute solution state, while their fluorescence is notably enhanced in the aggregation state (Figure 2) [159]. Intense dyes’ fluorescence may be the result of restricted intramolecular rotations in the aggregate state [160].
AIE dyes, which show high fluorescence emission in the aggregate states, are 9,10-distyrylanthracene (DSA), silacyclopentadiene (silole), tetraphenylethene (TPE), and their derivatives [161]. AIE dye-based aptasensor has been successfully developed for OTA detection in wine and coffee [159] and AFB1 in peanut oil and broad bean sauce [162].

3.3.4. Molecularly Imprinted Polymers

Molecularly imprinted polymers (MIPs) is a synthetic method, which is designed to mimic natural recognition entities like antibodies and biological receptors with specificities similar to antibody-antigen interactions (Figure 3) [163]. During molecular imprinting, cross-linked polymers are formed by free-radical co-polymerization of functional monomers and a cross-linker in the presence of an analyte (like mycotoxins) serving as template [164].
The advantages of MIP are primarily their high selectivity and affinity for the target molecule used in the imprinting procedure, their resistance, raised temperature and pressure, inertness to bases, acids, metal ions, and organic solvents. Moreover, their synthesis costs are low, the storage time can be very long, and the MIPs keep their recognition capacity for several years at room temperature [163,165]. MIPs have been developed for the analysis of AFB1 in wheat [166], OTA in beer and wine [167], ZEA in cereals [168,169], and offers a great potential for further development in mycotoxins’ detection [34].

4. Conclusions

Contamination of agricultural products by mycotoxins resulted in establishing their acceptable limits in food and in the development of sensitive and effective detection methods. A significant step in mycotoxin analysis is sample preparation and different extraction followed by purification protocols. The best extraction techniques should use a small amount of chemical solvent, good extraction efficiency, and be relatively fast. Although many analytical methods are continuously optimized and validated and many novel methods are still being developed, chromatographic techniques, especially the LC/MS-MS technique are an essential tool for the detection of numerous mycotoxins. Chromatographic techniques ensure high sensitivity and reliability, as well as enable the simultaneous detection of different mycotoxins, regardless of their chemical structure and biological activity. However, if mobility is needed and rapid on-site analysis is required, for example at a food production site, the use of immunoassay-based methods such as LFIA is a good option. In contrast to chromatographic techniques, no qualified personnel are needed, the tests are simple to use, and the costs are low. Recent advances in detection and analysis technology and the development of novel techniques such as electronic nose, aggregation-induced emission, fluorescent polarization, or molecularly imprinted polymers reveal new possibilities in mycotoxin determination and may, in the future, constitute additional or independent detection and analysis techniques.

Author Contributions

Conceptualization, M.B., M.S., M.C. and M.N.; supervision, M.B.; writing—original draft preparation E.J., M.N., L.G. and M.P.; writing—review and editing, M.B. and M.S. All authors have read and agreed to the published version of the manuscript.


Publication’s printing cost was co-financed by the European Union from the European Social Fund under the “InterDOC-STARt” project (POWR.03.02.00-00-I033/16-00).

Conflicts of Interest

The authors declare no conflict of interest.


  1. Liew, W.-P.-P.; Mohd-Redzwan, S. Mycotoxin: Its Impact on Gut Health and Microbiota. Front. Cell. Infect. Microbiol. 2018, 8, 60. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Palumbo, R.; Crisci, A.; Venâncio, A.; Cortiñas Abrahantes, J.; Dorne, J.-L.; Battilani, P.; Toscano, P. Occurrence and co-occurrence of mycotoxins in cereal-based feed and food. Microorganisms 2020, 8, 74. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Zain, M.E. Impact of mycotoxins on humans and animals. J. Saudi Chem. Soc. 2011, 15, 129–144. [Google Scholar] [CrossRef] [Green Version]
  4. Wokorach, G.; Landschoot, S.; Anena, J.; Audenaert, K.; Echodu, R.; Haesaert, G. Mycotoxin profile of staple grains in northern Uganda: Understanding the level of human exposure and potential risks. Food Control 2021, 122, 107813. [Google Scholar] [CrossRef]
  5. Abrunhosa, L.; Morales, H.; Soares, C.; Calado, T.; Vila-Chã, A.S.; Pereira, M.; Venâncio, A. A Review of Mycotoxins in Food and Feed Products in Portugal and Estimation of Probable Daily Intakes. Crit. Rev. Food Sci. Nutr. 2016, 56, 249–265. [Google Scholar] [CrossRef] [Green Version]
  6. Sanzani, S.M.; Reverberi, M.; Geisen, R. Mycotoxins in harvested fruits and vegetables: Insights in producing fungi, biological role, conducive conditions, and tools to manage postharvest contamination. Postharvest Biol. Technol. 2016, 122, 95–105. [Google Scholar] [CrossRef]
  7. Sedova, I.; Kiseleva, M.; Tutelyan, V. Mycotoxins in Tea: Occurrence, Methods of Determination and Risk Evaluation. Toxins 2018, 10, 444. [Google Scholar] [CrossRef] [Green Version]
  8. Ałtyn, I.; Twarużek, M. Mycotoxin Contamination Concerns of Herbs and Medicinal Plants. Toxins 2020, 12, 182. [Google Scholar] [CrossRef] [Green Version]
  9. Thanushree, M.P.; Sailendri, D.; Yoha, K.S.; Moses, J.A.; Anandharamakrishnan, C. Mycotoxin contamination in food: An exposition on spices. Trends Food Sci. Technol. 2019, 93, 69–80. [Google Scholar] [CrossRef]
  10. Potortì, A.G.; Tropea, A.; Lo Turco, V.; Pellizzeri, V.; Belfita, A.; Dugo, G.; Di Bella, G. Mycotoxins in spices and culinary herbs from Italy and Tunisia. Nat. Prod. Res. 2020, 34, 167–171. [Google Scholar] [CrossRef]
  11. Quintela, S. 5-Mycotoxins in Beverages: Occurrence, Regulation, Economic Impact and Cost-Effectiveness of Preventive and Removal Methods. In Safety Issues in Beverage Production; Grumezescu, A.M., Holban, A.M., Eds.; Academic Press: Cambridge, MA, USA, 2020; pp. 147–186. Available online: (accessed on 28 June 2021).
  12. Becker-Algeri, T.A.; Castagnaro, D.; de Bortoli, K.; de Souza, C.; Drunkler, D.A.; Badiale-Furlong, E. Mycotoxins in Bovine Milk and Dairy Products: A Review. J. Food Sci. 2016, 81, R544–R552. [Google Scholar] [CrossRef] [Green Version]
  13. Goncalves, L.; Dalla Rosa, A.; Gonzales, S.L.; Feltes, M.M.C.; Badiale-Furlong, E.; Dors, G.C. Incidence of aflatoxin M1 in fresh milk from small farms. Food Sci. Technol. 2017, 37, 11–15. [Google Scholar] [CrossRef] [Green Version]
  14. Agriopoulou, S.; Stamatelopoulou, E.; Varzakas, T. Advances in Occurrence, Importance, and Mycotoxin Control Strategies: Prevention and Detoxification in Foods. Foods 2020, 9, 137. [Google Scholar] [CrossRef]
  15. Karlovsky, P.; Suman, M.; Berthiller, F.; De Meester, J.; Eisenbrand, G.; Perrin, I.; Oswald, I.P.; Speijers, G.; Chiodini, A.; Recker, T.; et al. Impact of food processing and detoxification treatments on mycotoxin contamination. Mycotoxin Res. 2016, 32, 179–205. [Google Scholar] [CrossRef]
  16. Al-Jaal, B.; Salama, S.; Al-Qasmi, N.; Jaganjac, M. Mycotoxin contamination of food and feed in the Gulf Cooperation Council countries and its detection. Toxicon 2019, 171, 43–50. [Google Scholar] [CrossRef] [PubMed]
  17. Bullerman, L.; Bianchini, A. Stability of mycotoxins during food processing. Int. J. Food Microbiol. 2007, 119, 140–146. [Google Scholar] [CrossRef] [PubMed]
  18. Sun, L.-H.; Lei, M.-y.; Zhang, N.-Y.; Zhao, L.; Krumm, C.S.; Qi, D.-S. Hepatotoxic effects of mycotoxin combinations in mice. Food Chem. Toxicol. 2014, 74, 289–293. [Google Scholar] [CrossRef] [PubMed]
  19. Imaoka, T.; Yang, J.; Wang, L.; McDonald, M.G.; Afsharinejad, Z.; Bammler, T.K.; Van Ness, K.; Yeung, C.K.; Rettie, A.E.; Himmelfarb, J.; et al. Microphysiological system modeling of ochratoxin A-associated nephrotoxicity. Toxicology 2020, 444, 152582. [Google Scholar] [CrossRef] [PubMed]
  20. Ladeira, C. Chapter 20—Mycotoxins: Genotoxicity Studies and Methodologies. In Environmental Mycology in Public Health; Viegas, C., Pinheiro, A.C., Sabino, R., Viegas, S., Brandão, J., Veríssimo, C., Eds.; Academic Press: Amsterdam, The Netherlands, 2016; pp. 343–361. [Google Scholar] [CrossRef]
  21. Ratnaseelan, A.M.; Tsilioni, I.; Theoharides, T.C. Effects of Mycotoxins on Neuropsychiatric Symptoms and Immune Processes. Clin. Ther. 2018, 40, 903–917. [Google Scholar] [CrossRef]
  22. The International Agency for Research on Cancer. List of Classifications. Agents Classified by the IARC Monographs, Volumes 1–28. Available online: (accessed on 3 February 2021).
  23. Omotayo, O.P.; Omotayo, A.O.; Mwanza, M.; Babalola, O.O. Prevalence of Mycotoxins and Their Consequences on Human Health. Toxicol. Res. 2019, 35, 1–7. [Google Scholar] [CrossRef] [Green Version]
  24. Krska, R.; Schubert-Ullrich, P.; Molinelli, A.; Sulyok, M.; MacDonald, S.; Crews, C. Mycotoxin analysis: An update. Food Addit. Contam. Part A 2008, 25, 152–163. [Google Scholar] [CrossRef]
  25. The U.S. Food and Drug Administration. Guidance or Industry and FDA: Advisory Levels for Deoxynivalenol (DON) in Finished Wheat Products for Human Consumption and Grains and Grain By-Products Used for Animal Feed. Available online: (accessed on 3 February 2021).
  26. The U.S. Food and Drug Administration. Guidance for Industry: Action Levels for Poisonous or Deletorious Substances in Human Food and Animal Feed. Available online: (accessed on 3 February 2021).
  27. The European Commission. Commission Regulation (EC) No 1881/2006 of 19 December Setting Maximum Levels or Certain Contaminants in Foodstuff. Available online: (accessed on 3 February 2021).
  28. Food and Agriculture Organization of the United Nations. Worldwide Regulations for Mycotoxins in Food and Feed in 2003. Available online: (accessed on 3 February 2021).
  29. World Health Organization. Evaluation of Certain Contaminants in Food: Eighty-Third Report of the Joint FAO/WHO Expert Committee on Food Additives. Available online:;jsessionid=4E6EBA0A0F5160EC5DC55868695CF4E1?sequence=1 (accessed on 3 February 2021).
  30. Zhang, L.; Dou, X.-W.; Zhang, C.; Logrieco, A.F.; Yang, M.-H. A Review of Current Methods for Analysis of Mycotoxins in Herbal Medicines. Toxins 2018, 10, 65. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Hajslova, J.; Zachariasova, M.; Cajka, T. Analysis of Multiple Mycotoxins in Food. Methods Mol. Biol. 2011, 747, 233–258. [Google Scholar] [CrossRef] [PubMed]
  32. Stroka, J.; Maragos, C.M. Challenges in the analysis of multiple mycotoxins. World Mycotoxin J. 2016, 9, 847–861. [Google Scholar] [CrossRef]
  33. Tittlemier, S.A.; Cramer, B.; Dall’Asta, C.; Iha, M.H.; Lattanzio, V.M.T.; Maragos, C.; Solfrizzo, M.; Stranska, M.; Stroka, J.; Sumarah, M. Developments in mycotoxin analysis: An update for 2018–19. World Mycotoxin J. 2020, 13, 3–24. [Google Scholar] [CrossRef] [Green Version]
  34. Alshannaq, A.; Yu, J.-H. Occurrence, Toxicity, and Analysis of Major Mycotoxins in Food. Int. J. Environ. Res. Public Health 2017, 14, 632. [Google Scholar] [CrossRef] [Green Version]
  35. European, C. Commission Regulation (EC) No 401/2006 of 23 February 2006 laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs. Off. J. Eur. Union 2006, 70, 12–34. [Google Scholar]
  36. Commission, E.U. Commission Regulation (EU) No 519/2014 of 16 May 2014 amending Regulation (EC) No 401/2006 as regards methods of sampling of large lots, spices and food supplements, performance criteria for T-2, HT-2 toxin and citrinin and screening methods of analysis. Off. J. Eur. Union L 2014, 147, 29–43. [Google Scholar]
  37. Miraglia, M.; De Santis, B.; Minardi, V.; Debegnach, F.; Brera, C. The role of sampling in mycotoxin contamination: An holistic view. Food Addit. Contam. 2005, 22, 31–36. [Google Scholar] [CrossRef]
  38. Nakhjavan, B.; Ahmed, N.S.; Khosravifard, M. Development of an Improved Method of Sample Extraction and Quantitation of Multi-Mycotoxin in Feed by LC-MS/MS. Toxins 2020, 12, 462. [Google Scholar] [CrossRef]
  39. Spanjer, M.C.; Scholten, J.M.; Kastrup, S.; Jörissen, U.; Schatzki, T.F.; Toyofuku, N. Sample comminution for mycotoxin analysis: Dry milling or slurry mixing? Food Addit. Contam. 2006, 23, 73–83. [Google Scholar] [CrossRef] [PubMed]
  40. Pereira, V.L.; Fernandes, J.O.; Cunha, S.C. Comparative assessment of three cleanup procedures after QuEChERS extraction for determination of trichothecenes (type A and type B) in processed cereal-based baby foods by GC–MS. Food Chem. 2015, 182, 143–149. [Google Scholar] [CrossRef]
  41. González-Jartín, J.M.; Alfonso, A.; Rodríguez, I.; Sainz, M.J.; Vieytes, M.R.; Botana, L.M. A QuEChERS based extraction procedure coupled to UPLC-MS/MS detection for mycotoxins analysis in beer. Food Chem. 2019, 275, 703–710. [Google Scholar] [CrossRef] [PubMed]
  42. Frenich, A.G.; Romero-González, R.; Gómez-Pérez, M.L.; Vidal, J.L.M. Multi-mycotoxin analysis in eggs using a QuEChERS-based extraction procedure and ultra-high-pressure liquid chromatography coupled to triple quadrupole mass spectrometry. J. Chromatogr. A 2011, 1218, 4349–4356. [Google Scholar] [CrossRef]
  43. Desmarchelier, A.; Tessiot, S.; Bessaire, T.; Racault, L.; Fiorese, E.; Urbani, A.; Chan, W.-C.; Cheng, P.; Mottier, P. Combining the quick, easy, cheap, effective, rugged and safe approach and clean-up by immunoaffinity column for the analysis of 15 mycotoxins by isotope dilution liquid chromatography tandem mass spectrometry. J. Chromatogr. A 2014, 1337, 75–84. [Google Scholar] [CrossRef]
  44. Juan, C.; Mañes, J.; Font, G.; Juan-García, A. Determination of mycotoxins in fruit berry by-products using QuEChERS extraction method. LWT 2017, 86, 344–351. [Google Scholar] [CrossRef]
  45. Turner, N.W.; Subrahmanyam, S.; Piletsky, S.A. Analytical methods for determination of mycotoxins: A review. Anal. Chim. Acta 2009, 632, 168–180. [Google Scholar] [CrossRef]
  46. Andrade, P.D.; da Silva, J.L.G.; Caldas, E.D. Simultaneous analysis of aflatoxins B1, B2, G1, G2, M1 and ochratoxin A in breast milk by high-performance liquid chromatography/fluorescence after liquid–liquid extraction with low temperature purification (LLE–LTP). J. Chromatogr. A 2013, 1304, 61–68. [Google Scholar] [CrossRef] [PubMed]
  47. Xie, L.; Chen, M.; Ying, Y. Development of Methods for Determination of Aflatoxins. Crit. Rev. Food Sci. Nutr. 2016, 56, 2642–2664. [Google Scholar] [CrossRef]
  48. Rubert, J.; Dzuman, Z.; Vaclavikova, M.; Zachariasova, M.; Soler, C.; Hajslova, J. Analysis of mycotoxins in barley using ultra high liquid chromatography high resolution mass spectrometry: Comparison of efficiency and efficacy of different extraction procedures. Talanta 2012, 99, 712–719. [Google Scholar] [CrossRef] [PubMed]
  49. Miklós, G.; Angeli, C.; Ambrus, Á.; Nagy, A.; Kardos, V.; Zentai, A.; Kerekes, K.; Farkas, Z.; Jóźwiak, Á.; Bartók, T. Detection of Aflatoxins in Different Matrices and Food-Chain Positions. Front. Microbiol. 2020, 11, 1916. [Google Scholar] [CrossRef] [PubMed]
  50. Rico-Yuste, A.; Gómez-Arribas, L.N.; Pérez-Conde, M.C.; Urraca, J.L.; Moreno-Bondi, M.C. Rapid determination of Alternaria mycotoxins in tomato samples by pressurised liquid extraction coupled to liquid chromatography with fluorescence detection. Food Addit. Contam. Part A 2018, 35, 2175–2182. [Google Scholar] [CrossRef] [PubMed]
  51. Razzazi-Fazeli, E.; Reiter, E. Sample preparation and clean up in mycotoxin analysis: Principles, applications and recent developments. Determ. Mycotoxins Mycotoxigenic Fungi Food Feed 2011, 37–70. [Google Scholar] [CrossRef]
  52. Zougagh, M.; Ríos, Á. Supercritical fluid extraction of macrocyclic lactone mycotoxins in maize flour samples for rapid amperometric screening and alternative liquid chromatographic method for confirmation. J. Chromatogr. A 2008, 1177, 50–57. [Google Scholar] [CrossRef]
  53. Yang, Y.; Li, G.; Wu, D.; Liu, J.; Li, X.; Luo, P.; Hu, N.; Wang, H.; Wu, Y. Recent advances on toxicity and determination methods of mycotoxins in foodstuffs. Trends Food Sci. Technol. 2020, 96, 233–252. [Google Scholar] [CrossRef]
  54. González-Curbelo, M.Á.; Socas-Rodríguez, B.; Herrera-Herrera, A.V.; González-Sálamo, J.; Hernández-Borges, J.; Rodríguez-Delgado, M.Á. Evolution and applications of the QuEChERS method. TrAC Trends Anal. Chem. 2015, 71, 169–185. [Google Scholar] [CrossRef]
  55. Perestrelo, R.; Silva, P.; Porto-Figueira, P.; Pereira, J.A.M.; Silva, C.; Medina, S.; Câmara, J.S. QuEChERS-Fundamentals, relevant improvements, applications and future trends. Anal. Chim. Acta 2019, 1070, 1–28. [Google Scholar] [CrossRef]
  56. Song, S.; Ediage, E.N.; Wu, A.; De Saeger, S. Development and application of salting-out assisted liquid/liquid extraction for multi-mycotoxin biomarkers analysis in pig urine with high performance liquid chromatography/tandem mass spectrometry. J. Chromatogr. A 2013, 1292, 111–120. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Alvarez-Rivera, G.; Bueno, M.; Ballesteros-Vivas, D.; Mendiola, J.A.; Ibañez, E. Chapter 13-Pressurized Liquid Extraction. In Liquid-Phase Extraction; Poole, C.F., Ed.; Elsevier: Amsterdam, The Netherlands, 2020; pp. 375–398. [Google Scholar]
  58. Huertas-Pérez, J.F.; Arroyo-Manzanares, N.; García-Campaña, A.M.; Gámiz-Gracia, L. Solid phase extraction as sample treatment for the determination of Ochratoxin A in foods: A review. Crit. Rev. Food Sci. Nutr. 2017, 57, 3405–3420. [Google Scholar] [CrossRef] [PubMed]
  59. Pereira, V.L.; Fernandes, J.O.; Cunha, S.C. Mycotoxins in cereals and related foodstuffs: A review on occurrence and recent methods of analysis. Trends Food Sci. Technol. 2014, 36, 96–136. [Google Scholar] [CrossRef]
  60. Jiang, D.; Wei, D.; Wang, L.; Ma, S.; Du, Y.; Wang, M. Multiwalled Carbon Nanotube for One-Step Cleanup of 21 Mycotoxins in Corn and Wheat Prior to Ultraperformance Liquid Chromatography-Tandem Mass Spectrometry Analysis. Toxins 2018, 10, 409. [Google Scholar] [CrossRef] [Green Version]
  61. Wang, M.; Jiang, N.; Xian, H.; Wei, D.; Shi, L.; Feng, X. A single-step solid phase extraction for the simultaneous determination of 8 mycotoxins in fruits by ultra-high performance liquid chromatography tandem mass spectrometry. J. Chromatogr. A 2016, 1429, 22–29. [Google Scholar] [CrossRef]
  62. Dong, M.; Si, W.; Jiang, K.; Nie, D.; Wu, Y.; Zhao, Z.; De Saeger, S.; Han, Z. Multi-walled carbon nanotubes as solid-phase extraction sorbents for simultaneous determination of type A trichothecenes in maize, wheat and rice by ultra-high performance liquid chromatography-tandem mass spectrometry. J. Chromatogr. A 2015, 1423, 177–182. [Google Scholar] [CrossRef] [PubMed]
  63. Han, Z.; Jiang, K.; Fan, Z.; Diana Di Mavungu, J.; Dong, M.; Guo, W.; Fan, K.; Campbell, K.; Zhao, Z.; Wu, Y. Multi-walled carbon nanotubes-based magnetic solid-phase extraction for the determination of zearalenone and its derivatives in maize by ultra-high performance liquid chromatography-tandem mass spectrometry. Food Control 2017, 79, 177–184. [Google Scholar] [CrossRef]
  64. Dong, M.; Si, W.; Wang, W.; Bai, B.; Nie, D.; Song, W.; Zhao, Z.; Guo, Y.; Han, Z. Determination of type A trichothecenes in coix seed by magnetic solid-phase extraction based on magnetic multi-walled carbon nanotubes coupled with ultra-high performance liquid chromatography-tandem mass spectrometry. Anal. Bioanal. Chem. 2016, 408, 6823–6831. [Google Scholar] [CrossRef] [PubMed]
  65. Liu, X.; Liu, X.; Huang, P.; Wei, F.; Ying, G.; Lu, J.; Zhou, L.; Kong, W. Regeneration and Reuse of Immunoaffinity Column for Highly Efficient Clean-Up and Economic Detection of Ochratoxin A in Malt and Ginger. Toxins 2018, 10, 462. [Google Scholar] [CrossRef] [Green Version]
  66. Castegnaro, M.; Tozlovanu, M.; Wild, C.; Molinié, A.; Sylla, A.; Leszkowicz, A. Advantages and drawbacks of immunoaffinity columns in analysis of mycotoxins in food. Mol. Nutr. Food Res. 2006, 50, 480–487. [Google Scholar] [CrossRef]
  67. Irakli, M.N.; Skendi, A.; Papageorgiou, M.D. HPLC-DAD-FLD Method for Simultaneous Determination of Mycotoxins in Wheat Bran. J. Chromatogr. Sci. 2017, 55, 690–696. [Google Scholar] [CrossRef]
  68. Lattanzio, V.M.T.; Solfrizzo, M.; Powers, S.; Visconti, A. Simultaneous determination of aflatoxins, ochratoxin A and Fusarium toxins in maize by liquid chromatography/tandem mass spectrometry after multitoxin immunoaffinity cleanup. Rapid Commun. Mass Spectrom. Int. J. Devoted Rapid Dissem. Minute Res. Mass Spectrom. 2007, 21, 3253–3261. [Google Scholar] [CrossRef]
  69. Lattanzio, V.M.T.; Ciasca, B.; Powers, S.; Visconti, A. Improved method for the simultaneous determination of aflatoxins, ochratoxin A and Fusarium toxins in cereals and derived products by liquid chromatography–tandem mass spectrometry after multi-toxin immunoaffinity clean up. J. Chromatogr. A 2014, 1354, 139–143. [Google Scholar] [CrossRef]
  70. Le, V.T.; Vasseghian, Y.; Dragoi, E.-N.; Moradi, M.; Mousavi Khaneghah, A. A review on graphene-based electrochemical sensor for mycotoxins detection. Food Chem. Toxicol. 2021, 148, 111931. [Google Scholar] [CrossRef] [PubMed]
  71. Turner, N.W.; Bramhmbhatt, H.; Szabo-Vezse, M.; Poma, A.; Coker, R.; Piletsky, S.A. Analytical methods for determination of mycotoxins: An update (2009–2014). Anal. Chim. Acta 2015, 901, 12–33. [Google Scholar] [CrossRef] [PubMed]
  72. Urusov, A.E.; Zherdev, A.V.; Dzantiev, B.B. Immunochemical methods of mycotoxin analysis (review). Appl. Biochem. Microbiol. 2010, 46, 253–266. [Google Scholar] [CrossRef]
  73. Hendrickson, O.D.; Chertovich, J.O.; Zherdev, A.V.; Sveshnikov, P.G.; Dzantiev, B.B. Ultrasensitive magnetic ELISA of zearalenone with pre-concentration and chemiluminescent detection. Food Control 2018, 84, 330–338. [Google Scholar] [CrossRef]
  74. Lattanzio, V.M.T.; von Holst, C.; Lippolis, V.; De Girolamo, A.; Logrieco, A.F.; Mol, H.G.J.; Pascale, M. Evaluation of Mycotoxin Screening Tests in a Verification Study Involving First Time Users. Toxins 2019, 11, 129. [Google Scholar] [CrossRef] [Green Version]
  75. Wolf, K.; Schweigert, J.F. Mycotoxin Analysis: A Focus on Rapid Methods; Partnership for Aflatoxin Control in Africa: Addis Ababa, Ethiopia, 2018. [Google Scholar]
  76. Younis, M.; Younis, A.; Xia, X.-H. Use of Biosensors for Mycotoxins Analysis in Food Stuff. In Nanobiosensors: From Design to Applications; Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, Germany, 2020; pp. 171–201. [Google Scholar] [CrossRef]
  77. Evtugyn, G.A.; Shamagsumova, R.V.; Hianik, T. 2-Biosensors for detection mycotoxins and pathogenic bacteria in food. In Nanobiosensors; Grumezescu, A.M., Ed.; Academic Press: Cambridge, MA, USA, 2017; pp. 35–92. Available online: (accessed on 28 June 2021).
  78. Yang, J.; Li, J.; Jiang, Y.; Duan, X.; Qu, H.; Yang, B.; Chen, F.; Sivakumar, D. Natural Occurrence, Analysis, and Prevention of Mycotoxins in Fruits and their Processed Products. Crit. Rev. Food Sci. Nutr. 2014, 54, 64–83. [Google Scholar] [CrossRef]
  79. Wacoo, A.P.; Wendiro, D.; Vuzi, P.C.; Hawumba, J.F. Methods for Detection of Aflatoxins in Agricultural Food Crops. J. Appl. Chem. 2014, 2014, 706291. [Google Scholar] [CrossRef] [Green Version]
  80. Odhav, B.; Naicker, V. Mycotoxins in South African traditionally brewed beers. Food Addit. Contam. 2002, 19, 55–61. [Google Scholar] [CrossRef]
  81. Abrunhosa, L.; Paterson, R.R.M.; Kozakiewicz, Z.; Lima, N.; Venâncio, A. Mycotoxin production from fungi isolated from grapes. Lett. Appl. Microbiol. 2001, 32, 240–242. [Google Scholar] [CrossRef] [Green Version]
  82. Caldas, E.D.; Silva, A.C.S. Mycotoxins in corn-based food products consumed in Brazil: An exposure assessment for fumonisins. J. Agric. Food Chem. 2007, 55, 7974–7980. [Google Scholar] [CrossRef]
  83. Andrade, P.D.; de Mello, M.H.; França, J.A.; Caldas, E.D. Aflatoxins in food products consumed in Brazil: A preliminary dietary risk assessment. Food Addit. Contam. Part A 2013, 30, 127–136. [Google Scholar] [CrossRef] [PubMed]
  84. Rizzo, I.; Vedoya, G.; Maurutto, S.; Haidukowski, M.; Varsavsky, E. Assessment of toxigenic fungi on Argentinean medicinal herbs. Microbiol. Res. 2004, 159, 113–120. [Google Scholar] [CrossRef] [PubMed]
  85. Singh, J.; Mehta, A. Rapid and sensitive detection of mycotoxins by advanced and emerging analytical methods: A review. Food Sci. Nutr. 2020, 8, 2183–2204. [Google Scholar] [CrossRef]
  86. Zinedine, A.; Soriano, J.M.; Juan, C.; Mojemmi, B.; Moltó, J.C.; Bouklouze, A.; Cherrah, Y.; Idrissi, L.; Aouad, R.E.; Mañes, J. Incidence of ochratoxin A in rice and dried fruits from Rabat and Salé area, Morocco. Food Addit. Contam. 2007, 24, 285–291. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Moldoveanu, S.; David, V. Chapter 9—The Role of Derivatization in Chromatography. In Modern Sample Preparation for Chromatography; Moldoveanu, S., David, V., Eds.; Elsevier: Amsterdam, The Netherlands, 2015; pp. 307–331. [Google Scholar] [CrossRef]
  88. Malachová, A.; Stránská, M.; Václavíková, M.; Elliott, C.T.; Black, C.; Meneely, J.; Hajšlová, J.; Ezekiel, C.N.; Schuhmacher, R.; Krska, R. Advanced LC–MS-based methods to study the co-occurrence and metabolization of multiple mycotoxins in cereals and cereal-based food. Anal. Bioanal. Chem. 2018, 410, 801–825. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Pascale, M.; De Girolamo, A.; Lippolis, V.; Stroka, J.; Mol, H.G.J.; Lattanzio, V.M.T. Performance Evaluation of LC-MS Methods for Multimycotoxin Determination. J. AOAC Int. 2019, 102, 1708–1720. [Google Scholar] [CrossRef]
  90. Shi, H.; Li, S.; Bai, Y.; Prates, L.L.; Lei, Y.; Yu, P. Mycotoxin contamination of food and feed in China: Occurrence, detection techniques, toxicological effects and advances in mitigation technologies. Food Control 2018, 91, 202–215. [Google Scholar] [CrossRef]
  91. Smith, M.-C.; Madec, S.; Coton, E.; Hymery, N. Natural Co-Occurrence of Mycotoxins in Foods and Feeds and Their in vitro Combined Toxicological Effects. Toxins 2016, 8, 94. [Google Scholar] [CrossRef] [PubMed]
  92. Bessaire, T.; Mujahid, C.; Mottier, P.; Desmarchelier, A. Multiple Mycotoxins Determination in Food by LC-MS/MS: An International Collaborative Study. Toxins 2019, 11, 658. [Google Scholar] [CrossRef] [Green Version]
  93. Flores-Flores, M.E.; González-Peñas, E. An LC–MS/MS method for multi-mycotoxin quantification in cow milk. Food Chem. 2017, 218, 378–385. [Google Scholar] [CrossRef]
  94. Abdallah, M.F.; Girgin, G.; Baydar, T.; Krska, R.; Sulyok, M. Occurrence of multiple mycotoxins and other fungal metabolites in animal feed and maize samples from Egypt using LC-MS/MS. J. Sci. Food Agric. 2017, 97, 4419–4428. [Google Scholar] [CrossRef] [PubMed]
  95. Al-Taher, F.; Banaszewski, K.; Jackson, L.; Zweigenbaum, J.; Ryu, D.; Cappozzo, J. Rapid method for the determination of multiple mycotoxins in wines and beers by LC-MS/MS using a stable isotope dilution assay. J. Agric. Food Chem. 2013, 61, 2378–2384. [Google Scholar] [CrossRef] [PubMed]
  96. Rodríguez-Carrasco, Y.; Moltó, J.C.; Berrada, H.; Mañes, J. A survey of trichothecenes, zearalenone and patulin in milled grain-based products using GC–MS/MS. Food Chem. 2014, 146, 212–219. [Google Scholar] [CrossRef] [PubMed]
  97. Rodríguez-Carrasco, Y.; Berrada, H.; Font, G.; Mañes, J. Multi-mycotoxin analysis in wheat semolina using an acetonitrile-based extraction procedure and gas chromatography–tandem mass spectrometry. J. Chromatogr. A 2012, 1270, 28–40. [Google Scholar] [CrossRef] [PubMed]
  98. Welke, J.E.; Hoeltz, M.; Dottori, H.A.; Noll, I.B. Quantitative analysis of patulin in apple juice by thin-layer chromatography using a charge coupled device detector. Food Addit. Contam. Part A 2009, 26, 754–758. [Google Scholar] [CrossRef] [PubMed]
  99. Aiko, V.; Mehta, A. Prevalence of toxigenic fungi in common medicinal herbs and spices in India. 3 Biotech 2016, 6, 159. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  100. Tessini, C.; Mardones, C.; von Baer, D.; Vega, M.; Herlitz, E.; Saelzer, R.; Silva, J.; Torres, O. Alternatives for sample pre-treatment and HPLC determination of Ochratoxin A in red wine using fluorescence detection. Anal. Chim. Acta 2010, 660, 119–126. [Google Scholar] [CrossRef]
  101. Abdulkadar, A.H.W.; Al-Ali, A.A.; Al-Kildi, A.M.; Al-Jedah, J.H. Mycotoxins in food products available in Qatar. Food Control 2004, 15, 543–548. [Google Scholar] [CrossRef]
  102. Li, X.P.; Zhao, Y.G.; Chen, X.H.; Pan, S.D.; Jin, M.C. Simultaneous determination of four aflatoxins in walnut kernel using dispersive solid-phase extraction combined with ultra fast liquid chromatography-tandem mass spectrometry. Chin. J. Health Lab. Technol 2014, 24, 2647–2650. [Google Scholar]
  103. Liang, Y.; Huang, X.; Chen, X.; Zhang, W.; Ping, G.; Xiong, Y. Plasmonic ELISA for naked-eye detection of ochratoxin A based on the tyramine-H2O2 amplification system. Sens. Actuators B Chem. 2018, 259, 162–169. [Google Scholar] [CrossRef]
  104. Oplatowska-Stachowiak, M.; Reiring, C.; Sajic, N.; Haasnoot, W.; Brabet, C.; Campbell, K.; Elliott, C.T.; Salden, M. Development and in-house validation of a rapid and simple to use ELISA for the detection and measurement of the mycotoxin sterigmatocystin. Anal. Bioanal. Chem. 2018, 410, 3017–3023. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Li, P.; Zhang, Q.; Zhang, W. Immunoassays for aflatoxins. TrAC Trends Anal. Chem. 2009, 28, 1115–1126. [Google Scholar] [CrossRef]
  106. Solcan, C.; Gogu, M.; Floristean, V.; Oprisan, B.; Solcan, G. The hepatoprotective effect of sea buckthorn (Hippophae rhamnoides) berries on induced aflatoxin B1 poisoning in chickens1. Poult. Sci. 2013, 92, 966–974. [Google Scholar] [CrossRef] [PubMed]
  107. Thway, T.; Salimi-Moosavi, H. Evaluating the impact of matrix effects on biomarker assay sensitivity. Bioanalysis 2014, 6, 1081–1091. [Google Scholar] [CrossRef] [PubMed]
  108. Omar, S.S.; Haddad, M.A.; Parisi, S. Validation of HPLC and Enzyme-Linked Immunosorbent Assay (ELISA) Techniques for Detection and Quantification of Aflatoxins in Different Food Samples. Foods 2020, 9, 661. [Google Scholar] [CrossRef] [PubMed]
  109. Zheng, M.Z.; Richard, J.L.; Binder, J. A review of rapid methods for the analysis of mycotoxins. Mycopathologia 2006, 161, 261–273. [Google Scholar] [CrossRef]
  110. Santos, L.; Marín, S.; Sanchis, V.; Ramos, A.J. Screening of mycotoxin multicontamination in medicinal and aromatic herbs sampled in Spain. J. Sci. Food Agric. 2009, 89, 1802–1807. [Google Scholar] [CrossRef]
  111. Pleadin, J.; Perši, N.; Zadravec, M.; Sokolović, M.; Vulić, A.; Jaki, V.; Mitak, M. Correlation of Deoxynivalenol and Fumonisin Concentration Determined in Maize by Elisa Methods. J. Immunoass. Immunochem. 2012, 33, 414–421. [Google Scholar] [CrossRef]
  112. Xing, K.-Y.; Peng, J.; Shan, S.; Liu, D.-F.; Huang, Y.-N.; Lai, W.-H. Green Enzyme-Linked Immunosorbent Assay Based on the Single-Stranded Binding Protein-Assisted Aptamer for the Detection of Mycotoxin. Anal. Chem. 2020, 92, 8422–8426. [Google Scholar] [CrossRef]
  113. Zheng, Z.; Hanneken, J.; Houchins, D.; King, R.S.; Lee, P.; Richard, J.L. Validation of an ELISA test kit for the detection of ochratoxin A in several food commodities by comparison with HPLC. Mycopathologia 2005, 159, 265–272. [Google Scholar] [CrossRef]
  114. Song, S.; Liu, N.; Zhao, Z.; Njumbe Ediage, E.; Wu, S.; Sun, C.; De Saeger, S.; Wu, A. Multiplex Lateral Flow Immunoassay for Mycotoxin Determination. Anal. Chem. 2014, 86, 4995–5001. [Google Scholar] [CrossRef]
  115. Anfossi, L.; Baggiani, C.; Giovannoli, C.; D’Arco, G.; Giraudi, G. Lateral-flow immunoassays for mycotoxins and phycotoxins: A review. Anal. Bioanal. Chem. 2013, 405, 467–480. [Google Scholar] [CrossRef]
  116. Li, R.; Meng, C.; Wen, Y.; Fu, W.; He, P. Fluorometric lateral flow immunoassay for simultaneous determination of three mycotoxins (aflatoxin B1, zearalenone and deoxynivalenol) using quantum dot microbeads. Microchim. Acta 2019, 186, 748. [Google Scholar] [CrossRef]
  117. Wang, Y.; Xu, H.; Wei, M.; Gu, H.; Xu, Q.; Zhu, W. Study of superparamagnetic nanoparticles as labels in the quantitative lateral flow immunoassay. Mater. Sci. Eng. C 2009, 29, 714–718. [Google Scholar] [CrossRef]
  118. Zhang, X.; Yu, X.; Wen, K.; Li, C.; Mujtaba Mari, G.; Jiang, H.; Shi, W.; Shen, J.; Wang, Z. Multiplex Lateral Flow Immunoassays Based on Amorphous Carbon Nanoparticles for Detecting Three Fusarium Mycotoxins in Maize. J. Agric. Food Chem. 2017, 65, 8063–8071. [Google Scholar] [CrossRef]
  119. Li, Y.; Liu, L.; Kuang, H.; Xu, C. Visible and eco-friendly immunoassays for the detection of cyclopiazonic acid in maize and rice. J. Food Sci. 2020, 85, 105–113. [Google Scholar] [CrossRef]
  120. Anfossi, L.; Di Nardo, F.; Cavalera, S.; Giovannoli, C.; Spano, G.; Speranskaya, E.S.; Goryacheva, I.Y.; Baggiani, C. A lateral flow immunoassay for straightforward determination of fumonisin mycotoxins based on the quenching of the fluorescence of CdSe/ZnS quantum dots by gold and silver nanoparticles. Microchim. Acta 2018, 185, 94. [Google Scholar] [CrossRef] [PubMed]
  121. Jin, G.; Wu, X.; Cui, G.; Liu, L.; Kuang, H.; Xu, C. Development of an ic-ELISA and Immunochromatographic Strip Assay for the Detection of Diacetoxyscirpenol in Rice. ACS Omega 2020, 5, 17876–17882. [Google Scholar] [CrossRef] [PubMed]
  122. Ren, W.; Huang, Z.; Xu, Y.; Li, Y.; Ji, Y.; Su, B. Urchin-like gold nanoparticle-based immunochromatographic strip test for rapid detection of fumonisin B1 in grains. Anal. Bioanal. Chem. 2015, 407, 7341–7348. [Google Scholar] [CrossRef] [PubMed]
  123. Di Nardo, F.; Anfossi, L.; Giovannoli, C.; Passini, C.; Goftman, V.V.; Goryacheva, I.Y.; Baggiani, C. A fluorescent immunochromatographic strip test using Quantum Dots for fumonisins detection. Talanta 2016, 150, 463–468. [Google Scholar] [CrossRef] [Green Version]
  124. Liu, Z.; Hua, Q.; Wang, J.; Liang, Z.; Li, J.; Wu, J.; Shen, X.; Lei, H.; Li, X. A smartphone-based dual detection mode device integrated with two lateral flow immunoassays for multiplex mycotoxins in cereals. Biosens. Bioelectron. 2020, 158, 112178. [Google Scholar] [CrossRef]
  125. Krska, R.; Molinelli, A. Rapid test strips for analysis of mycotoxins in food and feed. Anal. Bioanal. Chem. 2009, 393, 67–71. [Google Scholar] [CrossRef] [PubMed]
  126. Perumal, V.; Hashim, U. Advances in biosensors: Principle, architecture and applications. J. Appl. Biomed. 2014, 12, 1–15. [Google Scholar] [CrossRef]
  127. Santana Oliveira, I.; da Silva Junior, A.G.; de Andrade, C.A.S.; Lima Oliveira, M.D. Biosensors for early detection of fungi spoilage and toxigenic and mycotoxins in food. Curr. Opin. Food Sci. 2019, 29, 64–79. [Google Scholar] [CrossRef]
  128. Malekzad, H.; Sahandi Zangabad, P.; Mirshekari, H.; Karimi, M.; Hamblin, M.R. Noble metal nanoparticles in biosensors: Recent studies and applications. Nanotechnol. Rev. 2017, 6, 301–329. [Google Scholar] [CrossRef]
  129. Evtugyn, G.; Subjakova, V.; Melikishvili, S.; Hianik, T. Chapter Seven—Affinity Biosensors for Detection of Mycotoxins in Food. In Advances in Food and Nutrition Research; Toldrá, F., Ed.; Academic Press: Cambridge, MA, USA, 2018; Volume 85, pp. 263–310. [Google Scholar]
  130. Doria, G.; Conde, J.; Veigas, B.; Giestas, L.; Almeida, C.; Assunção, M.; Rosa, J.; Baptista, P.V. Noble Metal Nanoparticles for Biosensing Applications. Sensors 2012, 12, 1657–1687. [Google Scholar] [CrossRef]
  131. Altintas, Z.; Davis, F.; Scheller, F.W. Applications of quantum dots in biosensors and diagnostics. Biosens. Nanotechnol. Appl. Health Care Diagn. 2017, 3, 185–199. [Google Scholar]
  132. Fernández, H.; Arévalo, F.J.; Granero, A.M.; Robledo, S.N.; Nieto, C.H.D.; Riberi, W.I.; Zon, M.A. Electrochemical Biosensors for the Determination of Toxic Substances Related to Food Safety Developed in South America: Mycotoxins and Herbicides. Chemosensors 2017, 5, 23. [Google Scholar] [CrossRef] [Green Version]
  133. Ding, J.; Qin, W. Recent advances in potentiometric biosensors. Trac. Trends Anal. Chem. 2020, 124, 115803. [Google Scholar] [CrossRef]
  134. Chai, C.; Oh, S.-W. Electrochemical impedimetric biosensors for food safety. Food Sci. Biotechnol. 2020, 29, 879–887. [Google Scholar] [CrossRef] [PubMed]
  135. Chen, C.; Wang, J. Optical biosensors: An exhaustive and comprehensive review. Analyst 2020, 145, 1605–1628. [Google Scholar] [CrossRef] [PubMed]
  136. Santos, A.O.; Vaz, A.; Rodrigues, P.; Veloso, A.C.A.; Venâncio, A.; Peres, A.M. Thin Films Sensor Devices for Mycotoxins Detection in Foods: Applications and Challenges. Chemosensors 2019, 7, 3. [Google Scholar] [CrossRef] [Green Version]
  137. Sharma, A.; Khan, R.; Catanante, G.; Sherazi, T.A.; Bhand, S.; Hayat, A.; Marty, J.L. Designed Strategies for Fluorescence-Based Biosensors for the Detection of Mycotoxins. Toxins 2018, 10, 197. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  138. Spinella, K.; Mosiello, L.; Palleschi, G.; Vitali, F. Development of a QCM (Quartz Crystal Microbalance) Biosensor to Detection of Mycotoxins. In Proceedings of the Sensors and Microsystems, Brescia, Italy, 5–7 February 2013; pp. 195–198. [Google Scholar]
  139. Tang, Y.; Tang, D.; Zhang, J.; Tang, D. Novel quartz crystal microbalance immunodetection of aflatoxin B1 coupling cargo-encapsulated liposome with indicator-triggered displacement assay. Anal. Chim. Acta 2018, 1031, 161–168. [Google Scholar] [CrossRef] [PubMed]
  140. Karczmarczyk, A.; Haupt, K.; Feller, K.-H. Development of a QCM-D biosensor for Ochratoxin A detection in red wine. Talanta 2017, 166, 193–197. [Google Scholar] [CrossRef] [PubMed]
  141. Yagati, A.K.; Chavan, S.G.; Baek, C.; Lee, M.-H.; Min, J. Label-free impedance sensing of aflatoxin B1 with polyaniline nanofibers/Au nanoparticle electrode array. Sensors 2018, 18, 1320. [Google Scholar] [CrossRef] [Green Version]
  142. Rehmat, Z.; Mohammed, W.S.; Sadiq, M.B.; Somarapalli, M.; Anal, A.K. Ochratoxin A detection in coffee by competitive inhibition assay using chitosan-based surface plasmon resonance compact system. Colloids Surf. B Biointerfaces 2019, 174, 569–574. [Google Scholar] [CrossRef]
  143. Khan, R.; Ben Aissa, S.; Sherazi, T.A.; Catanante, G.; Hayat, A.; Marty, J.L. Development of an impedimetric aptasensor for label free detection of patulin in apple juice. Molecules 2019, 24, 1017. [Google Scholar] [CrossRef] [Green Version]
  144. Khan, I.M.; Zhao, S.; Niazi, S.; Mohsin, A.; Shoaib, M.; Duan, N.; Wu, S.; Wang, Z. Silver nanoclusters based FRET aptasensor for sensitive and selective fluorescent detection of T-2 toxin. Sens. Actuators B Chem. 2018, 277, 328–335. [Google Scholar] [CrossRef]
  145. He, B.; Yan, X. An amperometric zearalenone aptasensor based on signal amplification by using a composite prepared from porous platinum nanotubes, gold nanoparticles and thionine-labelled graphene oxide. Microchim. Acta 2019, 186, 383. [Google Scholar] [CrossRef]
  146. Chen, X.; Huang, Y.; Ma, X.; Jia, F.; Guo, X.; Wang, Z. Impedimetric aptamer-based determination of the mold toxin fumonisin B1. Microchim. Acta 2015, 182, 1709–1714. [Google Scholar] [CrossRef]
  147. Xiang, Y.; Camarada, M.B.; Wen, Y.; Wu, H.; Chen, J.; Li, M.; Liao, X. Simple voltammetric analyses of ochratoxin A in food samples using highly-stable and anti-fouling black phosphorene nanosensor. Electrochim. Acta 2018, 282, 490–498. [Google Scholar] [CrossRef]
  148. Nolan, P.; Auer, S.; Spehar, A.; Elliott, C.T.; Campbell, K. Current trends in rapid tests for mycotoxins. Food Addit. Contam. Part A 2019, 36, 800–814. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  149. Camardo Leggieri, M.; Mazzoni, M.; Fodil, S.; Moschini, M.; Bertuzzi, T.; Prandini, A.; Battilani, P. An electronic nose supported by an artificial neural network for the rapid detection of aflatoxin B1 and fumonisins in maize. Food Control 2021, 123, 107722. [Google Scholar] [CrossRef]
  150. Ottoboni, M.; Pinotti, L.; Tretola, M.; Giromini, C.; Fusi, E.; Rebucci, R.; Grillo, M.; Tassoni, L.; Foresta, S.; Gastaldello, S.; et al. Combining E-Nose and Lateral Flow Immunoassays (LFIAs) for Rapid Occurrence/Co-Occurrence Aflatoxin and Fumonisin Detection in Maize. Toxins 2018, 10, 416. [Google Scholar] [CrossRef] [Green Version]
  151. Lippolis, V.; Ferrara, M.; Cervellieri, S.; Damascelli, A.; Epifani, F.; Pascale, M.; Perrone, G. Rapid prediction of ochratoxin A-producing strains of Penicillium on dry-cured meat by MOS-based electronic nose. Int. J. Food Microbiol. 2016, 218, 71–77. [Google Scholar] [CrossRef] [PubMed]
  152. Lippolis, V.; Cervellieri, S.; Damascelli, A.; Pascale, M.; Di Gioia, A.; Longobardi, F.; De Girolamo, A. Rapid prediction of deoxynivalenol contamination in wheat bran by MOS-based electronic nose and characterization of the relevant pattern of volatile compounds. J. Sci. Food Agric. 2018, 98, 4955–4962. [Google Scholar] [CrossRef]
  153. Lippolis, V.; Pascale, M.; Cervellieri, S.; Damascelli, A.; Visconti, A. Screening of deoxynivalenol contamination in durum wheat by MOS-based electronic nose and identification of the relevant pattern of volatile compounds. Food Control 2014, 37, 263–271. [Google Scholar] [CrossRef]
  154. Valenzano, S.; Lippolis, V.; Pascale, M.; De Marco, A.; Maragos, C.M.; Suman, M.; Visconti, A. Determination of Deoxynivalenol in Wheat Bran and Whole-Wheat Flour by Fluorescence Polarization Immunoassay. Food Anal. Methods 2014, 7, 806–813. [Google Scholar] [CrossRef]
  155. Huang, X.; Tang, X.; Jallow, A.; Qi, X.; Zhang, W.; Jiang, J.; Li, H.; Zhang, Q.; Li, P. Development of an Ultrasensitive and Rapid Fluorescence Polarization Immunoassay for Ochratoxin A in Rice. Toxins 2020, 12, 682. [Google Scholar] [CrossRef]
  156. Zhang, X.; Eremin, S.A.; Wen, K.; Yu, X.; Li, C.; Ke, Y.; Jiang, H.; Shen, J.; Wang, Z. Fluorescence Polarization Immunoassay Based on a New Monoclonal Antibody for the Detection of the Zearalenone Class of Mycotoxins in Maize. J. Agric. Food Chem. 2017, 65, 2240–2247. [Google Scholar] [CrossRef] [PubMed]
  157. Lippolis, V.; Pascale, M.; Visconti, A. Optimization of a Fluorescence Polarization Immunoassay for Rapid Quantification of Deoxynivalenol in Durum Wheat–Based Products. J. Food Prot. 2006, 69, 2712–2719. [Google Scholar] [CrossRef] [PubMed]
  158. Zhang, X.; Tang, Q.; Mi, T.; Zhao, S.; Wen, K.; Guo, L.; Mi, J.; Zhang, S.; Shi, W.; Shen, J.; et al. Dual-wavelength fluorescence polarization immunoassay to increase information content per screen: Applications for simultaneous detection of total aflatoxins and family zearalenones in maize. Food Control 2018, 87, 100–108. [Google Scholar] [CrossRef]
  159. Zhu, Y.; Xia, X.; Deng, S.; Yan, B.; Dong, Y.; Zhang, K.; Deng, R.; He, Q. Label-free fluorescent aptasensing of mycotoxins via aggregation-induced emission dye. Dye. Pigment. 2019, 170, 107572. [Google Scholar] [CrossRef]
  160. Li, J.; Kwon, N.; Jeong, Y.; Lee, S.; Kim, G.; Yoon, J. Aggregation-Induced Fluorescence Probe for Monitoring Membrane Potential Changes in Mitochondria. ACS Appl. Mater. Interfaces 2018, 10, 12150–12154. [Google Scholar] [CrossRef]
  161. Wang, H.; Liu, G. Advances in luminescent materials with aggregation-induced emission (AIE) properties for biomedical applications. J. Mater. Chem. B 2018, 6, 4029–4042. [Google Scholar] [CrossRef] [PubMed]
  162. Xia, X.; Wang, H.; Yang, H.; Deng, S.; Deng, R.; Dong, Y.; He, Q. Dual-terminal stemmed aptamer beacon for label-free detection of aflatoxin B1 in broad bean paste and peanut oil via aggregation-induced emission. J. Agric. Food Chem. 2018, 66, 12431–12438. [Google Scholar] [CrossRef]
  163. Vasapollo, G.; Sole, R.D.; Mergola, L.; Lazzoi, M.R.; Scardino, A.; Scorrano, S.; Mele, G. Molecularly Imprinted Polymers: Present and Future Prospective. Int. J. Mol. Sci. 2011, 12, 5908–5945. [Google Scholar] [CrossRef] [Green Version]
  164. Krska, R.; Welzig, E.; Berthiller, F.; Molinelli, A.; Mizaikoff, B. Advances in the analysis of mycotoxins and its quality assurance. Food Addit. Contam. 2005, 22, 345–353. [Google Scholar] [CrossRef]
  165. Appell, M.; Mueller, A. Mycotoxin Analysis Using Imprinted Materials Technology: Recent Developments. J. AOAC Int. 2016, 99, 861–864. [Google Scholar] [CrossRef]
  166. Guo, P.; Yang, W.; Hu, H.; Wang, Y.; Li, P. Rapid detection of aflatoxin B1 by dummy template molecularly imprinted polymer capped CdTe quantum dots. Anal. Bioanal. Chem. 2019, 411, 2607–2617. [Google Scholar] [CrossRef] [PubMed]
  167. Pacheco, J.G.; Castro, M.; Machado, S.; Barroso, M.F.; Nouws, H.P.A.; Delerue-Matos, C. Molecularly imprinted electrochemical sensor for ochratoxin A detection in food samples. Sens. Actuators B Chem. 2015, 215, 107–112. [Google Scholar] [CrossRef]
  168. Lucci, P.; Derrien, D.; Alix, F.; Pérollier, C.; Bayoudh, S. Molecularly imprinted polymer solid-phase extraction for detection of zearalenone in cereal sample extracts. Anal. Chim. Acta 2010, 672, 15–19. [Google Scholar] [CrossRef]
  169. Huang, Z.; He, J.; Li, H.; Zhang, M.; Wang, H.; Zhang, Y.; Li, Y.; You, L.; Zhang, S. Synthesis and application of magnetic-surfaced pseudo molecularly imprinted polymers for zearalenone pretreatment in cereal samples. Food Chem. 2020, 308, 125696. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Schematic diagram of fluorescence polarization immunoassay.
Figure 1. Schematic diagram of fluorescence polarization immunoassay.
Molecules 26 03981 g001
Figure 2. Scheme of the principle of aggregation-induced emission.
Figure 2. Scheme of the principle of aggregation-induced emission.
Molecules 26 03981 g002
Figure 3. Scheme of molecularly imprinted polymer preparation.
Figure 3. Scheme of molecularly imprinted polymer preparation.
Molecules 26 03981 g003
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Janik, E.; Niemcewicz, M.; Podogrocki, M.; Ceremuga, M.; Gorniak, L.; Stela, M.; Bijak, M. The Existing Methods and Novel Approaches in Mycotoxins’ Detection. Molecules 2021, 26, 3981.

AMA Style

Janik E, Niemcewicz M, Podogrocki M, Ceremuga M, Gorniak L, Stela M, Bijak M. The Existing Methods and Novel Approaches in Mycotoxins’ Detection. Molecules. 2021; 26(13):3981.

Chicago/Turabian Style

Janik, Edyta, Marcin Niemcewicz, Marcin Podogrocki, Michal Ceremuga, Leslaw Gorniak, Maksymilian Stela, and Michal Bijak. 2021. "The Existing Methods and Novel Approaches in Mycotoxins’ Detection" Molecules 26, no. 13: 3981.

Article Metrics

Back to TopTop