Thin Films Sensor Devices for Mycotoxins Detection in Foods: Applications and Challenges
Abstract
:1. Introduction
2. Conventional Analytical Methods for Mycotoxins Detection
3. Thin Film Based Sensors
3.1. Optical Sensors
3.1.1. Fluorescence Sensors
3.1.2. Surface Plasmon Resonance (SPR) Sensors
3.1.3. Total Internal Reflection Ellipsometry (TIRE)
3.2. Electrochemical Biosensors
3.3. Mass-Based Piezoelectric Biosensors (Quartz Crystal Microbalance)
4. Conclusions and Future Perspectives
Author Contributions
Funding
Conflicts of Interest
References
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Mycotoxin | Abbreviation | Food Matrix | Toxic effect | Limit EU * | Fungal Species | References |
---|---|---|---|---|---|---|
Aflatoxins | AFM1, AFM2, AFB1, AFB2, AFG1, AFG2 | Peanuts, maize, milk and derived, cereals, oilseeds | Hepatotoxic, carcinogenic, probable immune suppression and childhood stunting reduced growth | AFB1: 2–12 μg/kg AFB1: 0.1 μg/kg for cereal-based foods for children and medicinal purposes AFM1: 0.05 μg/kg in milk and 0.025 μg/kg in foods for infants Total aflatoxin: 4–15 μg/kg | Aspergillus flavus, A. parasiticus | [15,18,19,20,21] |
Ochratoxins | OTA, OTB, OTC | Cereals, coffee, cocoa, wine, beer, grapes, dried fruits | Nephrotoxic, hepatotoxic, neurotoxic, teratogenic, immunotoxic | 0.5–10 μg/kg | Aspergillus ochraceus, A. carbonarius, Penicillium verrucosum | [12,13,22,23] |
Fumonisins | FB1 e FB2 | Maize and maize based food, rice, sorghum, soybeans | Neurotoxic, genotoxic, immunotoxic, carcinogenic, hepatotoxic, nephrotoxic | 200–4000 μg/kg | Fusarium verticillioides, F. proliferatum | [14,24] |
Trichothecenes | Type A: HT-2, T-2, Type B: DON | Wheat, barley, and maize and less often in oats, rice, rye, sorghum and triticale | Inhibition of protein synthesis, immunosuppressive and cytotoxic effect | DON: 200–1750 μg/kg | Fusarium sporotrichioides, F. graminearum, F. culmorum | [2,13,14,16,25] |
Patulin | PAT | Apples and apple products, fruit juice | Genotoxic, embryotoxic, immunotoxic, teratogenic, carcinogenic | 10–50 μg/kg | Penicillium expansum | [13,26] |
Zearalenone | ZEA | Corn, oats | Hepatotoxic, genotoxic, immunotoxic, carcinogenic | 20–400 μg/kg | Fusarium graminearum | [14,27] |
Citrinin | CIT | Various commodities of plant origin, cereals, namely fermented rice | Nephrotoxic, neurotoxic, genotoxic, embryotoxic, immunotoxic | 2000 μg/kg for rice | P. citrinum, P. expansum, P. verrucosum, Aspergillus carneus, A. niveus, Monascus purpureus | [12,16,28] |
Method | Advantages | Disadvantages | Mycotoxin/Matrix | LOD | LOQ | References |
---|---|---|---|---|---|---|
TLC | Simple and inexpensive Can be used as a rapid screening method | Poor sensitivity Poor precision Quantitative approach only if coupled with a densitometer | DON/Wheat flour | 30 ng·mL−1 | 100 ng·mL−1 | [30,52,53] |
HPLC-FLD | Good selectivity Accurate identification Short analysis time Automatic analysis (autosampler) Official methods available | Expensive equipment Specialist expertise required Derivatization may be required | AFB1/Spices | 0.04 ng·mL−1 | 0.15 ng·mL−1 | [54,55] |
LC-MS | Selective and sensitive detection Capability to generate structural information of the target analyte Low detection limits Simultaneous analysis of multiple mycotoxins Minimum sample pre-treatment steps | Expensive equipment Specialist expertise required Sensitivity depends on ionization technique | AFB1/Wheat grain | 2 µg·kg−1 | 3.5 µg·kg−1 | [55,56,57] |
GC | Simultaneous analysis of multiple mycotoxins Selective and sensitive detection | Expensive equipment Specialist expertise required Derivatization required Non-linear calibration curve Carry over effects from previous sample | DON/Pasta | 0.5 µg·kg−1 | 1 µg·kg−1 | [4,35,58] |
ELISA | Convenient and sensitive detection Ease of operation Rapid sample screening Simultaneous analysis of multiple mycotoxins Low use of organic solvents | Matrix interference problems Cross-reactivity with related mycotoxins Possible false positive/negative results Narrow operating range | OTA/Corn | 4.0 ng·mL−1 | Not specified | [59] |
Spectral analysis technology | Rapid screening of a large number of samples Qualitative and quantitative information about the structure of mycotoxins Can be used in situ | Complicated interpretation of spectral data Spectra overlapping Possible false positive/negative results | Fumonisin/Corn | 100 μg·kg−1 | Not specified | [60,61] |
Method | Mycotoxin | Bioreceptor | Interface Material | Sample Type | Limit of Detection (LOD) | Linearity Range | Reference |
---|---|---|---|---|---|---|---|
Amperometric | CIT | Antibody | Au surface electrodeposited on a GCE | Rice | 0.1 ng·mL−1 | 0.5–50 ng·mL−1 | [116] |
AFM1 | Antibody | SPCE | Milk | 0.039·ng·mL−1 | 1–10.000 ng·L−1 | [117] | |
ZEA | Antibody | Au@AgPt | Milk | 0.0017 ng·mL−1 | 0.005–15 ng·mL−1 | [118] | |
AFB1 | Antibody | Chitosan-AuNPs modified gold microelectrode | Wheat | 0.15 ng·mL−1 | 1.6–32 ng·mL−1 | [119] | |
Conductometric | OTA | Enzyme | TLN/AuNPs/(PVA/PEI) | Olive oil | 1 nM | 2–100 nM | [120] |
AFB1 | Enzyme | Au + Pyroceramic + Cr | Standard solution | 50 ng·mL−1 | 0.25–1 mM | [121] | |
Impedimetric | OTA | Antibody | SAM (AUT/Au) | Coffee | 0.0008 ng·mL−1 | 0.5–6.0 ng·dL−1 | [122] |
OTA | Aptamers | SPCE | Cocoa beans | 0.15 ng·mL−1 | 0.15–2.5 ng·mL−1 | [123] | |
AFM1 | Aptamers | SPCE | Milk | Not specified | 20–1000 ng·kg−1 | [124] | |
AFM1 | Aptamers | SPCE | Buffer | 1.15 ng·L−1 | 2–150 ng·L−1 | [124] | |
AFM1 | Antibody | Ag wire | Milk | 0.001 ng·mL−1 | 6.25–100 pg·mL−1 | [125] | |
OTA | Aptamers | AuNPs–cPC | Soybean | 10−8 ng·mL−1 | 10−8–0.1 ng·mL−1 | [126] | |
OTA | Aptamers | Au electrode + AuNPs/Boltorn H30® | Beer | 0.02 nM | 0.1–100 nM | [127] | |
OTA | Aptamers | SPCE/PTH + IrO2 NPs | White wine | 0.014 nM; 5.65 ng·kg−1 | 0.01–100 nM | [128] | |
DON | Antibody | GCE + AuNPs/G/PhNO2 | Cereals | 0.3 ng·mL−1 | 6–30 ng·mL−1 | [129] | |
AFB1 | Antibody | CD-trodes modified with lipoic acid SAM | Peanut | 0.11 ng·mL−1 | 1.56–31.2 ng·mL−1 | [130] | |
OTA | Antibody | AuSPCE/BSA | Plant extracts | Not specified | 2.5–100 ng·mL−1 | [131] | |
Potentiometric | AFM1 | Antibody | Ag/AgCl | Standard solution | 0.04 ng·mL−1 | 0.25–2 ng·mL−1 | [132] |
AFM1 | Antibody | Ag/AgCl | Milk | 0.5 ng·mL−1 | Not specified | [132] | |
AFM1 | - | GCE + GQDs-α-CD + AgNPs | Milk | 2000 nM | 0.015–25 mM | [133] | |
OTA | Aptamers | GCE + AuNPs/MoSe2 | Red wine | 0.00008 nM | 0.0001–1 nM | [134] | |
Voltammetry | DON | Antibody | GCE + SWNTs/CS | Sorghum | 0.005 ng·mL−1 | 0.01–1000 ng·mL−1 | [135] |
AFB1 | Antibody | SPCE modified with AuNPs and PPy/ErGO film | Corn | 4.2 ng·mL−1 | 200–4500 ng·mL−1 | [136] | |
DON | Antibody | SPCE modified with AuNPs and PPy/ErGO film | Corn | 8.6 ng·mL−1 | 50–1000 ng·mL−1 | [136] | |
OTA | Antibody | GCE + PTH/AuNPs | Corn | 0.2 ng·mL−1 | 1–1000 ng·mL−1 | [137] | |
OTA | - | GCE + MIP/MWCNT | Beer and wine | 4.1 nM (1.7 ng·mL−1) | 50–1000 nM | [138] | |
AFB1 | Antibody | Au electrode + CNTs/PDDA/PdeAu | Standard solution | 0.03 ng·mL−1 | 0.05–25 ng·mL−1 | [139] | |
AFB1 | Antibody | Au electrode + CNTs/PDDA/PdeAu | Rice | 1250 ng·kg−1 | Not specified | [139] | |
OTA | Antibody + enzyme | AuSPE | Red wine | 15 ng·mL−1 | 10−2–103 ng·mL−1 | [140] | |
AFM1 | Antibody + enzyme | AuSPE | Milk | 0.037 ng·mL−1 | 10−2–103 ng·mL−1 | [140] | |
AFB1 | Aptamers | PAMAM G4 + Au electrode + cystamine | Peanuts | 0.40 nM | 0.1–10 nM | [141] |
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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. https://doi.org/10.3390/chemosensors7010003
Santos AO, Vaz A, Rodrigues P, Veloso ACA, Venâncio A, Peres AM. Thin Films Sensor Devices for Mycotoxins Detection in Foods: Applications and Challenges. Chemosensors. 2019; 7(1):3. https://doi.org/10.3390/chemosensors7010003
Chicago/Turabian StyleSantos, Andréia O., Andreia Vaz, Paula Rodrigues, Ana C. A. Veloso, Armando Venâncio, and António M. Peres. 2019. "Thin Films Sensor Devices for Mycotoxins Detection in Foods: Applications and Challenges" Chemosensors 7, no. 1: 3. https://doi.org/10.3390/chemosensors7010003
APA StyleSantos, A. O., Vaz, A., Rodrigues, P., Veloso, A. C. A., Venâncio, A., & Peres, A. M. (2019). Thin Films Sensor Devices for Mycotoxins Detection in Foods: Applications and Challenges. Chemosensors, 7(1), 3. https://doi.org/10.3390/chemosensors7010003