Advances in Analysis and Detection of Major Mycotoxins in Foods
Abstract
:1. Introduction
2. Extraction Solutions, Extraction Methodologies and Clean-Up Procedures of Mycotoxins
3. Analytical Techniques in Analysis and Detection of Mycotoxins
4. Rapid Diagnostic Methods for Mycotoxin Detection
4.1. Immunoassay-Based Methods
4.2. Biosensors in Mycotoxins Detection
4.2.1. Electrochemical Biosensors for Mycotoxins Detection
Impedimetric Sensors
Potentiometric Sensors
Amperometric Sensors
4.2.2. Optical Biosensors for Mycotoxins Detection
Surface Plasmon Resonance Sensors
4.2.3. Piezoelectric Biosensors for Mycotoxins Detection
Quartz Crystal Microbalance (QCM)
5. Emerging Technologies in Analysis and Detection of Mycotoxins
5.1. Proteomic and Genomic Methods
5.2. Molecular Techniques
5.3. Electronic Nose
5.4. Aggregation-Induced Emission Dye
5.5. Quantitative NMR
5.6. Hyperspectral Imaging
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Extraction Methods | Extraction Solvents | Limits | Benefits | Reference |
---|---|---|---|---|
QuEChERS | Organic solvents or mixtures (CH3CN, MeOH, MeOH/CH3CN) | Modifications of the original procedure, need of an additional enrichment step | Economical, fast, simple, detection of low ppb levels, better reproducibility and accuracy | [5] |
LLE | Mixture of organic solvents (hexane, cyclohexane) with diluted acids or water | Time consuming, the sample can be absorbed by the glass equipment depending on the matrix and the determined compounds | Effective, for small-scale preparations | [40] |
SLE | Mixture of organic solvents with diluted acids or water | Matrix effects | Smaller volumes of solvent | [32,45] |
ASE or PLE | Mixture of organic solvents (MeOH/CH3CN, CH3CN/water) | Expensive instruments, matrix components excessively coextracted | Fully automated, faster extraction compared to the conventional ones, minimal solvents, higher extraction efficiency | [22,46] |
SFE | Supercritical fluids (CO2), MeOH, ethanol, acetone | Need for specialized and very expensive equipment, not suitable for routine analysis | Fast technique, small solvent volumes, preconcentration effect, extraction of temperature sensible analytes | [22,45,47] |
MAE | Aqueous solution | Only applicable for thermally stable compounds, costly instruments | Reduced extraction time and extraction solvent | [48] |
VALDS–ME | Mixture of organic solvents dispersive solvent and water | Optimization after control a lot of parameters | Use of low density solvents, simple, fast, effective | [20] |
Sample | Origin | Number of Samples | Mycotoxins | LOD | LOQ | References |
---|---|---|---|---|---|---|
Herbs and herbal products | India | 63 | AFB1, AFB2, AFG1, AFG2, CIT | 10 ng/mL for AFB1 NA for others | NA | [69] |
Herbal medicines | Nigeria | 210 | AFB1, AFB2, AFG1, AFG2 | NA | NA | [70] |
Brazil nuts | Brazil | 67 | AFB1, AFB2, AFG1, AFG2 | NA | 2 mg/kg | [71] |
Almonds, cashew nuts, chestnuts, hazelnuts, pistachio nuts, walnuts | Saudi Arabia | 5 | AFB1, AFB2, AFG1, AFG2, CIT, OTs, PAT, T-2, ZEA, ST, DAS | NA | 5 μg/kg (for AFs), NA for others | [72] |
Medicinal plants | Pakistan | 30 | AFB1, AFB2, AFG1, AFG2, OTA | NA | NA | [73] |
Corn-based food products | Brazil | 208 | AFB1, AFB2, AFG1, AFG2 | NA | 2 µg/kg | [74] |
Mycotoxin | Year of Publication | Country | Sample | Extraction Solution | Extraction Method | Clean-Up | LOD | LOQ * | Reference |
---|---|---|---|---|---|---|---|---|---|
AFs | 2014 | China | Walnut kernel | Methanol–water (70:30, v/v) | Sonicating | Self-made amino-function nanometer Fe3O4 magnetic polymer SPE | 0.004–0.013 µg kg−1 | 0.012–0.042 µg kg−1 | [90] |
AFs, OTA Fusarium mycotoxins | 2014 | Italy | Cereals and derived products | Methanol–water (60:40, v/v) | Blending | IAC | 1 µg kg−1 for AFs and OTA 5–30 µg kg−1 for Fusarium toxins | Nd | [52] |
5 Alternaria mycotoxins, CIT | 2015 | Belgium | Tomato and tomato juice | Methanol 2,4-dinitrophenylhydrazine | Vortex | SPE cartridge | 1–20 µg kg−1 | 2–50 µg kg−1 | [91] |
4 Alternaria mycotoxins | 2016 | China | Wheat kernel | Acetonitrile–water–methanol (45:45:10, v/v/v) | Sonicating | SPE cartridge | 0.04–1.3 µg kg−1 | 0.1–4.2 | [92] |
AFs, FB1, FB2, DON, OTA, ZEA | 2016 | Thailand | Brown rice | Acetonitrile with 10% (v/v) acetic acid | Vortex | QuEChERS | 1.4–25 µg kg−1 | 4.1–75 µg kg−1 | [93] |
15 mycotoxins | 2016 | Spain | Cow milk | Acetonitrile (2% formic acid) | Shaking | Sodium acetate | 0.02−10.14 ng mL−1 | Nd | [94] |
16 mycotoxins | 2017 | China | Vegetable oils | 85% Acetonitrile | Shaking | QuEChERS | 0.04–2.9 ng g−1 | Nd | [95] |
11 mycotoxins | 2017 | USA | Infant cereals | Acetonitrile/water/formic acid, (80:19.9:0.1, v/v/v) | Shaking | Nd | 0.01−10.0 ng g−1 | 0.05–50 ng g–1 | [84] |
12 Fusarium mycotoxins | 2017 | Germany | Beer | Acetonitrile/water (70:30, v/v) Acetonitrile/water (84:16, v/v) | Vortex | SPE cartridge | 0.05–6.9 µg L−1 | 0.15–20 µg L−1 | [87] |
AFB1 OTA FB1 DON T2 HT-2 ZEA | 2017 | Italy | Cereal-based samples | Acetonitrile–water–acetic acid (79:20:1, v/v/v) | Shaking | Nd | 0.06–0.13 µg kg−1fo r AFB1 0.4–0.8 µg kg−1 for OTA 8−16 µg kg−1 for FB1 20 µg kg−1 for DON 4–8 µg kg−1 for T–2 20 µg kg−1 for HT–2 1.6–3.2 µg kg−1 for ZEA | Nd | [96] |
13 mycotoxins | 2017 | Korea | Cereal grains | Methanol 80%, containing 0.5% acetic acid | Shaking | IAC | 0.1−18.1 ng/g | 0.4–54.8 ng/g | [97] |
20 mycotoxins | 2019 | Korea | Soybean Paste | Methanol–water (60:40, v/v) and PBS | Blending | IAC | 0.06–4.68 µg kg−1 | 0.17−13.24 | [49] |
6 Alternaria toxins | 2019 | China | Grapes | Acetonitrile and dispersive solid phase extraction | Shaking | QuEChERS | 0.03–0.21 µg kg−1 | 0.09–0.48 µg kg−1 | [77] |
AFs, ZEA, α-ZOL | 2019 | Spain | Vegetable oils | Acetonitrile | Shaking | QuEChERS | Nd | 0.5 μg kg−1 for AFs 1 μg kg−1 for ZEA and α-ZOL | [93] |
Mycotoxin | Label Used | Commodity | Sensitivity | Reference |
---|---|---|---|---|
Deoxynivalenol (DON) Zearalenone (ZEA) T-2/H-T2-toxin | Epoxy-functionalized silica coated QDs | Barley | 1000 µg/kg 80 µg/kg 80 µg/kg | [106] |
Aflatoxin B1 (AFB1) Zearalenone (ZEA) Deoxynivalenol (DON) | Monoclonal antibodies (mAbs) with the conjugates bovine serum albumin (BSA) | Wheat and maize | 0.05 μg/kg 1 μg/kg 3 μg/kg | [107] |
Fumonisin B1 (FB1) Deoxynivalenol (DON) | Gold nanoparticles (AuNPs) | Maize | 2.0 ng mL−1 40 ng mL−1 | [108] |
Deoxynivalenol (DON) T-2 toxin (T-2) Zearalenone (ZEN) | Amorphous carbon nanoparticles (ACNPs) | Maize | 20 µg/kg 13 µg/kg 1 µg/kg | [109] |
Aflatoxin B1 (AFB1) Zearalenone (ZEN) Deoxynivalenol (DON) | CdSe/SiO2 quantum dot microbeads | Feedstuff | 10 pg mL−1 80 pg mL−1 500 pg mL−1 | [110] |
Zearalenone (ZEN) | Antibody-labeled quantum dot sumicro beads | Corn | 3.6 mg mL−1 | [111] |
Fumonisins (FUs) | CdSe/ZnS QD + GNP | Maize | 62.5 μg/kg | [102] |
Mycotoxin | Recognition Element | Transducer/Technique | Food | Detection Limit | Reference |
---|---|---|---|---|---|
AFB1 | Organic framework composite | Piezoelectric (QCM) | Peanut, pistachio, rice, and wheat | 2.8 pg mL−1 | [116] |
AFB1 | Antibody | Impedimetric (EIS) | Corn | 0.05 ng mL−1 | [117] |
AFB1 | Antibody | Piezoelectric (EQCM) | Cereal | 8 pg mL−1 | [118] |
AFB1 | Antibody | Piezoelectric (QCM) | Peanut | 0.83 ng kg−1 | [119] |
AFB1 | Antibody | Potentiometric (DPV) | Corn powder | 3.5 pg mL−1 | [120] |
Cyclopiazonic acid | Antibody | Optical (SPR) | Maize and cheese | 0.29 mg mL−1 | [121] |
DON, ZEN, T-2toxin | Antibody | Optical (SPR) | Wheat | 15μg/kg−1 24 μg/kg−1 12 μg/kg−1 | [122] |
HT-2 toxin, T-2 toxin, AFM1 | Antibody | Amperometric (CV) | Human urine | 0.4 ng mL−1 1 ng mL−1 0.3 ng mL−1 | [113] |
T-2 toxin, T-2 toxin-3-glucoside (T2-G) | Antibody | Optical (iSPR) | Wheat | 1.2 ng mL−1 | [123] |
OTA | Aptamer | Impedimetric (EIS) | Grape and commodities | 0.030 ng mL−1 | [124] |
OTA | Aptamer | SPR | Wine and peanut oil | 0.005 ng mL−1 | [125] |
OTA | Antibody | Piezoelectric (QCM) | Buffer | 17.2 ng mL−1 | [111] |
OTA | Aptamer | Amperometric (CV) | Red wine | 0.23 pg mL−1 | [126] |
OTA | Antibody | Piezoelectric (QCM) | Red wine | 0.16 ng mL−1 | [127] |
OTA | Antibody | Optical (SPR) | Coffee | 3.8 ng mL−1 | [128] |
OTA | Black phosphorene | Potentiometric (DPV) | Grape juice and red wine | 0.18 μg mL−1 | [129] |
OTA | Antibody | Piezoelectric (QCM-D) | Red wine | 0.16 ng mL−1 | [127] |
OTA, AFM1 | Antibody | Potentiometric (CV) | Red wine and milk | 0.15 ng mL−1 3.04 ng mL−1 | [130] |
AFM1 | Antibody | Optical (SPR) | Milk | 18 pg mL−1 | [131] |
PAT | Aptamer | Potentiometric (EIS/DPV) | Juice | 0.27 pg mL−1 | [132] |
PAT | Aptamer | Impedimetric (EIS) | Apple juice | 2.8 ng L−1 | [133] |
ZEN | Aptamer | Amperometric (CV/DPV) | Maize | 0.17 pg mL−1 | [134] |
ZEN | Antibody | Amperometric (CV/DPV) | Corn and corn products | 1.5 pg mL−1 | [135] |
ZEN | Aptamer | Potentiometric (CV/DPV) | Maize | 0.105 pg mL−1 | [136] |
DON, T-2, ZEA, FB1 | Antibody | Optical (iSPR) | Barley | 64 µg kg−1, 26 µg kg−1, 96 µg kg−1, 13 µg kg−1 | [137] |
Biosensors | Advantages | Limitations | Reference |
---|---|---|---|
Impedimetric | High sensitivity and selectivity, time-efficient, simple operation, fast response, mobility due to portable instrumentation, miniaturization | Complex construction, expensive labeling markers | [25,124,147] |
Potentiometric | Reduced analysis time, mobility due to portable instrumentation, miniaturization, high sensitivity and selectivity, use without sample treatment | The sensitivity and lifetime are seriously influenced by factors such as temperature, pH, immobilization support, and immunological cross-reaction | [129,147,148] |
Amperometric | Mobility due to portable instrumentation, miniaturization, high sensitivity and selectivity | Regeneration between measurements | [147] |
Surface plasmon resonance | High specificity and sensitivity, small size and cost-efficiency, direct, real-time analysis and detection without label, development of portable devices | The broad practical application is still under development | [25,144] |
Quartz crystal microbalance | Low cost with high sensitivity, selectivity, and possibility of reuse, real-time output, and label- or radiation-free entities, development of portable devices | Requirement of a relatively high background signal relative to the signal-on assay formation | [119,149] |
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Agriopoulou, S.; Stamatelopoulou, E.; Varzakas, T. Advances in Analysis and Detection of Major Mycotoxins in Foods. Foods 2020, 9, 518. https://doi.org/10.3390/foods9040518
Agriopoulou S, Stamatelopoulou E, Varzakas T. Advances in Analysis and Detection of Major Mycotoxins in Foods. Foods. 2020; 9(4):518. https://doi.org/10.3390/foods9040518
Chicago/Turabian StyleAgriopoulou, Sofia, Eygenia Stamatelopoulou, and Theodoros Varzakas. 2020. "Advances in Analysis and Detection of Major Mycotoxins in Foods" Foods 9, no. 4: 518. https://doi.org/10.3390/foods9040518
APA StyleAgriopoulou, S., Stamatelopoulou, E., & Varzakas, T. (2020). Advances in Analysis and Detection of Major Mycotoxins in Foods. Foods, 9(4), 518. https://doi.org/10.3390/foods9040518