Exploring Formation and Control of Hazards in Thermal Processing for Food Safety
Abstract
:1. Introduction
2. Polycyclic Aromatic Hydrocarbons (PAHs)
2.1. Formation Pathways
2.2. Influencing Factors
2.2.1. Food Raw Materials
2.2.2. Food Composition
2.2.3. Processing Patterns
2.3. Tracing Approaches
2.4. Control Measures
2.4.1. Mitigation Measures Prior to Thermal Processing
2.4.2. Optimization of Thermal Processing Techniques
2.4.3. Reduction Measures After Thermal Processing
3. Heterocyclic Aromatic Amines (HAAs)
3.1. Formation Pathways
3.1.1. Formation of Quinoxaline Heterocyclic Amines
3.1.2. Formation of Pyridine Heterocyclic Amines
3.1.3. Formation of Aminocarboline Heterocyclic Amines
3.2. Influencing Factors
3.2.1. Precursor Substances
3.2.2. Food Composition
3.2.3. Processing Patterns
3.2.4. Exogenous Substances
3.3. Tracing Approaches
3.4. Control Measures
3.4.1. Control of Precursor Substances
3.4.2. Optimization of Processing Patterns
3.4.3. Addition of Exogenous Substances
4. Furan
4.1. Formation Pathways
4.2. Influencing Factors
4.2.1. Processing Patterns
4.2.2. Precursor Substances
4.2.3. Exogenous Substances
4.3. Tracing Approaches
4.4. Control Measures
4.4.1. Optimize the Processing Patterns
4.4.2. Control of Precursor Substances
4.4.3. Addition of Exogenous Substances
4.4.4. Control of Storage Conditions
5. Acrylamide (AA)
5.1. Formation Pathways
5.1.1. Asparagine Pathway (Asn)
5.1.2. Non-Asparagine Pathways
5.2. Influencing Factors
5.2.1. Processing Patterns
5.2.2. Precursor Substances
5.2.3. Exogenous Substances
5.3. Tracing Approaches
5.4. Control Measures
5.4.1. Control Precursor Substances
5.4.2. Optimize Processing Patterns
5.4.3. Addition of Exogenous Substances
6. Trans Fatty Acids (TFAs)
6.1. Formation Pathways
6.1.1. Formation Mechanism of Monounsaturated Trans Fatty Acids
6.1.2. Formation Mechanism of Polyunsaturated Trans Fatty Acids
6.2. Influencing Factors
6.2.1. Processing Patterns
6.2.2. Precursor Substances
6.2.3. Exogenous Substances
6.3. Tracing Approaches
6.4. Control Measures
7. Advanced Glycation End-Products (AGEs)
7.1. Formation Pathways
7.2. Influencing Factors
7.2.1. Precursor Substances
7.2.2. Processing Patterns
7.2.3. Storage Conditions
7.2.4. Exogenous Substances
7.3. Tracing Approaches
7.4. Control Measures
7.4.1. Control Precursor Substances
7.4.2. Optimize Processing Patterns
7.4.3. Addition of Exogenous Substances
7.4.4. Control of Storage Conditions
8. Sterol Oxides
8.1. Formation Pathways
8.1.1. COPs Formation Pathways
8.1.2. POPs Formation Pathways
8.2. Influencing Factors
8.2.1. Processing Patterns
8.2.2. Food Components
8.2.3. Environmental Factors
8.2.4. Exogenous Substances
8.3. Tracing Approaches
8.4. Control Measures
8.4.1. Selection of Appropriate Raw Material
8.4.2. Optimize Processing Patterns
8.4.3. Addition of Exogenous Substances
8.4.4. Control of Storage Conditions
9. Conclusions and Outlook
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Food Type | Analytical Techniques | Validation Parameters | References |
---|---|---|---|
Smoked bacon | RP-HPLC-(+) ESI/MS | LOD: 0.1–0.25 μg/kg LOQ: 0.50 μg/kg Recovery: 74–100% | [58] |
Tea leaves | UPLC | LOD: 1.69–9.97 ng/kg LOQ: 5.12–30.21 ng/kg Recovery: 84.8–105.4% | [47] |
Tea and coffee | MSPE-GC–MS/MS | LOD: 0.1–0.3 ng/L Recovery: 84.5–112.6% | [48] |
Shrimp | Surface-enhanced Raman scattering (SERS) sensor (AuNPs) | LOD: 0.12 ng/mL RSD: 6.21% | [49] |
Chicken | SERS sensor based on gold nanostars@reduced graphene oxide (AuNS@rGO) | LOD: 0.0028 μg/L Recovery: 89.2–100.8% RSD: 2.42–6.53% | [50] |
Waters | Electroanalytical method on molecular imprinted polymer-glassy carbon electrode (MIP-GCE) | LOD: 12 nM LOQ: 40 nM | [59] |
Waters | Novel imprinted polymer nanofilm sensor | LOD: 0.001 ng/L LOQ: 0.01–0.1 μg/kg Recovery: 83–110% | [60] |
Waters | A novel hybrid plasmonic platform based on the synergetic combination of a molecularly imprinted polymer (MIP) thin film with Au nanoparticle (NPs) assemblies | LOD: 1 nM Recovery: 83–110% | [61] |
Milk | SPME-GC-FID | LOD: 0.003–0.020 ng/mL Recovery: 92.15–106.64% | [37] |
Food Type | Analytical Techniques | Validation Parameters | References |
---|---|---|---|
Freeze-dried pork and pork jerky | Reversed-phase (RP)-UPLC-MS/MS | LOD: 0.005–0.05 μg/kg LOQ: 0.01–0.1 μg/kg Recovery: 59.4–104% | [89] |
Pork patties | Fluorescence method | LOD: 0.224 μg/kg Recovery: 87.6–97.8% | [82] |
Cantonese mooncake | MSPE-UPLC-MS | LOD: 0.01–7.01 ng/g Recovery: 62.12–126.86% | [76] |
Fried chicken drumsticks | HPLC-MS | [8] | |
Roast beef | HAAs prediction model based on genetic algorithm and support vector regression | LOD: 0.028–0.214 ng/g LOQ: 0.097–0.625 ng/g Recovery: 101.8–105.6% | [77] |
Roasted and pan- fried pork, and beef patties | HPLC-quadrupole-orbitrap HRMS | LOD: 0.02–0.6 μg/kg LOQ: 0.05–2.0 μg/kg Recovery: 71.3–114.8% | [90] |
Roasted pork, fried chicken, etc. | HPLC-MS/MS | LOD: 0.020–0.375 μg/kg Recovery: 82.0–109.5% | [70] |
Bread, cakes, and French fries | MSPE-HPLC-MS/MS | LOD: 0.012–0.210 μg/kg LOQ: 0.043–0.650 μg/kg Recovery: 90.4–102.8% | [73] |
Food Type | Analytical Techniques | Validation Parameters | References |
---|---|---|---|
Coffee | GC-MS | LOQ: 5 μg/kg Recovery: 80–110% | [103] |
Semi-solid and paste-type foods | HS–SPME–GC/MS | LOD: 0.18 μg/kg LOQ: 0.54 μg/kg | [109] |
Eight food matrices | HS–SPME–GC/MS | LOD: 0.01–0.02 μg/kg LOQ: 0.04–0.06 μg/kg | [110] |
Various food samples | HS–SPME–Arrow GC–MS/MS | LOD: 0.001–1.071 μg/kg LOQ: 0.003–3.571 μg/kg | [105] |
Thermally processed Mopane worms, corn, and peanuts | HS–SPME–GC/FID | LOD: 0.54–3.5 μg/kg LOQ: 1.8–12 μg/kg | [111] |
Coffee | HS–GC/MS | LOD: 1.5–6.0 μg/kg LOQ: 5–20 μg/kg | [112] |
Five types of nuts | HS–SPME–GC/MS | LOD: 0.09 μg/kg LOQ: 0.27 μg/kg | [113] |
Dark chocolate | HS–SPME–GC/MS | LOD: 0.5 μg/kg LOQ: 1.5 μg/kg | [114] |
Coffee | HS–SPME–GC/MS | LOD: 0.02 μg/kg LOQ: 0.06 μg/kg | [115] |
Dried fruits and roasted nuts | HS–SPME–GC/MS | LOD: 0.012–0.425 μg/kg LOQ: 0.038–1.275 μg/kg | [116] |
Food Type | Analytical Techniques | Validation Parameters | References |
---|---|---|---|
Roasted almonds, raw ground pork, etc. | UPLC-MS/MS | LOD: 0.63 μg/L LOQ: 2.1 μg/L Recovery: 98.16–103.76% | [138] |
Cookies, bread, potato crisps, milk, etc. | Novel colorimetric analysis and UV-Vis spectral sensing platform | LOD: 0.16 μM | [131] |
Coffee, biscuit | Filtration- assisted optical detection | LOD: 14 μM | [145] |
White bread | Carbon quantum dots | LOD: 2.6 μM | [146] |
Potato chips | Dex-MMIPs/ HPLC-UV | LOD: 0.28 μM | [139] |
Roasted nut samples | Three-way junction-engineered LC aptasensor | LOD: 0.106 amol/L Recovery: 96.84–99.61% | [137] |
Potato chips samples | LC/MS-MS and FTIR | [140] | |
Biscuits, potato chips, etc. | UPLC-MS/MS | LOD: 0.63 μg/L LOQ: 2.1 μg/L Recovery: 98.16–103.76% | [138] |
Roasted chicory sample | LC-MS/MS | LOD: 5 μg/kg LOQ: 15 μg/L Recovery: 95.86–103.06% | [134] |
Food Type | Analytical Techniques | Validation Parameters | References |
---|---|---|---|
Milk | NIR | R2CV = 0.78 R2V = 0.37 | [172] |
Milk | Miniaturized near-infrared spectrophotometer | RPD = 2.0–2.9 | [173] |
Muffalo milk | 2-dimensional gas chromatography | [174] | |
Butters and margarines | Mid- and near-infrared spectrometers | SEP ≤ 2.62 RPD: 1.4–15.1 RER: 5.7–56.9 | [175] |
Rapeseed and soybean oil | Raman spectroscopy based on competitive adaptive reweighted sampling coupled with support vector regression | [176] | |
Edible oils | Raman spectroscopy and chemometric methods | Rcv = 0.9598, Rp = 0.9634, RMSEC = 0.351 | [177] |
Oleic and elaidic acids | Raman spectroscopy | [178] | |
Edible oils | Capillary electromigration methods | [179] | |
Edible oils | 1H NMR spectroscopy | [180] | |
Meat | GC-FID | [181] | |
Commercial instant noodle | GC | [182] | |
Vegetable oils | GC-MS-MIQ | [183] |
Food Type | Analytical Techniques | Validation Parameters | References |
---|---|---|---|
Patties | HPLC-MS/MS | LOD: 0.19–3.58 μmol/kg LOQ: 0.56–10.74 mg/kg | [215] |
Roasted chicken | ESI-LC-MS/MS | LOD: 0.30–19.02 ng/mL LOQ: 0.87–57.06 ng/mL Recovery: 71–110% | [223] |
Industrial bread | LC-Electrospray Ionization-MS/MS | LOD: 0.02–0.17 mg/kg LOQ: 0.03–0.57 mg/kg | [224] |
Butter cookies | HPLC-QqQ-MS/MS | [225] | |
Roast/Grilled meat | UPLC-MS/MS | LOD: 0.3–5.5 μg/L LOQ: 0.9–6.3 μg/L | [217] |
Beef | High-throughput DART-MS/MS | LOD: 0.15 μg/g LOQ: 0.6 μg/g | [216] |
Milk | UPLC-DAD | LOD: 0.50 g/g protein | [226] |
Dairy products | HPLC-MS/MS | LOD: 0.1 μg/kg | [227] |
Minced pork | HPLC-MS/MS | LOD: 4–5 g/L(CML); 12–15 g/L(CEL) | [228] |
Mutton | LC-MS/MS | LOD: 3.6 ng/mL (CML); 1.9 ng/mL (CEL) | [229] |
Bread | UPLC-MS/MS | LOD: 0.75 μg/kg (CML); 2.5 μg/kg (CEL) | [230] |
Roasted beef patties | UPLC-MS/MS | LOD: 0.052 ng/g (CML); 0.098 ng/g (CEL) | [231] |
Sterilized milk | UPLC-MS/MS | LOD: 0.05 mg/kg (CML) | [232] |
Infant formula | ELISA | LOD: 550–600 ng/mL (CML) | [233] |
Technology | Sample | Main Results | References |
---|---|---|---|
HPP | Table olives | HPP did not contribute to acrylamide formation. | [265] |
HPP | Black garlic | HPP increased Maillard reaction. | [266] |
US | Bovine serum albumin | US unfolded or enhanced aggregation behavior in protein samples, altering accessibility of lysine and arginine. | [267] |
PEF | In vitro and in vivo assays | PEF reduced 4.8% the AGE content in diabetic mices. | [268] |
Frying assisted with US and PEF | Potato chips | Use of US decreased the acrylamide content; the use of US coupled with PEF decreased even further the acrylamide content. | [269] |
Air Frying | Chicken breast and grape seed extracts | Air frying combined with grape seed extracts inhibited the formation of AGEs (CML and CEL), its precursors (GO, MGO) and increased oxidative stability. Air frying, even without the addition of grape seed extracts, promoted less CML, CEL, GO and MGO formation. | [270] |
Vacuum Frying | French fries and frying oil | Reduced formation of acrylamide content. | [271] |
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Liu, Z.; Gao, S.; Yuan, Z.; Yang, R.; Zhang, X.; El-Mesery, H.S.; Dai, X.; Lu, W.; Xu, R. Exploring Formation and Control of Hazards in Thermal Processing for Food Safety. Foods 2025, 14, 2168. https://doi.org/10.3390/foods14132168
Liu Z, Gao S, Yuan Z, Yang R, Zhang X, El-Mesery HS, Dai X, Lu W, Xu R. Exploring Formation and Control of Hazards in Thermal Processing for Food Safety. Foods. 2025; 14(13):2168. https://doi.org/10.3390/foods14132168
Chicago/Turabian StyleLiu, Zeyan, Shujie Gao, Zhecong Yuan, Renqing Yang, Xinai Zhang, Hany S. El-Mesery, Xiaoli Dai, Wenjie Lu, and Rongjin Xu. 2025. "Exploring Formation and Control of Hazards in Thermal Processing for Food Safety" Foods 14, no. 13: 2168. https://doi.org/10.3390/foods14132168
APA StyleLiu, Z., Gao, S., Yuan, Z., Yang, R., Zhang, X., El-Mesery, H. S., Dai, X., Lu, W., & Xu, R. (2025). Exploring Formation and Control of Hazards in Thermal Processing for Food Safety. Foods, 14(13), 2168. https://doi.org/10.3390/foods14132168