Submitted:
15 June 2026
Posted:
16 June 2026
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Methodology
3. Major Chemical Classes Detected in SEA Foods
4. Microchemical Sample Preparation Strategies
4.1. Miniaturized QuEChERS Approaches
4.2. Advanced Microextraction Techniques
4.3. Green and Sustainable Microextraction
5. Advances in Instrumental Detection
5.1. UHPLC–MS/MS Developments
5.2. HRMS
5.3. GC–MS/MS for Volatile Fungicides
6. Comparison Between Microchemical and Conventional Methods
7. Current Challenges, Analytical Gaps, and Future Perspectives
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgement
Conflicts of Interest
Abbreviations
| AGREE | Analytical GREEnness |
| CS2 | Carbon disulfide |
| DES | Deep eutectic solvents |
| DI-SPME | Direct immersion solid-phase microextraction |
| DLLME | Dispersive liquid–liquid microextraction |
| DMI | Demethylation inhibitor |
| d-SPE | Dispersive solid-phase extraction |
| ECD | Electron capture detector |
| EFSA | European Food Safety Authority |
| EMR-Lipid | Enhanced matrix removal–lipid |
| ETU | Ethylene thiourea |
| GAC | Green Analytical Chemistry |
| GC | Gas chromatography |
| GC-MS | Gas chromatography–mass spectrometry |
| GC-MS/MS | Gas chromatography–tandem mass spectrometry |
| GCB | Graphitized carbon black |
| HF-LPME | Hollow-fiber liquid-phase microextraction |
| HRMS | High-resolution mass spectrometry |
| HS-SPME | Headspace solid-phase microextraction |
| HPLC | High-performance liquid chromatography |
| IDMS | Isotope dilution mass spectrometry |
| IL | Ionic liquid |
| LC | Liquid chromatography |
| LC-HRMS | Liquid chromatography–high-resolution mass spectrometry |
| LC-MS/MS | Liquid chromatography–tandem mass spectrometry |
| LLE | Liquid–liquid extraction |
| LOQ | Limit of quantification |
| LPME | Liquid-phase microextraction |
| MeCN | Acetonitrile |
| MOF | Metal–organic framework |
| MRL | Maximum residue limit |
| MRM | Multiple reaction monitoring |
| MS | Mass spectrometry |
| MS/MS | Tandem mass spectrometry |
| MSPE | Magnetic solid-phase extraction |
| MSTFA | N-methyl-N-trimethylsilyl-trifluoroacetamide |
| NTS | Non-target screening |
| PSA | Primary–secondary amine |
| PT-PSE | Pipette-tip solid-phase extraction |
| PTU | Propylene thiourea |
| Q-TOF | Quadrupole time-of-flight |
| QqQ | Triple quadrupole |
| QoI | Quinone outside inhibitor |
| QuEChERS | Quick, Easy, Cheap, Effective, Rugged, and Safe |
| SDHI | Succinate dehydrogenase inhibitor |
| SDME | Single-drop microextraction |
| SEA | Southeast Asia |
| SBSE | Stir bar sorptive extraction |
| sMRM | Scheduled multiple reaction monitoring |
| SPE | Solid-phase extraction |
| SPME | Solid-phase microextraction |
| TOF | Time-of-flight |
| UHPLC | Ultra-high-performance liquid chromatography |
| UPHLC-MS/MS | Ultra-high-performance liquid chromatography–tandem mass spectrometry |
| UPLC | Ultra-performance liquid chromatography |
| UPLC-Orbitrap MS | Ultra-performance liquid chromatography–Orbitrap mass spectrometry |
| UPLC-MS/MS | Ultra-performance liquid chromatography–tandem mass spectrometry |
| UAME | Ultrasound-assisted microextraction |
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| Fungicide class | Representative actives commonly relevant to SEA foods (examples) | Chemical structure | Typical SEA foods/commodities where residues are often reported | SEA region signals (examples of monitoring contexts) | Indicative polarity (logP range; qualitative) | Example MRLs (EU examples from 2019–2026 literature/regulatory science) |
|---|---|---|---|---|---|---|
| Azoles (DMI; triazoles/imidazoles) | Tebuconazole, Difenoconazole |
Tebuconazole Difenoconazole |
Leafy greens, chili/pepper, tomatoes, rice-derived products, tropical fruits (mango), herbs/spices [24] | Vietnam vegetable monitoring (Mekong/Central areas), Malaysia highland vegetables, regional export chains for fruit/veg [25] | 3.5–4.5 (moderately hydrophobic; medium polarity) |
Difenoconazole (wheat/rye grain): proposed 0.3 mg/kg [26] |
| Strobilurins (QoI inhibitors) | Azoxystrobin, Pyraclostrobin |
Azoxystrobin Pyraclostrobin |
Fruits/vegetables (incl. peppers, leafy greens), rice, plantation crops; postharvest protection in some chains [24] | Reported frequently in multi-residue surveys in vegetables and specialty crops (regional monitoring contexts) [27] | 3.5–6.0 (moderate to hydrophobic) | Azoxystrobin (import tolerance examples exist for tropical fruits such as mango/oil palm fruit in EFSA assessments; commodity-specific values apply) [28] |
| SDHI fungicides | Boscalid, Fluopyram, Benzovindiflupyr |
Boscalid Fluopyram Benzovindiflupyr |
Vegetables (broccoli, leafy greens), fruits, herbs; intensive horticulture system [29] | Malaysia vegetable surveys and intensive horticulture contexts; Vietnam vegetable monitoring contexts [27] | 3.5–5.5 (often hydrophobic; low-to-medium polarity) | Boscalid (pomegranates): proposed MRL increase 0.01 into 2.0 mg/kg [30]. Fluopyram (broccoli): proposed 0.4 mg/kg [29]. |
| Benzimidazoles | Carbendazim, Thiophanate-methy |
Carbendazim Thiophanate-methy |
Leafy veg, fruits, peppers/spices; legacy use signals still appear in some monitoring datasets [24] | Malaysia vegetable studies report carbendazim among common residues; also seen in broader monitoring literature [31] | 1.0–2.0 (more polar than azoles/QoIs; moderate polarity) | EU risk management for benzimidazoles includes updated EFSA considerations (import tolerances/legacy residues; commodity-specific) [32] |
| Dithiocarbamates | Mancozeb | ![]() |
Tropical fruits (bananas, mango), vegetables, leafy greens; plantation agriculture contexts [33] | Regional relevance in plantations and vegetable production; exposure/monitoring discussions widely documented [33] |
logP often not meaningful for metal-complex mixtures; analytical behavior dominated by CS2 release (indirect) or newer speciation approaches [34] | EFSA has multiple recent MRL assessments for dithiocarbamates; example EFSA documentation discusses MRL setting/updates and scenarios [35] |
| Emerging fungicides & metabolites | Cyazofamid and metabolite CCIM |
Cyazofamid |
High-value vegetables (tomato/potato systems), specialty produce; detection increasing with LC-HRMS screening and expanded target lists | Emerging signals often appear when labs adopt LC-QTOF/Orbitrap suspect screening and updated MRM libraries; pepper/veg studies commonly list diverse fungicides [36] | Typically 3– more than 5 for many newer actives (often hydrophobic); metabolites may be less hydrophobic and more mobile | EU regulatory lists show ongoing MRL updates for multiple newer actives (commodity-specific amendments in recent OJ/EU regulations) |
| Instrument approach | Best suited fungicide classes/compounds | Main strengths | Main limitations | Typical analytical/regulatory usefulness | Representative SEA food examples | Indicate MRL examples |
|---|---|---|---|---|---|---|
| HPLC-UV/DAD/FLD | Simple targeted assays for selected benzimidazoles or postharvest fungicides | Lower cost, widely available, useful for single/few analytes | Lower selectivity than MS; matrix interference; weak for large multiclass panels; usually not preferred for confirmatory multiresidue work in complex foods | Screening or legacy routine assays where analyte scope is narrow | Applicable to targeted assays in fruits and vegetables, but increasingly displaced by LC-MS/MS in regional monitoring workflow | Useful only if method LOQ is comfortably below the relevant MRL; less ideal for multiclass compliance work [82] |
| GC-MS/MS | Volatile or semi-volatile, thermally stable fungicides such as captan, chlorothalonil, folpet, some dithiocarbamate-related workflows after derivatization/indirect approaches | High selectivity and sensitivity for amenable analytes; robust for confirmatory residue analysis | Not suitable for many polar/thermolabile fungicides; derivatization or indirect chemistry may be needed; matrix enhancement/suppression can remain significant | Confirmatory analysis for GC-amenable fungicides; often complementary to LC-MS/MS in multiclass methods | Thai Chinese kale and yard-long bean samples were analyzed by QuEChERS-GC-MS/MS; the study reported detectable residues including captan and emphasized the relevance of cooking for residue reduction in locally consumed vegetables [83] | ASEAN/Codex examples: onion bulb–iprodione 0.2 mg/kg in the ASEAN crops database; dithiocarbamate examples also appear for several ASEAN vegetables/fruits [84] |
| LC-MS/MS | Broadest routine scope for triazoles, strobilurins, SDHIs, benzimidazoles, phenylamides; e.g., difenoconazole, azoxystrobin, carbendazim, metalaxyl, boscalid, fluopyram, tebuconazole | High sensitivity, selectivity, wide linear range, strong fit for regulated multiresidue monitoring | Matrix effects remain substantial; method optimization and matrix-matched calibration are often necessary; expensive instrumentation | Gold-standard confirmatory and quantitative platform for routine MRL compliance | Central Vietnam monitoring found residues in 81% of 290 vegetable samples and 23% above MRLs; difenoconazole was among the most frequently detected compounds. Mekong Delta vegetables analyzed by modified QuEChERS-LC-MS/MS showed 59% samples above MRLs [8]. Filipino Cavendish bananas analyzed by LC-MS/MS plus GC-MS/MS frequently contained azoxystrobin, carbendazim, imazalil, and thiabendazole [27] | Codex examples particularly relevant to SEA trade crops: banana–azoxystrobin 2 mg/kg, banana–tebuconazole 1.5 mg/kg in ASEAN crops database, pineapple–carbendazim 5 mg/kg, rice (husked)–carbendazim 2 mg/kg, chili pepper–difenoconazole 0.9 mg/kg [82] |
| UHPLC-MS/MS / high-throughput LC-MS/MS | Same fungicide scope as LC-MS/MS, but optimized for faster runs and higher sample throughput | Shorter analysis time, better peak capacity, lower solvent use, good fit for surveillance laboratories | Still requires careful cleanup, matrix compensation, and validation; throughput gains may trade off against breadth in some workflows | Best for large monitoring programs and dense sample sets such as vegetables, chili powder, rice, tea | High-throughput LC-MS/MS has recently been validated for complex chilli powder matrices; recent food-method papers also show QuEChERS-UHPLC-MS/MS detecting fungicides efficiently in fruit matrices [85], where fungicides often dominate residue findings. These workflows are directly relevant to Southeast Asian spice and produce surveillance [86] | Particularly useful when required LOQs must stay below stringent MRLs in processed matrices such as spices, teas, and rice-based products [38] |
| LC-HRMS / UHPLC-QTOF / Orbitrap HRMS | Targeted multiclass fungicides plus suspect/non-target screening of metabolites and transformation products | Simultaneous targeted and suspect screening; better for retrospective data mining and unknowns; valuable where fungicide metabolites or emerging actives are missed by fixed target lists | More complex data processing; quantification and routine accreditation can be harder than triple quadrupole workflows; cost and expertise barriers | Excellent secondary platform for broad surveillance, discovery, and retrospective review; less commonly the first-line routine regulatory method | HRMS studies have shown simultaneous target analysis and suspect screening in fruits, reporting both confirmed residues and numerous tentative identifications beyond standard target panels; this is useful for tropical fruit export chains relevant to SEA [20] | Supports risk monitoring beyond current MRL lists by revealing transformation products and non-target residues that may not yet be in routine methods [87] |
| Ambient ionization MS (for example TAPI-TOF/MS) | Rapid targeted screening of selected pesticide/fungicide panels on simpler extracts | Very fast, minimal sample preparation, potentially deployable for triage screening | Lower maturity for formal MRL enforcement; often narrower scope and weaker robustness than LC-MS/MS confirmatory methods | Rapid screening before confirmatory LC-MS/MS | A 2025 tea study using TAPI-TOF/MS with LC-MS/MS cross-checking reported a 66.7% detection rate across tested tea samples, although azoxystrobin was not detected in that sample set. This approach is relevant to tea-producing/consuming SEA markets [88] | Best viewed as a pre-screening tool; positive or borderline findings should still be confirmed against the applicable MRL using validated confirmatory methods [89] |
| SERS and other Raman-based nanosensors | Fast screening of selected fungicides/pesticides; promising for surface residues and portable testing | Very rapid, low sample volume, field potential, increasingly improved by machine learning and substrate engineering | Reproducibility, substrate standardization, matrix interference, quantitation robustness, and regulatory acceptance remain limiting |
Field or marketplace screening; best coupled with confirmatory LC-MS/MS/GC-MS/MS | Particularly attractive for rapid screening of tropical fruits, leafy vegetables, herbs, and spices sold in decentralized SEA supply chains, though published regional fungicide-validation datasets remain fewer than LC-MS/MS datasets | Usually not used alone for official MRL compliance; best for screening below action thresholds followed by confirmatory testing [90] |
| Hyperspectral / NIR / imaging systems with machine learning | Non-destructive prediction of residue presence or contamination class, often for surface-associated residue | Fast, non-destructive, image-compatible, potentially portable and scalable | Usually indirect rather than analyte-specific; requires large calibration sets; weaker for definitive quantitation and legal enforcement | Rapid prescreening and sorting, not stand-alone compliance testing | Highly relevant for high-volume Southeast Asian produce chains such as chili, leafy greens, mango, banana, and pineapple, but still needs confirmatory chromatographic follow-up for fungicide-specific decisions | Not appropriate as sole basis for MRL compliance decisions [91] |
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