Mycotoxins occurrence in dry herbs used for tea preparation: method validation, analysis of bulk samples and dietary risk assessment

Mycotoxins occurrence in dry herbs used for tea preparation: method validation, analysis of bulk samples and dietary risk assessment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mycotoxins occurrence in dry herbs used for tea preparation: method validation, analysis of bulk samples and dietary risk assessment Camila Suguiura Evangelista, Denise Carvalho Mello, Eloisa Dutra Caldas, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8376617/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract In this work, a multi-mycotoxin analytical method was validated for the determination of 15 mycotoxins and related metabolites in dry herbs commonly used for tea preparation. Samples were extracted using a modified QuEChERS procedure, and quantification was performed by UHPLC-MS/MS with matrix-matched calibration and isotope-labeled internal standards dilution. At the lowest spiking level, recoveries ranged from 82% (AFB 1 ) to 111% (FB 3 ). Repeatability and intermediate precision (RSD) were below 20% for all analytes across three fortification levels. Ninety-one samples representing 33 types of dry herbs were analyzed, of which 25.3% were positive (≥ LOQ) for at least one mycotoxin. Zearalenone (ZEN) was the most frequently detected analyte (13.2%), followed by fumonisin B 2 (FB 2 , 4.4%), aflatoxin B 1 (AFB 1 , 3.3%), and ochratoxin A (OTA, 3.3%). A chronic dietary risk assessment for FB 2 and total zearalenone (ZEN + α-zearalenol) indicate no health concern for tea consumers, with estimated intakes not exceeding 5% of the established Health-Based Guidance Values. dry herbs tea mycotoxins isotope-labeled internal standards dietary risk assessment Figures Figure 1 Figure 2 Figure 3 Introduction A diverse range of botanical materials, such as leaves, herbs, roots, flowers, seeds, bark, algae, fungi and lichen, usually dried, are used in tea preparation (EMA, 2006 , 2010 ). Those beverages are obtained through decoction, infusion or maceration in water of one or more plant part(s), usually supplied in bulk form or sachets (tea bags), (EMA, 2010 ). Herbal teas are used as an alternative therapy in several countries, and their diverse composition, rich in antioxidants and bioactive compounds, could be an important key to improving poor-quality diets worldwide (Gil-Serna et al., 2020 ; Poswal et al., 2019 ). In Brazil, herbal tea includes the product made from a plant species authorized for its preparation, whole, fragmented, or ground, with or without fermentation, toasted or not (Brazil, 2022a ). According to Brazilian legislation, herbal teas are regulated as food or as herbal medicines, depending on their characteristics and the allegations made. Only teas regulated as herbal medicines can claim medicinal use, since they are regulated in the same way as traditional medicines (ANVISA, 2022 ). However, products with therapeutic claims that are not authorized for food tea, and medicinal plants are commonly found in markets and fairs and are widely consumed in the country. At the international level, there are maximum limits (MLs) set for pesticides in tea and herbs(CODEX, 2025 ) Brazilian legislation requires monitoring the presence of residues and contaminants in herbs that could be used as medicinal plants or herbal medicines (Brazil, 2014 ), and MLs are set for aflatoxin B 1 (5 µg/kg) and total aflatoxins (20 µg/kg) in some dry herbs used as medicinal plants (Brazil, 2024a , 2024b ), and for total arsenic, cadmium and lead in tea and vegetables used in infusions under the food classification (Brazil, 2022b). Mycotoxigenic fungi may infect dry herbs throughout the production chain and may also be transferred to beverages prepared from contaminated herbal substances through the infusion and decoction (Jai et al., 2021 ; Pallarés et al., 2017 ; Yu et al., 2022 ). Aflatoxins, fumonisins, ochratoxin A, trichothecenes and zearalenone are the most relevant mycotoxins known, both for their toxicity and occurrence in food. Aflatoxins (AFB 1 , AFB 2 , AFG 1 and AFG 2 ) are hepatotoxic, carcinogenic (IARC, 2012 ), and fumonisins (FB 1 , FB 2 and FB 3 ) exposure have been linked to the prevalence of esophageal cancer and an increased risk of neural tube defects (Alizadeh et al., 2012 ; Gelineau-van Waes et al., 2009 ; Yu et al., 2021 ). FB 1 and ochratoxin A (nefrotoxic) were classified as possible human carcinogens (IARC, 1993 , 2002 ). Exposure to deoxynivalenol (DON), an important member of the tricothecene group, can cause intestinal toxicity (acute exposure), reproductive toxicity, hepatotoxicity and nephrotoxicity (chronic exposure), while zearalenone exerts strong estrogenic and anabolic effects (Ropejko & Twarużek, 2021 ; Zhang et al., 2024 ). Several authors reported the occurrence of residues and contaminants in dry herbs and infusions (Abd El-Aty et al., 2014 ; Cladière et al., 2018 ; Oliveira et al., 2018 ; Mello et al., 2024 ; Pallarés et al., 2022 ; WHO, 2007 ; Zhang et al., 2022 ). Due to the complexity of the dry herb matrix, methods used to analyze mycotoxins in these matrices often face problems with extraction efficiency, low recovery, matrix effects, and high limit of quantification (LOQ) (Cho et al., 2019 ; Cladière et al., 2018 ; Reinholds et al., 2019 ; Zhang et al., 2023 ; Zhou, Yan, Wu, et al., 2022). Methods involve extraction with organic solvents, clean-up (solid phase extraction, dispersive liquid-liquid microextraction, immunoaffinity columns, QuEChERS), concentration/dilution, and identification/quantification, mainly by liquid chromatography (LC) and mass spectrometry (MS) (Cho et al., 2019 ; Reinholds et al., 2019 ; Zhang et al., 2023 ; Zhou, Yan, Wu, et al., 2022). Although some validated methods are available, most are limited to a small number of dry herb types or restricted groups of mycotoxins (Fontana et al., 2024 ; Jai et al., 2021 ; Lu et al., 2022 ; Zhou, Yan, Wu, et al., 2022). To the best of our knowledge, only two studies reported the occurrence of mycotoxins in dry herbs in Brazil (Caldeirão et al., 2021 ; Fontana et al., 2024 ). Both methods used modified QuEChERS procedures, followed by LC-MS/MS analysis. This study aimed to optimize and validate a method for the simultaneous analysis of aflatoxins (AFB 1 , AFB 2 , AFG 1 and AFG 2 ), citreoviridin (CTV), deoxynivalenol (DON), 15-acetyldeoxynivalenol (15-AcDON), 3-acetyldeoxynivalenol (3-AcDON), deoxynivalenol-3-glucoside (D3G), fumonisins (FB 1 , FB 2 and FB 3 ), ochratoxin A, zearalenone (ZEN) and alfa-zearalenol (α-ZEL) in 33 different species of dry herbs commonly used for tea preparation, using isotope labeled internal standards and LC-MS/MS. Material and methods Chemicals and reagents HPLC-grade acetonitrile (ACN), supelclean primary secondary amine (PSA), supelclean C18, sodium chloride (NaCl, ≥ 99,5%), HPLC-grade methanol (MeOH, ≥ 99,9%), ammonium formate (97%) were purchased from Sigma-Aldrich (St. Louis, MO, USA); magnesium sulfate anhydrous (MgSO4) and formic acid from Supelco (Bellefonte, PA); ammonium acetate, sodium acetate anhydrous (NaOAc, 99.5%) and acetic acid from J.T Baker (Phillipsburg, USA); sulfuric acid (> 51%) from Vetec; HPLC-grade toluene (TOL) was obtained from Mallinckrodt Baker (Phillipsburg, USA); ethyl acetate (EtAc) from Merck (Darmstadt, Germany); Graphisized Carbon Black (GCB) from Dinâmica (Indaiatuba, SP, Brazil); ultrapure water obtained through a Milli-Q purification system from Millipore (Bedford, MA, USA); hydrophilic PTFE syringe filter (0.45 µm pore size) from Filtrilo (Colombo, PR, Brazil). Standards of AFB 1 (99.0%), AFB 2 (99.0%), AFG 1 (99.0%), AFG 2 (99.5%) and d1-deoxynivalenol (d1-DON, 107.2 µg/mL, 93.3%) were obtained from Sigma-Aldrich (St. Louis, MO, USA). CTV (97.0%) was from Enzo Life Sciences International Inc. (Farmingdale, NY, USA). 15-AcDON (98.8%), 3-AcDON (99.4%), D3G (96.0%), DON, (98.3%), FB 1 (98%), FB 2 (97.9%), FB 3 (98.5%), OTA (99.5%), ZEN (99.66%), α-ZEL, (98.7%), (13C17)-AFB 1 (99.0%), (13C17)-AFG 1 (99.0%), (13C34)-FB 1 (96.3%), (13C20)-OTA (98.7%), (13C18)-ZEN (98,8%) were from Biopure (Tulin, Austria). The aflatoxins stock solutions were prepared in TOL-ACN (9:1), CVT in EtAc, OTA in TOL-Hac (99:1), and fumonisins in ACN-water (50:50), while the remaining compounds were prepared in ACN. Monthly, the concentrations of aflatoxins (AFs), OTA, ZEN, DON, 3-AcDON, 15-AcDON, and CTV solutions were checked using UV spectrophotometry, according to Andrade et al. ( 2017 ). A maximum variation of 3% in the estimated concentration in relation to the first check was considered acceptable. Mixed working solutions of all analytes were prepared in ACN and all solutions were stored in amber vials at -20 ◦C. Figure S1 shows the structures of all the mycotoxins investigated in this study. Samples Ninety-one bulk samples (examples in Figure S2) of 33 different dry herbs commonly used for tea preparation were purchased from retail stores and compounding pharmacies in the Federal District, Brazil. Details of collected samples can be found in Table S1 (Supplementary Material), including dry herbs prepared from different plant parts (bark, leaf, stalk, seed, and/or flower). Upon arrival at the laboratory, samples were stored at room temperature, and depending on the stiffness of the material collected (leaves, stems, flower stems, or bark), they were ground in a blender or a knife mill. Powdered materials were homogenized immediately before analysis. Samples were stored in polyethylene bags at room temperature until the analysis. LC–MS/MS conditions A Shimadzu system (LC-20AD pumps, a SIL-20AD autosampler, and CTO-20AC column oven - Kyoto, Japan) coupled with a 6500 + QTRAP triple quadrupole mass spectrometer from AB SCIEX (Foster, USA) was used for the analyses. Data acquisition was done with SCIEX OS (version 1.6.2.36627), using the Selected Reaction Monitoring (SRM) mode, while the control was performed using Analyst® software (version 1.6). The MS/MS parameters were optimized for each analyte by directly infusing mycotoxin solutions (50 to 100 ng/mL, dissolved in MeOH/H2O) into the mass spectrometer, using a flow rate of 10 µL/min. The effects of formic acid (0.1%) and ammonium formate (1 or 5 mM) or acetic acid (0.1%) and ammonium acetate (5 mM) were tested, and the best mobile phase additive was selected. Electrospray ionization was performed in multiple reaction monitoring (MRM) mode, operating in both positive (ESI+) and negative (ESI-) polarities. Declustering potential (DP), collision energy (CE), and collision cell exit potential (CXP) were optimized for the selected transitions at the best ESI polarity for each analyte. Ion source parameters were automatically optimized using flow injection analysis of a 75 ng/mL standard solution of the less sensitive compound in the preliminary tests, at 0.4 mL/min. Different parameters of the source were tested, including temperature (450 to 700°C), nebulizer (GS1) and heater gas (GS2) pressures (40 to 50 psi), curtain gas (CUR) pressure (20 to 50 psi) and collision-activated dissociation (CAD) gas (high, medium and low). Chromatographic separation was carried out with an ACQUITY UPLC BEH C18 column (30Å, 1.7 µm, 2.1 mm x 50 mm) and VanGuard ACQUITY BEH, 1.7 µm guard column, both from Waters (Milford, MA, USA). The temperature of the column was maintained at 40°C, and a flow rate of 0.4 mL/min was used. The mobile phase was composed of a gradient of water (A) and methanol (B), both with the additive selected during the analyte-dependent MS/MS parameters optimization process. The gradient started at 2% B, remained steady for 1 min; increased to 20% B over 1 min, maintained for 6 min; increased to 40% B and held for 1 min; increased to 60% B in 1.5 min; increased for 70% B in 4 min; increased to 95% B in 2 min and held for 2 min. The system was equilibrated for 5 minutes at the initial condition between consecutive runs. Figure S3 shows an ion-chromatogram containing all the mycotoxins (in-matrix). Extraction method optimization A composite sample was used as a blank model matrix for the extraction optimization and validation procedures. The choice of the different plant species included in this composite sample (boldo, senna, artichoke, chamomile, “espinheira santa”, gotu kola, guarana, and passion fruit) was described by Mello et al. ( 2024 ). Most dry herbs used in the composite sample were prepared from leaves, but bark, flowers, stem and seeds were also included. Modified QuEChERS procedures based on Mozzaquatro et al. ( 2022 ) and Zhang et al. ( 2016 ) were tested, and conditions evaluated are shown in Table S2. In summary, 1g of blank material was weighed into a 50 mL Falcon tube. Samples were spiked with the mycotoxin standards (concentrations ranging from 12 to 318 µg/kg) and left to stand for 1 hour for analyte-sample equilibration. Different extraction and clean-up procedures were tested (Table S2, procedures 1 to 4), including volume of milli-Q water and standing times to ensure sample hydration, extraction with 7.5 to 15 mL acidified ACN (1 to 10% formic acid), and addition of MgSO 4 with NaOAc or NaCl followed by vortex and centrifugation at 3,500 rpm for 5 min. An aliquot of the extract was transferred to a 15 mL Falcon tube containing MgSO 4 with PSA and/or C18 and carbon graphitized black (CGB), vortexed, and centrifuged. For procedures 1 to 3, 800 µL was transferred to a vial, evaporated to dryness (Centrivap Vacuum Concentrator System, LABCONCO/Germany) and redissolved in 240 µL of MeOH: H 2 O (50:50), while for procedure 4, 1.5 mL were evaporated to dryness and redissolved in 250 µL of MeOH: H 2 O (50:50). Extracts were filtered through a 0.45 µm syringe filter and injected into the LC-MS/MS. Recovery tests were carried out in triplicate for each extraction/clean-up procedure. Quantification was carried out using matrix-matched standard curves at concentration levels between 3.6 and 1000 µg/kg (5.3 to 442.5 ng/mL). Data were analyzed using GraphPad Prism 10.3.1 by two-way analysis of variance (ANOVA) followed by Tukey’s multiple comparisons test; the difference was considered significant when p < 0.05. Method validation The method with the best extraction results in the optimization step was validated according to the parameters established by the Brazilian National Institute of Metrology, Quality and Technology (INMETRO, 2020 ). When isotope-labeled internal calibration was used, an aliquot of 135 µL of the extract was transferred to an insert and mixed with 15 µL of the internal standards isotope working solution. The final concentration of the isotopes was: ( 13 C 17 )-AFB 1 = 3.73 ng/mL, ( 13 C 17 )-AFG 1 = 3.34 ng/mL, ( 13 C 34 )-FB 1 = 50.8 ng/mL, ( 13 C 20 )-OTA = 20.08 ng/mL, ( 13 C 18 )-ZEN 16.73 ng/mL, d1-DON = 214.4 ng/mL. For s electivity, f ortified and non-fortified composite blank samples were injected into the LC-MS/MS to evaluate the presence of interferents in the matrix in the same retention time (RT) and same ion ratio (IR) as the mycotoxins of interest. The matrix effect was estimated considering the ratio between the average instrument response (areas) of matrix-matched standards and neat solution standards, which were evaluated for each analyte at five concentration levels, three replicates at each level, using isotope-labeled internal and external calibration. Signal suppression/enhancement above 20% was considered an important matrix effect. Linearity was checked by analyzing the same set of samples used in the matrix effect evaluation, and the presence of outliers was verified by the Grubbs test. The linear parameters of the regression were estimated by the ordinary least squares method, the homogeneity of variances by the F-test, and the coefficient of determination (R 2 ) and significance of the regression obtained using ANOVA. For heteroscedastic data, different weighting factors were tested (1/x, 1/x 2 , 1/y and 1/y 2 ), and those with the lower sum of relative errors, with significant regressions and with no lack of fit were chosen for the regression. Calibration curves ranged from LOQ to up to 88xLOQ (ZEN). For isotope internal calibration, the relative areas (ratio between the analyte peak area and the corresponding isotope internal standard peak area) were used to obtain weighted/ordinary calibration curves. Recovery , expressed as %, was evaluated by fortifying the composite blank samples, at 3 different levels (low, intermediate and high, Table 1 ) with six replicates at each level. The experiment was carried out on the same day, by the same analyst and outliers were removed using the Grubbs test. Samples were quantified using in-matrix calibration curves. Repeatability was expressed as the relative standard deviations (%RSDr) of the replicates used in the recovery experiments. Intermediate precision was evaluated by the analysis of samples fortified in the same conditions as the recovery experiments but carried out on a different day (%RSDp), except for D3G, for which only 3 replicates were made both for the intermediate and high levels, due to the limited amount of standard available. LOQ was defined as the lowest level for which the method was fully validated (80 ≥ recovery ≤ 120%; RSD r ≤ 20%; RSD P ≤ 20%). Limits of detection (LOD) were set at the lowest concentration at which a substance could be detected. Table 1 Concentration levels (µg/kg) used in the validation procedure for each mycotoxin. Mycotoxin Low Medium High 15-AcDON 89.6 239.8 447.9 3-AcDON 71.2 190.7 356.1 AFB 1 4.8 83.2 224.6 AFB 2 4.8 68.2 169.6 AFG 1 3.6 68.0 170.0 AFG 2 4.8 91.6 225.3 CTV 9.6 112.9 282.2 DON 200.7 537.2 1003.3 D3G 120.2 318.6 601.2 FB 1 34.3 137.2 336.1 FB 2 2.2 25.0 31.5 FB 3 2.2 25.0 31.5 OTA 2.4 41.2 231.6 ZEN 5.3 89.8 466.5 α-ZEL 4.5 12.0 22.3 Dietary risk assessment Chronic intake of mycotoxins through the consumption of tea was estimated using a deterministic approach, following IPCS ( 2020 ) recommendation. Considering that the same person could use different dry herbs in tea preparations throughout the day, the present study grouped all dry herbs analyzed and estimated medians and 95th percentiles (P95) of contamination levels for each mycotoxin evaluated. Non-detected samples (< LOD) were assumed to be at ½ LOD, and samples between LOD and LOQ (LOD < Samples < LOQ) were replaced by the LOD. The exposure considered two different situations: a usual consumption of tea (1 cup of tea/day) and a high consumption (6 cups of tea/day), with either a median or a high contamination level (P95). According to the herb’s manufacturer, 3 to 18 grams of dry herb are recommended for the preparation of a cup of tea (200 mL; Table S1 ), so 3 g was used as a reference dose for the preparation. A body weight of 65 kg was considered for the adult population. The potential risks arising from mycotoxin exposure through the consumption of tea infusions were evaluated by comparing the estimated exposure with the respective Health-Based Guidance Values (HBGV) of the compound or the sum of compounds (IPCS, 2009 ). Results Optimization of LC-MS/MS The presence of formic acid (0.1%) and ammonium formate (1 or 5 mM) or acetic acid (0.1%) and ammonium acetate (5 mM) was evaluated in positive and negative mode to choose the best mobile phase additive. Direct infusion of mycotoxins solutions in positive mode showed higher intensities of the protonated adducts [M + H] + , using both ammonium formate (1 and 5mM; 0.1% formic acid) or ammonium acetate (5mM, 0.1% acetic acid) for all analytes, except for D3G, for which only the ammonium adduct was found. Higher intensities were observed for most analytes using ammonium formate (5mM; 0.1% formic acid). In the negative mode 3-AcDON, DON, D3G and α-ZEL showed higher intensities using ammonium formate (5mM; 0.1% formic acid), while 15-AcDON, OTA and ZEN showed better results with ammonium acetate (5mM; 0.1% acetic acid). Considering the overall results, ammonium formate (5mM, 0.1% formic acid) was selected as the additive for the mobile phase. The protonated forms [M + H] + were monitored in the positive mode, and in the negative mode, [M-H] − was monitored for ZEN, α-ZEL and [M + HCOO] − for D3G. The optimized ESI-MS/MS conditions and chromatographic parameters for mycotoxins and isotope internal standards are shown in Table S3. Ion source parameters were automatically optimized using flow injection analysis and the optimal conditions of the mass spectrometer ion source were CUR: at 30 psi, ion spray voltage at − 4500 V for ESI − and 5500 V for ESI + , CAD at high, ion source temperature at 450°C, GS1 at 50 psi, and GS2 at 40 psi. Optimization of a multi-mycotoxin modified QuECHERS extraction In this study, four different protocols of extraction were evaluated, based on the methods described by Mozzaquatro et al. (2022), Zhang et al.(2016) and tests carried out in the laboratory. Figure 1 shows the mean recovery rates (%) of the mycotoxins obtained using the different extraction procedures. Fumonisins (FB 1 , FB 2 and FB 3 ) and OTA were not detected when the extraction was carried out with 1% acidified ACN and NaOAc as a dispersion salt (Procedure 1), with recovery rates above 80% for the other mycotoxins. Acidifying the extraction solvent with 10% formic acid, using NaCl as the dispersion salt, and including C18 in the cleanup step (Procedure 2) yielded no recovery at the levels tested for AFB 1 , AFG 1 , and CTV, and recovery rates lower than 70% for 15-AcDON, 3-AcDON and DON. In procedure 3 (10% acidified ACN, NaCl as dispersion salt, PSA and C18 in the cleanup step), all mycotoxins showed recovery rates higher than 78%. In procedure 4 (C18 replaced by CGB), AFB 1 , AFB 2 , AFG 1 , AFG 2 , DON, and ZEN showed recovery rates lower than 80%, FB 1 was not detected, FB 2 and FB 3 were recovered in only one replicate, and OTA also showed a recovery rate lower than 25%. The results showed that procedure 3 performed better among the tested conditions and was submitted for validation. In summary, samples were extracted with 15 mL of acidified ACN (10% formic acid), 5g MgSO4 + NaCl (4:1; dispersion salt), 0.6g MgSO4 + PSA + C18 (6:1:1; cleanup). Multi-mycotoxins method validation The chromatogram of the composite blank sample did not show any interfering peaks eluting at the same retention time and the ions of the analytes of interest, indicating that the method has good selectivity. Matrix effects were evaluated using both external and internal calibration. For external calibration, only FBs (FB 1 , FB 2 , and FB 3 ) showed an enhanced signal, ranging from 270% (FB 1 /first level of calibration curve) to 2492% (FB 2 /fifth level of calibration curve; Fig. 2A). Ion suppression was observed for all other analytes, with AFG 2 showing the highest suppression (mean of -92.3% ± 1.2) and OTA the lowest (mean of -36.1% ± 9.8; Fig. 2B). Internal calibration using isotope dilution decreased the matrix effect for most analytes, keeping signal suppression/enhancement below 20% for 7 out of 14 analytes evaluated (Fig. 2). FBs still showed enhanced signal when using internal calibration (70.5 to 252%), although lower when compared to external calibration (Fig. 2A). D3G, 15AcDON, and 3AcDON showed higher matrix effects using internal calibration (153 to 202%) compared to external (-68 to -63%) and therefore the labeled internal standard d1-DON was not considered suitable for those compounds. Considering the results above, internal calibration was used for all analytes, except D3G, 15-AcDON, and 3-AcDON. An internal standard was not available for CVT. The analytical curves were prepared in-matrix (composite sample). Validation results are shown in Table 2. Homoscedastic behavior of the analytical curve residues (F calc < F crit .) was observed only for 15-AcDON, 3-AcDON and α-ZEL. For heteroscedastic compounds, the best weighting factors were 1/x 2 (AFB 1 , AFB 2 , AFG 2 , CTV, FB 1 and ZEN), 1/y 2 (AFG 1 , D3G and FB 2 ), 1/x (DON and FB 3 ) and 1/y (OTA). Coefficients of determination were higher than 0.99, except for FB 1 (0.98); regressions were significant (p < 0.05) and did not show any lack-of-fit for all analytes evaluated (data not shown). Table 2 Validation results obtained at 3 different concentration levels. Recovery (RSDr).% (n = 5–6) RSDp. % (n = 9–12) Mycotoxin Weighting fator LOQ/LOD (µg/kg) Low Medium High Low Medium High AFB 1 1/x 2 4.8/1.6 81.9(5.7) 89.7(8.5) 82.4(3.2) 8.8 10.7 13.2 AFB 2 1/x 2 4.8/1.6 97(6) 87.3(6.9) 85(8.5) 14.4 7.3 9.8 AFG 1 1/y 2 3.6/1.2 88.1(5.1) 90.2(10.0) 84.1(4.0) 15.0 12.4 12.4 AFG 2 1/x 2 4.8/1.6 96.2(8.9) 83.5(3.6) 86.7(9.6) 10.2 9.0 8.8 CTV 1/x 2 9.6/1.8 95.4(16.0) 114.3(7.8) 115.5(6.8) 14.9 13.4 11.3 DON 1/x 201/67 92.4(9.6) 105.8(11.3) 100.1(8.1) 10.8 11.9 9.2 15-AcDON Ordinary 90/30 98.4(8.8) 97.8(8.1) 94.8(7.3) 7.0 6.6 7.9 3-AcDON Ordinary 71/24 93.3(11.4) 90.6(5.7) 89.2(6.0) 8.8 5.9 5.4 D3G 1/y 2 120/40 95.1(10.9) 83.2(11.2) 102.3(7.6) 10.7 9.6 13.1 FB 1 1/x 2 34/11 80.5(5.5) 80.6(8.5) 92.3(12.0) 6.5 14.7 12.5 FB 2 1/y 2 2.2/0.7 107.1(6.1) 91.7(10.8) 98.4(8.7) 12.4 10.8 14.3 FB 3 1/x 2.2/0.7 110.7(19.9) 86.4(9.9) 89.2(13.1) 19 12 13.6 OTA 1/y 2.4/0.8 86.8(13.2) 97.6(17.5) 82.8(10.1) 12.8 12.4 8.3 ZEN 1/x 2 5.3/1.8 102.1(6.8) 89.5(5.7) 83.8(6.5) 10.6 9.8 12.1 α-ZEL Ordinary 4.55/1.5 93.1(7.1) 97.3(8.8) 88.9(8.3) 9.5 15.2 10.0 LOQ: limit of quantification; LOD: limit of detection; %RSDr.: relative standard deviations obtained from replicates used in the recovery experiments; %RSDp.: relative standard deviations obtained from replicates of intermediate precision experiments. Recoveries ranged from 81.9 (AFB 1 ) to 111% (FB 3 ) at the lowest level of fortification and from 82.4 (AFB 1 ) to 116% (CTV) at the highest level, using matrix matched curves and isotope internal standard for quantification, except for 15-AcDON, 3-AcDON, D3G and CTV for which quantification were carried out using only matrix matched curves. Both RSDr and RSDp were below 20% for all mycotoxins in all three levels evaluated. Limits of quantification (LOQs) ranged from 2.2 µg/kg (FB 2 and FB 3 ) to 201 µg/kg (DON) (80 ≥ recovery ≤ 120%; RSD r ≤ 20%; RSD P ≤ 20%) and LODs from 0.7 µg/kg (FB 2 and FB 3 ) to 67 µg/kg (Table 2). Mycotoxins occurrence in dry herbs used for tea preparation A total of 91 samples of dry herbs for tea preparation were analyzed with the validated method. Samples with contamination levels above the linear range of the analytical curve were diluted for the quantification process. A total of 23 samples (25.3%) were positive (≥ LOQ) for at least one mycotoxin analyzed and co-occurrence of different mycotoxins was found in five samples. ZEN was the most frequent mycotoxin found in the samples (13.2%), followed by FB 2 (4.4%), AFB 1 (3.3%) and OTA (3.3%). Trace levels of those mycotoxins (LOD > Samples < LOQ) were found in 22 samples, mainly of ZEN and FB 2 . Only ten out of the 33 different dry herbs analyzed did not contain any mycotoxin (< LOD) ( Arnica, Assa-peixe, Barbatimão, Boldo, Carqueja, Cáscara sagrada, Chapéu de couro , Chlorella, Peruvian maca and Spirulina). A summary of the results is shown in Table 3, and the results of each sample are in Table S1. Aflatoxins (AFB 1 , AFB 2 , AFG 1 ) were quantified in 7 samples at levels ranging from 7.7 (AFG 1 ; Muira puama, bark) to 465.2 µg/kg (AFB 2 ; Senna, leaf and bark). Three samples contained aflatoxins at trace levels and there was no co-occurrence in the samples. FB 2 was the only fumonisin detected in the samples (11 samples), mainly guarana (3 samples), and seven at trace levels (≥ LOD < LOQ); levels in the four quantified samples ranged from 2.2 (Guarana seed) to 10.1 µg/kg (Angelika leaf). Three samples were contaminated with OTA, with levels between 2.7 (Tribulus, fruit dry extract) and 11.6 µg/kg (Gotu kola, leaf; Fig. 3). OTA was also detected in samples of Angelika (leaf), Cat’s claw (bark), Guarana (seed) and Horse chestnut (seed). Table 3 Occurrence of mycotoxins in samples of dry herbs used for tea preparation. Mycotoxin Positive samples a (%) Quantified samples (%) b Mean ± SD (Range), µg/kg AFB 1 3 (3.3) 3 (3.3) 15. 4 ± 11.5 (7.8–28.6) AFB 2 4 (4.4) 2 (2.2) 256.1 ± 295.7 (47.1-465.2) AFG 1 2 (2.2) 2 (2.2) 35.1 ± 38.7 (7.7–62.4) AFG 2 1 (1.1) 0 – FB 2 11 (12.1) 4 (4.4) 5.0 ± 3.5 (2.2–10.1) OTA 7 (7.7) 3 (3.3) 8.1 ± 4.7 (2.7–11.6) ZEN 19 (20.9) 12 (13.2) 280.2 ± 585.5(6.5-1954.8) α-ZEL 3 (3.3) 2 (2.2) 23.4 ± 23.3 (7.0-39.9) a > LOD; b ≥ LOQ; SD = standard deviation; LOQ = limit of quantification; LOD = limit of detection Nineteen samples were contaminated with ZEN, of which 12 at levels ≥ LOQ; three horsetail samples contained the highest levels found in the study (from 366.3 to 1954.8 µg/kg; Table 3). α-ZEL, a ZEN metabolite, was found in two horsetail samples, at levels (7.0 and 39.9 µg/kg). DON and its derivatives (15-AcDON, 3-AcDON and D3G), CTV, fumonisins B 1 and B 3 were not found in any of the samples analyzed. Chronic dietary risk assessment The assessment was done for mycotoxins in which the occurrence represented at least 10% of the samples (≥ LOQ and trace levels), that is, for fumonisin B 2 and total zearalenone (ZEN + α-ZOL) (Table 3). The HBGV established is 2 µg/kg bw day for fumonisins (FB 1 , FB 2 , FB 3 – alone or in combination;(JECFA, 2002) and 0.25 µg/kg bw day for ZEN and its metabolites (EFSA, 2016). Risk may exist when the exposure exceeds the HBGV. Results of dietary exposure are shown in Table 4. For FB 2 , intake ranged from 0.0171 ng/kg bw day (mean consumption and median contamination level) to 0.2049 ng/ kg bw day (high consumption and P95 of contamination level), representing 0.001% to 0.01% of the fumonisins HBGV. For total ZEN, the intake ranged from 0.0750 to 12.8 ng/kg bw day, representing 0.03% to 5.1% of the HBGV. These results showed that consumption of herbal teas is not a major source of exposure to these mycotoxins, even when extreme scenarios are considered. Table 4 Dietary risk assessment of FB2 and TZEN (ZEN + αZOL) through the consumption of tea infusions. Mycotoxin Consumption (g/day) a Contamination (µg/kg) Intake b (ng/ kg bw day) % HBGV Median P95 Median P95 Median P95 FB 2 3 0.4 0.7 0.0171 0.0342 0.001 0.002 18 0.1025 0.2049 0.01 0.01 TZEN 3 1.6 46.3 0.0750 2.1381 0.03 0.9 18 0.4500 12.8285 0.2 5.1 FB 2 = fumonisin B 2 ; TZEN = total zearalenone; P95 = percentile 95; HBGV = health-based guidance values [FB 2 = 2 µg/kg bw (JECFA, 2002); TZEN = 0.25 µg/kg bw (EFSA, 2016)]; a mean consumers − 1 cup of tea per day (3g/200 mL) and high consumers – 6 cups/day; b body weight of 65 kg for the adult population. Discussion This study optimized and validated a method for the simultaneous analysis of 15 mycotoxins in 33 different dry herbs commonly used for tea preparation. Samples were extracted/cleaned up using a modified QuEChERS, like other studies (Caldeirão et al., 2021 ; Cho et al., 2019 ; Fontana et al., 2024 ; Pallarés, Berrada, et al., 2022 ). All of them used acidified acetonitrile at levels below 2% and clean-up using a QuEChERS mixture containing C18, except for Fontana et al. ( 2024 ), who used graphitized carbon black (CGB). In the present study, FBs and OTA were better extracted with 10% acidified acetonitrile, which was used in the method. NaCl was used as a dispersion salt, PSA and C18 in the cleanup step. PSA was needed to improve the recovery of AFB 1 , AFG 1 , CTV, 15-AcDON, 3-AcDON and DON when compared with using only C18. The analytical method was validated using a composite sample containing different herbs and plant parts. Matrix effects were higher than previously reported in the literature, mainly for fumonisins (up to 2,000% using external calibration). For example, a method that also used QuEChERs prior to LC-MS/MS reported matrix effects values of -1 to 51% for FB 1 and − 16 to -31% for FB 2 , depending on the dry herb (Fontana et al., 2024 ). The study also reported matrix effects for aflatoxins ranging from − 12 (AFG 2 ) to -71% (AFB 2 ) for Melissa officinalis and from − 20 (AFB 1 ) to 31% (AFG 2 ) for Malva sylvestris . The present study was the only one to report using a composite sample for validation procedures. Other researchers analyzed limited plant species (Fontana et al., 2024 ; Pallarés, Tolosa, et al., 2022 ), validated the method using individual species (Zhou et al., 2022 ), or used different species to typify different parts of plants (Cho et al., 2019 ). To the best of our knowledge, this is the first study to report using isotope dilution for the multi-mycotoxin analysis in dry herbs used for tea preparation. It is interesting to notice that, except for fumonisins, signal suppression was observed when external calibration was used, while enhancement was observed with internal calibration, especially for DON and its derivative/metabolites. LOQs established for the present method were within the same range of those reported by Fontana et al.(2024) for aflatoxins (5 µg/kg), DON (250 µg/kg- Melissa officinalis ), but were considerably lower for fumonisins (FB 1 and FB 2 , 500 µg/kg), OTA (10 µg/kg) and ZEN (250–500 µg/kg). Reinholds et al.(2019) achieved lower LOQs for AFB 1 (0.4 µg/kg), OTA (0.8 µg/kg) and DON (34 µg/kg) using modified QuEChERS, followed by HPLC-TOF-MS, however, they developed a separate method for DON analysis. Lower LOQs were also achieved by Wan et al.(2025) for DON (8.3 µg/kg), 3-AcDON (5.0 µg/kg), 15-AcDON (6.0 µg/kg), AFs (0.7–0.8 µg/kg) and OTA (0.7 µg/kg), although the present method obtained better results for FB 1 /FB 2 (82.5 µg/kg) and ZEN (7.5 µg/kg). Wan et al.(2025) used only fresh leaves of Camellia formosensis for the validation procedures. The low sensitivity of the method for DON and its derivatives could mislead the non-detected samples of the present work. About 25% of samples analyzed were contaminated with at least one mycotoxin and co-occurrence of different mycotoxins was found in 5% of the samples. ZEN and FB 2 were the main mycotoxins found. Samples of horse chestnut, green tea, senna, and horseradish were the samples with the highest aflatoxin levels, and those of mulungu and horsetail contained the highest ZEN levels. Stevic et al. (2012) evaluated microbiological characteristics of several medicinal plants and found that horsetail was one of the most contaminated with molds, mainly from Fusarium and Aspergillus. Table 5 summarizes the published studies on the occurrence of mycotoxins in dry herbs used for tea preparation. Two studies evaluated samples collected in Brazil. Caldeirão et al. ( 2021 ) analyzed 58 samples from 20 different dry herbs, and found samples contaminated with aflatoxins (7 to 17% of the samples) and OTA (19%); both occurrence and contamination levels were higher than those found in the present study, except for AFB 2 (up to 465.2 µg/kg; Table 3 ). Fontana et al. ( 2024 ) did not find any of the mycotoxins investigated in the analyzed 42 samples, and the authors indicated that correct drying and storage procedures were applied to the products. However, it is important to emphasize that fungus infection and mycotoxin production may start in the field (Taniwaki et al., 2018 ; X. Zhang et al., 2022 ), and although adequate drying and storage may control aflatoxins contamination (Müller & Basedow, 2007 ; Pitt et al., 2013 ), it does not eliminate the mycotoxin already present in the herbs. Table 5 Published studies on the occurrence and exposure assessment of mycotoxins in dry herbs used for tea preparation. Country / n° mycotoxin analyzed (reference) Type of tea (n° samples) Mean contamination level (range), µg/kg Mean Intake, ng/ kg bw day (%HBGV) Brazil / 14 (Caldeirão et al., 2021 ) 20 different species (58) AFB 1 : NR (74–1,993) AFB 2 : NR (49–184) AFG 1 : NR (99–1,627) OTA: NR (45–404) AFs: 0.009–0.022 (18–44) a OTA: 0.018 (805) b Brazil / 11 (Fontana et al., 2024 ) Melissa officinalis and Malva sylvestris m (42) AFs, DON, FBs, OTA and ZEN: ND NE China / 7 (Chen et al., 2020) 13 different species (48) AFB 1 : NR (0.1–3.8) AFB 2 : NR (0.4–0.5) AFG 1 : NR (0.8) AFG 2 : NR (0.9–2.1) OTA: NR (0.3–515) NE China / 16 (Zhou et al., 2022 ) Green, oolong, black, and dark tea (352) AFs: 1.3–10.6 (NR – 47.2) OTA: 0.09–129.8 (NR – 11,354) ZEN: 0.17–2.1 (NR – 8.4) α-ZEL: 17.8–24.3 (NR – 116.2) DON: 15.9 − 184 (NR – 1,748) 3-AcDON: 7.1–7.8 (NR – 36.6) 15-AcDON: 15–84.7 (NR – 748) AFs: NR (0.00118–0.499) c OTA: 0.003–7.2 (0.00021–0.51) d TZEN: 3.4–7.7 (0.014–0.031) d TDON: 0.921–113 (0.0009–0.113) d Korea / 11 (Cho et al., 2019 ) 20 different species (100) AFB 1 : 5 AFB 2 , AFG 1 , AFG 2 : ND OTA: 25.3 (1.4–58.3) ZEN: 7.4 (2.9–15.2) DON: 28.9 (2.1 – 128.9) FB 1 : 17.2 (0.8–33.7) FB 2 : 1.3 (0.9–1.6) FB 3 : 47.2 (0.7–205.4) NE Latvia / 42 (Reinholds et al., 2020 ) e Camellia sinensis (140) and herbal teas (26) AFs: 1.5–8.2 (1.4–103) OTA: 0.6–3.0 (1.1–7.7) TDON: 103–3,599 (97.1–17,360) ZEN: 11.3 (NR – 56.1) f AFs: 0.0764–0.2933 (0.04–0.17) g OTA: 0.0296–0.11 (0.17–2.05) h TDON: 4.7–129 (1.0–78.9) h ZEN: 0.513 (0.20–1.1) f,h Morocco / 15 (Jai et al., 2021 ) Green tea (111) AFB 2 : 0.13 (4.9–7.4) AFG 1 : 0.03 (1.1–1.6) ZEN: 2.6–9.4 (15.3–45.8) AFB 2 : 0.01–1.8 (NE) i AFG 1 : 0.002–0.3 (NE) i ZEN: 0.6–1.3 (0.2–0.5) i Portugal /38 (Assunção et al., 2021 ) Green tea, bulk and bags (20) NR AFB 1 : 0.00002–0,00028 (17,445,715–1,428,571) j ZEN: 0.0003–0.0036 (0.000005–0.000014) k FB 1 : 0.0005–0.0063 (0.000005–0.000063) k Portugal / 5 (Duarte et al., 2020 ) Tea and medicinal plants (37) AFs: 14.7 (2.8 − 8.2) ZEN: 8.9 (1.8–19.0) AFB 1 : 0.02–0.24 (12.1–122.5) l ZEN: 0.02–0.17 (0.01 − 0.07) l Taiwan / 16 (Wan et al., 2025 ) Green, oolong, black, and Pu-erh (8) AFM 1 : 2.6 (2,15–3.0) FB 2 : 198.9 ZEN: 87.5 AFM 1 : 0.09–0.3 (46,200–9,561) m FB 2 : 11.1–39.1 (0.5–2.0) m ZEN: 1.4–4.9 (0.6–2.0) m HBGV: Health-based guidance values; NR: not reported; ND: not detected (samples < LOD); NE = not estimated; TZEN = ZEN + metabolites; TDON = DON + metabolites; a Estimation made for every kind of dry herbs; MOE estimated considering a BMDL10 of 0.4 µg/kg bw day; b Estimation made for every kind of dry herbs; MOE estimated considering a BMDL10 of 14.5 µg/kg bw day; c Reported as cancer risk (cancer/year 10 5 individuals); d Reported as HQ (HQ = Intake/PMTDI) - DON and its acetylated derivatives = 1.0 µg/kg bw/day, ZEN and its modified forms = 0.25 µg/kg bw/day and OTA = 0.0143 µg/kg bw/day; e Estimation made both for upper bound and maximum concentration levels; f only for Pu-erh samples; g MOE estimated considering a BMDL10 of 170 ng/kg bw day; Values described were not consistent with the MOE estimation; h DON and its acetylated derivatives = 1.0 µg/kg bw/day, ZEN and its modified forms = 0.25 µg/kg bw/day and OTA = 17.1 ng/kg bw/day; i Lower – upper bound; PMTDI (ZEN) = 0.25 µg/kg bw/day; j Just one contaminated sample; MOE estimated considering a BMDL10 of 0.4 µg/kg bw day; k Just one contaminated sample; Reported as HQ (HQ = Intake/PMTDI); PMTDI (ZEN) = 0.25 µg/kg bw/day; FB 1 = 0.1 µg/kg bw/day; l TDI (AFs) = 0.2 ng/kg bw/day; TDI (ZEN) = 0.25 ng/kg bw/day; m Exposure was estimated for two age groups (19–65 years old and > 65 years old) and two populational groups (whole and consumers only); For AFM 1 , MOE was estimated considering a BMDL10 of 0.4 µg/kg bw day; PMTDI (ZEN) = 0.25 µg/kg bw/day; PMTDI (FB 1 /FB 2 ) = FB 1 = 2 µg/kg bw/day. The types of herbs analyzed, the occurrence and the levels of mycotoxins found vary widely in studies conducted elsewhere (Table 5 ). In a large study conducted in China (348 samples), OTA (11,354 µg/kg in dark tea) and DON (1,748 µg/kg, oolong) were present at the highest levels (Zhou, Yan, Wu, et al., 2022). Cho et al. ( 2019 ) found up to 10% of the 100 functional and medicinal herb Korean samples contaminated, with the highest levels for DON (128.9 µg/kg) and FB 3 (205.4 µg/kg). Reinholds et al. (2021) found that about 40% of the 166 samples from Latvia were contaminated with aflatoxins, 66% with DON and its derivatives, with a TDON level (DON, D3G, 3-AcDON, 15-AcDON) reaching 17,360 in a Pu-erh sample. Jai et al. ( 2021 ) found 2% of the 111 samples from Morocco contaminated with AFB 2 and/or AFG 1 , and 35% with ZEN (up to 45.8 µg/kg). Duarte et al. ( 2020 ) detected AFs and ZEN in tea and medicinal plants from Portugal and Wan et al. ( 2025 ) found FB 2 in one green tea sample and ZEN in one black tea sample. In Brazil, herbal teas are regulated as either food or herbal medicines, which can claim medicinal use (ANVISA, 2022 ); however, medicinal plants can also be used for tea preparation. From the 91 herb samples analyzed, nine fell under the food category, nine as medicinal plants, 11 could be used in the preparation of herbal medicine, 32 belonged to two categories (e.g food and herbal medicine/medicinal plant and herbal medicine) and 30 samples were not listed in the legislation in any category, as they were composed of different plant species than described in the technical documents, other plant parts or not described at all. Brazilian MLs are only established for dry herbs used as medicinal plants (AFs = 20 µg/kg; AFB 1 = 5 µg/kg). If it were to apply these limits to all types of herbs analyzed in the present study, samples of green tea (leaf and stalk; AFB 2 = 47.1 µg/kg), horse chestnut (seed; AFB 1 = 28.6 µg/kg), horseradish tree (leaf; AFG 1 = 62.4 µg/kg) and sena (leaf and bark; AFB 2 = 465.2 µg/kg) would exceed the ML. The Brazilian Health Surveillance Agency requires producers to monitor mycotoxins in dry herbs used for herbal medicine preparation whenever reports of the occurrence are available (ANVISA, 2019 ). However, to our knowledge, there is no published compilation of this information, which makes it challenging to identify which plants and which mycotoxins should be monitored in dry herbs in Brazil. The present study showed the occurrence of eight mycotoxins in at least 22 species of dry herbs, information that could be used to create a database as a source for producers monitoring actions. Furthermore, discussions on the establishment of MLs for mycotoxins in herbal teas commercialized in Brazil should be engaged, considering both the present study and the occurrence reports available in the literature. The chronic dietary risk assessment conducted for total ZEA and FB 2 showed no risk of exposure through the consumption of tea infusion by the Brazilian population. As a conservative approach, this study considered that all mycotoxins present in the dry herb were transferred to the infusion ready for consumption, an assumption confirmed by Reinholds et al.(2019) for ZEN. Other studies, however, showed a decrease in mycotoxin concentration in the herb infusion, depending on the mycotoxin and the infusion preparation. Caldeirão et al.(2021) showed that no AFG 1 and OTA were transferred to the infusion, and a reduction of up to 95% on AFB 1 content could be achieved during the tea preparation, considering the physical-chemical properties of the compounds. In a study by Chalyy et al. ( 2021 ), 83% of the initial OTA content was transferred to the infusion, while ZEN had from 75 to 100% reduction. Wan et al(2025) evaluated naturally contaminated tea samples with ZEN, FB 2 and AFM 1 and found that less than 1% mycotoxin levels were transferred into tea infusion during the first brewing (up to 2% after five brewing). If a decrease in mycotoxin concentration was considered in the present study, the estimated exposure would be even lower as well as the risks from tea consumption. Other studies also showed that the risk to mycotoxins from tea consumption was low, even when considering conservative approaches (Table 5 ). In Brazil, Caldeirão et al.(2021) evaluated risks from exposure to aflatoxins (AFB 1 and AFB 2 ), OTA, sterigmatocystin and HT-2 (a trichothecene) considering daily tea consumption of 200 mL of individual types of herbs (rosemary, star anise and sage). The hazard quotient (HQ) calculated for HT-2 showed a potential health concern in infusions of espinheira santa (4.5) and mint (2.2). The margin of exposure (MOE) for aflatoxins were below 50 (Table 5 ) for rosemary, star anise and sage, which may indicate a potential health risk for a genotoxic compound (MOE < 10,000). MOE was 805.5 for OTA and 26.7 for STC, but as these mycotoxins are not genotoxic, no potential health risk is expected. Using both deterministic and probabilistic approaches, Zhou et al. ( 2022 ) found no potential risk to the Chinese population from the exposure to 16 mycotoxins through the consumption of tea as a beverage or a dietary supplement (green, oolong, black and dark tea). Reinholds et al. ( 2020 ) estimated that the exposure of the Latvian population to mycotoxins through the consumption of tea (black, green, oolong and Pu-erh) represented up to 78.9% of the HBGV for DON. Although it was mentioned there were no health risks for AFs, the MOE estimated from data presented in the paper were < 10,000, which indicates a health concern. Assunção et al.(2021) estimated the intake of AFB 1 , FB 1 and ZEN through the consumption of green tea in Portugal (10 cups of tea, 150 mL each) and found no potential health risks. However, exposure was estimated considering only one positive sample for each mycotoxin, which is very limited. In another Portuguese study, the exposure to AFs and ZEN through tea consumption represented 12.1 to 122% of a Tolerable Daily Intake (TDI) for AFs and up to 0.07% of the HBGV for ZEN (Duarte et al., 2020 ). However, the TDI approach for AFs is not recommended as they are genotoxic compounds. In Taiwan, the mycotoxin exposure from the tea brewed up to 5 times (consumers only) and individual concentration levels of contaminated samples represented up to 2% of the established HBGV for ZEN and FB 2 (Wan et al., 2025 ). Although most studies showed no health concern from exposure to mycotoxins through the consumption of tea, some of them have indicated a potential health risk from exposure to aflatoxins, based on a very low number of positive samples. In the present study, the chronic dietary risk assessment was carried out only for FB 2 and TZEN, precisely due to the low number of positive samples for the other mycotoxins, which limits the assessment. One limitation of this study is the high LOD/LOQ obtained for DON and its derivatives, which may have influenced the ability to detect those mycotoxins in the samples analyzed. It is well known how good agricultural and manufacturing practices can contribute to the control of mycotoxin contamination. Therefore, improvements must be implemented in the herbal tea production chain to ensure that the products have the lowest possible level of mycotoxin contamination. Furthermore, continuous monitoring actions must be conducted to provide more occurrence data that would allow a broader chronic dietary risk assessment evaluation. In summary, this study establishes a single QuEChERS-based LC-MS/MS method that was fully validated for the simultaneous determination of 15 mycotoxins in complex herbal matrices used for tea preparation. By incorporating composite-sample validation and isotope-labeled internal standards, matrix effects were markedly reduced and quantitative accuracy was improved, enabling reliable multi-analyte monitoring of dry herbs. Among the 91 dry herbs analyzed, 25.3% contained at least one mycotoxin and co-occurrence was observed in five samples. Dietary exposure to total ZEN and FB 2 from tea infusions was below health-based guidance values, however, the occurrence of elevated contamination in some samples underscores the need for targeted monitoring and reinforced producer-level control measures. Declarations Funding This Project was financially supported by the Foundation for Research Support of the Federal District / FAP-DF (PROJETO Nº 263/2020 - EDITAL Nº 03/2018 - Processo nº 00193-00001659/2019-45) and University of Brasília (EDITAL DPI/DPG N. 04/2024). C.S Evangelista received a Master Scholarship from the University of Brasília and from FAP-DF. CRediT authorship contribution statement Eloisa Dutra Caldas, Patrícia Diniz Andrade : Conceptualization, writing, review and editting. Camila Suguiura Evangelista , Denise Carvalho Mello : sample collection, formal analysis, methodology. Patrícia Diniz Andrade : Funding acquisition, project administration. Eloisa Dutra Caldas : supervision. Camila Suguiura Evangelista : writing - first draft. All authors have read and agreed to the published version of the manuscript. Conflicts of interest: None References Abd El-Aty, A. M., Choi, J. H., Rahman, M. M., Kim, S. W., Tosun, A., & Shim, J. H. (2014). 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07:09:21","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":189318,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8376617/v1/ac114413c433d897739e9565.html"},{"id":99789021,"identity":"d740ee56-1e60-4c12-8d29-5147b6181291","added_by":"auto","created_at":"2026-01-08 12:48:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":249860,"visible":true,"origin":"","legend":"\u003cp\u003eRecoveries (%) obtained in the different extraction procedures (n=\u003cem\u003e3\u003c/em\u003e). Detailed information on the procedures tested is available in Table S1. Different low letter cases indicate significant differences at p \u0026lt; 0.05 between procedures tested for each mycotoxin.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8376617/v1/897e7ca75e6af7fb4f700dab.png"},{"id":99342521,"identity":"0883b5b8-15c2-49e6-be3e-e060cb551f6a","added_by":"auto","created_at":"2026-01-01 07:09:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":509582,"visible":true,"origin":"","legend":"\u003cp\u003eMatrix effects (%) for external and internal calibration in three calibration levels (LL = low level; ML= medium level; HL = high level; n= 7-9 replicates at each level). No internal standard was available for CTV. A) Results for fumonisins. B) Results for deoxynivalenol and its derivatives, aflatoxins, CTV, ochratoxin A, zearalenone and its derivatives.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8376617/v1/26ad12d86a94485354694a28.png"},{"id":99342523,"identity":"87f374fa-f4d3-4872-ba49-1657c9c1a0f0","added_by":"auto","created_at":"2026-01-01 07:09:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":222279,"visible":true,"origin":"","legend":"\u003cp\u003eChromatogram of a positive sample of Gotu kola (Hydrocotyle asiatica), showing the co-occurrence of zearalenone (9.2 µg/kg), ochratoxin A (11.6 µg/kg)\u0026nbsp; and fumonisin B\u003csub\u003e2\u003c/sub\u003e (traces).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8376617/v1/d9d1ccee2051e2f54c7c61ab.png"},{"id":100356152,"identity":"2ed28ae7-267a-42f5-85a3-b3a7a9fe9abe","added_by":"auto","created_at":"2026-01-16 06:53:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2337725,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8376617/v1/2ce825d0-c143-4d03-bf3a-0538363d0bdc.pdf"},{"id":99342519,"identity":"a8d2e25f-2293-4681-aae7-06a116cdb9fb","added_by":"auto","created_at":"2026-01-01 07:09:20","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2148167,"visible":true,"origin":"","legend":"","description":"","filename":"Suplementarymaterialmycotoxinsdryherbstea.docx","url":"https://assets-eu.researchsquare.com/files/rs-8376617/v1/a38522195172f2850d96f65c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mycotoxins occurrence in dry herbs used for tea preparation: method validation, analysis of bulk samples and dietary risk assessment","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA diverse range of botanical materials, such as leaves, herbs, roots, flowers, seeds, bark, algae, fungi and lichen, usually dried, are used in tea preparation (EMA, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Those beverages are obtained through decoction, infusion or maceration in water of one or more plant part(s), usually supplied in bulk form or sachets (tea bags), (EMA, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Herbal teas are used as an alternative therapy in several countries, and their diverse composition, rich in antioxidants and bioactive compounds, could be an important key to improving poor-quality diets worldwide (Gil-Serna et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Poswal et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Brazil, herbal tea includes the product made from a plant species authorized for its preparation, whole, fragmented, or ground, with or without fermentation, toasted or not (Brazil, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). According to Brazilian legislation, herbal teas are regulated as food or as herbal medicines, depending on their characteristics and the allegations made. Only teas regulated as herbal medicines can claim medicinal use, since they are regulated in the same way as traditional medicines (ANVISA, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, products with therapeutic claims that are not authorized for food tea, and medicinal plants are commonly found in markets and fairs and are widely consumed in the country.\u003c/p\u003e \u003cp\u003eAt the international level, there are maximum limits (MLs) set for pesticides in tea and herbs(CODEX, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) Brazilian legislation requires monitoring the presence of residues and contaminants in herbs that could be used as medicinal plants or herbal medicines (Brazil, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and MLs are set for aflatoxin B\u003csub\u003e1\u003c/sub\u003e (5 \u0026micro;g/kg) and total aflatoxins (20 \u0026micro;g/kg) in some dry herbs used as medicinal plants (Brazil, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e), and for total arsenic, cadmium and lead in tea and vegetables used in infusions under the food classification (Brazil, 2022b).\u003c/p\u003e \u003cp\u003eMycotoxigenic fungi may infect dry herbs throughout the production chain and may also be transferred to beverages prepared from contaminated herbal substances through the infusion and decoction (Jai et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pallar\u0026eacute;s et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Aflatoxins, fumonisins, ochratoxin A, trichothecenes and zearalenone are the most relevant mycotoxins known, both for their toxicity and occurrence in food. Aflatoxins (AFB\u003csub\u003e1\u003c/sub\u003e, AFB\u003csub\u003e2\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e and AFG\u003csub\u003e2\u003c/sub\u003e) are hepatotoxic, carcinogenic (IARC, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and fumonisins (FB\u003csub\u003e1\u003c/sub\u003e, FB\u003csub\u003e2\u003c/sub\u003e and FB\u003csub\u003e3\u003c/sub\u003e) exposure have been linked to the prevalence of esophageal cancer and an increased risk of neural tube defects (Alizadeh et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Gelineau-van Waes et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). FB\u003csub\u003e1\u003c/sub\u003e and ochratoxin A (nefrotoxic) were classified as possible human carcinogens (IARC, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1993\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Exposure to deoxynivalenol (DON), an important member of the tricothecene group, can cause intestinal toxicity (acute exposure), reproductive toxicity, hepatotoxicity and nephrotoxicity (chronic exposure), while zearalenone exerts strong estrogenic and anabolic effects (Ropejko \u0026amp; Twarużek, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral authors reported the occurrence of residues and contaminants in dry herbs and infusions (Abd El-Aty et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Cladi\u0026egrave;re et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Oliveira et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mello et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pallar\u0026eacute;s et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; WHO, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Due to the complexity of the dry herb matrix, methods used to analyze mycotoxins in these matrices often face problems with extraction efficiency, low recovery, matrix effects, and high limit of quantification (LOQ) (Cho et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Cladi\u0026egrave;re et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Reinholds et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhou, Yan, Wu, et al., 2022). Methods involve extraction with organic solvents, clean-up (solid phase extraction, dispersive liquid-liquid microextraction, immunoaffinity columns, QuEChERS), concentration/dilution, and identification/quantification, mainly by liquid chromatography (LC) and mass spectrometry (MS) (Cho et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Reinholds et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhou, Yan, Wu, et al., 2022). Although some validated methods are available, most are limited to a small number of dry herb types or restricted groups of mycotoxins (Fontana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Jai et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhou, Yan, Wu, et al., 2022). To the best of our knowledge, only two studies reported the occurrence of mycotoxins in dry herbs in Brazil (Caldeir\u0026atilde;o et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fontana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Both methods used modified QuEChERS procedures, followed by LC-MS/MS analysis.\u003c/p\u003e \u003cp\u003eThis study aimed to optimize and validate a method for the simultaneous analysis of aflatoxins (AFB\u003csub\u003e1\u003c/sub\u003e, AFB\u003csub\u003e2\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e and AFG\u003csub\u003e2\u003c/sub\u003e), citreoviridin (CTV), deoxynivalenol (DON), 15-acetyldeoxynivalenol (15-AcDON), 3-acetyldeoxynivalenol (3-AcDON), deoxynivalenol-3-glucoside (D3G), fumonisins (FB\u003csub\u003e1\u003c/sub\u003e, FB\u003csub\u003e2\u003c/sub\u003e and FB\u003csub\u003e3\u003c/sub\u003e), ochratoxin A, zearalenone (ZEN) and alfa-zearalenol (α-ZEL) in 33 different species of dry herbs commonly used for tea preparation, using isotope labeled internal standards and LC-MS/MS.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eChemicals and reagents\u003c/h2\u003e \u003cp\u003eHPLC-grade acetonitrile (ACN), supelclean primary secondary amine (PSA), supelclean C18, sodium chloride (NaCl, \u0026ge; 99,5%), HPLC-grade methanol (MeOH, \u0026ge; 99,9%), ammonium formate (97%) were purchased from Sigma-Aldrich (St. Louis, MO, USA); magnesium sulfate anhydrous (MgSO4) and formic acid from Supelco (Bellefonte, PA); ammonium acetate, sodium acetate anhydrous (NaOAc, 99.5%) and acetic acid from J.T Baker (Phillipsburg, USA); sulfuric acid (\u0026gt;\u0026thinsp;51%) from Vetec; HPLC-grade toluene (TOL) was obtained from Mallinckrodt Baker (Phillipsburg, USA); ethyl acetate (EtAc) from Merck (Darmstadt, Germany); Graphisized Carbon Black (GCB) from Din\u0026acirc;mica (Indaiatuba, SP, Brazil); ultrapure water obtained through a Milli-Q purification system from Millipore (Bedford, MA, USA); hydrophilic PTFE syringe filter (0.45 \u0026micro;m pore size) from Filtrilo (Colombo, PR, Brazil).\u003c/p\u003e \u003cp\u003eStandards of AFB\u003csub\u003e1\u003c/sub\u003e (99.0%), AFB\u003csub\u003e2\u003c/sub\u003e (99.0%), AFG\u003csub\u003e1\u003c/sub\u003e (99.0%), AFG\u003csub\u003e2\u003c/sub\u003e (99.5%) and d1-deoxynivalenol (d1-DON, 107.2 \u0026micro;g/mL, 93.3%) were obtained from Sigma-Aldrich (St. Louis, MO, USA). CTV (97.0%) was from Enzo Life Sciences International Inc. (Farmingdale, NY, USA). 15-AcDON (98.8%), 3-AcDON (99.4%), D3G (96.0%), DON, (98.3%), FB\u003csub\u003e1\u003c/sub\u003e (98%), FB\u003csub\u003e2\u003c/sub\u003e (97.9%), FB\u003csub\u003e3\u003c/sub\u003e (98.5%), OTA (99.5%), ZEN (99.66%), α-ZEL, (98.7%), (13C17)-AFB\u003csub\u003e1\u003c/sub\u003e (99.0%), (13C17)-AFG\u003csub\u003e1\u003c/sub\u003e (99.0%), (13C34)-FB\u003csub\u003e1\u003c/sub\u003e (96.3%), (13C20)-OTA (98.7%), (13C18)-ZEN (98,8%) were from Biopure (Tulin, Austria). The aflatoxins stock solutions were prepared in TOL-ACN (9:1), CVT in EtAc, OTA in TOL-Hac (99:1), and fumonisins in ACN-water (50:50), while the remaining compounds were prepared in ACN. Monthly, the concentrations of aflatoxins (AFs), OTA, ZEN, DON, 3-AcDON, 15-AcDON, and CTV solutions were checked using UV spectrophotometry, according to Andrade et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A maximum variation of 3% in the estimated concentration in relation to the first check was considered acceptable. Mixed working solutions of all analytes were prepared in ACN and all solutions were stored in amber vials at -20 ◦C. Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e shows the structures of all the mycotoxins investigated in this study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSamples\u003c/h3\u003e\n\u003cp\u003eNinety-one bulk samples (examples in Figure S2) of 33 different dry herbs commonly used for tea preparation were purchased from retail stores and compounding pharmacies in the Federal District, Brazil. Details of collected samples can be found in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e (Supplementary Material), including dry herbs prepared from different plant parts (bark, leaf, stalk, seed, and/or flower). Upon arrival at the laboratory, samples were stored at room temperature, and depending on the stiffness of the material collected (leaves, stems, flower stems, or bark), they were ground in a blender or a knife mill. Powdered materials were homogenized immediately before analysis. Samples were stored in polyethylene bags at room temperature until the analysis.\u003c/p\u003e\n\u003ch3\u003eLC–MS/MS conditions\u003c/h3\u003e\n\u003cp\u003eA Shimadzu system (LC-20AD pumps, a SIL-20AD autosampler, and CTO-20AC column oven - Kyoto, Japan) coupled with a 6500\u0026thinsp;+\u0026thinsp;QTRAP triple quadrupole mass spectrometer from AB SCIEX (Foster, USA) was used for the analyses. Data acquisition was done with SCIEX OS (version 1.6.2.36627), using the Selected Reaction Monitoring (SRM) mode, while the control was performed using Analyst\u0026reg; software (version 1.6). The MS/MS parameters were optimized for each analyte by directly infusing mycotoxin solutions (50 to 100 ng/mL, dissolved in MeOH/H2O) into the mass spectrometer, using a flow rate of 10 \u0026micro;L/min. The effects of formic acid (0.1%) and ammonium formate (1 or 5 mM) or acetic acid (0.1%) and ammonium acetate (5 mM) were tested, and the best mobile phase additive was selected. Electrospray ionization was performed in multiple reaction monitoring (MRM) mode, operating in both positive (ESI+) and negative (ESI-) polarities. Declustering potential (DP), collision energy (CE), and collision cell exit potential (CXP) were optimized for the selected transitions at the best ESI polarity for each analyte. Ion source parameters were automatically optimized using flow injection analysis of a 75 ng/mL standard solution of the less sensitive compound in the preliminary tests, at 0.4 mL/min. Different parameters of the source were tested, including temperature (450 to 700\u0026deg;C), nebulizer (GS1) and heater gas (GS2) pressures (40 to 50 psi), curtain gas (CUR) pressure (20 to 50 psi) and collision-activated dissociation (CAD) gas (high, medium and low).\u003c/p\u003e \u003cp\u003eChromatographic separation was carried out with an ACQUITY UPLC BEH C18 column (30\u0026Aring;, 1.7 \u0026micro;m, 2.1 mm x 50 mm) and VanGuard ACQUITY BEH, 1.7 \u0026micro;m guard column, both from Waters (Milford, MA, USA). The temperature of the column was maintained at 40\u0026deg;C, and a flow rate of 0.4 mL/min was used. The mobile phase was composed of a gradient of water (A) and methanol (B), both with the additive selected during the analyte-dependent MS/MS parameters optimization process. The gradient started at 2% B, remained steady for 1 min; increased to 20% B over 1 min, maintained for 6 min; increased to 40% B and held for 1 min; increased to 60% B in 1.5 min; increased for 70% B in 4 min; increased to 95% B in 2 min and held for 2 min. The system was equilibrated for 5 minutes at the initial condition between consecutive runs. Figure S3 shows an ion-chromatogram containing all the mycotoxins (in-matrix).\u003c/p\u003e\n\u003ch3\u003eExtraction method optimization\u003c/h3\u003e\n\u003cp\u003eA composite sample was used as a blank model matrix for the extraction optimization and validation procedures. The choice of the different plant species included in this composite sample (boldo, senna, artichoke, chamomile, \u0026ldquo;espinheira santa\u0026rdquo;, gotu kola, guarana, and passion fruit) was described by Mello et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Most dry herbs used in the composite sample were prepared from leaves, but bark, flowers, stem and seeds were also included. Modified QuEChERS procedures based on Mozzaquatro et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Zhang et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) were tested, and conditions evaluated are shown in Table S2.\u003c/p\u003e \u003cp\u003eIn summary, 1g of blank material was weighed into a 50 mL Falcon tube. Samples were spiked with the mycotoxin standards (concentrations ranging from 12 to 318 \u0026micro;g/kg) and left to stand for 1 hour for analyte-sample equilibration. Different extraction and clean-up procedures were tested (Table S2, procedures 1 to 4), including volume of milli-Q water and standing times to ensure sample hydration, extraction with 7.5 to 15 mL acidified ACN (1 to 10% formic acid), and addition of MgSO\u003csub\u003e4\u003c/sub\u003e with NaOAc or NaCl followed by vortex and centrifugation at 3,500 rpm for 5 min. An aliquot of the extract was transferred to a 15 mL Falcon tube containing MgSO\u003csub\u003e4\u003c/sub\u003e with PSA and/or C18 and carbon graphitized black (CGB), vortexed, and centrifuged. For procedures 1 to 3, 800 \u0026micro;L was transferred to a vial, evaporated to dryness (Centrivap Vacuum Concentrator System, LABCONCO/Germany) and redissolved in 240 \u0026micro;L of MeOH: H\u003csub\u003e2\u003c/sub\u003eO (50:50), while for procedure 4, 1.5 mL were evaporated to dryness and redissolved in 250 \u0026micro;L of MeOH: H\u003csub\u003e2\u003c/sub\u003eO (50:50). Extracts were filtered through a 0.45 \u0026micro;m syringe filter and injected into the LC-MS/MS. Recovery tests were carried out in triplicate for each extraction/clean-up procedure. Quantification was carried out using matrix-matched standard curves at concentration levels between 3.6 and 1000 \u0026micro;g/kg (5.3 to 442.5 ng/mL). Data were analyzed using GraphPad Prism 10.3.1 by two-way analysis of variance (ANOVA) followed by Tukey\u0026rsquo;s multiple comparisons test; the difference was considered significant when p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003ch3\u003eMethod validation\u003c/h3\u003e\n\u003cp\u003eThe method with the best extraction results in the optimization step was validated according to the parameters established by the Brazilian National Institute of Metrology, Quality and Technology (INMETRO, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). When isotope-labeled internal calibration was used, an aliquot of 135 \u0026micro;L of the extract was transferred to an insert and mixed with 15 \u0026micro;L of the internal standards isotope working solution. The final concentration of the isotopes was: (\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003e17\u003c/sub\u003e)-AFB\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.73 ng/mL, (\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003e17\u003c/sub\u003e)-AFG\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.34 ng/mL, (\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003e34\u003c/sub\u003e)-FB\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;50.8 ng/mL, (\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003e20\u003c/sub\u003e)-OTA\u0026thinsp;=\u0026thinsp;20.08 ng/mL, (\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003e18\u003c/sub\u003e)-ZEN 16.73 ng/mL, d1-DON\u0026thinsp;=\u0026thinsp;214.4 ng/mL.\u003c/p\u003e \u003cp\u003eFor s\u003cem\u003eelectivity, f\u003c/em\u003eortified and non-fortified composite blank samples were injected into the LC-MS/MS to evaluate the presence of interferents in the matrix in the same retention time (RT) and same ion ratio (IR) as the mycotoxins of interest. The \u003cem\u003ematrix effect\u003c/em\u003e was estimated considering the ratio between the average instrument response (areas) of matrix-matched standards and neat solution standards, which were evaluated for each analyte at five concentration levels, three replicates at each level, using isotope-labeled internal and external calibration. Signal suppression/enhancement above 20% was considered an important matrix effect.\u003c/p\u003e \u003cp\u003e \u003cem\u003eLinearity\u003c/em\u003e was checked by analyzing the same set of samples used in the matrix effect evaluation, and the presence of outliers was verified by the Grubbs test. The linear parameters of the regression were estimated by the ordinary least squares method, the homogeneity of variances by the F-test, and the coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e) and significance of the regression obtained using ANOVA. For heteroscedastic data, different weighting factors were tested (1/x, 1/x\u003csup\u003e2\u003c/sup\u003e, 1/y and 1/y\u003csup\u003e2\u003c/sup\u003e), and those with the lower sum of relative errors, with significant regressions and with no lack of fit were chosen for the regression. Calibration curves ranged from LOQ to up to 88xLOQ (ZEN). For isotope internal calibration, the relative areas (ratio between the analyte peak area and the corresponding isotope internal standard peak area) were used to obtain weighted/ordinary calibration curves.\u003c/p\u003e \u003cp\u003e \u003cem\u003eRecovery\u003c/em\u003e, expressed as %, was evaluated by fortifying the composite blank samples, at 3 different levels (low, intermediate and high, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) with six replicates at each level. The experiment was carried out on the same day, by the same analyst and outliers were removed using the Grubbs test. Samples were quantified using in-matrix calibration curves. \u003cem\u003eRepeatability\u003c/em\u003e was expressed as the relative standard deviations (%RSDr) of the replicates used in the recovery experiments. \u003cem\u003eIntermediate precision\u003c/em\u003e was evaluated by the analysis of samples fortified in the same conditions as the recovery experiments but carried out on a different day (%RSDp), except for D3G, for which only 3 replicates were made both for the intermediate and high levels, due to the limited amount of standard available. LOQ was defined as the lowest level for which the method was fully validated (80\u0026thinsp;\u0026ge;\u0026thinsp;recovery\u0026thinsp;\u0026le;\u0026thinsp;120%; RSD\u003csub\u003er\u003c/sub\u003e \u0026le; 20%; RSD\u003csub\u003eP\u003c/sub\u003e \u0026le; 20%). Limits of detection (LOD) were set at the lowest concentration at which a substance could be detected.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConcentration levels (\u0026micro;g/kg) used in the validation procedure for each mycotoxin.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMycotoxin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15-AcDON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e239.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e447.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-AcDON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e356.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e224.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e169.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e170.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFG\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e225.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e282.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e537.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1003.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e318.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e601.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e336.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFB\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e231.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e466.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα-ZEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDietary risk assessment\u003c/h2\u003e \u003cp\u003eChronic intake of mycotoxins through the consumption of tea was estimated using a deterministic approach, following IPCS (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) recommendation. Considering that the same person could use different dry herbs in tea preparations throughout the day, the present study grouped all dry herbs analyzed and estimated medians and 95th percentiles (P95) of contamination levels for each mycotoxin evaluated. Non-detected samples (\u0026lt;\u0026thinsp;LOD) were assumed to be at \u0026frac12; LOD, and samples between LOD and LOQ (LOD\u0026thinsp;\u0026lt;\u0026thinsp;Samples\u0026thinsp;\u0026lt;\u0026thinsp;LOQ) were replaced by the LOD.\u003c/p\u003e \u003cp\u003eThe exposure considered two different situations: a usual consumption of tea (1 cup of tea/day) and a high consumption (6 cups of tea/day), with either a median or a high contamination level (P95). According to the herb\u0026rsquo;s manufacturer, 3 to 18 grams of dry herb are recommended for the preparation of a cup of tea (200 mL; Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), so 3 g was used as a reference dose for the preparation. A body weight of 65 kg was considered for the adult population. The potential risks arising from mycotoxin exposure through the consumption of tea infusions were evaluated by comparing the estimated exposure with the respective Health-Based Guidance Values (HBGV) of the compound or the sum of compounds (IPCS, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eOptimization of LC-MS/MS\u003c/h2\u003e\n \u003cp\u003eThe presence of formic acid (0.1%) and ammonium formate (1 or 5 mM) or acetic acid (0.1%) and ammonium acetate (5 mM) was evaluated in positive and negative mode to choose the best mobile phase additive. Direct infusion of mycotoxins solutions in positive mode showed higher intensities of the protonated adducts [M + H]\u003csup\u003e+\u003c/sup\u003e, using both ammonium formate (1 and 5mM; 0.1% formic acid) or ammonium acetate (5mM, 0.1% acetic acid) for all analytes, except for D3G, for which only the ammonium adduct was found. Higher intensities were observed for most analytes using ammonium formate (5mM; 0.1% formic acid). In the negative mode 3-AcDON, DON, D3G and α-ZEL showed higher intensities using ammonium formate (5mM; 0.1% formic acid), while 15-AcDON, OTA and ZEN showed better results with ammonium acetate (5mM; 0.1% acetic acid). Considering the overall results, ammonium formate (5mM, 0.1% formic acid) was selected as the additive for the mobile phase. The protonated forms [M + H]\u003csup\u003e+\u003c/sup\u003e were monitored in the positive mode, and in the negative mode, [M-H]\u003csup\u003e−\u003c/sup\u003e was monitored for ZEN, α-ZEL and [M + HCOO]\u003csup\u003e−\u003c/sup\u003e for D3G. The optimized ESI-MS/MS conditions and chromatographic parameters for mycotoxins and isotope internal standards are shown in Table S3. Ion source parameters were automatically optimized using flow injection analysis and the optimal conditions of the mass spectrometer ion source were CUR: at 30 psi, ion spray voltage at − 4500 V for ESI\u003csup\u003e−\u003c/sup\u003e and 5500 V for ESI\u003csup\u003e+\u003c/sup\u003e, CAD at high, ion source temperature at 450°C, GS1 at 50 psi, and GS2 at 40 psi.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eOptimization of a multi-mycotoxin modified QuECHERS extraction\u003c/h2\u003e\n \u003cp\u003eIn this study, four different protocols of extraction were evaluated, based on the methods described by Mozzaquatro et al. (2022), Zhang et al.(2016) and tests carried out in the laboratory. Figure\u0026nbsp;1 shows the mean recovery rates (%) of the mycotoxins obtained using the different extraction procedures. Fumonisins (FB\u003csub\u003e1\u003c/sub\u003e, FB\u003csub\u003e2\u003c/sub\u003e and FB\u003csub\u003e3\u003c/sub\u003e) and OTA were not detected when the extraction was carried out with 1% acidified ACN and NaOAc as a dispersion salt (Procedure 1), with recovery rates above 80% for the other mycotoxins. Acidifying the extraction solvent with 10% formic acid, using NaCl as the dispersion salt, and including C18 in the cleanup step (Procedure 2) yielded no recovery at the levels tested for AFB\u003csub\u003e1\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e, and CTV, and recovery rates lower than 70% for 15-AcDON, 3-AcDON and DON.\u003c/p\u003e\n \u003cp\u003eIn procedure 3 (10% acidified ACN, NaCl as dispersion salt, PSA and C18 in the cleanup step), all mycotoxins showed recovery rates higher than 78%. In procedure 4 (C18 replaced by CGB), AFB\u003csub\u003e1\u003c/sub\u003e, AFB\u003csub\u003e2\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e, AFG\u003csub\u003e2\u003c/sub\u003e, DON, and ZEN showed recovery rates lower than 80%, FB\u003csub\u003e1\u003c/sub\u003e was not detected, FB\u003csub\u003e2\u003c/sub\u003e and FB\u003csub\u003e3\u003c/sub\u003e were recovered in only one replicate, and OTA also showed a recovery rate lower than 25%. The results showed that procedure 3 performed better among the tested conditions and was submitted for validation. In summary, samples were extracted with 15 mL of acidified ACN (10% formic acid), 5g MgSO4 + NaCl (4:1; dispersion salt), 0.6g MgSO4 + PSA + C18 (6:1:1; cleanup).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eMulti-mycotoxins method validation\u003c/h2\u003e\n \u003cp\u003eThe chromatogram of the composite blank sample did not show any interfering peaks eluting at the same retention time and the ions of the analytes of interest, indicating that the method has good selectivity. Matrix effects were evaluated using both external and internal calibration. For external calibration, only FBs (FB\u003csub\u003e1\u003c/sub\u003e, FB\u003csub\u003e2\u003c/sub\u003e, and FB\u003csub\u003e3\u003c/sub\u003e) showed an enhanced signal, ranging from 270% (FB\u003csub\u003e1\u003c/sub\u003e/first level of calibration curve) to 2492% (FB\u003csub\u003e2\u003c/sub\u003e/fifth level of calibration curve; Fig.\u0026nbsp;2A). Ion suppression was observed for all other analytes, with AFG\u003csub\u003e2\u003c/sub\u003e showing the highest suppression (mean of -92.3% ± 1.2) and OTA the lowest (mean of -36.1% ± 9.8; Fig.\u0026nbsp;2B).\u003c/p\u003e\n \u003cp\u003eInternal calibration using isotope dilution decreased the matrix effect for most analytes, keeping signal suppression/enhancement below 20% for 7 out of 14 analytes evaluated (Fig.\u0026nbsp;2). FBs still showed enhanced signal when using internal calibration (70.5 to 252%), although lower when compared to external calibration (Fig.\u0026nbsp;2A). D3G, 15AcDON, and 3AcDON showed higher matrix effects using internal calibration (153 to 202%) compared to external (-68 to -63%) and therefore the labeled internal standard d1-DON was not considered suitable for those compounds. Considering the results above, internal calibration was used for all analytes, except D3G, 15-AcDON, and 3-AcDON. An internal standard was not available for CVT. The analytical curves were prepared in-matrix (composite sample).\u003c/p\u003e\n \u003cp\u003eValidation results are shown in Table\u0026nbsp;2. Homoscedastic behavior of the analytical curve residues (F\u003csub\u003ecalc\u003c/sub\u003e \u0026lt; F\u003csub\u003ecrit\u003c/sub\u003e.) was observed only for 15-AcDON, 3-AcDON and α-ZEL. For heteroscedastic compounds, the best weighting factors were 1/x\u003csup\u003e2\u003c/sup\u003e (AFB\u003csub\u003e1\u003c/sub\u003e, AFB\u003csub\u003e2\u003c/sub\u003e, AFG\u003csub\u003e2\u003c/sub\u003e, CTV, FB\u003csub\u003e1\u003c/sub\u003e and ZEN), 1/y\u003csup\u003e2\u003c/sup\u003e (AFG\u003csub\u003e1\u003c/sub\u003e, D3G and FB\u003csub\u003e2\u003c/sub\u003e), 1/x (DON and FB\u003csub\u003e3\u003c/sub\u003e) and 1/y (OTA). Coefficients of determination were higher than 0.99, except for FB\u003csub\u003e1\u003c/sub\u003e (0.98); regressions were significant (p \u0026lt; 0.05) and did not show any lack-of-fit for all analytes evaluated (data not shown).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eValidation results obtained at 3 different concentration levels.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eRecovery (RSDr).% (n = 5–6)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eRSDp. % (n = 9–12)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMycotoxin\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWeighting fator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLOQ/LOD (µg/kg)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8/1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81.9(5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.7(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82.4(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8/1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87.3(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/y\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6/1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.1(5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90.2(10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.1(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFG\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8/1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.2(8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83.5(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86.7(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.6/1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.4(16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e114.3(7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115.5(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201/67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.4(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105.8(11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.1(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15-AcDON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOrdinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.4(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.8(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94.8(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-AcDON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOrdinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71/24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.3(11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90.6(5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.2(6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD3G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/y\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120/40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.1(10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83.2(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102.3(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34/11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80.5(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80.6(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.3(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/y\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2/0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107.1(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91.7(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.4(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFB\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2/0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110.7(19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86.4(9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.2(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4/0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.8(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.6(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82.8(10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3/1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102.1(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.5(5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83.8(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eα-ZEL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOrdinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.55/1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.1(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.3(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.9(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003eLOQ: limit of quantification; LOD: limit of detection; %RSDr.: relative standard deviations obtained from replicates used in the recovery experiments; %RSDp.: relative standard deviations obtained from replicates of intermediate precision experiments.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eRecoveries ranged from 81.9 (AFB\u003csub\u003e1\u003c/sub\u003e) to 111% (FB\u003csub\u003e3\u003c/sub\u003e) at the lowest level of fortification and from 82.4 (AFB\u003csub\u003e1\u003c/sub\u003e) to 116% (CTV) at the highest level, using matrix matched curves and isotope internal standard for quantification, except for 15-AcDON, 3-AcDON, D3G and CTV for which quantification were carried out using only matrix matched curves. Both RSDr and RSDp were below 20% for all mycotoxins in all three levels evaluated. Limits of quantification (LOQs) ranged from 2.2 µg/kg (FB\u003csub\u003e2\u003c/sub\u003e and FB\u003csub\u003e3\u003c/sub\u003e) to 201 µg/kg (DON) (80 ≥ recovery ≤ 120%; RSD\u003csub\u003er\u003c/sub\u003e ≤ 20%; RSD\u003csub\u003eP\u003c/sub\u003e ≤ 20%) and LODs from 0.7 µg/kg (FB\u003csub\u003e2\u003c/sub\u003e and FB\u003csub\u003e3\u003c/sub\u003e) to 67 µg/kg (Table\u0026nbsp;2).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eMycotoxins occurrence in dry herbs used for tea preparation\u003c/h2\u003e\n \u003cp\u003eA total of 91 samples of dry herbs for tea preparation were analyzed with the validated method. Samples with contamination levels above the linear range of the analytical curve were diluted for the quantification process. A total of 23 samples (25.3%) were positive (≥ LOQ) for at least one mycotoxin analyzed and co-occurrence of different mycotoxins was found in five samples. ZEN was the most frequent mycotoxin found in the samples (13.2%), followed by FB\u003csub\u003e2\u003c/sub\u003e (4.4%), AFB\u003csub\u003e1\u003c/sub\u003e (3.3%) and OTA (3.3%). Trace levels of those mycotoxins (LOD \u0026gt; Samples \u0026lt; LOQ) were found in 22 samples, mainly of ZEN and FB\u003csub\u003e2\u003c/sub\u003e. Only ten out of the 33 different dry herbs analyzed did not contain any mycotoxin (\u0026lt; LOD) (\u003cem\u003eArnica, Assa-peixe, Barbatimão, Boldo, Carqueja, Cáscara sagrada, Chapéu de couro\u003c/em\u003e, Chlorella, Peruvian maca and Spirulina).\u003c/p\u003e\n \u003cp\u003eA summary of the results is shown in Table\u0026nbsp;3, and the results of each sample are in Table S1. Aflatoxins (AFB\u003csub\u003e1\u003c/sub\u003e, AFB\u003csub\u003e2\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e) were quantified in 7 samples at levels ranging from 7.7 (AFG\u003csub\u003e1\u003c/sub\u003e; Muira puama, bark) to 465.2 µg/kg (AFB\u003csub\u003e2\u003c/sub\u003e; Senna, leaf and bark). Three samples contained aflatoxins at trace levels and there was no co-occurrence in the samples. FB\u003csub\u003e2\u003c/sub\u003e was the only fumonisin detected in the samples (11 samples), mainly guarana (3 samples), and seven at trace levels (≥ LOD \u0026lt; LOQ); levels in the four quantified samples ranged from 2.2 (Guarana seed) to 10.1 µg/kg (Angelika leaf). Three samples were contaminated with OTA, with levels between 2.7 (Tribulus, fruit dry extract) and 11.6 µg/kg (Gotu kola, leaf; Fig.\u0026nbsp;3). OTA was also detected in samples of Angelika (leaf), Cat’s claw (bark), Guarana (seed) and Horse chestnut (seed).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eOccurrence of mycotoxins in samples of dry herbs used for tea preparation.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMycotoxin\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive samples\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eQuantified\u003c/p\u003e\n \u003cp\u003esamples (%)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean ± SD (Range),\u003c/p\u003e\n \u003cp\u003eµg/kg\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15. 4 ± 11.5 (7.8–28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e256.1 ± 295.7 (47.1-465.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.1 ± 38.7 (7.7–62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFG\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e–\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0 ± 3.5 (2.2–10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.1 ± 4.7 (2.7–11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e280.2 ± 585.5(6.5-1954.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eα-ZEL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.4 ± 23.3 (7.0-39.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003e \u0026gt; LOD; \u003csup\u003eb\u003c/sup\u003e ≥ LOQ; SD = standard deviation; LOQ = limit of quantification; LOD = limit of detection\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eNineteen samples were contaminated with ZEN, of which 12 at levels ≥ LOQ; three horsetail samples contained the highest levels found in the study (from 366.3 to 1954.8 µg/kg; Table\u0026nbsp;3). α-ZEL, a ZEN metabolite, was found in two horsetail samples, at levels (7.0 and 39.9 µg/kg). DON and its derivatives (15-AcDON, 3-AcDON and D3G), CTV, fumonisins B\u003csub\u003e1\u003c/sub\u003e and B\u003csub\u003e3\u003c/sub\u003e were not found in any of the samples analyzed.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eChronic dietary risk assessment\u003c/h2\u003e\n \u003cp\u003eThe assessment was done for mycotoxins in which the occurrence represented at least 10% of the samples (≥ LOQ and trace levels), that is, for fumonisin B\u003csub\u003e2\u003c/sub\u003e and total zearalenone (ZEN + α-ZOL) (Table\u0026nbsp;3). The HBGV established is 2 µg/kg bw day for fumonisins (FB\u003csub\u003e1\u003c/sub\u003e, FB\u003csub\u003e2\u003c/sub\u003e, FB\u003csub\u003e3\u003c/sub\u003e – alone or in combination;(JECFA, 2002) and 0.25 µg/kg bw day for ZEN and its metabolites (EFSA, 2016). Risk may exist when the exposure exceeds the HBGV.\u003c/p\u003e\n \u003cp\u003eResults of dietary exposure are shown in Table\u0026nbsp;4. For FB\u003csub\u003e2\u003c/sub\u003e, intake ranged from 0.0171 ng/kg bw day (mean consumption and median contamination level) to 0.2049 ng/ kg bw day (high consumption and P95 of contamination level), representing 0.001% to 0.01% of the fumonisins HBGV. For total ZEN, the intake ranged from 0.0750 to 12.8 ng/kg bw day, representing 0.03% to 5.1% of the HBGV. These results showed that consumption of herbal teas is not a major source of exposure to these mycotoxins, even when extreme scenarios are considered.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDietary risk assessment of FB2 and TZEN (ZEN + αZOL) through the consumption of tea infusions.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMycotoxin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eConsumption (g/day)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eContamination\u003c/p\u003e\n \u003cp\u003e(µg/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eIntake\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(ng/ kg bw day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e% HBGV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTZEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e46.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.8285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eFB\u003csub\u003e2\u003c/sub\u003e = fumonisin B\u003csub\u003e2\u003c/sub\u003e; TZEN = total zearalenone; P95 = percentile 95; HBGV = health-based guidance values [FB\u003csub\u003e2\u003c/sub\u003e = 2 µg/kg bw (JECFA, 2002); TZEN = 0.25 µg/kg bw (EFSA, 2016)]; \u003csup\u003ea\u003c/sup\u003emean consumers − 1 cup of tea per day (3g/200 mL) and high consumers – 6 cups/day; \u003csup\u003eb\u003c/sup\u003ebody weight of 65 kg for the adult population.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study optimized and validated a method for the simultaneous analysis of 15 mycotoxins in 33 different dry herbs commonly used for tea preparation. Samples were extracted/cleaned up using a modified QuEChERS, like other studies (Caldeir\u0026atilde;o et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Cho et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Fontana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pallar\u0026eacute;s, Berrada, et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). All of them used acidified acetonitrile at levels below 2% and clean-up using a QuEChERS mixture containing C18, except for Fontana et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who used graphitized carbon black (CGB). In the present study, FBs and OTA were better extracted with 10% acidified acetonitrile, which was used in the method. NaCl was used as a dispersion salt, PSA and C18 in the cleanup step. PSA was needed to improve the recovery of AFB\u003csub\u003e1\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e, CTV, 15-AcDON, 3-AcDON and DON when compared with using only C18.\u003c/p\u003e \u003cp\u003eThe analytical method was validated using a composite sample containing different herbs and plant parts. Matrix effects were higher than previously reported in the literature, mainly for fumonisins (up to 2,000% using external calibration). For example, a method that also used QuEChERs prior to LC-MS/MS reported matrix effects values of -1 to 51% for FB\u003csub\u003e1\u003c/sub\u003e and \u0026minus;\u0026thinsp;16 to -31% for FB\u003csub\u003e2\u003c/sub\u003e, depending on the dry herb (Fontana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The study also reported matrix effects for aflatoxins ranging from \u0026minus;\u0026thinsp;12 (AFG\u003csub\u003e2\u003c/sub\u003e) to -71% (AFB\u003csub\u003e2\u003c/sub\u003e) for \u003cem\u003eMelissa officinalis\u003c/em\u003e and from \u0026minus;\u0026thinsp;20 (AFB\u003csub\u003e1\u003c/sub\u003e) to 31% (AFG\u003csub\u003e2\u003c/sub\u003e) for \u003cem\u003eMalva sylvestris\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe present study was the only one to report using a composite sample for validation procedures. Other researchers analyzed limited plant species (Fontana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pallar\u0026eacute;s, Tolosa, et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), validated the method using individual species (Zhou et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), or used different species to typify different parts of plants (Cho et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). To the best of our knowledge, this is the first study to report using isotope dilution for the multi-mycotoxin analysis in dry herbs used for tea preparation. It is interesting to notice that, except for fumonisins, signal suppression was observed when external calibration was used, while enhancement was observed with internal calibration, especially for DON and its derivative/metabolites.\u003c/p\u003e \u003cp\u003eLOQs established for the present method were within the same range of those reported by Fontana et al.(2024) for aflatoxins (5 \u0026micro;g/kg), DON (250 \u0026micro;g/kg- \u003cem\u003eMelissa officinalis\u003c/em\u003e), but were considerably lower for fumonisins (FB\u003csub\u003e1\u003c/sub\u003e and FB\u003csub\u003e2\u003c/sub\u003e, 500 \u0026micro;g/kg), OTA (10 \u0026micro;g/kg) and ZEN (250\u0026ndash;500 \u0026micro;g/kg). Reinholds et al.(2019) achieved lower LOQs for AFB\u003csub\u003e1\u003c/sub\u003e (0.4 \u0026micro;g/kg), OTA (0.8 \u0026micro;g/kg) and DON (34 \u0026micro;g/kg) using modified QuEChERS, followed by HPLC-TOF-MS, however, they developed a separate method for DON analysis. Lower LOQs were also achieved by Wan et al.(2025) for DON (8.3 \u0026micro;g/kg), 3-AcDON (5.0 \u0026micro;g/kg), 15-AcDON (6.0 \u0026micro;g/kg), AFs (0.7\u0026ndash;0.8 \u0026micro;g/kg) and OTA (0.7 \u0026micro;g/kg), although the present method obtained better results for FB\u003csub\u003e1\u003c/sub\u003e/FB\u003csub\u003e2\u003c/sub\u003e (82.5 \u0026micro;g/kg) and ZEN (7.5 \u0026micro;g/kg). Wan et al.(2025) used only fresh leaves of \u003cem\u003eCamellia formosensis\u003c/em\u003e for the validation procedures. The low sensitivity of the method for DON and its derivatives could mislead the non-detected samples of the present work.\u003c/p\u003e \u003cp\u003eAbout 25% of samples analyzed were contaminated with at least one mycotoxin and co-occurrence of different mycotoxins was found in 5% of the samples. ZEN and FB\u003csub\u003e2\u003c/sub\u003e were the main mycotoxins found. Samples of horse chestnut, green tea, senna, and horseradish were the samples with the highest aflatoxin levels, and those of mulungu and horsetail contained the highest ZEN levels. Stevic et al. (2012) evaluated microbiological characteristics of several medicinal plants and found that horsetail was one of the most contaminated with molds, mainly from \u003cem\u003eFusarium\u003c/em\u003e and \u003cem\u003eAspergillus.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the published studies on the occurrence of mycotoxins in dry herbs used for tea preparation. Two studies evaluated samples collected in Brazil. Caldeir\u0026atilde;o et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) analyzed 58 samples from 20 different dry herbs, and found samples contaminated with aflatoxins (7 to 17% of the samples) and OTA (19%); both occurrence and contamination levels were higher than those found in the present study, except for AFB\u003csub\u003e2\u003c/sub\u003e (up to 465.2 \u0026micro;g/kg; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Fontana et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) did not find any of the mycotoxins investigated in the analyzed 42 samples, and the authors indicated that correct drying and storage procedures were applied to the products. However, it is important to emphasize that fungus infection and mycotoxin production may start in the field (Taniwaki et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; X. Zhang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and although adequate drying and storage may control aflatoxins contamination (M\u0026uuml;ller \u0026amp; Basedow, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pitt et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), it does not eliminate the mycotoxin already present in the herbs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePublished studies on the occurrence and exposure assessment of mycotoxins in dry herbs used for tea preparation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry / n\u0026deg; mycotoxin analyzed (reference)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of tea\u003c/p\u003e \u003cp\u003e(n\u0026deg; samples)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean contamination level (range), \u0026micro;g/kg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Intake, ng/ kg bw day\u003c/p\u003e \u003cp\u003e(%HBGV)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrazil / 14\u003c/p\u003e \u003cp\u003e(Caldeir\u0026atilde;o et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 different species\u003c/p\u003e \u003cp\u003e(58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e: NR (74\u0026ndash;1,993)\u003c/p\u003e \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e: NR (49\u0026ndash;184)\u003c/p\u003e \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e: NR (99\u0026ndash;1,627)\u003c/p\u003e \u003cp\u003eOTA: NR (45\u0026ndash;404)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFs: 0.009\u0026ndash;0.022 (18\u0026ndash;44)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOTA: 0.018 (805)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrazil / 11\u003c/p\u003e \u003cp\u003e(Fontana et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMelissa officinalis\u003c/em\u003e and \u003cem\u003eMalva sylvestris\u003c/em\u003em (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFs, DON, FBs, OTA and ZEN: ND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina / 7\u003c/p\u003e \u003cp\u003e(Chen et al., 2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 different species (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e: NR (0.1\u0026ndash;3.8)\u003c/p\u003e \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e: NR (0.4\u0026ndash;0.5)\u003c/p\u003e \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e: NR (0.8)\u003c/p\u003e \u003cp\u003eAFG\u003csub\u003e2\u003c/sub\u003e: NR (0.9\u0026ndash;2.1)\u003c/p\u003e \u003cp\u003eOTA: NR (0.3\u0026ndash;515)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChina / 16\u003c/p\u003e \u003cp\u003e(Zhou et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreen, oolong, black, and dark tea (352)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFs: 1.3\u0026ndash;10.6 (NR \u0026ndash; 47.2)\u003c/p\u003e \u003cp\u003eOTA: 0.09\u0026ndash;129.8 (NR \u0026ndash; 11,354)\u003c/p\u003e \u003cp\u003eZEN: 0.17\u0026ndash;2.1 (NR \u0026ndash; 8.4)\u003c/p\u003e \u003cp\u003eα-ZEL: 17.8\u0026ndash;24.3 (NR \u0026ndash; 116.2)\u003c/p\u003e \u003cp\u003eDON: 15.9 \u0026minus;\u0026thinsp;184 (NR \u0026ndash; 1,748)\u003c/p\u003e \u003cp\u003e3-AcDON: 7.1\u0026ndash;7.8 (NR \u0026ndash; 36.6)\u003c/p\u003e \u003cp\u003e15-AcDON: 15\u0026ndash;84.7 (NR \u0026ndash; 748)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFs: NR (0.00118\u0026ndash;0.499)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOTA: 0.003\u0026ndash;7.2 (0.00021\u0026ndash;0.51)\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTZEN: 3.4\u0026ndash;7.7 (0.014\u0026ndash;0.031)\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTDON: 0.921\u0026ndash;113 (0.0009\u0026ndash;0.113)\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKorea / 11\u003c/p\u003e \u003cp\u003e(Cho et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 different species (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e: 5\u003c/p\u003e \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e, AFG\u003csub\u003e1\u003c/sub\u003e, AFG\u003csub\u003e2\u003c/sub\u003e: ND\u003c/p\u003e \u003cp\u003eOTA: 25.3 (1.4\u0026ndash;58.3)\u003c/p\u003e \u003cp\u003eZEN: 7.4 (2.9\u0026ndash;15.2)\u003c/p\u003e \u003cp\u003eDON: 28.9 (2.1 \u0026ndash; 128.9)\u003c/p\u003e \u003cp\u003eFB\u003csub\u003e1\u003c/sub\u003e: 17.2 (0.8\u0026ndash;33.7)\u003c/p\u003e \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e: 1.3 (0.9\u0026ndash;1.6)\u003c/p\u003e \u003cp\u003eFB\u003csub\u003e3\u003c/sub\u003e: 47.2 (0.7\u0026ndash;205.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLatvia / 42\u003c/p\u003e \u003cp\u003e(Reinholds et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamellia sinensis (140) and herbal teas (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFs: 1.5\u0026ndash;8.2 (1.4\u0026ndash;103)\u003c/p\u003e \u003cp\u003eOTA: 0.6\u0026ndash;3.0 (1.1\u0026ndash;7.7)\u003c/p\u003e \u003cp\u003eTDON: 103\u0026ndash;3,599 (97.1\u0026ndash;17,360)\u003c/p\u003e \u003cp\u003eZEN: 11.3 (NR \u0026ndash; 56.1)\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFs: 0.0764\u0026ndash;0.2933 (0.04\u0026ndash;0.17)\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOTA: 0.0296\u0026ndash;0.11 (0.17\u0026ndash;2.05)\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTDON: 4.7\u0026ndash;129 (1.0\u0026ndash;78.9)\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eZEN: 0.513 (0.20\u0026ndash;1.1)\u003csup\u003ef,h\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorocco / 15\u003c/p\u003e \u003cp\u003e(Jai et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreen tea (111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e: 0.13 (4.9\u0026ndash;7.4)\u003c/p\u003e \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e: 0.03 (1.1\u0026ndash;1.6)\u003c/p\u003e \u003cp\u003eZEN: 2.6\u0026ndash;9.4 (15.3\u0026ndash;45.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFB\u003csub\u003e2\u003c/sub\u003e: 0.01\u0026ndash;1.8 (NE)\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAFG\u003csub\u003e1\u003c/sub\u003e: 0.002\u0026ndash;0.3 (NE)\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eZEN: 0.6\u0026ndash;1.3 (0.2\u0026ndash;0.5)\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortugal /38\u003c/p\u003e \u003cp\u003e(Assun\u0026ccedil;\u0026atilde;o et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreen tea, bulk and bags (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e: 0.00002\u0026ndash;0,00028\u003c/p\u003e \u003cp\u003e(17,445,715\u0026ndash;1,428,571)\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eZEN: 0.0003\u0026ndash;0.0036\u003c/p\u003e \u003cp\u003e(0.000005\u0026ndash;0.000014)\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFB\u003csub\u003e1\u003c/sub\u003e: 0.0005\u0026ndash;0.0063 (0.000005\u0026ndash;0.000063)\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortugal / 5\u003c/p\u003e \u003cp\u003e(Duarte et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTea and medicinal plants (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFs: 14.7 (2.8 \u0026minus;\u0026thinsp;8.2)\u003c/p\u003e \u003cp\u003eZEN: 8.9 (1.8\u0026ndash;19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e: 0.02\u0026ndash;0.24 (12.1\u0026ndash;122.5)\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eZEN: 0.02\u0026ndash;0.17 (0.01 \u0026minus;\u0026thinsp;0.07)\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaiwan / 16\u003c/p\u003e \u003cp\u003e(Wan et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreen, oolong, black, and Pu-erh (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFM\u003csub\u003e1\u003c/sub\u003e: 2.6 (2,15\u0026ndash;3.0)\u003c/p\u003e \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e: 198.9\u003c/p\u003e \u003cp\u003eZEN: 87.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFM\u003csub\u003e1\u003c/sub\u003e: 0.09\u0026ndash;0.3 (46,200\u0026ndash;9,561)\u003csup\u003em\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFB\u003csub\u003e2\u003c/sub\u003e: 11.1\u0026ndash;39.1 (0.5\u0026ndash;2.0)\u003csup\u003em\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eZEN: 1.4\u0026ndash;4.9 (0.6\u0026ndash;2.0)\u003csup\u003em\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eHBGV: Health-based guidance values; NR: not reported; ND: not detected (samples\u0026thinsp;\u0026lt;\u0026thinsp;LOD); NE\u0026thinsp;=\u0026thinsp;not estimated; TZEN\u0026thinsp;=\u0026thinsp;ZEN\u0026thinsp;+\u0026thinsp;metabolites; TDON\u0026thinsp;=\u0026thinsp;DON\u0026thinsp;+\u0026thinsp;metabolites; \u003csup\u003ea\u003c/sup\u003eEstimation made for every kind of dry herbs; MOE estimated considering a BMDL10 of 0.4 \u0026micro;g/kg bw day; \u003csup\u003eb\u003c/sup\u003eEstimation made for every kind of dry herbs; MOE estimated considering a BMDL10 of 14.5 \u0026micro;g/kg bw day; \u003csup\u003ec\u003c/sup\u003eReported as cancer risk (cancer/year 10\u003csup\u003e5\u003c/sup\u003e individuals); \u003csup\u003ed\u003c/sup\u003eReported as HQ (HQ\u0026thinsp;=\u0026thinsp;Intake/PMTDI) - DON and its acetylated derivatives\u0026thinsp;=\u0026thinsp;1.0 \u0026micro;g/kg bw/day, ZEN and its modified forms\u0026thinsp;=\u0026thinsp;0.25 \u0026micro;g/kg bw/day and OTA\u0026thinsp;=\u0026thinsp;0.0143 \u0026micro;g/kg bw/day; \u003csup\u003ee\u003c/sup\u003e Estimation made both for upper bound and maximum concentration levels; \u003csup\u003ef\u003c/sup\u003eonly for Pu-erh samples; \u003csup\u003eg\u003c/sup\u003eMOE estimated considering a BMDL10 of 170 ng/kg bw day; Values described were not consistent with the MOE estimation; \u003csup\u003eh\u003c/sup\u003eDON and its acetylated derivatives\u0026thinsp;=\u0026thinsp;1.0 \u0026micro;g/kg bw/day, ZEN and its modified forms\u0026thinsp;=\u0026thinsp;0.25 \u0026micro;g/kg bw/day and OTA\u0026thinsp;=\u0026thinsp;17.1 ng/kg bw/day; \u003csup\u003ei\u003c/sup\u003eLower \u0026ndash; upper bound; PMTDI (ZEN)\u0026thinsp;=\u0026thinsp;0.25 \u0026micro;g/kg bw/day; \u003csup\u003ej\u003c/sup\u003eJust one contaminated sample; MOE estimated considering a BMDL10 of 0.4 \u0026micro;g/kg bw day; \u003csup\u003ek\u003c/sup\u003eJust one contaminated sample; Reported as HQ (HQ\u0026thinsp;=\u0026thinsp;Intake/PMTDI); PMTDI (ZEN)\u0026thinsp;=\u0026thinsp;0.25 \u0026micro;g/kg bw/day; FB\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.1 \u0026micro;g/kg bw/day; \u003csup\u003el\u003c/sup\u003eTDI (AFs)\u0026thinsp;=\u0026thinsp;0.2 ng/kg bw/day; TDI (ZEN)\u0026thinsp;=\u0026thinsp;0.25 ng/kg bw/day; \u003csup\u003em\u003c/sup\u003eExposure was estimated for two age groups (19\u0026ndash;65 years old and \u003cem\u003e\u0026gt;\u003c/em\u003e\u0026thinsp;65 years old) and two populational groups (whole and consumers only); For AFM\u003csub\u003e1\u003c/sub\u003e, MOE was estimated considering a BMDL10 of 0.4 \u0026micro;g/kg bw day; PMTDI (ZEN)\u0026thinsp;=\u0026thinsp;0.25 \u0026micro;g/kg bw/day; PMTDI (FB\u003csub\u003e1\u003c/sub\u003e/FB\u003csub\u003e2\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;FB\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2 \u0026micro;g/kg bw/day.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe types of herbs analyzed, the occurrence and the levels of mycotoxins found vary widely in studies conducted elsewhere (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In a large study conducted in China (348 samples), OTA (11,354 \u0026micro;g/kg in dark tea) and DON (1,748 \u0026micro;g/kg, oolong) were present at the highest levels (Zhou, Yan, Wu, et al., 2022). Cho et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found up to 10% of the 100 functional and medicinal herb Korean samples contaminated, with the highest levels for DON (128.9 \u0026micro;g/kg) and FB\u003csub\u003e3\u003c/sub\u003e (205.4 \u0026micro;g/kg). Reinholds et al. (2021) found that about 40% of the 166 samples from Latvia were contaminated with aflatoxins, 66% with DON and its derivatives, with a TDON level (DON, D3G, 3-AcDON, 15-AcDON) reaching 17,360 in a Pu-erh sample. Jai et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found 2% of the 111 samples from Morocco contaminated with AFB\u003csub\u003e2\u003c/sub\u003e and/or AFG\u003csub\u003e1\u003c/sub\u003e, and 35% with ZEN (up to 45.8 \u0026micro;g/kg). Duarte et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) detected AFs and ZEN in tea and medicinal plants from Portugal and Wan et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) found FB\u003csub\u003e2\u003c/sub\u003e in one green tea sample and ZEN in one black tea sample.\u003c/p\u003e \u003cp\u003eIn Brazil, herbal teas are regulated as either food or herbal medicines, which can claim medicinal use (ANVISA, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); however, medicinal plants can also be used for tea preparation. From the 91 herb samples analyzed, nine fell under the food category, nine as medicinal plants, 11 could be used in the preparation of herbal medicine, 32 belonged to two categories (e.g food and herbal medicine/medicinal plant and herbal medicine) and 30 samples were not listed in the legislation in any category, as they were composed of different plant species than described in the technical documents, other plant parts or not described at all. Brazilian MLs are only established for dry herbs used as medicinal plants (AFs\u0026thinsp;=\u0026thinsp;20 \u0026micro;g/kg; AFB\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5 \u0026micro;g/kg). If it were to apply these limits to all types of herbs analyzed in the present study, samples of green tea (leaf and stalk; AFB\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;47.1 \u0026micro;g/kg), horse chestnut (seed; AFB\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;28.6 \u0026micro;g/kg), horseradish tree (leaf; AFG\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;62.4 \u0026micro;g/kg) and sena (leaf and bark; AFB\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;465.2 \u0026micro;g/kg) would exceed the ML.\u003c/p\u003e \u003cp\u003eThe Brazilian Health Surveillance Agency requires producers to monitor mycotoxins in dry herbs used for herbal medicine preparation whenever reports of the occurrence are available (ANVISA, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, to our knowledge, there is no published compilation of this information, which makes it challenging to identify which plants and which mycotoxins should be monitored in dry herbs in Brazil. The present study showed the occurrence of eight mycotoxins in at least 22 species of dry herbs, information that could be used to create a database as a source for producers monitoring actions. Furthermore, discussions on the establishment of MLs for mycotoxins in herbal teas commercialized in Brazil should be engaged, considering both the present study and the occurrence reports available in the literature.\u003c/p\u003e \u003cp\u003eThe chronic dietary risk assessment conducted for total ZEA and FB\u003csub\u003e2\u003c/sub\u003e showed no risk of exposure through the consumption of tea infusion by the Brazilian population. As a conservative approach, this study considered that all mycotoxins present in the dry herb were transferred to the infusion ready for consumption, an assumption confirmed by Reinholds et al.(2019) for ZEN. Other studies, however, showed a decrease in mycotoxin concentration in the herb infusion, depending on the mycotoxin and the infusion preparation. Caldeir\u0026atilde;o et al.(2021) showed that no AFG\u003csub\u003e1\u003c/sub\u003e and OTA were transferred to the infusion, and a reduction of up to 95% on AFB\u003csub\u003e1\u003c/sub\u003e content could be achieved during the tea preparation, considering the physical-chemical properties of the compounds. In a study by Chalyy et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), 83% of the initial OTA content was transferred to the infusion, while ZEN had from 75 to 100% reduction. Wan et al(2025) evaluated naturally contaminated tea samples with ZEN, FB\u003csub\u003e2\u003c/sub\u003e and AFM\u003csub\u003e1\u003c/sub\u003e and found that less than 1% mycotoxin levels were transferred into tea infusion during the first brewing (up to 2% after five brewing). If a decrease in mycotoxin concentration was considered in the present study, the estimated exposure would be even lower as well as the risks from tea consumption.\u003c/p\u003e \u003cp\u003eOther studies also showed that the risk to mycotoxins from tea consumption was low, even when considering conservative approaches (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In Brazil, Caldeir\u0026atilde;o et al.(2021) evaluated risks from exposure to aflatoxins (AFB\u003csub\u003e1\u003c/sub\u003e and AFB\u003csub\u003e2\u003c/sub\u003e), OTA, sterigmatocystin and HT-2 (a trichothecene) considering daily tea consumption of 200 mL of individual types of herbs (rosemary, star anise and sage). The hazard quotient (HQ) calculated for HT-2 showed a potential health concern in infusions of \u003cem\u003eespinheira santa\u003c/em\u003e (4.5) and mint (2.2). The margin of exposure (MOE) for aflatoxins were below 50 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) for rosemary, star anise and sage, which may indicate a potential health risk for a genotoxic compound (MOE\u0026thinsp;\u0026lt;\u0026thinsp;10,000). MOE was 805.5 for OTA and 26.7 for STC, but as these mycotoxins are not genotoxic, no potential health risk is expected.\u003c/p\u003e \u003cp\u003eUsing both deterministic and probabilistic approaches, Zhou et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found no potential risk to the Chinese population from the exposure to 16 mycotoxins through the consumption of tea as a beverage or a dietary supplement (green, oolong, black and dark tea). Reinholds et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) estimated that the exposure of the Latvian population to mycotoxins through the consumption of tea (black, green, oolong and Pu-erh) represented up to 78.9% of the HBGV for DON. Although it was mentioned there were no health risks for AFs, the MOE estimated from data presented in the paper were \u0026lt;\u0026thinsp;10,000, which indicates a health concern.\u003c/p\u003e \u003cp\u003eAssun\u0026ccedil;\u0026atilde;o et al.(2021) estimated the intake of AFB\u003csub\u003e1\u003c/sub\u003e, FB\u003csub\u003e1\u003c/sub\u003e and ZEN through the consumption of green tea in Portugal (10 cups of tea, 150 mL each) and found no potential health risks. However, exposure was estimated considering only one positive sample for each mycotoxin, which is very limited. In another Portuguese study, the exposure to AFs and ZEN through tea consumption represented 12.1 to 122% of a Tolerable Daily Intake (TDI) for AFs and up to 0.07% of the HBGV for ZEN (Duarte et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the TDI approach for AFs is not recommended as they are genotoxic compounds. In Taiwan, the mycotoxin exposure from the tea brewed up to 5 times (consumers only) and individual concentration levels of contaminated samples represented up to 2% of the established HBGV for ZEN and FB\u003csub\u003e2\u003c/sub\u003e (Wan et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough most studies showed no health concern from exposure to mycotoxins through the consumption of tea, some of them have indicated a potential health risk from exposure to aflatoxins, based on a very low number of positive samples. In the present study, the chronic dietary risk assessment was carried out only for FB\u003csub\u003e2\u003c/sub\u003e and TZEN, precisely due to the low number of positive samples for the other mycotoxins, which limits the assessment.\u003c/p\u003e \u003cp\u003eOne limitation of this study is the high LOD/LOQ obtained for DON and its derivatives, which may have influenced the ability to detect those mycotoxins in the samples analyzed. It is well known how good agricultural and manufacturing practices can contribute to the control of mycotoxin contamination. Therefore, improvements must be implemented in the herbal tea production chain to ensure that the products have the lowest possible level of mycotoxin contamination. Furthermore, continuous monitoring actions must be conducted to provide more occurrence data that would allow a broader chronic dietary risk assessment evaluation.\u003c/p\u003e \u003cp\u003eIn summary, this study establishes a single QuEChERS-based LC-MS/MS method that was fully validated for the simultaneous determination of 15 mycotoxins in complex herbal matrices used for tea preparation. By incorporating composite-sample validation and isotope-labeled internal standards, matrix effects were markedly reduced and quantitative accuracy was improved, enabling reliable multi-analyte monitoring of dry herbs. Among the 91 dry herbs analyzed, 25.3% contained at least one mycotoxin and co-occurrence was observed in five samples. Dietary exposure to total ZEN and FB\u003csub\u003e2\u003c/sub\u003e from tea infusions was below health-based guidance values, however, the occurrence of elevated contamination in some samples underscores the need for targeted monitoring and reinforced producer-level control measures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis Project was financially supported by the Foundation for Research Support of the Federal District / FAP-DF (PROJETO N\u0026ordm; 263/2020 - EDITAL N\u0026ordm; 03/2018 - Processo n\u0026ordm; 00193-00001659/2019-45) and University of Bras\u0026iacute;lia (EDITAL DPI/DPG N. 04/2024). C.S Evangelista received a Master Scholarship from the University of Bras\u0026iacute;lia and from FAP-DF.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCRediT authorship contribution statement\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEloisa Dutra Caldas, Patr\u0026iacute;cia Diniz Andrade\u003c/strong\u003e: Conceptualization, writing, review and editting. \u003cstrong\u003eCamila Suguiura Evangelista\u003c/strong\u003e, \u003cstrong\u003eDenise Carvalho Mello\u003c/strong\u003e: sample collection, formal analysis, methodology. \u003cstrong\u003ePatr\u0026iacute;cia Diniz Andrade\u003c/strong\u003e: Funding acquisition, project administration. \u003cstrong\u003eEloisa Dutra Caldas\u003c/strong\u003e: supervision. \u003cstrong\u003eCamila Suguiura Evangelista\u003c/strong\u003e: writing - first draft. All authors have read and agreed to the published version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest: None\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbd El-Aty, A. M., Choi, J. H., Rahman, M. M., Kim, S. W., Tosun, A., \u0026amp; Shim, J. H. (2014). Residues and contaminants in tea and tea infusions: a review. \u003cem\u003eFood Additives and Contaminants - Part A Chemistry, Analysis, Control, Exposure and Risk Assessment\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(11). https://doi.org/10.1080/19440049.2014.958575\u003c/li\u003e\n\u003cli\u003eAlizadeh, A. M., Roshandel, G., Roudbarmohammadi, S., Roudbary, M., Sohanaki, H., Ghiasian, S. A., Taherkhani, A., Semnani, S., \u0026amp; Aghasi, M. (2012). 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Development of a Novel UPLC-MS/MS Method for the Simultaneous Determination of 16 Mycotoxins in Different Tea Categories. \u003cem\u003eToxins\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(3). https://doi.org/10.3390/toxins14030169\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"mycotoxin-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"myre","sideBox":"Learn more about [Mycotoxin Research](http://link.springer.com/journal/12549)","snPcode":"12550","submissionUrl":"https://submission.nature.com/new-submission/12550/3","title":"Mycotoxin Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"dry herbs, tea, mycotoxins, isotope-labeled internal standards, dietary risk assessment","lastPublishedDoi":"10.21203/rs.3.rs-8376617/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8376617/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this work, a multi-mycotoxin analytical method was validated for the determination of 15 mycotoxins and related metabolites in dry herbs commonly used for tea preparation. Samples were extracted using a modified QuEChERS procedure, and quantification was performed by UHPLC-MS/MS with matrix-matched calibration and isotope-labeled internal standards dilution. At the lowest spiking level, recoveries ranged from 82% (AFB\u003csub\u003e1\u003c/sub\u003e) to 111% (FB\u003csub\u003e3\u003c/sub\u003e). Repeatability and intermediate precision (RSD) were below 20% for all analytes across three fortification levels. Ninety-one samples representing 33 types of dry herbs were analyzed, of which 25.3% were positive (\u0026ge;\u0026thinsp;LOQ) for at least one mycotoxin. Zearalenone (ZEN) was the most frequently detected analyte (13.2%), followed by fumonisin B\u003csub\u003e2\u003c/sub\u003e (FB\u003csub\u003e2\u003c/sub\u003e, 4.4%), aflatoxin B\u003csub\u003e1\u003c/sub\u003e (AFB\u003csub\u003e1\u003c/sub\u003e, 3.3%), and ochratoxin A (OTA, 3.3%). A chronic dietary risk assessment for FB\u003csub\u003e2\u003c/sub\u003e and total zearalenone (ZEN\u0026thinsp;+\u0026thinsp;α-zearalenol) indicate no health concern for tea consumers, with estimated intakes not exceeding 5% of the established Health-Based Guidance Values.\u003c/p\u003e","manuscriptTitle":"Mycotoxins occurrence in dry herbs used for tea preparation: method validation, analysis of bulk samples and dietary risk assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-01 07:09:16","doi":"10.21203/rs.3.rs-8376617/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-17T13:14:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-12T15:42:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-12T15:42:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T08:49:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87184247010502922706118208607073379565","date":"2026-01-13T14:18:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66934263111190904087240269886190103375","date":"2025-12-30T14:19:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-30T11:29:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-20T17:35:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-20T17:35:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Mycotoxin Research","date":"2025-12-16T13:07:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"mycotoxin-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"myre","sideBox":"Learn more about [Mycotoxin Research](http://link.springer.com/journal/12549)","snPcode":"12550","submissionUrl":"https://submission.nature.com/new-submission/12550/3","title":"Mycotoxin Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d4612deb-7626-4e7e-9e89-6d04d370ab94","owner":[],"postedDate":"January 1st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T10:58:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-01 07:09:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8376617","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8376617","identity":"rs-8376617","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}