{"paper_id":"30f330ca-b625-4967-9ff7-348777566b86","body_text":"Simultaneous evaluation ochratoxin A, aflatoxins, and zearalenone contamination level in Iran’s frijoles during years 2019-2022 using HPLC-FLD | 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 Simultaneous evaluation ochratoxin A, aflatoxins, and zearalenone contamination level in Iran’s frijoles during years 2019-2022 using HPLC-FLD fatemeh kardani, Aniseh zarei jelyani, Mohammad Hashemi, Marzieh Rashedinia, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3275679/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Considering the importance of frijoles in Iran as a favorite and widely consumed food, for the first time, research was conducted on the contamination of frijoles with mycotoxins. Mycotoxins were measured with a recovery of 95–102% by high-performance liquid chromatography (HPLC) and extracted and purified using a conventional commercial immunoaffinity column. In this research, 450 samples of frijoles, including 150 beans, 150 lentils, and 150 peas were examined. All the beans and peas were free of mycotoxins, and only 5 lentil samples contained mycotoxins. Two samples were contaminated with Aflatoxin B2 (AFB2) and (Aflatoxin G1) AFG1 toxins, one sample was contaminated with Ochratoxin A (OTA), one sample was contaminated with (Zearalenone) ZEA and another sample was contaminated with AFG1) was identified, the value was detected 14.2 ± 0.16 ng/g and < LOQ, which was lower than the detectable level in Iran and the European Union. The results in this research show the improvement of the sanitary conditions of cultivation, harvesting, and storage after the harvesting of frijoles in Iran. High-performance liquid chromatography (HPLC) aflatoxins ochratoxin A zearalenone frijol Figures Figure 1 Figure 2 1. Introduction Grain legumes or frijoles are edible seeds with high protein content, commonly used for food applications. Considering the nutritional value of frijoles and the potential substitute for protein of animal products, they play an important role in the food supply of countries. While consumption of grain legumes varies around the world, vegetarians are the population that specifically consumes more grain legume products (Kunz, Wanko et al. 2020 ).Concerns about food contamination with toxigenic fungi and their effects on human health have recently been noticed. Most corps, such as grains, wheat, maize, legumes, nuts, oil seeds and rice, can be infected by microscopic molds can produce toxic secondary metabolites, namely mycotoxins (Mazaheri 2023 ).It has been well established that the toxic metabolites of fungi or mycotoxins have been responsible for many epidemics in human and farm animals (Agriopoulou, Stamatelopoulou et al. 2020 ). Fungal contamination is intensified under the effect of environmental factors such as temperature, humidity and rainfall during cultivation, harvesting and storage after harvest (Agriopoulou, Stamatelopoulou et al. 2020 ). Aflatoxins (B1, B2, G1 and G2) are the most mycotoxins produced by the fungi Aspergillus species (A. flavus and A. parasiticus). In addition, during the storage of plant crops in non-optimal conditions, there is a possibility of production of ochratoxin A from several species of Aspergillus and Penicillium (Fakoor Janati, Beheshti et al. 2011 ). Among the mycotoxins, aflatoxins (AFT), zearalenone (ZEA), ochratoxin A (OTA), and deoxynivalenol are of particular importance because they cause liver and kidney cancer, hepatotoxicity, nephrotoxicity, estrogenic effect, and growth impairment for chronic exposure (Mazaheri 2023 ). Numerous studies have shown AFT and OTA contamination in cereals, coffee beans and dried fruits, as well as in products of plant origin such as wine and beer. However, limited studies have reported levels of aflatoxin and OTA contamination in legumes. Contamination of mycotoxins in grain legumes generally occurs due to long-term storage in improper conditions, especially in farms and markets before consumption (Fakoor Janati, Beheshti et al. 2011 , Kunz, Wanko et al. 2020 , Acuña-Gutiérrez, Jiménez et al. 2022 ). Although previous studies have shown that the level of AFT and OTA in the samples of some legumes, such as beans, mung bean, peas, lentils and cotyledons, was lower than the permissible limit or lower than the detection limit (Fakoor Janati, Beheshti et al. 2011 , Ahmadi, Jahed Khaniki et al. 2022 ), but it is important to protect the health of consumers through the implementation of a series of effective measures to reduce aflatoxin contamination to the lowest possible level. Failure to do so may have irreparable economic consequences for producers and deprive consumers of the pleasure of consuming valuable sources of healthy nutrients. Due to the increasing awareness of many countries about the carcinogenic, mutagenic and teratogenic effects of mycotoxins on humans and animals, they have established maximum acceptable levels for these toxins in food (Logotheti, Kotsovili-Tseleni et al. 2009 ). The maximum limit levels of aflatoxin AFB, total aflatoxin AFT and OTA in frijoles are 5, 15 and 20 ng/g in the national standard of Iran, respectively (INSO 5925, 2020) but for ZEA no limit has been set in frijoles. In 1998, the Commission of the European Communities established a maximum acceptable level of AFB1 in a range of commodities for human consumption of 2 ng/g (Mirabolfathy, Osboo et al. 2019 ). Recently, the European Union Commission increased the maximum level of frijoles intended for direct human consumption or use as raw materials in the food industry to 8 ng/g and for AFT from 4 to 10 ng/g. Considering the extent of cultivation and consumption of frijoles in the world, so contamination with mycotoxins could be a potential hazard to the health of consumers. In addition, the limitation of studies related to the measurement of mycotoxins in frijoles, this study was conducted with the aim of determining the presence and levels of AFT, OTA and ZEA in beans, lentils and chickpea (n = 150) that are sold and consumed in the supply level of the Iranian market. 2. Materials and methods 2.1. Sampling A total of 450 samples of frijoles were sampled by inspectors of food control centers in Ahvaz and Shiraz from January 2020 to December 2022. Sample collection was according to the method described in Commission Regulation (EC) No. 401/2006 (EC, 2006b) and then during October 2020 to December 2021 according to Commission Regulation No. 178/2010 (EC, 2010b) was done. For this purpose, 100 samples weighing 300 or 200 gs were mixed and divided into three or two sub-samples of 10 kg each. After preparing sub-samples for analysis and further analytical tests, the tests were carried out in the toxicology laboratories of food control laboratories in Ahvaz and Shiraz. 2.2. Chemicals and reagents Aflatoxin G1, G2, B1, B2, and ochratoxin A (OTA) standards were obtained from Sigma. Methanol, acetonitrile, and HPLC grade water were used. Sodium chloride, potassium bromide, nitric acid and phosphate buffer pH = 7.4, 0.2 g KCl, 0.20 g KH 2 PO 4 , 1.16 g anhydrous Na 2 HPO 4 or 2.92 g salt H 2 PO 4 , 2.2 g salt were added. 900 mL of water, and the pH was adjusted to 7.4. 2.3. Standard preparation After preparing the standard solutions of each AFT, and OTA, their concentration was measured using a UV-Visible spectrometer through the official method of AOAC No. 971.22. The working standard solution was prepared by diluting the mixed standards, the 40 ng/mL stock standard (AFB1, AFG1 = 16 ng/g; AFB2, AFG2 = 4 ng/g), with methanol and water by HPLC. 2.4. Instrumentation To separate aflatoxins, a Knauer model HPLC device equipped with an ultraviolet, and fluorescence detector made in Germany was used. A Cintra101 model GBC spectrometer made in Australia was used to determine the absorbance, λmax, a (the wavelength with the highest absorption), and λmax,e (the wavelength with the highest emission). To achieve the best degree of separation, and separation of the mobile phase, it was optimized. For this purpose, different solvents such as water, ethanol, methanol, and acetonitrile were used as the mobile phase with different percentages, which the results showed. The best separation time was obtained from a mixture of two solvents, water, and methanol with a percentage of 55:45, and a flow rate of 0.8 mL/min. To investigate the disturbances in the measurement of the target compounds, the control experiment was carried out using the mobile phase, and the solution. The sample was performed in the absence of analytes, and no interference peak was observed in the peak position of the target analytes. Also, λmax,a, and λmax,e of the detector were selected for the maximum sensitivity of 280, and 275 nm, respectively. Using these conditions, the total analysis time took less than 45 minutes. 2.5. Extraction purification Preparation of ochratoxin A was as follows For this purpose, 1 g of salt was added to 25 g of ground sample. Then 100 mL of extraction solvent (4.8 volume of acetonitrile − 1.6 volume of water) was added, and shaken for 3 minutes. The obtained extract was passed through filter paper, 10 mL of filtered extract was diluted with 50 mL of PBS buffer, and the diluted solution was passed through GFF. 55 mL of the diluted extract was used to pass through the immunoaffinity column. After the temperature of the immunoaffinity column reached room temperature, the tank was connected to the head of the column by an adapter, and 10 mL of PBS was transferred to the tank. It was passed through the column without pressure. 55 mL of the diluted extract was passed through the column at a speed of one to two drops per second. The column was washed with 15 mL of PBS, and finally dried for 5 seconds by positive air pressure. Then 1500 µL of methanol - acetic acid at a volume ratio of 98 methanol, and 2 volumes of acetic acid were passed through the column, and the passed solution was collected in a clean vial. 1500 µL of deionized water were added to the vial, then vortexed and injected into the device. The test method for the preparation of zearalenone was as follows 1 g of salt was added to 25 g of the ground sample. Then 100 mL of extraction solvent (4.8 volumes of acetonitrile − 1.6 volumes of water) was added and the shaker was stirred for 3 minutes. The extract obtained from filter paper was passed, 10 mL of the filtered extract was diluted with 65 mL of deionized water, and the diluted solution was passed through GFF, after which 10 mL of PBS was passed. 65 mL of the diluted extract was passed through the column at a speed of one to two drops per second. The column was washed with 15 mL of PBS and dried for 5 seconds with positive air pressure. Next, 2000 µL of methanol were passed through the column and the solution was collected in a clean vial. 2000 µL of deionized water were added to the vial, vortexed and injected into the HPLC machine. Preparation of aflatoxins is done as follows Weighing 25 g of the sample, adding 2.5 g of sodium chloride and 100 cc of 80% methanol, in the following shaking for 30 min and filtering with GFF. Remove 10 cc of the filtered solution along with 60 cc of deionized water and passed through GFF. Next pass 40 cc of the diluted extract through the immunoaffinity column and collect and bring to a volume of 3 cc. Figure 1 illustrates the general principles of the preparation process. 3. Results 3.1. Statistical assessment of analytical data After evaluating of the optimal conditions, the figures of merit such as calibration curve, line equation, detection limit, correlation coefficient, repeatability and reproducibility, precision and accuracy, and finally the measurement of the desired target compounds in real samples were investigated and evaluated. 3.1.1. Calibration curve and linear range The calibration curves and the equation of the line related to the target compounds were obtained by plotting the ratio of the peak area of each compound against the species concentration. After extracting the target compounds by extraction method, the calibration curve for the target concentration from 0.01-30, 0.03-40 and 0.2–350 ng/g were linear for AF, OTA and ZEN respectively. Table.1 shows the calibration curve data related to each of the target compounds. The experiments were repeated 5 times in each concentration of the calibration curve. The target correlation coefficient was more than 0.9901. 3.1.2. Calculation of the limit of detection and limit of quantification To estimate the detection limit of the method, the lowest concentration of Mycotoxins compounds was selected from the calibration curve. This value was equal to 0.1 µg/L for all four desired compounds. The standard deviation corresponding to 10 measurements at this concentration was calculated for all four compounds and by putting its value in Eq. ( 1 ), the detection limit of the method for mycotoxins compounds was obtained. To calculate the quantification limit of the method, the standard deviation corresponding to 10 measurements of four analytes is placed in Eq. ( 2 ). Table.1 shows the figures of merit obtained from the calibration curves. Where m is the slope of the calibration curve and S b , standard deviation of blank, which can be obtained by several successive injections of a low concentration from the calibration curve. S b by averaging the repetition of the obtained data and suitable replacement in the equation, the detection limit is calculated. Using the above equation, the experimental LODs for aflatoxin obtained in range 0.0031–0.0044, 0.0148 and 0.0601 ng/g were for AF, OTA and ZEN respectively. The LOQs (quantity limit) is generally referred to a place that is equal to 10 times the standard deviation of repeated measurements on the blank. LOQs for aflatoxin obtained in range 0.0083–0.013, 0.042 and 0.213 ng/g were for AF, OTA and ZEN respectively. 3. 1.3. Accuracy and precision The intra-day and inter-day precisions of the assay were evaluated by analyzing quality control samples at three concentration levels (0.3, 5, 15 µg/kg , 10, 150, 300 and 3, 15, 30 for AF, OTA and ZEN respectively) on the same day and the five consecutive days. The results of accuracy and precision are presented in Table 2 . The inter-day %RSD for all compounds (AFB 1 , AFB 2 , AFG 1 , and AFG2) was 2.38–3.96%. Also, the intra-day RSD were less than 2.22–4.53%. Also, recovery values for aflatoxins in the mentioned concentrations were obtained in the range of 96.82–107% (Table 2 ). Table 1 Figures of merit of the method for determination mycotoxins (n = 5) Analyte Range (ng g − 1 ) Slope ± SD R 2 In spiked bean (ng g − 1 ) LOD LOQ AFB1 0.01-30 5.98 + 007 0.9957 0.0031 0.0113 AFB 2 0.01-30 4.87 + 007 0.9901 0.0044 0.0123 AFG 1 0.01-30 5. 68 + 007 0.9943 0.0038 0.0083 AFG 2 0.01-30 6.76 + 006 0.9936 0.0035 0.013 OTA 0.03-40 6.48 + 005 0.9936 0.0148 0.042 ZEA 0.2–350 4. 44 + 004 0.9958 0.0601 0.213 Table 2 Accuracy and precision for mycotoxins determination in optimal HPLC conditions for mycotoxins standard and spiked bean. Mycotoxins Spiked concentration Mycotoxins solution Spike bean Within -day(n = 5) Between-day (n = 5) Within-day (n = 5) Between-day (n = 5) Accuracy (%) RSD (%) Accuracy (%) RSD (%) Recovery (%) RSD (%) Recovery (%) RSD (%) AF B1 15 98.66 3. 12 97.91 3.07 99.83 4.55 97.12 3.45 5 99.95 2. 48 97.75 2.22 97.36 4.33 97.61 3.43 0.3 101.02 3.52 97.33 3.48 99.22 4.53 87.65 3. 87 AF B2 15 99.93 3. 32 98.99 3.73 98.16 4.63 98.56 3.06 5 97.56 4. 31 96.34 3.12 99.48 4.42 97.79 3.53 0.3 99.95 3. 21 98.62 3.36 99.62 4.79 97.68 3.32 AF G1 15 102.01 2. 48 102.1 4.23 99.26 4.56 96.46 3.48 5 99.96 3. 36 101.02 3.89 98.35 2.65 97.87 3.98 0.3 98.44 3.06 97.62 3.71 99.31 4.62 97.89 3.739 AF G2 15 96.33 3.35 101.12 3.85 99.63 3.65 97.56 3.41 5 101.06 3. 63 97.74 2.61 99.54 3.42 97.68 3.63 0.3 99.35 3.96 99.62 3.21 96.64 4.25 97.94 3.74 ZEA 300 98.77 2.95 97.35 3.29 100.44 4.34 97.29 3.52 150 97.87 1.75 102.85 3.46 99.56 4.52 97.61 3.29 10 101.03 3.06 96.04 4.21 99.27 4.38 97.56 3.14 OTA 30 96.79 1.69 99.85 4.11 99.62 4.33 96.48 2.32 15 96.89 3.41 96.98 3.23 99.78 4.65 97.54 3.08 3 98.92 3.16 97.63 2.61 97.88 4.55 97.16 2.78 Accuracy analyzed by HPLC-FLD of the method was determined by repeated analysis of blank cereal samples with target analytes at three concentration levels (0.3, 5, 15 µg/ kg,10, 150, 300 and 3, 15, 30 for AF, OTA and ZEN respectively). The blank frijoles samples extract (n = 3) was extracted and analyzed as described under the analytical procedure. Using the calibration curves and the equation specified below, the recovery value was calculated with the measured concentrations: Where C found , C real , and C added , respectively, are the mycotoxins concentrations in the real samples after being added to a known quantity of standard, the mycotoxins concentration in the sample of mycotoxins, and the known amount of standard that was spiked into the sample of frijol. The relative standard deviation (RSD) from five repetitions used as an indicator of precision. The mixed standard solutions were added to the frijol samples to make them 0.3, 5, 15 µg/kg10, 150, 300 and 3, 15, 30 for AF, OTA and ZEN respectively, and the recovery experiments were repeated thirty times. The samples' average mycotoxins recovery varied from 80.0–104.0%. According to Table 3 , the samples' respective relative standard deviations (RSD) varied from 1.6–8.3%. To rule out interference caused by contamination from the equipment, solvents, instrument, or chemicals utilized, the reagent and instrument blank were regularly run. Table 3. Recovery and relative standard deviation (RSD) of mycotoxins in different frijol samples (n=3). Bean Lentil Chickpea Spiked level Recovery RSD Recovery RSD Recovery RSD Analytes (ng/g) (%) (%) (%) (%) (%) (%) AFB1 15 96.99 3.21 99.53 3.12 98.88 4.38 5 98.38 4.23 98.82 3.26 99.56 3.13 AFB2 15 103.15 2.39 96.46 3.43 98.61 3.62 5 100.23 3.21 102.75 2.36 88.95 4.38 AFG1 15 99.28 3.13 97.54 3.36 98.88 3.84 5 98.53 3.18 97.93 3.05 96.82 3.54 AFG 15 96.63 3.41 96.16 3.18 103.11 3.86 5 98.96 3.53 98.67 3.83 98.07 3.47 OTA 150 103.32 3.62 93.78 3.02 98.12 4.38 10 98.79 3.13 98.15 3.86 98.26 3.96 ZEA 15 98.43 3.34 99.56 3.25 98.93 3.11 3 98.71 3.41 97.45 3.83 98.98 4.01 3.4.1. Measurement of uncertainty The four major contributions to uncertainty are recorded in Table 4 based on the validation data. It shows the uncertainty values calculated for the simultaneous measurement of mycotoxins. The estimated uncertainties of 0.118, 0.0794, 0.100, 0.0009, 0.024 and 1.230 for AF, OTA and ZEA respectively. Table 4 Description of the components taken into account for estimating uncertainty. Uncertainty values Uncertainty components AFB1 AFB2 AFG1 AFG2 OTA ZEA u 2 M 0.00109284 0.0006733 0.000188 0.00022 0.000482 0.000175 £u 2 vi 0.00011 0.000009 0.0001 0.000482 0.000492 0.000145 u 2 r 0.0005433 9.2592211 0.00107 0.00022 0.0001 0.0016 u 2 R 0.00180906 0.0007031 0.001192 0.00013 0.022533 1.05431 u 2 0.00353223 0.0014780 0.00255 0.00046 0.00115 0.000293 2u = U(ng/g) 0.11889284 0.0793492 0.100788 0.000991 0.024263 1.230141 4. Discussion 4.1. Application to real samples After applying the method on frijol samples, interpretation and analysis of the simultaneous amount of AF, OTA and ZEA was done. The interpretation and analysis of the results are shown in Table 5 . As can be inferred, frijol products are at a very favorable level regarding contamination with mycotoxins. Of the 150 bean samples tested, no mycotoxin was detected, but in 150 lentil samples collected, aflatoxin was detected in 5 samples. Out of 5 samples, two samples were contaminated with AFB2 and AFG1 toxins, and one sample was contaminated with OTA, another sample was contaminated with ZEA and another sample was contaminated with AFG1. All the detected mycotoxins were below the EU limit (European Commission 2006), so it can be said that the lentil samples are at a very good level in terms of mycotoxins, and no mycotoxins were detected in the 150 chickpea samples analyzed. The results obtained in this research, two general conclusions can be drawn about the level of mycotoxin contamination of frijoles: 1- The Health Organization and the Food and Drug Organization as well as the Agricultural Organization of Iran have very good control over the frijol products and 2- The level of contamination of frijoles with mycotoxins. Mycotoxins are much lower than in crops such as cereals. In Fig. 2 , the chromatograms demonstrated selectivity of the optimized method established by blank sample and a sample spiked with mycotoxins. Also, the peaks of mycotoxins were well separated from each other, there were no interfering peaks coincide at the retention times of each mycotoxin. Therefore, satisfied selectivity and specificity of the procedure were obtained. Table 5 Mycotoxins contamination in frijol samples in the Iranian market. Type of cereal Number of samples analyses AF OTA ZEA AFB1 AFB2 AFG1 AFG2 Bean 150 ND ND ND ND ND ND Lentil 150 1 < MLRs 2 < MLRs 2 < MLRs ND 1 < MLRs 1 < MLRs Chickpea 150 ND ND ND ND ND ND 4.2. Investigation and interpretation of aflatoxins in frijoles in comparison cereal Aflatoxin contamination in frijoles can be different based on factors such as pre-harvest and post-harvest conditions, storage methods, and transportation methods. Comparative studies that analyze the occurrence of aflatoxin in frijoles from Iran and other countries can provide insight into the relative risks associated with the consumption of these beans. Publicly available data from government authorities, scientific literature, or international organizations can help identify this rate of occurrence. Countries use various mitigation strategies to minimize aflatoxin contamination in food products. These strategies can include good agricultural practices, proper storage and handling, and post-harvest treatments. By comparing the strategies implemented in Iran with other countries, it is possible to evaluate the effectiveness of different approaches in reducing aflatoxin contamination. More research and analysis are needed to provide an in-depth and comprehensive comparison of aflatoxin levels in frijoles between Iran and other countries. Conducting country-specific studies and collecting representative data helps to make a more accurate and comprehensive comparison. But so far, no comprehensive study has been conducted on the presence of aflatoxins in the frijole’s products class in any country in the world. In this study, for the first time, we specifically evaluated the presence of aflatoxins in the frijole’s products. In this study, the presence and amount of aflatoxins in frijoles were compared with the presence and amount of aflatoxins in cereals. The study on cereals was conducted by our research group on 450 samples including 150 rice samples, 150 wheat samples and 150 corn samples (Kardani, Rashedinia et al.). Preparation methods were the same for legumes and cereal. The results obtained from the evaluation of 450 frijoles samples are shown in Table 5 . As the results show, no mycotoxin was detected in the tested bean sample, but aflatoxin was detected in the collected lentil sample. All the detected mycotoxins were below the limit of the European Union (European Commission 2006), Therefore, as the results show, the lentil samples are at a very good level, and no mycotoxins were observed in the analyzed Chickpea samples. The detected values in the examined cereal samples are shown in Table 6 . Compared to frijoles, more aflatoxins were detected in cereals. Among the 150 rice samples analyzed, 15 samples were infected with AFG2 AFB1 and 5 samples were infected with AFG1 below the MRL (≤ 15 µg/kg). While the incidence of AFG2 level in 2 samples is higher than the EU limit (European Commission 2006). Also, OTA and ZEN were not detected in any sample. AFB1 and AFB2 were analyzed in four maize samples, and AFB2 concentration exceeded the EU ML in two samples. ZEN values were observed in 10 samples, the determined concentrations were lower than EU ML. Furthermore, OTA was not detected in any corn samples. In a total of 150 wheat samples, 13 samples were infected with AFB1, AFB2, and the detected values were lower than the MRL (15 µg/kg), and only in one sample, OTA was detected, and ZEN was not found in any sample. Two conclusions can be inferred from the obtained results: 1- In Iran, the control of leguminous products is much more appropriate than that of grains. 2- The degree of mycotoxin contamination of beans. Mycotoxins are much lower than in crops such as grains. The probability of the second inference is much higher than the first inference, because due to the nature of legumes and their storage in Iran, they are less exposed to aflatoxin contamination. Table 6 Mycotoxins contamination in cereal samples in the Iranian market. Type of cereal Number of samples analyses AF OTA ZEN AFB1 AFB2 AFG1 AFG2 Rice 150 15< MLRs ND 5< MLRs 15(2 sample > MLRs) ND ND Corn 150 4 4(2sample > MLRs) ND 10< MLRs Wheat 150 13< MLRs 13< MLRs ND ND ND ND 5. Conclusions The analysis of aflatoxins, mycotoxins and zearalenone in frijol samples is of great importance in human health. This study proved the simultaneous determination and analysis of AFs (B1, B2, G1 and G2), OTA, and ZEA in frijoles. This method is an excellent candidate for future standardization due to its reliability and efficiency for the screening and analysis of mycotoxins. The investigated parameters for this study include linear range, recovery detection limit and standard deviation. The LOD and LOQ obtained for the samples were in the range of 0.01–0.03 ng/g, for AFB1 and AFG1, 0.003 and 0.01 ng/g for AFB2 and AFG2, 0.02 and 0.1ng/g for OTA and 0.06 ng/g for ZEA respectively. Our method offers accurate, sensitive and simple HPLC-FLD methods that reduce the total analysis time as well as the cost of the method for the determination of mycotoxins. In this study, AFTs, OTA and ZEA, were investigated for combating highly toxic mycotoxins in frijoles. For this purpose, a total of 450 samples of different frijoles were collected from agricultural markets and local supermarkets during the years 2019–2022. The results clearly showed that frijoles consumed in Iran are in a very good condition in terms of mycotoxins, and the number of mycotoxins is completely controlled and below the MRL. Out of 450 cereal samples analyzed, only 5 samples contained mycotoxins, the detected amounts of which were below the MRL. These results show that leguminous products in Iran are well controlled by the Health Organization and the Food and Drug Organization. Declarations Acknowledgements: All financial sources were acknowledged Author contribution: Conceptualization: FK, AZ; Methodology: FK, AZ, MR; Formal analysis and investigation: FK, AZ, MR, SSH; Writing original draft preparation: FK, AZ, SSH; Writing, review and editing: FK, SSH, AZ, MH, SMA, MM. Funding: The Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran, and the Food and Food and Drug Administration, Shiraz University of medical sciences of Shiraz, Iran, funded for this study. Competing Interests Declaration: According to the authors, they do not have any competing interests. Human and Animal Rights: This article does not contain any studies with human or animal subjects. References Acuña‐Gutiérrez, C., V. M. Jiménez and J. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-3275679\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":228377837,\"identity\":\"5fa52b8a-ca70-42fb-925e-a03c7149dcb9\",\"order_by\":0,\"name\":\"fatemeh kardani\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBACCQiW4AfzGBtsIELEaJFsYANrSSNaCwNMy2HCWiTbzz688XOHhQT//OajGz7uOJ/YP7v54AOGGptoXFqkedKNLXvPSEhIHGNLuznzzO3EGXeOJRswHEvLbcChRY4hjU2Ct02ijuEYj9lt3rbbiQ03cswkgC7ErYX/GZvk3zYJCflj/N9u/207lzifkBZpiTQ2aaAtEgbHeNhuM7YdSNxASIvkjGfM1rJALYbH0sxu9rYlG2+8kZZskIDHLxLn0xhvvm2rk5A7fPjZjZ9tdrLzbiQffPChxganFgzgCFaZQKxyELAnRfEoGAWjYBSMDAAAUhRc/vRrea8AAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0001-8027-8093\",\"institution\":\"Shahid Chamran University of Ahvaz Faculty of Science\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"fatemeh\",\"middleName\":\"\",\"lastName\":\"kardani\",\"suffix\":\"\"},{\"id\":228377838,\"identity\":\"58c46801-1696-4734-9c3e-112c238655f9\",\"order_by\":1,\"name\":\"Aniseh zarei jelyani\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shiraz University of Medical Sciences Faculty of Dentistry\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Aniseh\",\"middleName\":\"zarei\",\"lastName\":\"jelyani\",\"suffix\":\"\"},{\"id\":228377839,\"identity\":\"b5182936-843c-434c-b796-1b8e9906a6b4\",\"order_by\":2,\"name\":\"Mohammad Hashemi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammad\",\"middleName\":\"\",\"lastName\":\"Hashemi\",\"suffix\":\"\"},{\"id\":228377840,\"identity\":\"7f5031fb-1d1c-4070-ac83-0e7aa1efdd73\",\"order_by\":3,\"name\":\"Marzieh Rashedinia\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shiraz University of Medical Sciences Faculty of Dentistry\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Marzieh\",\"middleName\":\"\",\"lastName\":\"Rashedinia\",\"suffix\":\"\"},{\"id\":228377841,\"identity\":\"96dad15b-4caf-4ac6-be7b-cffd66fdcbcd\",\"order_by\":4,\"name\":\"Saeedeh Shariati\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ahvaz Jundishapur University: Ahvaz Jondishapour University of Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Saeedeh\",\"middleName\":\"\",\"lastName\":\"Shariati\",\"suffix\":\"\"},{\"id\":228377842,\"identity\":\"fbb720c1-fdda-4da6-ac88-007e47f4c47b\",\"order_by\":5,\"name\":\"Masoud Mahdavinia\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ahvaz Jundishapur University: Ahvaz Jondishapour University of Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Masoud\",\"middleName\":\"\",\"lastName\":\"Mahdavinia\",\"suffix\":\"\"},{\"id\":228377843,\"identity\":\"a858ccaf-a4ce-4080-a856-ee7773086ec4\",\"order_by\":6,\"name\":\"Seyyed Mohammad Ali Noori\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ahvaz Jundishapur University: Ahvaz Jondishapour University of Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Seyyed\",\"middleName\":\"Mohammad Ali\",\"lastName\":\"Noori\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2023-08-18 14:37:57\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-3275679/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-3275679/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":42260402,\"identity\":\"e426f269-851e-4bc1-873d-c0c0684c0582\",\"added_by\":\"auto\",\"created_at\":\"2023-08-28 18:27:19\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":168962,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eGeneral principles of the preparation process frijol samples\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3275679/v1/ba6334d5deb3939454a79949.png\"},{\"id\":42260400,\"identity\":\"4d1ca22d-8843-4e40-b1f0-cf05add7b023\",\"added_by\":\"auto\",\"created_at\":\"2023-08-28 18:27:18\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":46709,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eChromatogs of (a) standard solution of AFB1 , AFG1, AFB2 ,AFG2, OTA, and ZEA in methanol and(b,c) unspiked samples lentil\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3275679/v1/3bb3249ad10cd24cf0c15eab.png\"},{\"id\":43371688,\"identity\":\"a156e84d-9f04-4731-a034-cedc8b04b28e\",\"added_by\":\"auto\",\"created_at\":\"2023-09-19 15:30:17\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":741420,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3275679/v1/6dc0cb58-fdae-4954-b70a-7341dd1ccb95.pdf\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Simultaneous evaluation ochratoxin A, aflatoxins, and zearalenone contamination level in Iran’s frijoles during years 2019-2022 using HPLC-FLD\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eGrain legumes or frijoles are edible seeds with high protein content, commonly used for food applications. Considering the nutritional value of frijoles and the potential substitute for protein of animal products, they play an important role in the food supply of countries. While consumption of grain legumes varies around the world, vegetarians are the population that specifically consumes more grain legume products (Kunz, Wanko et al. \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).Concerns about food contamination with toxigenic fungi and their effects on human health have recently been noticed. Most corps, such as grains, wheat, maize, legumes, nuts, oil seeds and rice, can be infected by microscopic molds can produce toxic secondary metabolites, namely mycotoxins (Mazaheri \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e).It has been well established that the toxic metabolites of fungi or mycotoxins have been responsible for many epidemics in human and farm animals (Agriopoulou, Stamatelopoulou et al. \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Fungal contamination is intensified under the effect of environmental factors such as temperature, humidity and rainfall during cultivation, harvesting and storage after harvest (Agriopoulou, Stamatelopoulou et al. \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Aflatoxins (B1, B2, G1 and G2) are the most mycotoxins produced by the fungi Aspergillus species (A. flavus and A. parasiticus). In addition, during the storage of plant crops in non-optimal conditions, there is a possibility of production of ochratoxin A from several species of Aspergillus and Penicillium (Fakoor Janati, Beheshti et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e). Among the mycotoxins, aflatoxins (AFT), zearalenone (ZEA), ochratoxin A (OTA), and deoxynivalenol are of particular importance because they cause liver and kidney cancer, hepatotoxicity, nephrotoxicity, estrogenic effect, and growth impairment for chronic exposure (Mazaheri \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Numerous studies have shown AFT and OTA contamination in cereals, coffee beans and dried fruits, as well as in products of plant origin such as wine and beer. However, limited studies have reported levels of aflatoxin and OTA contamination in legumes. Contamination of mycotoxins in grain legumes generally occurs due to long-term storage in improper conditions, especially in farms and markets before consumption (Fakoor Janati, Beheshti et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e, Kunz, Wanko et al. \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e, Acu\\u0026ntilde;a-Guti\\u0026eacute;rrez, Jim\\u0026eacute;nez et al. \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). Although previous studies have shown that the level of AFT and OTA in the samples of some legumes, such as beans, mung bean, peas, lentils and cotyledons, was lower than the permissible limit or lower than the detection limit (Fakoor Janati, Beheshti et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e, Ahmadi, Jahed Khaniki et al. \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), but it is important to protect the health of consumers through the implementation of a series of effective measures to reduce aflatoxin contamination to the lowest possible level. Failure to do so may have irreparable economic consequences for producers and deprive consumers of the pleasure of consuming valuable sources of healthy nutrients. Due to the increasing awareness of many countries about the carcinogenic, mutagenic and teratogenic effects of mycotoxins on humans and animals, they have established maximum acceptable levels for these toxins in food (Logotheti, Kotsovili-Tseleni et al. \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). The maximum limit levels of aflatoxin AFB, total aflatoxin AFT and OTA in frijoles are 5, 15 and 20 ng/g in the national standard of Iran, respectively (INSO 5925, 2020) but for ZEA no limit has been set in frijoles. In 1998, the Commission of the European Communities established a maximum acceptable level of AFB1 in a range of commodities for human consumption of 2 ng/g (Mirabolfathy, Osboo et al. \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Recently, the European Union Commission increased the maximum level of frijoles intended for direct human consumption or use as raw materials in the food industry to 8 ng/g and for AFT from 4 to 10 ng/g. Considering the extent of cultivation and consumption of frijoles in the world, so contamination with mycotoxins could be a potential hazard to the health of consumers. In addition, the limitation of studies related to the measurement of mycotoxins in frijoles, this study was conducted with the aim of determining the presence and levels of AFT, OTA and ZEA in beans, lentils and chickpea (n\\u0026thinsp;=\\u0026thinsp;150) that are sold and consumed in the supply level of the Iranian market.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1. Sampling\\u003c/h2\\u003e \\u003cp\\u003eA total of 450 samples of frijoles were sampled by inspectors of food control centers in Ahvaz and Shiraz from January 2020 to December 2022. Sample collection was according to the method described in Commission Regulation (EC) No. 401/2006 (EC, 2006b) and then during October 2020 to December 2021 according to Commission Regulation No. 178/2010 (EC, 2010b) was done. For this purpose, 100 samples weighing 300 or 200 gs were mixed and divided into three or two sub-samples of 10 kg each. After preparing sub-samples for analysis and further analytical tests, the tests were carried out in the toxicology laboratories of food control laboratories in Ahvaz and Shiraz.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2. Chemicals and reagents\\u003c/h2\\u003e \\u003cp\\u003eAflatoxin G1, G2, B1, B2, and ochratoxin A (OTA) standards were obtained from Sigma. Methanol, acetonitrile, and HPLC grade water were used. Sodium chloride, potassium bromide, nitric acid and phosphate buffer pH\\u0026thinsp;=\\u0026thinsp;7.4, 0.2 g KCl, 0.20 g KH\\u003csub\\u003e2\\u003c/sub\\u003ePO\\u003csub\\u003e4\\u003c/sub\\u003e, 1.16 g anhydrous Na\\u003csub\\u003e2\\u003c/sub\\u003eHPO\\u003csub\\u003e4\\u003c/sub\\u003e or 2.92 g salt H\\u003csub\\u003e2\\u003c/sub\\u003ePO\\u003csub\\u003e4\\u003c/sub\\u003e, 2.2 g salt were added. 900 mL of water, and the pH was adjusted to 7.4.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3. Standard preparation\\u003c/h2\\u003e \\u003cp\\u003eAfter preparing the standard solutions of each AFT, and OTA, their concentration was measured using a UV-Visible spectrometer through the official method of AOAC No. 971.22. The working standard solution was prepared by diluting the mixed standards, the 40 ng/mL stock standard (AFB1, AFG1\\u0026thinsp;=\\u0026thinsp;16 ng/g; AFB2, AFG2\\u0026thinsp;=\\u0026thinsp;4 ng/g), with methanol and water by HPLC.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4. Instrumentation\\u003c/h2\\u003e \\u003cp\\u003eTo separate aflatoxins, a Knauer model HPLC device equipped with an ultraviolet, and fluorescence detector made in Germany was used. A Cintra101 model GBC spectrometer made in Australia was used to determine the absorbance, λmax, a (the wavelength with the highest absorption), and λmax,e (the wavelength with the highest emission). To achieve the best degree of separation, and separation of the mobile phase, it was optimized. For this purpose, different solvents such as water, ethanol, methanol, and acetonitrile were used as the mobile phase with different percentages, which the results showed. The best separation time was obtained from a mixture of two solvents, water, and methanol with a percentage of 55:45, and a flow rate of 0.8 mL/min. To investigate the disturbances in the measurement of the target compounds, the control experiment was carried out using the mobile phase, and the solution. The sample was performed in the absence of analytes, and no interference peak was observed in the peak position of the target analytes. Also, λmax,a, and λmax,e of the detector were selected for the maximum sensitivity of 280, and 275 nm, respectively. Using these conditions, the total analysis time took less than 45 minutes.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5. Extraction purification\\u003c/h2\\u003e \\u003cp\\u003e \\u003cstrong\\u003ePreparation of ochratoxin A was as follows\\u003c/strong\\u003e \\u003cp\\u003eFor this purpose, 1 g of salt was added to 25 g of ground sample. Then 100 mL of extraction solvent (4.8 volume of acetonitrile \\u0026minus;\\u0026thinsp;1.6 volume of water) was added, and shaken for 3 minutes. The obtained extract was passed through filter paper, 10 mL of filtered extract was diluted with 50 mL of PBS buffer, and the diluted solution was passed through GFF. 55 mL of the diluted extract was used to pass through the immunoaffinity column. After the temperature of the immunoaffinity column reached room temperature, the tank was connected to the head of the column by an adapter, and 10 mL of PBS was transferred to the tank. It was passed through the column without pressure. 55 mL of the diluted extract was passed through the column at a speed of one to two drops per second. The column was washed with 15 mL of PBS, and finally dried for 5 seconds by positive air pressure. Then 1500 \\u0026micro;L of methanol - acetic acid at a volume ratio of 98 methanol, and 2 volumes of acetic acid were passed through the column, and the passed solution was collected in a clean vial. 1500 \\u0026micro;L of deionized water were added to the vial, then vortexed and injected into the device.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eThe test method for the preparation of zearalenone was as follows\\u003c/strong\\u003e \\u003cp\\u003e1 g of salt was added to 25 g of the ground sample. Then 100 mL of extraction solvent (4.8 volumes of acetonitrile \\u0026minus;\\u0026thinsp;1.6 volumes of water) was added and the shaker was stirred for 3 minutes. The extract obtained from filter paper was passed, 10 mL of the filtered extract was diluted with 65 mL of deionized water, and the diluted solution was passed through GFF, after which 10 mL of PBS was passed. 65 mL of the diluted extract was passed through the column at a speed of one to two drops per second. The column was washed with 15 mL of PBS and dried for 5 seconds with positive air pressure. Next, 2000 \\u0026micro;L of methanol were passed through the column and the solution was collected in a clean vial. 2000 \\u0026micro;L of deionized water were added to the vial, vortexed and injected into the HPLC machine.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003ePreparation of aflatoxins is done as follows\\u003c/strong\\u003e \\u003cp\\u003eWeighing 25 g of the sample, adding 2.5 g of sodium chloride and 100 cc of 80% methanol, in the following shaking for 30 min and filtering with GFF. Remove 10 cc of the filtered solution along with 60 cc of deionized water and passed through GFF. Next pass 40 cc of the diluted extract through the immunoaffinity column and collect and bring to a volume of 3 cc. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e illustrates the general principles of the preparation process.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.1. Statistical assessment of analytical data\\u003c/h2\\u003e\\n \\u003cp\\u003eAfter evaluating of the optimal conditions, the figures of merit such as calibration curve, line equation, detection limit, correlation coefficient, repeatability and reproducibility, precision and accuracy, and finally the measurement of the desired target compounds in real samples were investigated and evaluated.\\u003c/p\\u003e\\n \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section3\\\"\\u003e\\n \\u003ch2\\u003e3.1.1. Calibration curve and linear range\\u003c/h2\\u003e\\n \\u003cp\\u003eThe calibration curves and the equation of the line related to the target compounds were obtained by plotting the ratio of the peak area of each compound against the species concentration. After extracting the target compounds by extraction method, the calibration curve for the target concentration from 0.01-30, 0.03-40 and 0.2\\u0026ndash;350 ng/g were linear for AF, OTA and ZEN respectively. Table.1 shows the calibration curve data related to each of the target compounds. The experiments were repeated 5 times in each concentration of the calibration curve. The target correlation coefficient was more than 0.9901.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section3\\\"\\u003e\\n \\u003ch2\\u003e3.1.2. Calculation of the limit of detection and limit of quantification\\u003c/h2\\u003e\\n \\u003cp\\u003eTo estimate the detection limit of the method, the lowest concentration of Mycotoxins compounds was selected from the calibration curve. This value was equal to 0.1 \\u0026micro;g/L for all four desired compounds. The standard deviation corresponding to 10 measurements at this concentration was calculated for all four compounds and by putting its value in Eq.\\u0026nbsp;(\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), the detection limit of the method for mycotoxins compounds was obtained. To calculate the quantification limit of the method, the standard deviation corresponding to 10 measurements of four analytes is placed in Eq.\\u0026nbsp;(\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Table.1 shows the figures of merit obtained from the calibration curves.\\u003c/p\\u003e\\n \\u003cdiv id=\\\"Equ1\\\" class=\\\"Equation\\\"\\u003e\\n \\u003cdiv class=\\\"EquationNumber\\\"\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\" width=\\\"204\\\" height=\\\"113\\\"\\u003e\\u003c/div\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003eWhere m is the slope of the calibration curve and \\u003cem\\u003eS\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003eb\\u003c/em\\u003e\\u003c/sub\\u003e, standard deviation of blank, which can be obtained by several successive injections of a low concentration from the calibration curve. \\u003cem\\u003eS\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003eb\\u003c/em\\u003e\\u003c/sub\\u003e by averaging the repetition of the obtained data and suitable replacement in the equation, the detection limit is calculated. Using the above equation, the experimental LODs for aflatoxin obtained in range 0.0031\\u0026ndash;0.0044, 0.0148 and 0.0601 ng/g were for AF, OTA and ZEN respectively. The LOQs (quantity limit) is generally referred to a place that is equal to 10 times the standard deviation of repeated measurements on the blank. LOQs for aflatoxin obtained in range 0.0083\\u0026ndash;0.013, 0.042 and 0.213 ng/g were for AF, OTA and ZEN respectively.\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003ch3\\u003e3. 1.3. Accuracy and precision\\u003c/h3\\u003e\\n\\u003cp\\u003eThe intra-day and inter-day precisions of the assay were evaluated by analyzing quality control samples at three concentration levels (0.3, 5, 15 \\u0026micro;g/kg\\u003csup\\u003e,\\u003c/sup\\u003e 10, 150, 300 and 3, 15, 30 for AF, OTA and ZEN respectively) on the same day and the five consecutive days. The results of accuracy and precision are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. The inter-day %RSD for all compounds (AFB\\u003csub\\u003e1\\u003c/sub\\u003e, AFB\\u003csub\\u003e2\\u003c/sub\\u003e, AFG\\u003csub\\u003e1\\u003c/sub\\u003e, and AFG2) was 2.38\\u0026ndash;3.96%. Also, the intra-day RSD were less than 2.22\\u0026ndash;4.53%. Also, recovery values for aflatoxins in the mentioned concentrations were obtained in the range of 96.82\\u0026ndash;107% (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\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\\u003eFigures of merit of the method for determination mycotoxins (n\\u0026thinsp;=\\u0026thinsp;5)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\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=\\\"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 \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eAnalyte\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eRange (ng g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eSlope\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eIn spiked bean (ng g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLOD\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLOQ\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAFB1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.01-30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"+\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5.98\\u0026thinsp;+\\u0026thinsp;007\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.9957\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0031\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.0113\\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=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.01-30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"+\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.87\\u0026thinsp;+\\u0026thinsp;007\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.9901\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0044\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.0123\\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=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.01-30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"+\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5. 68\\u0026thinsp;+\\u0026thinsp;007\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.9943\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0038\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.0083\\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=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.01-30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"+\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6.76\\u0026thinsp;+\\u0026thinsp;006\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.9936\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0035\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.013\\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=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.03-40\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"+\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6.48\\u0026thinsp;+\\u0026thinsp;005\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.9936\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0148\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.042\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eZEA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.2\\u0026ndash;350\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"+\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4. 44\\u0026thinsp;+\\u0026thinsp;004\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.9958\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0601\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.213\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption 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align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eMycotoxins\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eSpiked\\u003c/p\\u003e \\u003cp\\u003econcentration\\u003c/p\\u003e 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namest=\\\"c9\\\"\\u003e \\u003cp\\u003eBetween-day (n\\u0026thinsp;=\\u0026thinsp;5)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAccuracy\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eRSD\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eAccuracy\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eRSD\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eRecovery\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eRSD\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eRecovery\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eRSD\\u003c/p\\u003e \\u003cp\\u003e(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAF B1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e98.66\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3. 12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.91\\u003c/p\\u003e \\u003c/td\\u003e 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align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2. 48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e97.36\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.43\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e101.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.52\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e87.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3. 87\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAF B2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e99.93\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3. 32\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e98.99\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e98.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e98.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.06\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e97.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4. 31\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e96.34\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e 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\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e98.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.36\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.32\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAF G1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e102.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2. 48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e102.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.26\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e96.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e99.96\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3. 36\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e101.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e98.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e2.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.87\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.98\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e98.44\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.06\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.31\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.739\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAF G2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e96.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e101.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e3.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.41\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e101.06\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3. 63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.74\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.54\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e3.42\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e99.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.96\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e99.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e96.64\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.94\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.74\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eZEA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e300\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e98.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.95\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e100.44\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.34\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.52\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e97.87\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e102.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.52\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e101.03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.06\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e96.04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.14\\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=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e96.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.69\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e99.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e96.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e2.32\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e96.89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.41\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e96.98\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3.23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e99.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.54\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e3.08\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e98.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e97.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e97.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e97.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e2.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eAccuracy analyzed by HPLC-FLD of the method was determined by repeated analysis of blank cereal samples with target analytes at three concentration levels (0.3, 5, 15 \\u0026micro;g/ kg,10, 150, 300 and 3, 15, 30 for AF, OTA and ZEN respectively). The blank frijoles samples extract (n\\u0026thinsp;=\\u0026thinsp;3) was extracted and analyzed as described under the analytical procedure. Using the calibration curves and the equation specified below, the recovery value was calculated with the measured concentrations:\\u003c/p\\u003e \\u003cp\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\" height=\\\"56\\\" width=\\\"232\\\"\\u003e\\u003c/p\\u003e\\u003cp\\u003eWhere C\\u003csub\\u003efound\\u003c/sub\\u003e, C\\u003csub\\u003ereal\\u003c/sub\\u003e, and C\\u003csub\\u003eadded\\u003c/sub\\u003e, respectively, are the mycotoxins concentrations in the real samples after being added to a known quantity of standard, the mycotoxins concentration in the sample of mycotoxins, and the known amount of standard that was spiked into the sample of frijol. The relative standard deviation (RSD) from five repetitions used as an indicator of precision. The mixed standard solutions were added to the frijol samples to make them 0.3, 5, 15 \\u0026micro;g/kg10, 150, 300 and 3, 15, 30 for AF, OTA and ZEN respectively, and the recovery experiments were repeated thirty times. The samples' average mycotoxins recovery varied from 80.0\\u0026ndash;104.0%. According to Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, the samples' respective relative standard deviations (RSD) varied from 1.6\\u0026ndash;8.3%. To rule out interference caused by contamination from the equipment, solvents, instrument, or chemicals utilized, the reagent and instrument blank were regularly run.\\u003c/p\\u003e \\u003cp\\u003eTable 3.\\u0026nbsp;Recovery and relative standard deviation (RSD) of mycotoxins in different frijol samples (n=3).\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"588\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.095400340715502%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10.051107325383304%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"20.61328790459966%\\\" colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 20.5015%;\\\"\\u003e\\n \\u003cp\\u003eBean\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"20.61328790459966%\\\" colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 20.5015%;\\\"\\u003e\\n \\u003cp\\u003eLentil\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"31.686541737649062%\\\" colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 31.3453%;\\\"\\u003e\\n \\u003cp\\u003eChickpea\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"16.949152542372882%\\\" valign=\\\"top\\\" style=\\\"width: 16.9434%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003eSpiked level\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003eRecovery\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003eRSD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003eRecovery\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003eRSD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003eRecovery\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003eRSD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eAnalytes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e(ng/g)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e(%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e(%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e(%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e(%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e(%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e(%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eAFB1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e96.99\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e99.53\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e4.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e4.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e99.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eAFB2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e103.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e2.39\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e96.46\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e100.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e102.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e2.36\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e88.95\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e4.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eAFG1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e99.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e97.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.36\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.84\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.53\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e97.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e96.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eAFG\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e96.63\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e96.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e103.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.53\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.83\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eOTA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e150\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e103.32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e93.78\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e4.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.79\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.86\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003eZEA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e99.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e3.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"12.033898305084746%\\\" valign=\\\"top\\\" style=\\\"width: 12.0298%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"10%\\\" valign=\\\"top\\\" style=\\\"width: 9.9966%;\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e97.45\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"7.796610169491525%\\\" valign=\\\"top\\\" style=\\\"width: 7.794%;\\\"\\u003e\\n \\u003cp\\u003e3.83\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"12.88135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 12.877%;\\\"\\u003e\\n \\u003cp\\u003e98.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"18.8135593220339%\\\" valign=\\\"top\\\" style=\\\"width: 18.6377%;\\\"\\u003e\\n \\u003cp\\u003e4.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\u003c/br\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4.1. Measurement of uncertainty\\u003c/h2\\u003e \\u003cp\\u003eThe four major contributions to uncertainty are recorded in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e based on the validation data. It shows the uncertainty values calculated for the simultaneous measurement of mycotoxins. The estimated uncertainties of 0.118, 0.0794, 0.100, 0.0009, 0.024 and 1.230 for AF, OTA and ZEA respectively.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDescription of the components taken into account for estimating uncertainty.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\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 \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"7\\\" nameend=\\\"c8\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eUncertainty values\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eUncertainty components\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAFB1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eAFB2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eAFG1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eAFG2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eOTA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eZEA\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eu\\u003csup\\u003e2\\u003c/sup\\u003e\\u003csub\\u003eM\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.00109284\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0006733\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000188\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.00022\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.000482\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.000175\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026pound;u\\u003csup\\u003e2\\u003c/sup\\u003e\\u003csub\\u003evi\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.00011\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.000009\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.0001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.000482\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.000492\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.000145\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eu\\u003csup\\u003e2\\u003c/sup\\u003e\\u003csub\\u003er\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0005433\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9.2592211\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.00107\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.00022\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.0001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.0016\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eu\\u003csup\\u003e2\\u003c/sup\\u003e\\u003csub\\u003eR\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.00180906\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0007031\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.001192\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.00013\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.022533\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e1.05431\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eu\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.00353223\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0014780\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.00255\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.00046\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.00115\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.000293\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e2u\\u0026thinsp;=\\u0026thinsp;U(ng/g)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.11889284\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.0793492\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.100788\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.000991\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.024263\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e1.230141\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1. Application to real samples\\u003c/h2\\u003e \\u003cp\\u003eAfter applying the method on frijol samples, interpretation and analysis of the simultaneous amount of AF, OTA and ZEA was done. The interpretation and analysis of the results are shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e. As can be inferred, frijol products are at a very favorable level regarding contamination with mycotoxins. Of the 150 bean samples tested, no mycotoxin was detected, but in 150 lentil samples collected, aflatoxin was detected in 5 samples. Out of 5 samples, two samples were contaminated with AFB2 and AFG1 toxins, and one sample was contaminated with OTA, another sample was contaminated with ZEA and another sample was contaminated with AFG1. All the detected mycotoxins were below the EU limit (European Commission 2006), so it can be said that the lentil samples are at a very good level in terms of mycotoxins, and no mycotoxins were detected in the 150 chickpea samples analyzed. The results obtained in this research, two general conclusions can be drawn about the level of mycotoxin contamination of frijoles: 1- The Health Organization and the Food and Drug Organization as well as the Agricultural Organization of Iran have very good control over the frijol products and 2- The level of contamination of frijoles with mycotoxins. Mycotoxins are much lower than in crops such as cereals. In Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, the chromatograms demonstrated selectivity of the optimized method established by blank sample and a sample spiked with mycotoxins. Also, the peaks of mycotoxins were well separated from each other, there were no interfering peaks coincide at the retention times of each mycotoxin. Therefore, satisfied selectivity and specificity of the procedure were obtained.\\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\\u003eMycotoxins contamination in frijol samples in the Iranian market.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\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 \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eType of cereal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNumber of samples analyses\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c6\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eAF\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eOTA\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eZEA\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAFB1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eAFB2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eAFG1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eAFG2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBean\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLentil\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1\\u0026thinsp;\\u0026lt;\\u0026thinsp;MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u0026thinsp;\\u0026lt;\\u0026thinsp;MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2\\u0026thinsp;\\u0026lt;\\u0026thinsp;MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e1\\u0026thinsp;\\u0026lt;\\u0026thinsp;MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e1\\u0026thinsp;\\u0026lt;\\u0026thinsp;MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eChickpea\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.2. Investigation and interpretation of aflatoxins in frijoles in comparison cereal\\u003c/h2\\u003e \\u003cp\\u003eAflatoxin contamination in frijoles can be different based on factors such as pre-harvest and post-harvest conditions, storage methods, and transportation methods. Comparative studies that analyze the occurrence of aflatoxin in frijoles from Iran and other countries can provide insight into the relative risks associated with the consumption of these beans. Publicly available data from government authorities, scientific literature, or international organizations can help identify this rate of occurrence. Countries use various mitigation strategies to minimize aflatoxin contamination in food products. These strategies can include good agricultural practices, proper storage and handling, and post-harvest treatments. By comparing the strategies implemented in Iran with other countries, it is possible to evaluate the effectiveness of different approaches in reducing aflatoxin contamination. More research and analysis are needed to provide an in-depth and comprehensive comparison of aflatoxin levels in frijoles between Iran and other countries. Conducting country-specific studies and collecting representative data helps to make a more accurate and comprehensive comparison. But so far, no comprehensive study has been conducted on the presence of aflatoxins in the frijole\\u0026rsquo;s products class in any country in the world. In this study, for the first time, we specifically evaluated the presence of aflatoxins in the frijole\\u0026rsquo;s products. In this study, the presence and amount of aflatoxins in frijoles were compared with the presence and amount of aflatoxins in cereals. The study on cereals was conducted by our research group on 450 samples including 150 rice samples, 150 wheat samples and 150 corn samples (Kardani, Rashedinia et al.). Preparation methods were the same for legumes and cereal. The results obtained from the evaluation of 450 frijoles samples are shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e. As the results show, no mycotoxin was detected in the tested bean sample, but aflatoxin was detected in the collected lentil sample. All the detected mycotoxins were below the limit of the European Union (European Commission 2006), Therefore, as the results show, the lentil samples are at a very good level, and no mycotoxins were observed in the analyzed Chickpea samples. The detected values in the examined cereal samples are shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e. Compared to frijoles, more aflatoxins were detected in cereals. Among the 150 rice samples analyzed, 15 samples were infected with AFG2 AFB1 and 5 samples were infected with AFG1 below the MRL (\\u0026le;\\u0026thinsp;15 \\u0026micro;g/kg). While the incidence of AFG2 level in 2 samples is higher than the EU limit (European Commission 2006). Also, OTA and ZEN were not detected in any sample. AFB1 and AFB2 were analyzed in four maize samples, and AFB2 concentration exceeded the EU ML in two samples. ZEN values were observed in 10 samples, the determined concentrations were lower than EU ML. Furthermore, OTA was not detected in any corn samples. In a total of 150 wheat samples, 13 samples were infected with AFB1, AFB2, and the detected values were lower than the MRL (15 \\u0026micro;g/kg), and only in one sample, OTA was detected, and ZEN was not found in any sample. Two conclusions can be inferred from the obtained results: 1- In Iran, the control of leguminous products is much more appropriate than that of grains. 2- The degree of mycotoxin contamination of beans. Mycotoxins are much lower than in crops such as grains. The probability of the second inference is much higher than the first inference, because due to the nature of legumes and their storage in Iran, they are less exposed to aflatoxin contamination.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eMycotoxins contamination in cereal samples in the Iranian market.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\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 \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eType of cereal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNumber of samples analyses\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c6\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eAF\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eOTA\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eZEN\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAFB1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eAFB2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eAFG1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eAFG2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRice\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15\\u0026lt; MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5\\u0026lt; MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e15(2 sample\\u0026thinsp;\\u0026gt;\\u0026thinsp;MLRs)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCorn\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4(2sample\\u0026thinsp;\\u0026gt;\\u0026thinsp;MLRs)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e10\\u0026lt; MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWheat\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e13\\u0026lt; MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e13\\u0026lt; MLRs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eND\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"5. Conclusions\",\"content\":\"\\u003cp\\u003eThe analysis of aflatoxins, mycotoxins and zearalenone in frijol samples is of great importance in human health. This study proved the simultaneous determination and analysis of AFs (B1, B2, G1 and G2), OTA, and ZEA in frijoles. This method is an excellent candidate for future standardization due to its reliability and efficiency for the screening and analysis of mycotoxins. The investigated parameters for this study include linear range, recovery detection limit and standard deviation. The LOD and LOQ obtained for the samples were in the range of 0.01\\u0026ndash;0.03 ng/g, for AFB1 and AFG1, 0.003 and 0.01 ng/g for AFB2 and AFG2, 0.02 and 0.1ng/g for OTA and 0.06 ng/g for ZEA respectively. Our method offers accurate, sensitive and simple HPLC-FLD methods that reduce the total analysis time as well as the cost of the method for the determination of mycotoxins. In this study, AFTs, OTA and ZEA, were investigated for combating highly toxic mycotoxins in frijoles. For this purpose, a total of 450 samples of different frijoles were collected from agricultural markets and local supermarkets during the years 2019\\u0026ndash;2022. The results clearly showed that frijoles consumed in Iran are in a very good condition in terms of mycotoxins, and the number of mycotoxins is completely controlled and below the MRL. Out of 450 cereal samples analyzed, only 5 samples contained mycotoxins, the detected amounts of which were below the MRL. These results show that leguminous products in Iran are well controlled by the Health Organization and the Food and Drug Organization.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll financial sources were acknowledged\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contribution:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eConceptualization: FK, AZ; Methodology: FK, AZ, MR; Formal analysis and investigation: FK, AZ, MR, SSH; Writing original draft preparation: FK, AZ, SSH; Writing, review and editing: FK, SSH, AZ, MH, SMA, MM.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran, and the Food and Food and Drug Administration, Shiraz University of medical sciences of Shiraz, Iran, funded for this study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting Interests Declaration:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAccording to the authors, they do not have any competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHuman and Animal Rights:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis article does not contain any studies with human or animal subjects.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAcu\\u0026ntilde;a‐Guti\\u0026eacute;rrez, C., V. M. Jim\\u0026eacute;nez and J. M\\u0026uuml;ller (2022). \\u0026quot;Occurrence of mycotoxins in pulses.\\u0026quot; Comprehensive Reviews in Food Science and Food Safety \\u003cstrong\\u003e21\\u003c/strong\\u003e(5): 4002-4017.\\u003c/li\\u003e\\n\\u003cli\\u003eAgriopoulou, S., E. Stamatelopoulou and T. Varzakas (2020). \\u0026quot;Advances in analysis and detection of major mycotoxins in foods.\\u0026quot; Foods \\u003cstrong\\u003e9\\u003c/strong\\u003e(4): 518.\\u003c/li\\u003e\\n\\u003cli\\u003eAhmadi, M., G. Jahed Khaniki, N. Shariatifar and E. Molaee-Aghaee (2022). \\u0026quot;Investigation of aflatoxins level in some packaged and bulk legumes collected from Tehran market of Iran.\\u0026quot; International Journal of Environmental Analytical Chemistry \\u003cstrong\\u003e102\\u003c/strong\\u003e(16): 4804-4813.\\u003c/li\\u003e\\n\\u003cli\\u003eFakoor Janati, S. S., H. R. Beheshti, N. Khoshbakht Fahim and J. Feizy (2011). \\u0026quot;Aflatoxins and ochratoxinin A in bean from Iran.\\u0026quot; Bulletin of environmental contamination and toxicology \\u003cstrong\\u003e87\\u003c/strong\\u003e: 194-197.\\u003c/li\\u003e\\n\\u003cli\\u003eKardani, F., M. Rashedinia, M. Hashemi, S. Sh and S. M. A. Noori \\u0026quot;Simultaneous Evaluation and Monitoring Ochratoxin a, Aflatoxins, and Zearalenone Contamination Level in Iran\\u0026apos;s Cereals During Years 2019-2022 Using HPLC-FLD.\\u0026quot;\\u003c/li\\u003e\\n\\u003cli\\u003eKunz, B. M., F. Wanko, S. Kemmlein, A. Bahlmann, S. Rohn and R. Maul (2020). \\u0026quot;Development of a rapid multi-mycotoxin LC-MS/MS stable isotope dilution analysis for grain legumes and its application on 66 market samples.\\u0026quot; Food Control \\u003cstrong\\u003e109\\u003c/strong\\u003e: 106949.\\u003c/li\\u003e\\n\\u003cli\\u003eLogotheti, M., A. Kotsovili-Tseleni, G. Arsenis and N. Legakis (2009). \\u0026quot;Multiplex PCR for the discrimination of A. fumigatus, A. flavus, A. niger and A. terreus.\\u0026quot; Journal of microbiological methods \\u003cstrong\\u003e76\\u003c/strong\\u003e(2): 209-211.\\u003c/li\\u003e\\n\\u003cli\\u003eMazaheri, M. (2023). \\u0026quot;Investigating the possibility of the occurrence of mycotoxins in rice and rice flour imported to Iran.\\u0026quot; Journal of Food Composition and Analysis: 105464.\\u003c/li\\u003e\\n\\u003cli\\u003eMirabolfathy, M., R. K. Osboo and V. Rahjoo (2019). \\u0026quot;Important mycotoxins, Iran status.\\u0026quot; Annu. Rev. Res \\u003cstrong\\u003e5\\u003c/strong\\u003e(1): 1-10.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"High-performance liquid chromatography (HPLC), aflatoxins, ochratoxin A, zearalenone, frijol\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-3275679/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-3275679/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eConsidering the importance of frijoles in Iran as a favorite and widely consumed food, for the first time, research was conducted on the contamination of frijoles with mycotoxins. Mycotoxins were measured with a recovery of 95\\u0026ndash;102% by high-performance liquid chromatography (HPLC) and extracted and purified using a conventional commercial immunoaffinity column. In this research, 450 samples of frijoles, including 150 beans, 150 lentils, and 150 peas were examined. All the beans and peas were free of mycotoxins, and only 5 lentil samples contained mycotoxins. Two samples were contaminated with Aflatoxin B2 (AFB2) and (Aflatoxin G1) AFG1 toxins, one sample was contaminated with Ochratoxin A (OTA), one sample was contaminated with (Zearalenone) ZEA and another sample was contaminated with AFG1) was identified, the value was detected 14.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.16 ng/g and \\u0026lt;\\u0026thinsp;LOQ, which was lower than the detectable level in Iran and the European Union. The results in this research show the improvement of the sanitary conditions of cultivation, harvesting, and storage after the harvesting of frijoles in Iran.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Simultaneous evaluation ochratoxin A, aflatoxins, and zearalenone contamination level in Iran’s frijoles during years 2019-2022 using HPLC-FLD\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2023-08-28 18:27:13\",\"doi\":\"10.21203/rs.3.rs-3275679/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"5c98e767-2716-4586-9786-fb31561ca40f\",\"owner\":[],\"postedDate\":\"August 28th, 2023\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2023-09-19T15:22:10+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2023-08-28 18:27:13\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-3275679\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-3275679\",\"identity\":\"rs-3275679\",\"version\":[\"v1\"]},\"buildId\":\"_2-kVJe1T_tPrBINL-cwx\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}