HPLC-MS/MS Monitoring and Health Risk Assessment of Carbosulfan and its Metabolites in Date Palm Fruit (Phoenix dactylifera)

HPLC-MS/MS Monitoring and Health Risk Assessment of Carbosulfan and its Metabolites in Date Palm Fruit (Phoenix dactylifera) | 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 Article HPLC-MS/MS Monitoring and Health Risk Assessment of Carbosulfan and its Metabolites in Date Palm Fruit (Phoenix dactylifera) Rana Morsi, Kilani Ghoudi, Basant Elabyad, Zaina Kadoura, Hind Zeidane, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5022517/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract This study investigated residual levels of carbosulfan and its metabolites in date palm fruit in the UAE using HPLC-MS/MS and QuEChERS method. The method demonstrated excellent linearity (R 2 > 0.998), low LOD (0.001–0.04 𝜇g/kg) and LOQ (0.003-0.1 𝜇g/kg), and high recoveries (92%-103%) with low RSD values (1–9%). The matrix effect was negligible (-16.43–17.09%), and uncertainty measurements did not exceed the 50% limit. Carbosulfan was present in all samples, exceeding its MRL in 46% of the samples. Carbofuran and 3-hydroxycarbofuran exceeded their MRL in 4.87% and 40% of the samples, respectively, while 3-ketocarbofuran levels were below the MRL. Dibutylamine was found in 82% of the samples, with an average concentration of 9.01 µg/kg. The health risk assessment for children and adults showed that all HQ values were below the safety limit of 1.0, indicating that date consumption poses no adverse health risks for either adults or children. Physical sciences/Chemistry/Analytical chemistry Physical sciences/Chemistry/Chemical safety Physical sciences/Chemistry/Environmental chemistry Carbosulfan metabolites date palm QuEChERS Human health HPLC-MS/MS Figures Figure 1 Figure 2 Figure 3 1. Introduction The date palm ( Phoenix dactylifera ) fruit is a nutritional treasure that offers a rich blend of essential nutrients crucial for human health. It is rich in dietary fiber, which is beneficial for digestive health, and contains moderate amounts of vitamins A, C, and B-complex 1 – 3 . It is also abundant in essential minerals such as potassium, selenium, magnesium, iron, and others, which are vital for bodily functions 1 , 2 , 4 , 5 . Furthermore, date fruit is an excellent energy source due to its high sugar content, primarily consisting of fructose, glucose, and sucrose 6 . Studies have also highlighted dates’ antioxidant 7 , antimutagenic 8 , anti-inflammatory 9 , gastroprotective 10 , hepatoprotective 11 , and anticancer 12 properties. Given their nutritional and medicinal value, date fruit is a critical ingredient in producing various products, including food items, cosmetics, and medicinal products 13 – 15 . Additionally, date palms are among the earliest cultivated plants, with a history of cultivation that spans over 6000 years 2 . It plays a pivotal role as a fruit crop worldwide in arid and semi-arid regions 16 . More than 2,000 date varieties are cultivated worldwide, predominantly in the Middle East and North Africa 17 . According to the Food and Agriculture Organization of the United Nations (FAO), the United Arab Emirates (UAE) stands as one of the top 10 leading countries for date fruit production, with an annual output of approximately 397,328.94 tons 18 , and holds the second position globally for date exports, exporting 258,655.19 tons annually 19 . This high production rate in the UAE coincides with a significant consumption level, where, on average, a person consumes about 114.3 grams of dates daily, equivalent to 10 date fruits 20 . Like other types of fruits, dates can be contaminated with pesticide residues, posing considerable health risks 21 – 23 . The consumption of dates or other food contaminated with pesticides underscores the need for rigorous monitoring programs and regulatory measures to ensure food safety. Consequently, national and international organizations, such as the Codex Alimentarius (CA) and the European Union (EU), have established Maximum Residue Levels (MRLs) to protect consumer health and ensure food safety 23 – 25 . The high consumption of dates in the UAE highlights the importance of monitoring pesticide residue levels in this fruit to protect public health and uphold food safety standards. A recent study by Morsi et al. found carbamate residues in date fruits in the UAE, with carbosulfan detected in all samples analyzed. Notably, 38.2% of these samples had carbosulfan levels exceeding its MRL of 10 µg/kg 26 . Carbosulfan, an insecticide in the carbamate class, is moderately toxic but highly effective against a broad spectrum of insects. It is known to degrade quickly in the environment, making it widely used in crop protection 27 , 28 . However, consumption of food contaminated with carbosulfan can lead to human poisoning, fatigue, headache, blurred vision, a drop in blood pressure, and loss of consciousness 27 . Therefore, monitoring carbosulfan residue levels in agricultural products is crucial to ensure food safety. Moreover, carbosulfan can degrade easily into carbofuran through hydrolysis and further metabolize to 3-hydroxycarbofuran and 3-ketocarbofuran through hydroxylation and oxidation, respectively 29 , 30 . These metabolites are more toxic than carbosulfan, increasing the risk of human exposure 28 , 31 . Dibutylamine, 7-phenolcarbofuran, 3-hydroxy-7-phenolcarbofuran, and 3-keto-7-phenolcarbofuran are other detected metabolites of carbosulfan 32 . The metabolic pathway of carbosulfan is presented in Supplementary Fig. S1 online. Previous studies have investigated levels of carbosulfan and its metabolites in various crops, including cucumbers 28 , rice 33 , and oranges 34 , among others. To our knowledge, no research has been published on determining levels of carbosulfan metabolites in date palm fruit on a global scale. Given the UAE’s status as a premier exporter of date fruit 19 , coupled with high local consumption rates 20 and preliminary evidence of carbosulfan presence in UAE-grown dates 26 , ensuring the safety and quality of these fruits becomes critically important. This context underscores the necessity of our study, which aims to fill a significant gap in existing research by detecting and quantifying the residual levels of carbosulfan and its four metabolites—carbofuran, dibutylamine, carbofuran-3-hydroxy, and carbofuran-3-keto—in dates cultivated in the UAE. For sample preparation, we utilized the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method, followed by High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) for analysis, ensuring precise and reliable quantification of pesticide residues. Additionally, a probabilistic health risk assessment study was conducted to estimate the health risks associated with carbosulfan and its metabolites for adults and children. 2. Materials and methods 2.1. Chemicals and reagents High purity standards of carbosulfan, carbofuran, 3-hydroxycarbofuran, 3-ketocarbofuran, and dibutylamine were purchased from Dr. Ehrenstorfer (Augsburg, Germany). Carbofuran d3 internal standard, sodium chloride (NaCl), ammonium formate, anhydrous magnesium sulfate (MgSO 4 ), and glacial acetic acid were obtained from Sigma-Aldrich (St. Louis, MO, USA). Acetonitrile and methanol (HPLC grade ≥ 99.9%) were provided by Honeywell (Seelze, Germany). Milli-Q Plus system was used to purify water (MilliporeSigma, USA). QuEChERS dispersive solid-phase extraction (d-SPE) kits were supplied by Agilent Technologies Inc. (Wilmington, DE, USA). Millex PTFE syringe filters were procured from Merck Millipore (Carrigtwohill, Ireland). 2.2. Preparation of standards and calibration curves Stock standard solutions (200 mg/kg) and working standard solutions were prepared in methanol and stored in the dark at -18 o C. Calibration curves were prepared using mixed standard solutions at various concentrations. Calibration curves were constructed both within the date matrix and in a pure solvent to assess the matrix effect. These curves covered a concentration range of 0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1.0, 5.0, 10, 50, and 100 𝜇g/kg, with a fixed concentration of 10 𝜇g/kg of carbofuran d3 used as an internal standard for all samples. The calibration curves were derived by plotting the relative responses of each analyte, determined by the ratio of the analyte’s peak area to that of the internal standard’s peak area, across the stated concentration range (0.001-100 𝜇g/kg). 2.3. Sample collection and preparation A total of 50 fresh samples of dates, including various types cultivated in the UAE, were randomly collected from different markets and farms. Permissions were obtained from all farm owners before any samples were collected. The collected samples were enclosed in sterile polypropylene bags for transport to the laboratory. In the laboratory, samples were refrigerated at 4 o C until analysis. The European SANTE/11312/2021 guidelines were followed for handling, collecting, storing, processing, and preparing date samples 35 . QuEChERS was selected as the extraction method due to its demonstrated efficiency for complex matrices like dates 21 , 22 , 36 , 37 . Alternative extraction methods such as liquid-liquid extraction (LLE) and solid-phase extraction (SPE) were considered but found less suitable. LLE presents challenges with emulsion formation and phase separation in date matrices, while SPE is more time-consuming, costly, and prone to cartridge clogging due to matrix interferences. QuEChERS offers efficient removal of matrix interferents through salting-out and dispersive clean-up steps. The QuEChERS method employed for sample preparation was adapted from the approach previously detailed by Morsi et al. 26 . In brief, 50 g of dates (without caps and pits) and 75 mL of cold purified water were transferred to a food processor, where they were blended at high speed until the mixture was homogenized entirely into a date paste. For sample extraction, 10 g of the homogenized date paste was placed into a 50 mL polypropylene centrifuge tube. Then, 100 𝜇L of carbofuran d3 (100 𝜇L/kg) was added to the paste. After this, 10 mL of acetonitrile (containing 0.1% acetic acid) was added to the sample, and the mixture was vortexed. The tube was then placed in a dark, cold place for 60 minutes. After this, 4 g of anhydrous MgSO 4 and 1 g of NaCl were added to the mixture, and they were mixed and then centrifuged at 4500 rpm for 10 minutes. For clean-up, the supernatant was transferred to a 15 mL QuEChERS d-SPE tube composed of 400 mg primary secondary amine (PSA), 400 mg graphitized carbon black (GCB), 400 mg octadecylsilane chemically bonded silica, endcapped (C18EC), and 1200 mg MgSO 4 , which was then vortexed and centrifuged at 4500 rpm for another 10 minutes. The resulting extract was transferred to a glass tube, dried, and dissolved again in 1 mL of mobile phase B (methanol and acetonitrile, 2:1) before filtering through a 0.45 𝜇m PTFE syringe filter for HPLC-MS/MS analysis. To ensure the reliability of the results, each sample was analyzed in triplicates. 2.4. HPLC-MS/MS HPLC instrument (Nexera-i LC-2040C 3D, Kyoto, Japan) coupled with an 8030 Shimadzu triple quadrupole mass spectrometer (Kyoto, Japan) was used for the analytical determination of carbosulfan and its metabolites. The separation was carried out on an ACQUITY UPLC BEH C18 column (2.1 mm x 150 mm x 1.7 𝜇m) supplied by Waters (Milford, USA), with a temperature maintained at 43 o C. The mobile phase consisted of water with 10 mM ammonium formate (pH = 3) (A) and a mixture of methanol and acetonitrile (2:1) (B), employing a gradient elution at a flow rate of 0.2 mL/min. The total run time was 15 minutes, and an injection volume of 15 𝜇L was used. The gradient elution was performed as follows: 0-3.5 min, 15% (B); 3.5-5 min, 15–96% (B); 5-11.5 min, 96% (B); 11.5–13 min, 96 − 15% (B); and 13-15min, 15% (B). The MS/MS detection was performed in the positive electrospray ionization (ESI) mode. The multiple reaction monitoring (MRM) method was used to quantify carbosulfan and its metabolites selectively and sensitively. The MS/MS parameters for carbosulfan, its metabolites, and the internal standard (carbofuran d3) are detailed in Supplementary Table S1 online. 2.5. Matrix effect The presence of interferences in natural matrices, such as dates, can significantly affect the performance of analytical methods. Therefore, investigating the matrix effect is crucial when dealing with such matrices. Matrix effects were evaluated by comparing the slopes of matrix-matched calibration curves with those of solvent-based calibration curves of target analytes using the following formula: Matrix effect% = \(\:\frac{slope\left(matrix-matched\:curve\right)-slope\:(solvent-based\:curve)}{slope\:(solvent-based\:curve)}\:x\:100\%\) The values of the matrix effect can be either positive due to ion enhancement or negative due to ion suppression. Depending on their values, matrix effects can be categorized into soft, medium, and strong 38 , 39 . It is considered soft if the obtained value ranges from − 20–20% 40 . In this case, the matrix effect is negligible, and calibration curves prepared in the solvent, which are simpler, easier, and less time-consuming, can be used according to the European SANTE/12830/2020 guidelines 41 . However, if obtained values exceed ± 20, indicating medium or strong matrix effects, solvent-based calibration curves cannot be used 40 . 2.6. Method validation The proposed analytical method was validated by assessing its sensitivity, accuracy, and precision per the European SANTE/11312/2021 guidelines 35 . Sensitivity was determined by evaluating linearity and limits of detection (LOD). Accuracy and precision were assessed based on limits of quantification (LOQ), recovery rates, repeatability, and intermediate precision. Linearity was evaluated using solvent-based calibration curves covering a concentration range of 0.001-100 𝜇g/kg and expressed as the coefficient of determination (R 2 ). LOD and LOQ were calculated based on the standard deviation of multiple blank measurements. We conducted 20 measurements of blank samples to determine the mean blank signal \(\:{(\stackrel{-}{S}}_{bl})\) and its standard deviation ( \(\:{\sigma\:}_{bl})\) . The minimum distinguishable analytical signal ( \(\:{S}_{m})\:\) was calculated using the formula: $$\:{S}_{m}={\stackrel{-}{S}}_{bl}+k{\sigma\:}_{bl}$$ where k is 3 for LOD and 10 for LOQ, corresponding to a signal-to-noise ratio (S/N) greater than 3 and 10, respectively. \(\:{S}_{m}\) was then converted to the corresponding minimum concentration ( \(\:{c}_{m}\) ) using the formula: $$\:{c}_{m}=\frac{{S}_{m}-\:{\stackrel{-}{S}}_{bl}}{m}$$ where \(\:{c}_{m}\) represents the limits of detection or quantitation, and m represents the slope of the calibration curves. As \(\:{S}_{m}-{\stackrel{-}{S}}_{bl}=k{\sigma\:}_{bl}\) , we can calculate \(\:{c}_{m}\) as follows: $$\:{c}_{m}=k\frac{\:{\stackrel{-}{S}}_{bl}}{m}$$ This indicates that \(\:{c}_{m}\) represents the LOD when k = 3 and the LOQ when k = 10. Our approach for determining LOD and LOQ follows the methodology outlined by Skoog et al. (32, p.20) 42 . These calculations ensure that the LOD represents the lowest concentration of an analyte that can be reliably detected. In contrast, the LOQ represents the lowest concentration that can be quantitatively measured with sufficient precision. Recoveries, repeatability, and intermediate precision were determined by spiking blank date samples with a mixture of standards at two concentration levels of 0.5 and 10 𝜇g/kg in three replicates. The relative standard deviation (RSD) was used to evaluate the repeatability and intermediate precision. For repeatability, six replicates were analyzed on the same day, whereas 12 replicates were analyzed on two consecutive days (6 analyses/day) for intermediate precision. Following the European SANTE/11312/2021 guidelines, recoveries should range between 60% and 140%, while RSD values should not exceed 20% 35 . 2.7. Measurement uncertainty Method validation and measurement uncertainty (MU) are essential to determine whether an analytical method meets legal requirements. MU is a parameter that describes the dispersion of every measurement 43 , 44 . To comply with the European Commission SANTE/11312/2021 guidelines, MU values should not exceed 50% 35 . MU, referred to as \(\:\stackrel{\prime }{U}\) , was estimated using the following equation: $$\:\stackrel{´}{U}=k\:\stackrel{´}{u}$$ where \(\:k\) is a coverage factor of 2 and \(\:\stackrel{´}{u}\) is the relative standard uncertainty. The standard uncertainty was estimated based on bias and within-laboratory variability. The bias is based on recovery data, while within-laboratory variability is based on precision data generated in the method validation experiments. The \(\:\stackrel{´}{u}\) was measured for each compound using the following: $$\:\stackrel{´}{u}=\sqrt{{\stackrel{´}{u}\left(bias\right)}^{2}+{\stackrel{´}{u}\left(precision\right)}^{2}}$$ where \(\:\stackrel{´}{u}\left(bias\right)\) is the uncertainty component for the bias, and \(\:\stackrel{´}{u}\left(precision\right)\) is the uncertainty component for the precision. The bias is the difference between the measured and actual values, which is the difference between the spiked and measured concentrations. The \(\:\stackrel{´}{u}\left(bias\right)\) can be calculated using the following: $$\:\stackrel{´}{u}\left(bias\right)=\sqrt{{{mean}^{2}}_{bias}+SD.{{P}^{2}}_{bias}}$$ where \(\:{{mean}^{2}}_{bias}\) is the mean of the relative bias, and \(\:SD.{{P}^{2}}_{bias}\) is the population standard deviation of the relative bias. On the other hand, the value of \(\:\stackrel{´}{u}\left(precision\right)\) is estimated from the %RSD of the reproducibility data for each compound: $$\:\stackrel{´}{u}\left(precision\right)=\%RSD$$ 2.8. Exposure assessment The United States Environmental Protection Agency (US-EPA) recommends using Hazard Quotient (HQ) and Hazard Index (HI) to assess risk after various exposures. HQ measures risk from a single chemical, while HI quantifies risk from a mixture of chemicals. HQ is the ratio of exposure to an appropriate reference, such as the MRL, acceptable daily intake (ADI), or reference dose (RfD). HI is the sum of the HQs for all chemicals in a mixture. An HQ ≤ 1 indicates that adverse effects are unlikely, signifying negligible hazard. HI sums HQs for substances affecting the same target organ or system, with an HI < 1 indicating no likely adverse effects from lifetime exposure. Traditional risk assessment approaches are deterministic, often reporting risks using central tendency, high-end measures (e.g., 90th percentile), or maximum anticipated exposure. Following the 1997 release of EPA’s Policy for using probabilistic analysis in risk assessment 45 , Probabilistic Risk Assessment (PRA) became critical in risk assessment, incorporating variability and uncertainty in exposure estimation. PRA estimates the distribution of exposure or risk, determines uncertainty/variability, and identifies key contributors to variability. US-EPA emphasizes communicating PRA results by providing distributions of exposure or risk estimates rather than single point estimates 45 . The PRA analysis was carried out in this study using Monte-Carlo simulation with 100,000 replicates 46 . The HQs were computed for each simulation replicate, and the 95th percentile of the HQ distribution was used to assess exposure risk. The HQ was calculated for adults and children as follows: $$\:HQ=\frac{EED}{ADI}$$ where EED (mg/kg bw/d) is the estimated exposure, and ADI (mg/kg bw/d) is the acceptable daily intake. The estimated exposure can be calculated as follows: $$\:EED=\frac{CRL*\:FI}{BW}$$ where CRL (mg/kg) is the calculated residue level, FI (kg/d) is the food intake, and BW (kg) is the body weight. The FI or daily consumption of dates for adults is assumed to be normally distributed with a mean of 114.3 g/day as found by Ismail et al. (2006), with the standard deviation approximated as 30 g/day to reflect the range of measurements reported 20 . The FI for children was also assumed to be normally distributed with a mean of 35 g/day, as reported by Morsi et al. 26 , using the same coefficient of variation as the adult population, resulting in a standard deviation of 9.2 g/day. The body weight for an adult was taken to be 70 kg, while that for a child was taken to be 15 kg. The RfDs for carbosulfan and carbofuran are 0.01 mg/kg-day and 0.005 mg/kg-day, respectively ( https://iris.epa.gov/AtoZ/?list_type=alpha ). RfDs are not available for the other metabolites. 3. Results and discussion 3.1. Matrix effect The matrix effect is one of the main challenges encountered when analyzing complex matrices using LC-MS due to the presence of co-eluting compounds. These compounds can affect the ionization of target analytes and interfere with their analysis, impacting the overall performance of the analytical method. The effects can manifest as either a decrease (ion suppression) or an increase (ion enhancement) in the analyte’s signal 38 – 40 . Therefore, it is imperative to mitigate matrix-induced effects. To overcome matrix effects, various approaches have been employed, including proper sample extraction and clean-up steps, the use of matrix-matched or standard addition calibration curves, and the utilization of deuterated or isotopically labeled internal standards, which can reduce the impact of the matrix on the obtained results 39 , 40 . Other strategies to reduce the matrix effect include minimizing the injection volume, diluting the sample, increasing the elution gradient time, and reducing the flow rate. The matrix effects were investigated for carbosulfan and its four metabolites (Table 1 ). The obtained matrix effect values ranged from − 16.43–17.09%; all are within the soft range ( ≤ ± 20), indicating negligible matrix effect. Carbofuran was the only compound with a negative value (-16.43%), indicating a decrease in its signal due to ion suppression. On the other hand, carbosulfan, dibutylamine, carbofuran-3-hydroxy, and carbofuran-3-keto had matrix effect values of 3.46%, 8.88%, 0.14%, and 17.09%, respectively. The positive values indicate an increase in their signal due to ion enhancement. According to the European SANTE/12830/2020 guidelines, solvent-based calibration curves can be used if values of the matrix effect don’t exceed ± 20 41 . Therefore, in our study, calibration curves prepared in methanol were used to quantify the residual levels of carbosulfan and its metabolites in dates. The negligible effect of the matrix suggests that the extraction and clean-up techniques are appropriate. The deuterated internal standard might also be attributed to the insignificant matrix effect. Table 1 Validation parameters of carbosulfan and its metabolites in dates. Analyte Linear dynamic range (𝜇g/kg) R 2 LOD (𝜇g/kg) LOQ (𝜇g/kg) Matrix Effect (%) Carbosulfan 0.001-100 0.9999 0.0011 0.0032 3.46 Dibutylamine 0.001-100 0.9991 0.0012 0.0036 8.88 Carbofuran 0.001-100 0.9993 0.0012 0.0035 -16.43 3-Hydroxycarbofuran 0.01–100 0.9983 0.0119 0.0359 0.14 3-Ketocarbofuran 0.05–100 0.9999 0.0487 0.1474 17.09 To contextualize our matrix effect results, a comparison was made with previous findings by Soler et al., who analyzed carbosulfan and its metabolites in tangerine matrix. Their study reported substantially higher matrix effects, with enhancement observed for all compounds: carbosulfan (1.3%), carbofuran (43.2%), 3-hydroxycarbofuran (34.5%), 3-ketocarbofuran (59.2%), and dibutylamine (89.7%) 34 . In contrast, our method demonstrated significantly better control of matrix effects in date matrix, with values ranging from − 16.43–17.09%. Notably, while carbofuran exhibited ion enhancement (43.2%) in tangerine matrix, it showed ion suppression (-16.43%) in date matrix, highlighting the matrix-dependent nature of these effects. The substantially lower matrix effects achieved in our method, despite dates being known for their complex matrix composition rich in sugars and other potentially interfering compounds, can be attributed to our optimized extraction and clean-up procedures, along with the use of deuterated internal standard. These results demonstrate the effectiveness of our method in managing matrix effects for the analysis of carbosulfan and its metabolites in dates. 3.2. Method validation The developed method was validated in terms of sensitivity, accuracy, and precision by determining the linearity, LOD, LOQ, recoveries, repeatability (intraday), and intermediate precision (interday), following the European SANTE/11312/2021 guidelines 35 . 3.2.1. Linearity, LOD, and LOQ The results of linearity, LOD, and LOQ are summarized in Table 1 . Excellent linearity was obtained for carbosulfan, dibutylamine, carbofuran, 3-ketocarbofuran, with R 2 > 0.999. Similarly, 3-hydroxycarbofuran demonstrated very good linearity with R 2 > 0.998. The LOD values were determined to be 0.001 𝜇g/kg for carbosulfan, dibutylamine, and carbofuran, while 3-hydroxycarbofuran and 3-ketocarbofuran exhibited LODs of 0.011 𝜇g/kg and 0.048 𝜇g/kg, respectively. The LOQ values were determined to be 0.003 µg/kg for carbosulfan, dibutylamine, and carbofuran; 0.03 µg/kg for 3-hydroxycarbofuran; and 0.14 µg/kg for 3-ketocarbofuran. These findings indicate the method's robust sensitivity, with LOD and LOQ values well below the MRL for all analyzed compounds, highlighting its efficacy in detecting carbosulfan and its metabolites in date samples. A critical comparison with existing literature highlights significant methodological advancements achieved by our study. The R², LOD, and LOQ values we obtained show substantial improvements compared to the results reported by Song et al.. They found R² values just over 0.990 and reported much higher LOD and LOQ values for carbosulfan, carbofuran, and 3-hydroxycarbofuran. Specifically, their LOD values were 2 µg/kg, 1 µg/kg, and 10 µg/kg, respectively, while LOQ values were 0.9 µg/kg, 0.3 µg/kg, and 4 µg/kg 28 . Our findings also surpassed those of Soler et al., who investigated the same five compounds. They reported R² values between 0.988 and 0.996. For LOQ values, they found 0.01 mg/kg for carbosulfan, carbofuran, 3-hydroxycarbofuran, and dibutylamine, with 3-ketocarbofuran at 0.03 mg/kg 34 . Moreover, Zhang et al. reported R 2 > 0.999 for carbosulfan, carbofuran, 3-hydroxycarbofuran, aligning with our reported R 2 for carbosulfan and carbofuran but higher than our reported R 2 for 3-hydroxycarbofuran (R 2 > 0.998). Their LOD values, depending on the matrix, ranged from 0.0027 to 0.0042 mg/kg for carbosuflan, 0.0040 to 0.0074 mg/kg for carbofuran, and 0.0094 to 0.012 mg/kg for 3-hydroxycarbofuran, which are higher than our reported LOD values 33 . This comprehensive comparison demonstrates our method's superior performance and reliability in quantifying trace levels of carbosulfan and its metabolites. 3.2.2. Accuracy and precision The method’s accuracy was evaluated by comparing the measured values to the true values of the samples, expressed as the recovery. Recoveries were determined by spiking blank date samples with a mixture of carbosulfan and its metabolites at concentrations of 0.5 𝜇g/kg and 10 𝜇g/kg in three replicates. The recovery values of this study are presented in Table 2 . All analytes exhibited recovery values ranging from 92–103%, which fall within the acceptable range suggested by the European SANTE/11312/2021 guidelines 35 . Precision was assessed through repeatability (intraday) and intermediate precision (interday) and expressed as the RSD. Repeatability was determined by analyzing six replicates on the same day, while intermediate precision was assessed over two consecutive days, analyzing twelve replicates after spiking blank date samples with a mixture of carbosulfan and its metabolites at concentrations of 0.5 𝜇g/kg and 10 𝜇g/kg. The RSD values obtained ranged from 1–9%, as shown in Table 2 . The recoveries and RSD values indicate that the developed method is accurate and precise. Table 2 Recovery, repeatability, and intermediate precision at 0.5 𝜇g/kg and 10 𝜇g/kg. Analyte 0.5 𝜇g/kg 10 𝜇g/kg Recovery % RSD% Intraday RSD% Interday (n = 2) Recovery % RSD% Intraday RSD% Interday (n = 2) Carbosulfan 101 4 7 102 6 4 Dibutylamine 95 7 5 96 4 3 Carbofuran 99 1 8 100 2 3 3-Hydroxycarbofuran 103 2 2 101 4 6 3-Ketocarbofuran 92 2 6 93 4 9 A comparison of recoveries and RSD values in this study with those reported in other studies reveals our method’s superior performance. Song et al. reported recovery values ranging from 87.2–91% with RSD of 3.2–8.1% for carbosulfan, carbofuran, and 3-hydroxycarbofuran 28 . Zhang et al. studied the same compounds and obtained recoveries of 72.71–105.07% with RSDs of 2–8.8% for the same compounds 33 . Although the values reported by Song et al. and Zhang et al. are within the acceptable range set by the European Commission, our study achieved better recoveries for the same compounds (92–103% with RSDs of 1–9%). The validation of the proposed method has proven its reliability and consistent performance across all evaluated parameters. The results demonstrate that the method is well-suited for accurately and sensitively detecting trace amounts of carbosulfan metabolites in dates. 3.3. Uncertainty measurements The MU for carbosulfan and its metabolites was calculated following the European Commission SANTE/11312/2021 guidelines 35 . This was done by multiplying a coverage factor ( \(\:k\) ) of 2 by the standard uncertainty ( \(\:\stackrel{´}{u}).\) A coverage factor of 2 represents a 95% confidence interval. The MU was calculated at two concentration levels: 0.5 µg/kg and 10 µg/kg (Fig. 1 ). The calculated MUs for all compounds at these two concentration levels were within the acceptable limit of 50%, indicating that the analytical method is reliable and meets regulatory standards. The validated method parameters demonstrate significant practical implications for routine analysis of dates. The controlled matrix effects (within ± 20%) enable the use of simpler and less time-consuming solvent-based calibration curves, while the excellent recovery rates (92–103%) and measurement uncertainties (within 50%) ensure reliable quantification across a wide concentration range. Together, these performance characteristics, meeting strict European SANTE guidelines, make the method suitable for routine monitoring in food safety laboratories. The practical reliability of the method is crucial for regulatory compliance testing, particularly in detecting MRL exceedances in commercial samples, ensuring food safety, and facilitating international trade of dates. This practical significance is clearly demonstrated in the following real sample analysis, where the method successfully detected multiple instances of regulatory non-compliance. 3.4. Real samples The content of carbosulfan and its metabolites (dibutylamine, carbofuran, 3-hydroxycarbofuran, and 3-ketocarbofuran) was analyzed in 50 samples of various date varieties using the developed method. The detected concentration of these compounds is detailed in Supplementary Table S2 online. Table 3 displays the distribution of carbosulfan and its metabolites in the date samples. Carbosulfan was detected in all samples, with concentrations ranging from 1.28 to 27.39 µg/kg, exceeding its MRL of 10 µg/kg in 23 samples. Dibutylamine and carbofuran were found in 41 samples, with concentrations ranging from 0.27 to 45.65 µg/kg and 0.063 to 4.28 µg/kg, respectively. Carbofuran exceeded its MRL of 3 µg/kg in 2 samples. Table 3 Distribution of carbosulfan and its metabolites in date samples. Analyte Contaminated Samples No. (%) > MRL No. (%) Average concentration (𝜇g/kg) Concentration range (min-max) (𝜇g/kg) MRL c (𝜇g/kg) Carbosulfan 50 (100%) 23 (46%) 9.75 1.28–27.39 10 Dibutylamine 41 (82%) NA a 9.01 0.27–45.65 NA Carbofuran 41 (82%) 2 (4.87%) 0.64 0.06–4.28 3 3-hydroxycarbofuran 25 (50%) 10 (40%) 3.78 0.46–13.62 3 3-ketocarbofuran 43 (86%) ND b 0.36 0.13–1.01 3 a NA: Not available. b ND: Not detected. c MRL: The maximum residue limit according to the CA and EU. Dibutylamine isn’t classified as a pesticide; therefore, it does not have established regulatory standards or guidelines for safe exposure levels, either nationally or internationally, by organizations such as the CA or the EU. Dibutylamine was found in 82% of the samples, with an average concentration of 9.01 µg/kg. In some samples, the concentration was notably high, reaching up to 45.65 µg/kg. While dibutylamine is known to be a metabolite of carbosulfan, its high prevalence and elevated concentrations suggest possible additional sources. These could include degradation of other N-methylcarbamate pesticides used in date cultivation, breakdown of agricultural chemicals containing butyl groups, or contamination from agricultural inputs such as fertilizers or plasticizers. The elevated levels might also be influenced by environmental conditions such as temperature, humidity, and light in UAE's climate, which can affect pesticide stability in agricultural products. The absence of regulatory standards for dibutylamine makes it challenging to assess the safety and potential risks associated with its presence in food products. While acute toxicity data exists for some exposure routes, long-term health effects from dietary exposure remain poorly understood. Consequently, determining safe exposure levels is difficult, complicating the evaluation of its impact on human health. While our risk assessment focused on metabolites with established toxicological profiles and regulatory limits, the high frequency and levels of dibutylamine detection warrant further investigation. Therefore, it is crucial to consider the potential cumulative effects of dibutylamine on consumers and establish limits and guidelines to safeguard human health and ensure environmental safety. This is particularly important given its frequent detection in our samples and potential presence in other agricultural products. Further research is needed to elucidate its formation pathways in agricultural products and establish its toxicological profile for comprehensive risk assessment. 3-Hydroxycarbofuran was detected in 25 samples, with concentrations ranging from 0.46 to 13.62 µg/kg, and exceeded its MRL of 3 µg/kg in 10 samples. Lastly, 3-ketocarbofuran was found in 43 samples, all below its MRL, with an average concentration of 0.3 µg/kg. These findings indicate a significant exposure to carbosulfan and its metabolites in date fruits cultivated in the UAE, a country noted for its substantial date production and consumption, and which holds the second position globally in date exports. This underscores the critical need for rigorous monitoring to safeguard public health, maintain the reputation of this vital agricultural sector, and adhere to the high standards required for global trade. 3.5. Exposure assessment This risk assessment focuses exclusively on dietary exposure through date consumption, as it represents the primary route of exposure for the general population. Other potential routes such as dermal or inhalation exposure were not considered as they are primarily relevant for occupational exposure during pesticide application rather than consumer exposure through food consumption. The sample data described above was used to assess the health risk of exposure. We analyzed the risk of exposure to each pesticide separately. However, since the substances considered are all metabolites of carbosulfan, the residues of carbofuran and other metabolites are a consequence of carbosulfan sprayed on crops. Therefore, dietary intake risk assessment should consider the total carbosulfan exposure. Moreover, carbofuran is more toxic than carbosulfan 28 , 31 ; thus, the total carbofuran exposure should be considered when analyzing the dietary risk of carbofuran exposure. To do this, we also studied the total exposure to carbofuran and carbosulfan by converting their respective metabolites. The conversion was done using molecular weights and the following formula: where C TP is the total residue of the pesticide studied, Co P is the observed residue of the pesticide of interest, C Oi is the observed residue of its i th metabolite, M P is the molecular weight of the pesticide of interest, and M i is the molecular weight of its i th metabolite. We did not include dibutylamine since it is not reported by any regulatory standard nor considered a pesticide. We note that the total calculated carbofuran residue ranged from 0.19 to 13.76 µg/kg. It exceeded the MRL of 3 µg/kg for 26% of the samples. In contrast, the total calculated carbosulfan residue ranged from 3.07 to 38.53 µg/kg, exceeding the MRL of 10 µg/kg for 62% of the samples. This increase is mainly due to carbosulfan resulting from the conversion of carbofuran, 3-hydroxycarbofuran, and 3-ketocarbofuran. These levels of total carbosulfan are alarming and require a review of the norm allowed in applying this pesticide. The high detection rate of dibutylamine (82% of samples) with concentrations up to 45.65 µg/kg is noteworthy, especially given the absence of established MRLs for this metabolite in international standards. The PRA approach described earlier was implemented using Monte-Carlo simulation, where both CRL and FI were treated as random variables. The computations were performed using body weights of 70 kg for adults and 15 kg for children. For CRL, a lognormal distribution was chosen as it best fit the sample data. Regarding the distribution of date consumption (FI) in the UAE, while no established distribution exists in literature, we adopted a normal distribution with parameters matching those reported in the empirical study of Ismail et al. 20 . Although this choice could be considered arbitrary since Ismail et al. only reported summary statistics, it aligns with common practice. While some literature suggests that fruit and vegetable consumption is sometimes modeled using a lognormal distribution 46 , we addressed this uncertainty by including a comprehensive sensitivity analysis of the FI distribution. RfDs are not available for 3-hydroxycarbofuran and 3-ketocarbofuran; therefore, the total residue for carbofuran and carbosulfan was used to account for the risk from exposure to these metabolites by converting the metabolites into their original substances. The MRLs of 3-hydroxycarbofuran and the 3-ketocarbofuran were used in the HQ formula instead of RfDs to obtain their HQ distributions. The HQ distributions for carbosulfan and its metabolites considered for adults and children are shown in Supplementary Fig. S2 and Fig. S3 online, respectively. Table 4 clearly shows that, for adults and children, the 95th percentiles of HQ distribution for all pesticides are less than 1.0, and their sums are also less than 1.0, indicating that they do not present adverse health effects. To see the total exposure risk, including metabolites, we used the HQ distributions for the total calculated residue of carbosulfan and carbofuran. Figure 2 and Fig. 3 illustrate these distributions for adults and children, respectively. As shown in Table 4 , the 95th quantiles are 0.00526 for the total carbosulfan and 0.00264 for the total carbofuran for the adult population, while they are 0.00748 and 0.00373, respectively, for children. Again, both are smaller than 1.0, indicating that from date consumption, carbosulfan and carbofuran do not present adverse health risks for adults or children. While our HQ analysis indicates minimal health risks (HQ < 1), the exceedance of international MRLs suggests opportunities for enhancing pesticide management practices. As the UAE currently relies on EU and Codex standards, development of region-specific guidelines considering local agricultural conditions would strengthen the monitoring and control of pesticide applications in date palm cultivation. Table 4 95th HQ percentile of the different pesticides for adults and children. Pesticide 95th HQ percentile for adult 95th HQ percentile for children Carbosulfan 0.0037 0.000534 Carbofuran 0.00067 0.00097 3-Hydroxycarbofuran 0.00589 0.00839 3-Ketocarbofuran 0.00043 0.00061 Total carbosulfan 0.00526 0.00748 Total carbofuran 0.00264 0.00373 To account for uncertainty in the FI distribution, we conducted a sensitivity analysis examining eight different scenarios. The base case (scenario 1) used a normal distribution with mean 114.3 g and standard deviation 30 g. Scenarios 2 and 3 increased the mean by 10% and 20%, respectively, while scenario 4 increased the standard deviation by 20%. Scenarios 5–8 explored the impact of using a lognormal distribution: scenario 5 maintained the base parameters, scenario 6 increased the mean by 10%, scenario 7 increased the mean by 20%, and scenario 8 increased the standard deviation by 20%. Table 5 presents the effects of these changes on the 95th quantile of the HQ distribution for each metabolite. Results showed that while increases in mean or standard deviation led to higher HQ values, changing the distribution from normal to lognormal had minimal impact. Importantly, HQ values for all metabolites remained well below the acceptable limit of 1, even with 20% increases in mean or standard deviation. Table 5 95th percentile of HQ for adults under different food intake distribution scenarios: sensitivity analysis of carbosulfan and its metabolites. Setting Carbosulfan Carbofuran 3-Hydroxycarbofuran 3-Ketocarbofuran Total carbosulfan Total carbofuran 1 0.0037 0.00067 0.00589 0.00043 0.00526 0.00264 2 0.00408 0.00074 0.00646 0.00047 0.00571 0.00284 3 0.00439 0.00080 0.00698 0.00051 0.00617 0.00309 4 0.00380 0.00068 0.00596 0.00044 0.00539 0.00266 5 0.00372 0.00066 0.00590 0.00043 0.00524 0.00261 6 0.00405 0.00073 0.00645 0.00047 0.00570 0.00281 7 0.00439 0.00080 0.00698 0.00051 0.00615 0.00311 8 0.00379 0.00068 0.00594 0.00044 0.00536 0.00262 4. Conclusion This study examined levels of carbosulfan and its metabolites in UAE date palm fruit using HPLC-MS/MS methodology with QuEChERS extraction. The developed method demonstrated strong linearity (R² > 0.998), low LOD/LOQ values (below the MRL), high recoveries, and acceptable RSD values. All samples contained at least one residue, with carbosulfan, carbofuran, and 3-hydroxycarbofuran exceeding the MRL in some cases. Additionally, dibutylamine was detected in 82% of the samples, with concentrations reaching up to 45.65 µg/kg in some samples. Health risk assessment indicated no adverse effects from date consumption, with all HQ values below 1.0 for both adults and children. While our findings align with international MRL standards due to the absence of regional guidelines, the observed exceedance rates highlight the urgent need for region-specific standards. As the UAE's second-largest global date exporter, our findings provide crucial baseline data for optimizing pesticide management. We recommend the implementation of systematic monitoring protocols, enhancement of farmer education programs on proper pesticide usage, and development of comprehensive region-specific guidelines that consider local agricultural practices while maintaining compliance with international standards. Future research should focus on establishing regional MRLs that consider local agricultural practices and environmental conditions, particularly for metabolites like dibutylamine that currently lack regulatory standards. Additionally, the high detection rates of certain metabolites necessitate a review of current pesticide application practices and the development of targeted intervention programs to ensure sustainable and safe date production. Declarations Acknowledgments The authors acknowledge the financial support of the Research Office of the United Arab Emirates University [fund # 31S462] and the SURE PLUS fund. Author contributions R.M developed the method, performed the validation study, analyzed and interpretated the data, and drafted the manuscript. K.G: performed the probabilistic study for the health risk assessment, analyzed the obtained results, and prepared Table 4 and Figures 2 and 3. B.E , Z.K , H.Z , and B.A conducted the experiments. M.M contributed to the conception of the work,supervised the work, and reviewed the manuscript. All authors approved the final form of the manuscript. Data Availability All data generated or analysed during this study are included in this published article and its Supplementary Information files. Additional information Competing interests: The authors declare no competing interests. References Al-Farsi, M. & Lee, C. Nutritional and Functional Properties of Dates: A Review. 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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-5022517","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":367489795,"identity":"4ef18234-a1ff-4459-a0cf-bc90735b2b4a","order_by":0,"name":"Rana Morsi","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Rana","middleName":"","lastName":"Morsi","suffix":""},{"id":367489796,"identity":"a2bc8f54-b246-444e-8e35-facf1442aa22","order_by":1,"name":"Kilani Ghoudi","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Kilani","middleName":"","lastName":"Ghoudi","suffix":""},{"id":367489797,"identity":"e9f6a552-256a-4612-bb2a-35cf07e7fcc0","order_by":2,"name":"Basant Elabyad","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Basant","middleName":"","lastName":"Elabyad","suffix":""},{"id":367489798,"identity":"42376a70-c966-4901-b87e-7fcf011d5e24","order_by":3,"name":"Zaina Kadoura","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Zaina","middleName":"","lastName":"Kadoura","suffix":""},{"id":367489799,"identity":"2d041808-dc4e-4cf0-8918-cc41864ecd8e","order_by":4,"name":"Hind Zeidane","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Hind","middleName":"","lastName":"Zeidane","suffix":""},{"id":367489800,"identity":"c5cda96e-6de1-44a3-a6f9-10e238e4bfc5","order_by":5,"name":"Bayan Al-Meetani","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Bayan","middleName":"","lastName":"Al-Meetani","suffix":""},{"id":367489801,"identity":"bfa374fb-43ff-4d67-9ccf-33204764382a","order_by":6,"name":"Mohammed A. Meetani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBADHn7S1B8AapFsIFULg8EBYlXrTjt88PGHmjsyxjeSHz7mYbCTZ2A/jF+32e20ZIMDx57xmN1IMzbmYUg2bOBJSyCgJcdM4gDbYaCWBDNpHgZmoPIcAwJa8r//OPDvMI/xjPTvv3kY6hMY+N9/IGQLG8PBtsM8BhI5Zsw8DIcTGCRy8OoA+cVY4mzfYR6JM2+KJecYHDdsk3hGyGHJDz9UfDtsz9+evvHDm4pqeX7+5Af4rUEFQPPZSFE/CkbBKBgFowA7AADhCkQ2W5pgGwAAAABJRU5ErkJggg==","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":true,"prefix":"","firstName":"Mohammed","middleName":"A.","lastName":"Meetani","suffix":""}],"badges":[],"createdAt":"2024-09-03 06:50:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5022517/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5022517/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-79871-5","type":"published","date":"2024-11-14T15:56:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68518247,"identity":"bdc53237-b683-4a07-a526-e77db0bef835","added_by":"auto","created_at":"2024-11-08 07:17:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26041,"visible":true,"origin":"","legend":"\u003cp\u003e%MU for each compound at a concentration level of a) 0.5 µg/kg; and b) 10 µg/kg.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5022517/v1/39a0c7d4b89838035c3db252.png"},{"id":68518248,"identity":"85f9c070-9c77-44f5-9e64-0f53a446c028","added_by":"auto","created_at":"2024-11-08 07:17:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":74347,"visible":true,"origin":"","legend":"\u003cp\u003eHQ due to the total residues of a) carbosulfan; and b) carbofuran in date samples for adults.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5022517/v1/06676409e103ada5cb725d01.png"},{"id":68518249,"identity":"7b2d9389-6332-411c-8453-0fc1e0c180fb","added_by":"auto","created_at":"2024-11-08 07:17:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73669,"visible":true,"origin":"","legend":"\u003cp\u003eHQ due to the total residues of a) carbosulfan; and b) carbofuran in date samples for children.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5022517/v1/ef3466120c697b2ee6c5cb7b.png"},{"id":69285060,"identity":"1f92c4f5-e8de-456e-96dd-8793a408d1c6","added_by":"auto","created_at":"2024-11-18 19:23:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1047918,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5022517/v1/8c56a2f8-866f-4334-98da-3fbc04cbaf32.pdf"},{"id":68518250,"identity":"7454d2eb-63d4-4605-aab0-0a54544891cb","added_by":"auto","created_at":"2024-11-08 07:17:59","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1231687,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5022517/v1/f24e482b1a2a22e237559f83.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"HPLC-MS/MS Monitoring and Health Risk Assessment of Carbosulfan and its Metabolites in Date Palm Fruit (Phoenix dactylifera)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe date palm (\u003cem\u003ePhoenix dactylifera\u003c/em\u003e) fruit is a nutritional treasure that offers a rich blend of essential nutrients crucial for human health. It is rich in dietary fiber, which is beneficial for digestive health, and contains moderate amounts of vitamins A, C, and B-complex\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. It is also abundant in essential minerals such as potassium, selenium, magnesium, iron, and others, which are vital for bodily functions\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Furthermore, date fruit is an excellent energy source due to its high sugar content, primarily consisting of fructose, glucose, and sucrose\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Studies have also highlighted dates\u0026rsquo; antioxidant\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, antimutagenic\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, anti-inflammatory\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, gastroprotective\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, hepatoprotective\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, and anticancer\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e properties. Given their nutritional and medicinal value, date fruit is a critical ingredient in producing various products, including food items, cosmetics, and medicinal products \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAdditionally, date palms are among the earliest cultivated plants, with a history of cultivation that spans over 6000 years\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. It plays a pivotal role as a fruit crop worldwide in arid and semi-arid regions\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. More than 2,000 date varieties are cultivated worldwide, predominantly in the Middle East and North Africa\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. According to the Food and Agriculture Organization of the United Nations (FAO), the United Arab Emirates (UAE) stands as one of the top 10 leading countries for date fruit production, with an annual output of approximately 397,328.94 tons\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and holds the second position globally for date exports, exporting 258,655.19 tons annually\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. This high production rate in the UAE coincides with a significant consumption level, where, on average, a person consumes about 114.3 grams of dates daily, equivalent to 10 date fruits\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Like other types of fruits, dates can be contaminated with pesticide residues, posing considerable health risks\u003csup\u003e\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The consumption of dates or other food contaminated with pesticides underscores the need for rigorous monitoring programs and regulatory measures to ensure food safety. Consequently, national and international organizations, such as the Codex Alimentarius (CA) and the European Union (EU), have established Maximum Residue Levels (MRLs) to protect consumer health and ensure food safety\u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe high consumption of dates in the UAE highlights the importance of monitoring pesticide residue levels in this fruit to protect public health and uphold food safety standards. A recent study by Morsi et al. found carbamate residues in date fruits in the UAE, with carbosulfan detected in all samples analyzed. Notably, 38.2% of these samples had carbosulfan levels exceeding its MRL of 10 \u0026micro;g/kg\u003csup\u003e26\u003c/sup\u003e. Carbosulfan, an insecticide in the carbamate class, is moderately toxic but highly effective against a broad spectrum of insects. It is known to degrade quickly in the environment, making it widely used in crop protection\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, consumption of food contaminated with carbosulfan can lead to human poisoning, fatigue, headache, blurred vision, a drop in blood pressure, and loss of consciousness\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Therefore, monitoring carbosulfan residue levels in agricultural products is crucial to ensure food safety.\u003c/p\u003e \u003cp\u003eMoreover, carbosulfan can degrade easily into carbofuran through hydrolysis and further metabolize to 3-hydroxycarbofuran and 3-ketocarbofuran through hydroxylation and oxidation, respectively\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. These metabolites are more toxic than carbosulfan, increasing the risk of human exposure\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Dibutylamine, 7-phenolcarbofuran, 3-hydroxy-7-phenolcarbofuran, and 3-keto-7-phenolcarbofuran are other detected metabolites of carbosulfan\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The metabolic pathway of carbosulfan is presented in Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e online.\u003c/p\u003e \u003cp\u003ePrevious studies have investigated levels of carbosulfan and its metabolites in various crops, including cucumbers\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, rice\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, and oranges\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, among others. To our knowledge, no research has been published on determining levels of carbosulfan metabolites in date palm fruit on a global scale. Given the UAE\u0026rsquo;s status as a premier exporter of date fruit\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, coupled with high local consumption rates\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and preliminary evidence of carbosulfan presence in UAE-grown dates\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, ensuring the safety and quality of these fruits becomes critically important. This context underscores the necessity of our study, which aims to fill a significant gap in existing research by detecting and quantifying the residual levels of carbosulfan and its four metabolites\u0026mdash;carbofuran, dibutylamine, carbofuran-3-hydroxy, and carbofuran-3-keto\u0026mdash;in dates cultivated in the UAE. For sample preparation, we utilized the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method, followed by High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) for analysis, ensuring precise and reliable quantification of pesticide residues. Additionally, a probabilistic health risk assessment study was conducted to estimate the health risks associated with carbosulfan and its metabolites for adults and children.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Chemicals and reagents\u003c/h2\u003e \u003cp\u003eHigh purity standards of carbosulfan, carbofuran, 3-hydroxycarbofuran, 3-ketocarbofuran, and dibutylamine were purchased from Dr. Ehrenstorfer (Augsburg, Germany). Carbofuran d3 internal standard, sodium chloride (NaCl), ammonium formate, anhydrous magnesium sulfate (MgSO\u003csub\u003e4\u003c/sub\u003e), and glacial acetic acid were obtained from Sigma-Aldrich (St. Louis, MO, USA). Acetonitrile and methanol (HPLC grade\u0026thinsp;\u0026ge;\u0026thinsp;99.9%) were provided by Honeywell (Seelze, Germany). Milli-Q Plus system was used to purify water (MilliporeSigma, USA). QuEChERS dispersive solid-phase extraction (d-SPE) kits were supplied by Agilent Technologies Inc. (Wilmington, DE, USA). Millex PTFE syringe filters were procured from Merck Millipore (Carrigtwohill, Ireland).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Preparation of standards and calibration curves\u003c/h2\u003e \u003cp\u003eStock standard solutions (200 mg/kg) and working standard solutions were prepared in methanol and stored in the dark at -18\u003csup\u003eo\u003c/sup\u003eC. Calibration curves were prepared using mixed standard solutions at various concentrations. Calibration curves were constructed both within the date matrix and in a pure solvent to assess the matrix effect. These curves covered a concentration range of 0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1.0, 5.0, 10, 50, and 100 \u0026#120583;g/kg, with a fixed concentration of 10 \u0026#120583;g/kg of carbofuran d3 used as an internal standard for all samples. The calibration curves were derived by plotting the relative responses of each analyte, determined by the ratio of the analyte\u0026rsquo;s peak area to that of the internal standard\u0026rsquo;s peak area, across the stated concentration range (0.001-100 \u0026#120583;g/kg).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Sample collection and preparation\u003c/h2\u003e \u003cp\u003eA total of 50 fresh samples of dates, including various types cultivated in the UAE, were randomly collected from different markets and farms. Permissions were obtained from all farm owners before any samples were collected. The collected samples were enclosed in sterile polypropylene bags for transport to the laboratory. In the laboratory, samples were refrigerated at 4\u003csup\u003eo\u003c/sup\u003eC until analysis. The European SANTE/11312/2021 guidelines were followed for handling, collecting, storing, processing, and preparing date samples\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eQuEChERS was selected as the extraction method due to its demonstrated efficiency for complex matrices like dates\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Alternative extraction methods such as liquid-liquid extraction (LLE) and solid-phase extraction (SPE) were considered but found less suitable. LLE presents challenges with emulsion formation and phase separation in date matrices, while SPE is more time-consuming, costly, and prone to cartridge clogging due to matrix interferences. QuEChERS offers efficient removal of matrix interferents through salting-out and dispersive clean-up steps. The QuEChERS method employed for sample preparation was adapted from the approach previously detailed by Morsi et al.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In brief, 50 g of dates (without caps and pits) and 75 mL of cold purified water were transferred to a food processor, where they were blended at high speed until the mixture was homogenized entirely into a date paste. For sample extraction, 10 g of the homogenized date paste was placed into a 50 mL polypropylene centrifuge tube. Then, 100 \u0026#120583;L of carbofuran d3 (100 \u0026#120583;L/kg) was added to the paste. After this, 10 mL of acetonitrile (containing 0.1% acetic acid) was added to the sample, and the mixture was vortexed. The tube was then placed in a dark, cold place for 60 minutes. After this, 4 g of anhydrous MgSO\u003csub\u003e4\u003c/sub\u003e and 1 g of NaCl were added to the mixture, and they were mixed and then centrifuged at 4500 rpm for 10 minutes. For clean-up, the supernatant was transferred to a 15 mL QuEChERS d-SPE tube composed of 400 mg primary secondary amine (PSA), 400 mg graphitized carbon black (GCB), 400 mg octadecylsilane chemically bonded silica, endcapped (C18EC), and 1200 mg MgSO\u003csub\u003e4\u003c/sub\u003e, which was then vortexed and centrifuged at 4500 rpm for another 10 minutes. The resulting extract was transferred to a glass tube, dried, and dissolved again in 1 mL of mobile phase B (methanol and acetonitrile, 2:1) before filtering through a 0.45 \u0026#120583;m PTFE syringe filter for HPLC-MS/MS analysis. To ensure the reliability of the results, each sample was analyzed in triplicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. HPLC-MS/MS\u003c/h2\u003e \u003cp\u003eHPLC instrument (Nexera-i LC-2040C 3D, Kyoto, Japan) coupled with an 8030 Shimadzu triple quadrupole mass spectrometer (Kyoto, Japan) was used for the analytical determination of carbosulfan and its metabolites. The separation was carried out on an ACQUITY UPLC BEH C18 column (2.1 mm x 150 mm x 1.7 \u0026#120583;m) supplied by Waters (Milford, USA), with a temperature maintained at 43\u003csup\u003eo\u003c/sup\u003eC. The mobile phase consisted of water with 10 mM ammonium formate (pH\u0026thinsp;=\u0026thinsp;3) (A) and a mixture of methanol and acetonitrile (2:1) (B), employing a gradient elution at a flow rate of 0.2 mL/min. The total run time was 15 minutes, and an injection volume of 15 \u0026#120583;L was used. The gradient elution was performed as follows: 0-3.5 min, 15% (B); 3.5-5 min, 15\u0026ndash;96% (B); 5-11.5 min, 96% (B); 11.5\u0026ndash;13 min, 96\u0026thinsp;\u0026minus;\u0026thinsp;15% (B); and 13-15min, 15% (B). The MS/MS detection was performed in the positive electrospray ionization (ESI) mode. The multiple reaction monitoring (MRM) method was used to quantify carbosulfan and its metabolites selectively and sensitively. The MS/MS parameters for carbosulfan, its metabolites, and the internal standard (carbofuran d3) are detailed in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e online.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Matrix effect\u003c/h2\u003e \u003cp\u003eThe presence of interferences in natural matrices, such as dates, can significantly affect the performance of analytical methods. Therefore, investigating the matrix effect is crucial when dealing with such matrices. Matrix effects were evaluated by comparing the slopes of matrix-matched calibration curves with those of solvent-based calibration curves of target analytes using the following formula:\u003c/p\u003e \u003cp\u003eMatrix effect% = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{slope\\left(matrix-matched\\:curve\\right)-slope\\:(solvent-based\\:curve)}{slope\\:(solvent-based\\:curve)}\\:x\\:100\\%\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe values of the matrix effect can be either positive due to ion enhancement or negative due to ion suppression. Depending on their values, matrix effects can be categorized into soft, medium, and strong\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. It is considered soft if the obtained value ranges from \u0026minus;\u0026thinsp;20\u0026ndash;20%\u003csup\u003e40\u003c/sup\u003e. In this case, the matrix effect is negligible, and calibration curves prepared in the solvent, which are simpler, easier, and less time-consuming, can be used according to the European SANTE/12830/2020 guidelines\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. However, if obtained values exceed\u0026thinsp;\u0026plusmn;\u0026thinsp;20, indicating medium or strong matrix effects, solvent-based calibration curves cannot be used\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Method validation\u003c/h2\u003e \u003cp\u003eThe proposed analytical method was validated by assessing its sensitivity, accuracy, and precision per the European SANTE/11312/2021 guidelines\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Sensitivity was determined by evaluating linearity and limits of detection (LOD). Accuracy and precision were assessed based on limits of quantification (LOQ), recovery rates, repeatability, and intermediate precision.\u003c/p\u003e \u003cp\u003eLinearity was evaluated using solvent-based calibration curves covering a concentration range of 0.001-100 \u0026#120583;g/kg and expressed as the coefficient of determination (R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eLOD and LOQ were calculated based on the standard deviation of multiple blank measurements. We conducted 20 measurements of blank samples to determine the mean blank signal \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{(\\stackrel{-}{S}}_{bl})\\)\u003c/span\u003e\u003c/span\u003e and its standard deviation (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{bl})\\)\u003c/span\u003e\u003c/span\u003e. The minimum distinguishable analytical signal (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{S}_{m})\\:\\)\u003c/span\u003e\u003c/span\u003ewas calculated using the formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{S}_{m}={\\stackrel{-}{S}}_{bl}+k{\\sigma\\:}_{bl}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere k is 3 for LOD and 10 for LOQ, corresponding to a signal-to-noise ratio (S/N) greater than 3 and 10, respectively. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{S}_{m}\\)\u003c/span\u003e\u003c/span\u003e was then converted to the corresponding minimum concentration (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{m}\\)\u003c/span\u003e\u003c/span\u003e) using the formula:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{c}_{m}=\\frac{{S}_{m}-\\:{\\stackrel{-}{S}}_{bl}}{m}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{m}\\)\u003c/span\u003e\u003c/span\u003e represents the limits of detection or quantitation, and m represents the slope of the calibration curves. As \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{S}_{m}-{\\stackrel{-}{S}}_{bl}=k{\\sigma\\:}_{bl}\\)\u003c/span\u003e\u003c/span\u003e, we can calculate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{m}\\)\u003c/span\u003e\u003c/span\u003e as follows:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{c}_{m}=k\\frac{\\:{\\stackrel{-}{S}}_{bl}}{m}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis indicates that \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{m}\\)\u003c/span\u003e\u003c/span\u003e represents the LOD when k\u0026thinsp;=\u0026thinsp;3 and the LOQ when k\u0026thinsp;=\u0026thinsp;10. Our approach for determining LOD and LOQ follows the methodology outlined by Skoog et al. (32, p.20)\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. These calculations ensure that the LOD represents the lowest concentration of an analyte that can be reliably detected. In contrast, the LOQ represents the lowest concentration that can be quantitatively measured with sufficient precision.\u003c/p\u003e \u003cp\u003eRecoveries, repeatability, and intermediate precision were determined by spiking blank date samples with a mixture of standards at two concentration levels of 0.5 and 10 \u0026#120583;g/kg in three replicates. The relative standard deviation (RSD) was used to evaluate the repeatability and intermediate precision. For repeatability, six replicates were analyzed on the same day, whereas 12 replicates were analyzed on two consecutive days (6 analyses/day) for intermediate precision. Following the European SANTE/11312/2021 guidelines, recoveries should range between 60% and 140%, while RSD values should not exceed 20%\u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Measurement uncertainty\u003c/h2\u003e \u003cp\u003eMethod validation and measurement uncertainty (MU) are essential to determine whether an analytical method meets legal requirements. MU is a parameter that describes the dispersion of every measurement\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. To comply with the European Commission SANTE/11312/2021 guidelines, MU values should not exceed 50%\u003csup\u003e35\u003c/sup\u003e. MU, referred to as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\\prime }{U}\\)\u003c/span\u003e\u003c/span\u003e, was estimated using the following equation:\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:\\stackrel{\u0026acute;}{U}=k\\:\\stackrel{\u0026acute;}{u}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:k\\)\u003c/span\u003e\u003c/span\u003e is a coverage factor of 2 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}\\)\u003c/span\u003e\u003c/span\u003e is the relative standard uncertainty. The standard uncertainty was estimated based on bias and within-laboratory variability. The bias is based on recovery data, while within-laboratory variability is based on precision data generated in the method validation experiments. The \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}\\)\u003c/span\u003e\u003c/span\u003e was measured for each compound using the following:\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e\n$$\\:\\stackrel{\u0026acute;}{u}=\\sqrt{{\\stackrel{\u0026acute;}{u}\\left(bias\\right)}^{2}+{\\stackrel{\u0026acute;}{u}\\left(precision\\right)}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}\\left(bias\\right)\\)\u003c/span\u003e\u003c/span\u003e is the uncertainty component for the bias, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}\\left(precision\\right)\\)\u003c/span\u003e\u003c/span\u003e is the uncertainty component for the precision. The bias is the difference between the measured and actual values, which is the difference between the spiked and measured concentrations. The \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}\\left(bias\\right)\\)\u003c/span\u003e\u003c/span\u003e can be calculated using the following:\u003cdiv id=\"Equf\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equf\" name=\"EquationSource\"\u003e\n$$\\:\\stackrel{\u0026acute;}{u}\\left(bias\\right)=\\sqrt{{{mean}^{2}}_{bias}+SD.{{P}^{2}}_{bias}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{mean}^{2}}_{bias}\\)\u003c/span\u003e\u003c/span\u003e is the mean of the relative bias, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:SD.{{P}^{2}}_{bias}\\)\u003c/span\u003e\u003c/span\u003e is the population standard deviation of the relative bias. On the other hand, the value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}\\left(precision\\right)\\)\u003c/span\u003e\u003c/span\u003e is estimated from the %RSD of the reproducibility data for each compound:\u003cdiv id=\"Equg\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equg\" name=\"EquationSource\"\u003e\n$$\\:\\stackrel{\u0026acute;}{u}\\left(precision\\right)=\\%RSD$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Exposure assessment\u003c/h2\u003e \u003cp\u003eThe United States Environmental Protection Agency (US-EPA) recommends using Hazard Quotient (HQ) and Hazard Index (HI) to assess risk after various exposures. HQ measures risk from a single chemical, while HI quantifies risk from a mixture of chemicals. HQ is the ratio of exposure to an appropriate reference, such as the MRL, acceptable daily intake (ADI), or reference dose (RfD). HI is the sum of the HQs for all chemicals in a mixture. An HQ\u0026thinsp;\u0026le;\u0026thinsp;1 indicates that adverse effects are unlikely, signifying negligible hazard. HI sums HQs for substances affecting the same target organ or system, with an HI\u0026thinsp;\u0026lt;\u0026thinsp;1 indicating no likely adverse effects from lifetime exposure.\u003c/p\u003e \u003cp\u003eTraditional risk assessment approaches are deterministic, often reporting risks using central tendency, high-end measures (e.g., 90th percentile), or maximum anticipated exposure. Following the 1997 release of EPA\u0026rsquo;s Policy for using probabilistic analysis in risk assessment\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, Probabilistic Risk Assessment (PRA) became critical in risk assessment, incorporating variability and uncertainty in exposure estimation. PRA estimates the distribution of exposure or risk, determines uncertainty/variability, and identifies key contributors to variability. US-EPA emphasizes communicating PRA results by providing distributions of exposure or risk estimates rather than single point estimates\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe PRA analysis was carried out in this study using Monte-Carlo simulation with 100,000 replicates\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The HQs were computed for each simulation replicate, and the 95th percentile of the HQ distribution was used to assess exposure risk. The HQ was calculated for adults and children as follows:\u003cdiv id=\"Equh\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equh\" name=\"EquationSource\"\u003e\n$$\\:HQ=\\frac{EED}{ADI}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere EED (mg/kg bw/d) is the estimated exposure, and ADI (mg/kg bw/d) is the acceptable daily intake. The estimated exposure can be calculated as follows:\u003cdiv id=\"Equi\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equi\" name=\"EquationSource\"\u003e\n$$\\:EED=\\frac{CRL*\\:FI}{BW}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere CRL (mg/kg) is the calculated residue level, FI (kg/d) is the food intake, and BW (kg) is the body weight. The FI or daily consumption of dates for adults is assumed to be normally distributed with a mean of 114.3 g/day as found by Ismail et al. (2006), with the standard deviation approximated as 30 g/day to reflect the range of measurements reported\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The FI for children was also assumed to be normally distributed with a mean of 35 g/day, as reported by Morsi et al.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, using the same coefficient of variation as the adult population, resulting in a standard deviation of 9.2 g/day. The body weight for an adult was taken to be 70 kg, while that for a child was taken to be 15 kg. The RfDs for carbosulfan and carbofuran are 0.01 mg/kg-day and 0.005 mg/kg-day, respectively (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.epa.gov/AtoZ/?list_type=alpha\u003c/span\u003e\u003cspan address=\"https://iris.epa.gov/AtoZ/?list_type=alpha\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). RfDs are not available for the other metabolites.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Matrix effect\u003c/h2\u003e \u003cp\u003eThe matrix effect is one of the main challenges encountered when analyzing complex matrices using LC-MS due to the presence of co-eluting compounds. These compounds can affect the ionization of target analytes and interfere with their analysis, impacting the overall performance of the analytical method. The effects can manifest as either a decrease (ion suppression) or an increase (ion enhancement) in the analyte\u0026rsquo;s signal\u003csup\u003e\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Therefore, it is imperative to mitigate matrix-induced effects. To overcome matrix effects, various approaches have been employed, including proper sample extraction and clean-up steps, the use of matrix-matched or standard addition calibration curves, and the utilization of deuterated or isotopically labeled internal standards, which can reduce the impact of the matrix on the obtained results\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Other strategies to reduce the matrix effect include minimizing the injection volume, diluting the sample, increasing the elution gradient time, and reducing the flow rate.\u003c/p\u003e \u003cp\u003eThe matrix effects were investigated for carbosulfan and its four metabolites (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The obtained matrix effect values ranged from \u0026minus;\u0026thinsp;16.43\u0026ndash;17.09%; all are within the soft range (\u0026thinsp;\u0026le;\u0026thinsp;\u0026plusmn;\u0026thinsp;20), indicating negligible matrix effect. Carbofuran was the only compound with a negative value (-16.43%), indicating a decrease in its signal due to ion suppression. On the other hand, carbosulfan, dibutylamine, carbofuran-3-hydroxy, and carbofuran-3-keto had matrix effect values of 3.46%, 8.88%, 0.14%, and 17.09%, respectively. The positive values indicate an increase in their signal due to ion enhancement. According to the European SANTE/12830/2020 guidelines, solvent-based calibration curves can be used if values of the matrix effect don\u0026rsquo;t exceed\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003csup\u003e41\u003c/sup\u003e. Therefore, in our study, calibration curves prepared in methanol were used to quantify the residual levels of carbosulfan and its metabolites in dates. The negligible effect of the matrix suggests that the extraction and clean-up techniques are appropriate. The deuterated internal standard might also be attributed to the insignificant matrix effect.\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\u003eValidation parameters of carbosulfan and its metabolites in dates.\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\"\u003e \u003cp\u003eAnalyte\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinear dynamic range\u003c/p\u003e \u003cp\u003e(\u0026#120583;g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOD\u003c/p\u003e \u003cp\u003e(\u0026#120583;g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLOQ\u003c/p\u003e \u003cp\u003e(\u0026#120583;g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMatrix Effect (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbosulfan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001-100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDibutylamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001-100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001-100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0012\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\u003e-16.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Hydroxycarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Ketocarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.09\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\u003eTo contextualize our matrix effect results, a comparison was made with previous findings by Soler et al., who analyzed carbosulfan and its metabolites in tangerine matrix. Their study reported substantially higher matrix effects, with enhancement observed for all compounds: carbosulfan (1.3%), carbofuran (43.2%), 3-hydroxycarbofuran (34.5%), 3-ketocarbofuran (59.2%), and dibutylamine (89.7%)\u003csup\u003e34\u003c/sup\u003e. In contrast, our method demonstrated significantly better control of matrix effects in date matrix, with values ranging from \u0026minus;\u0026thinsp;16.43\u0026ndash;17.09%. Notably, while carbofuran exhibited ion enhancement (43.2%) in tangerine matrix, it showed ion suppression (-16.43%) in date matrix, highlighting the matrix-dependent nature of these effects. The substantially lower matrix effects achieved in our method, despite dates being known for their complex matrix composition rich in sugars and other potentially interfering compounds, can be attributed to our optimized extraction and clean-up procedures, along with the use of deuterated internal standard. These results demonstrate the effectiveness of our method in managing matrix effects for the analysis of carbosulfan and its metabolites in dates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Method validation\u003c/h2\u003e \u003cp\u003eThe developed method was validated in terms of sensitivity, accuracy, and precision by determining the linearity, LOD, LOQ, recoveries, repeatability (intraday), and intermediate precision (interday), following the European SANTE/11312/2021 guidelines\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Linearity, LOD, and LOQ\u003c/h2\u003e \u003cp\u003eThe results of linearity, LOD, and LOQ are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Excellent linearity was obtained for carbosulfan, dibutylamine, carbofuran, 3-ketocarbofuran, with R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.999. Similarly, 3-hydroxycarbofuran demonstrated very good linearity with R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.998. The LOD values were determined to be 0.001 \u0026#120583;g/kg for carbosulfan, dibutylamine, and carbofuran, while 3-hydroxycarbofuran and 3-ketocarbofuran exhibited LODs of 0.011 \u0026#120583;g/kg and 0.048 \u0026#120583;g/kg, respectively. The LOQ values were determined to be 0.003 \u0026micro;g/kg for carbosulfan, dibutylamine, and carbofuran; 0.03 \u0026micro;g/kg for 3-hydroxycarbofuran; and 0.14 \u0026micro;g/kg for 3-ketocarbofuran. These findings indicate the method's robust sensitivity, with LOD and LOQ values well below the MRL for all analyzed compounds, highlighting its efficacy in detecting carbosulfan and its metabolites in date samples.\u003c/p\u003e \u003cp\u003eA critical comparison with existing literature highlights significant methodological advancements achieved by our study. The R\u0026sup2;, LOD, and LOQ values we obtained show substantial improvements compared to the results reported by Song et al.. They found R\u0026sup2; values just over 0.990 and reported much higher LOD and LOQ values for carbosulfan, carbofuran, and 3-hydroxycarbofuran. Specifically, their LOD values were 2 \u0026micro;g/kg, 1 \u0026micro;g/kg, and 10 \u0026micro;g/kg, respectively, while LOQ values were 0.9 \u0026micro;g/kg, 0.3 \u0026micro;g/kg, and 4 \u0026micro;g/kg\u003csup\u003e28\u003c/sup\u003e. Our findings also surpassed those of Soler et al., who investigated the same five compounds. They reported R\u0026sup2; values between 0.988 and 0.996. For LOQ values, they found 0.01 mg/kg for carbosulfan, carbofuran, 3-hydroxycarbofuran, and dibutylamine, with 3-ketocarbofuran at 0.03 mg/kg\u003csup\u003e34\u003c/sup\u003e. Moreover, Zhang et al. reported R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.999 for carbosulfan, carbofuran, 3-hydroxycarbofuran, aligning with our reported R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e for carbosulfan and carbofuran but higher than our reported R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e for 3-hydroxycarbofuran (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.998). Their LOD values, depending on the matrix, ranged from 0.0027 to 0.0042 mg/kg for carbosuflan, 0.0040 to 0.0074 mg/kg for carbofuran, and 0.0094 to 0.012 mg/kg for 3-hydroxycarbofuran, which are higher than our reported LOD values\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This comprehensive comparison demonstrates our method's superior performance and reliability in quantifying trace levels of carbosulfan and its metabolites.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Accuracy and precision\u003c/h2\u003e \u003cp\u003eThe method\u0026rsquo;s accuracy was evaluated by comparing the measured values to the true values of the samples, expressed as the recovery. Recoveries were determined by spiking blank date samples with a mixture of carbosulfan and its metabolites at concentrations of 0.5 \u0026#120583;g/kg and 10 \u0026#120583;g/kg in three replicates. The recovery values of this study are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All analytes exhibited recovery values ranging from 92\u0026ndash;103%, which fall within the acceptable range suggested by the European SANTE/11312/2021 guidelines\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Precision was assessed through repeatability (intraday) and intermediate precision (interday) and expressed as the RSD. Repeatability was determined by analyzing six replicates on the same day, while intermediate precision was assessed over two consecutive days, analyzing twelve replicates after spiking blank date samples with a mixture of carbosulfan and its metabolites at concentrations of 0.5 \u0026#120583;g/kg and 10 \u0026#120583;g/kg. The RSD values obtained ranged from 1\u0026ndash;9%, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The recoveries and RSD values indicate that the developed method is accurate and precise.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRecovery, repeatability, and intermediate precision at 0.5 \u0026#120583;g/kg and 10 \u0026#120583;g/kg.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.5 \u0026#120583;g/kg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e10 \u0026#120583;g/kg\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecovery %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRSD%\u003c/p\u003e \u003cp\u003eIntraday\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRSD%\u003c/p\u003e \u003cp\u003eInterday (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecovery %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRSD%\u003c/p\u003e \u003cp\u003eIntraday\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRSD%\u003c/p\u003e \u003cp\u003eInterday (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbosulfan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDibutylamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Hydroxycarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Ketocarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\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\u003eA comparison of recoveries and RSD values in this study with those reported in other studies reveals our method\u0026rsquo;s superior performance. Song et al. reported recovery values ranging from 87.2\u0026ndash;91% with RSD of 3.2\u0026ndash;8.1% for carbosulfan, carbofuran, and 3-hydroxycarbofuran\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Zhang et al. studied the same compounds and obtained recoveries of 72.71\u0026ndash;105.07% with RSDs of 2\u0026ndash;8.8% for the same compounds\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Although the values reported by Song et al. and Zhang et al. are within the acceptable range set by the European Commission, our study achieved better recoveries for the same compounds (92\u0026ndash;103% with RSDs of 1\u0026ndash;9%).\u003c/p\u003e \u003cp\u003eThe validation of the proposed method has proven its reliability and consistent performance across all evaluated parameters. The results demonstrate that the method is well-suited for accurately and sensitively detecting trace amounts of carbosulfan metabolites in dates.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Uncertainty measurements\u003c/h2\u003e \u003cp\u003eThe MU for carbosulfan and its metabolites was calculated following the European Commission SANTE/11312/2021 guidelines\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. This was done by multiplying a coverage factor (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:k\\)\u003c/span\u003e\u003c/span\u003e) of 2 by the standard uncertainty (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{\u0026acute;}{u}).\\)\u003c/span\u003e\u003c/span\u003e A coverage factor of 2 represents a 95% confidence interval. The MU was calculated at two concentration levels: 0.5 \u0026micro;g/kg and 10 \u0026micro;g/kg (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The calculated MUs for all compounds at these two concentration levels were within the acceptable limit of 50%, indicating that the analytical method is reliable and meets regulatory standards.\u003c/p\u003e \u003cp\u003eThe validated method parameters demonstrate significant practical implications for routine analysis of dates. The controlled matrix effects (within \u0026plusmn;\u0026thinsp;20%) enable the use of simpler and less time-consuming solvent-based calibration curves, while the excellent recovery rates (92\u0026ndash;103%) and measurement uncertainties (within 50%) ensure reliable quantification across a wide concentration range. Together, these performance characteristics, meeting strict European SANTE guidelines, make the method suitable for routine monitoring in food safety laboratories. The practical reliability of the method is crucial for regulatory compliance testing, particularly in detecting MRL exceedances in commercial samples, ensuring food safety, and facilitating international trade of dates. This practical significance is clearly demonstrated in the following real sample analysis, where the method successfully detected multiple instances of regulatory non-compliance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Real samples\u003c/h2\u003e \u003cp\u003eThe content of carbosulfan and its metabolites (dibutylamine, carbofuran, 3-hydroxycarbofuran, and 3-ketocarbofuran) was analyzed in 50 samples of various date varieties using the developed method. The detected concentration of these compounds is detailed in Supplementary Table S2 online. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the distribution of carbosulfan and its metabolites in the date samples. Carbosulfan was detected in all samples, with concentrations ranging from 1.28 to 27.39 \u0026micro;g/kg, exceeding its MRL of 10 \u0026micro;g/kg in 23 samples. Dibutylamine and carbofuran were found in 41 samples, with concentrations ranging from 0.27 to 45.65 \u0026micro;g/kg and 0.063 to 4.28 \u0026micro;g/kg, respectively. Carbofuran exceeded its MRL of 3 \u0026micro;g/kg in 2 samples.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of carbosulfan and its metabolites in date samples.\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalyte\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContaminated Samples \u003c/p\u003e \u003cp\u003eNo. (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt; MRL\u003c/p\u003e \u003cp\u003eNo. (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage concentration\u003c/p\u003e \u003cp\u003e(\u0026#120583;g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConcentration range (min-max)\u003c/p\u003e \u003cp\u003e(\u0026#120583;g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMRL\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(\u0026#120583;g/kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbosulfan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.28\u0026ndash;27.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDibutylamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u0026ndash;45.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u0026ndash;4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-hydroxycarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u0026ndash;13.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-ketocarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eNA: Not available.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003eb\u003c/sup\u003eND: Not detected.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ec\u003c/sup\u003eMRL: The maximum residue limit according to the CA and EU.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDibutylamine isn\u0026rsquo;t classified as a pesticide; therefore, it does not have established regulatory standards or guidelines for safe exposure levels, either nationally or internationally, by organizations such as the CA or the EU. Dibutylamine was found in 82% of the samples, with an average concentration of 9.01 \u0026micro;g/kg. In some samples, the concentration was notably high, reaching up to 45.65 \u0026micro;g/kg. While dibutylamine is known to be a metabolite of carbosulfan, its high prevalence and elevated concentrations suggest possible additional sources. These could include degradation of other N-methylcarbamate pesticides used in date cultivation, breakdown of agricultural chemicals containing butyl groups, or contamination from agricultural inputs such as fertilizers or plasticizers. The elevated levels might also be influenced by environmental conditions such as temperature, humidity, and light in UAE's climate, which can affect pesticide stability in agricultural products. The absence of regulatory standards for dibutylamine makes it challenging to assess the safety and potential risks associated with its presence in food products. While acute toxicity data exists for some exposure routes, long-term health effects from dietary exposure remain poorly understood. Consequently, determining safe exposure levels is difficult, complicating the evaluation of its impact on human health. While our risk assessment focused on metabolites with established toxicological profiles and regulatory limits, the high frequency and levels of dibutylamine detection warrant further investigation. Therefore, it is crucial to consider the potential cumulative effects of dibutylamine on consumers and establish limits and guidelines to safeguard human health and ensure environmental safety. This is particularly important given its frequent detection in our samples and potential presence in other agricultural products. Further research is needed to elucidate its formation pathways in agricultural products and establish its toxicological profile for comprehensive risk assessment.\u003c/p\u003e \u003cp\u003e3-Hydroxycarbofuran was detected in 25 samples, with concentrations ranging from 0.46 to 13.62 \u0026micro;g/kg, and exceeded its MRL of 3 \u0026micro;g/kg in 10 samples. Lastly, 3-ketocarbofuran was found in 43 samples, all below its MRL, with an average concentration of 0.3 \u0026micro;g/kg. These findings indicate a significant exposure to carbosulfan and its metabolites in date fruits cultivated in the UAE, a country noted for its substantial date production and consumption, and which holds the second position globally in date exports. This underscores the critical need for rigorous monitoring to safeguard public health, maintain the reputation of this vital agricultural sector, and adhere to the high standards required for global trade.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Exposure assessment\u003c/h2\u003e \u003cp\u003eThis risk assessment focuses exclusively on dietary exposure through date consumption, as it represents the primary route of exposure for the general population. Other potential routes such as dermal or inhalation exposure were not considered as they are primarily relevant for occupational exposure during pesticide application rather than consumer exposure through food consumption.\u003c/p\u003e \u003cp\u003eThe sample data described above was used to assess the health risk of exposure. We analyzed the risk of exposure to each pesticide separately. However, since the substances considered are all metabolites of carbosulfan, the residues of carbofuran and other metabolites are a consequence of carbosulfan sprayed on crops. Therefore, dietary intake risk assessment should consider the total carbosulfan exposure. Moreover, carbofuran is more toxic than carbosulfan\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e; thus, the total carbofuran exposure should be considered when analyzing the dietary risk of carbofuran exposure. To do this, we also studied the total exposure to carbofuran and carbosulfan by converting their respective metabolites. The conversion was done using molecular weights and the following formula:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ewhere C\u003csub\u003eTP\u003c/sub\u003e is the total residue of the pesticide studied, Co\u003csub\u003eP\u003c/sub\u003e is the observed residue of the pesticide of interest, C\u003csub\u003eOi\u003c/sub\u003e is the observed residue of its i\u003csup\u003eth\u003c/sup\u003e metabolite, M\u003csub\u003eP\u003c/sub\u003e is the molecular weight of the pesticide of interest, and M\u003csub\u003ei\u003c/sub\u003e is the molecular weight of its i\u003csup\u003eth\u003c/sup\u003e metabolite. We did not include dibutylamine since it is not reported by any regulatory standard nor considered a pesticide. We note that the total calculated carbofuran residue ranged from 0.19 to 13.76 \u0026micro;g/kg. It exceeded the MRL of 3 \u0026micro;g/kg for 26% of the samples. In contrast, the total calculated carbosulfan residue ranged from 3.07 to 38.53 \u0026micro;g/kg, exceeding the MRL of 10 \u0026micro;g/kg for 62% of the samples. This increase is mainly due to carbosulfan resulting from the conversion of carbofuran, 3-hydroxycarbofuran, and 3-ketocarbofuran. These levels of total carbosulfan are alarming and require a review of the norm allowed in applying this pesticide. The high detection rate of dibutylamine (82% of samples) with concentrations up to 45.65 \u0026micro;g/kg is noteworthy, especially given the absence of established MRLs for this metabolite in international standards.\u003c/p\u003e \u003cp\u003eThe PRA approach described earlier was implemented using Monte-Carlo simulation, where both CRL and FI were treated as random variables. The computations were performed using body weights of 70 kg for adults and 15 kg for children. For CRL, a lognormal distribution was chosen as it best fit the sample data. Regarding the distribution of date consumption (FI) in the UAE, while no established distribution exists in literature, we adopted a normal distribution with parameters matching those reported in the empirical study of Ismail et al.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Although this choice could be considered arbitrary since Ismail et al. only reported summary statistics, it aligns with common practice. While some literature suggests that fruit and vegetable consumption is sometimes modeled using a lognormal distribution\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, we addressed this uncertainty by including a comprehensive sensitivity analysis of the FI distribution.\u003c/p\u003e \u003cp\u003eRfDs are not available for 3-hydroxycarbofuran and 3-ketocarbofuran; therefore, the total residue for carbofuran and carbosulfan was used to account for the risk from exposure to these metabolites by converting the metabolites into their original substances. The MRLs of 3-hydroxycarbofuran and the 3-ketocarbofuran were used in the HQ formula instead of RfDs to obtain their HQ distributions. The HQ distributions for carbosulfan and its metabolites considered for adults and children are shown in Supplementary Fig. S2 and Fig. S3 online, respectively. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e clearly shows that, for adults and children, the 95th percentiles of HQ distribution for all pesticides are less than 1.0, and their sums are also less than 1.0, indicating that they do not present adverse health effects. To see the total exposure risk, including metabolites, we used the HQ distributions for the total calculated residue of carbosulfan and carbofuran. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate these distributions for adults and children, respectively. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the 95th quantiles are 0.00526 for the total carbosulfan and 0.00264 for the total carbofuran for the adult population, while they are 0.00748 and 0.00373, respectively, for children. Again, both are smaller than 1.0, indicating that from date consumption, carbosulfan and carbofuran do not present adverse health risks for adults or children. While our HQ analysis indicates minimal health risks (HQ\u0026thinsp;\u0026lt;\u0026thinsp;1), the exceedance of international MRLs suggests opportunities for enhancing pesticide management practices. As the UAE currently relies on EU and Codex standards, development of region-specific guidelines considering local agricultural conditions would strengthen the monitoring and control of pesticide applications in date palm cultivation.\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\u003e95th HQ percentile of the different pesticides for adults and children.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePesticide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95th HQ percentile for adult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95th HQ percentile for children\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbosulfan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Hydroxycarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Ketocarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal carbosulfan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.00526\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.00748\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal carbofuran\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.00264\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.00373\u003c/b\u003e\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\u003eTo account for uncertainty in the FI distribution, we conducted a sensitivity analysis examining eight different scenarios. The base case (scenario 1) used a normal distribution with mean 114.3 g and standard deviation 30 g. Scenarios 2 and 3 increased the mean by 10% and 20%, respectively, while scenario 4 increased the standard deviation by 20%. Scenarios 5\u0026ndash;8 explored the impact of using a lognormal distribution: scenario 5 maintained the base parameters, scenario 6 increased the mean by 10%, scenario 7 increased the mean by 20%, and scenario 8 increased the standard deviation by 20%. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the effects of these changes on the 95th quantile of the HQ distribution for each metabolite. Results showed that while increases in mean or standard deviation led to higher HQ values, changing the distribution from normal to lognormal had minimal impact. Importantly, HQ values for all metabolites remained well below the acceptable limit of 1, even with 20% increases in mean or standard deviation.\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\u003e95th percentile of HQ for adults under different food intake distribution scenarios: sensitivity analysis of carbosulfan and its metabolites.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSetting\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbosulfan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarbofuran\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3-Hydroxycarbofuran\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3-Ketocarbofuran\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal carbosulfan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal carbofuran\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0037\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00067\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00589\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00043\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00526\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00264\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00262\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. Conclusion","content":"\u003cp\u003eThis study examined levels of carbosulfan and its metabolites in UAE date palm fruit using HPLC-MS/MS methodology with QuEChERS extraction. The developed method demonstrated strong linearity (R\u0026sup2; \u0026gt; 0.998), low LOD/LOQ values (below the MRL), high recoveries, and acceptable RSD values. All samples contained at least one residue, with carbosulfan, carbofuran, and 3-hydroxycarbofuran exceeding the MRL in some cases. Additionally, dibutylamine was detected in 82% of the samples, with concentrations reaching up to 45.65 \u0026micro;g/kg in some samples. Health risk assessment indicated no adverse effects from date consumption, with all HQ values below 1.0 for both adults and children. While our findings align with international MRL standards due to the absence of regional guidelines, the observed exceedance rates highlight the urgent need for region-specific standards. As the UAE's second-largest global date exporter, our findings provide crucial baseline data for optimizing pesticide management. We recommend the implementation of systematic monitoring protocols, enhancement of farmer education programs on proper pesticide usage, and development of comprehensive region-specific guidelines that consider local agricultural practices while maintaining compliance with international standards. Future research should focus on establishing regional MRLs that consider local agricultural practices and environmental conditions, particularly for metabolites like dibutylamine that currently lack regulatory standards. Additionally, the high detection rates of certain metabolites necessitate a review of current pesticide application practices and the development of targeted intervention programs to ensure sustainable and safe date production.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors\u0026nbsp;acknowledge the financial support of the Research Office of the United Arab Emirates University [fund # 31S462] and the SURE PLUS fund.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eR.M\u0026nbsp;\u003c/strong\u003edeveloped the method, performed the validation study, analyzed and interpretated the data, and drafted the manuscript. \u003cstrong\u003eK.G:\u003c/strong\u003e performed the probabilistic study for the health risk assessment, analyzed the obtained results, and prepared Table 4 and Figures 2 and 3. \u003cstrong\u003eB.E\u003c/strong\u003e, \u003cstrong\u003eZ.K\u003c/strong\u003e, \u003cstrong\u003eH.Z\u003c/strong\u003e, and \u003cstrong\u003eB.A\u003c/strong\u003e conducted the experiments. \u003cstrong\u003eM.M\u003c/strong\u003e contributed to the conception of the work,supervised the work, and reviewed the manuscript. All authors approved the final form of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its Supplementary Information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAl-Farsi, M. \u0026amp; Lee, C. Nutritional and Functional Properties of Dates: A Review. \u003cem\u003eCrit. Rev. Food Sci. Nutr.\u003c/em\u003e \u003cb\u003e48\u003c/b\u003e, 877\u0026ndash;887 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang, Z. X., Shi, L. E. \u0026amp; Aleid, S. M. 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(1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchuhmacher, M., Meneses, M., Xifr\u0026oacute;, A. \u0026amp; Domingo, J. L. The use of Monte-Carlo simulation techniques for risk assessment: study of a municipal waste incinerator. \u003cem\u003eChemosphere\u003c/em\u003e. \u003cb\u003e43\u003c/b\u003e, 787\u0026ndash;799 (2001).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Carbosulfan, metabolites, date palm, QuEChERS, Human health, HPLC-MS/MS","lastPublishedDoi":"10.21203/rs.3.rs-5022517/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5022517/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated residual levels of carbosulfan and its metabolites in date palm fruit in the UAE using HPLC-MS/MS and QuEChERS method. The method demonstrated excellent linearity (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.998), low LOD (0.001\u0026ndash;0.04 \u0026#120583;g/kg) and LOQ (0.003-0.1 \u0026#120583;g/kg), and high recoveries (92%-103%) with low RSD values (1\u0026ndash;9%). The matrix effect was negligible (-16.43\u0026ndash;17.09%), and uncertainty measurements did not exceed the 50% limit. Carbosulfan was present in all samples, exceeding its MRL in 46% of the samples. Carbofuran and 3-hydroxycarbofuran exceeded their MRL in 4.87% and 40% of the samples, respectively, while 3-ketocarbofuran levels were below the MRL. Dibutylamine was found in 82% of the samples, with an average concentration of 9.01 \u0026micro;g/kg. The health risk assessment for children and adults showed that all HQ values were below the safety limit of 1.0, indicating that date consumption poses no adverse health risks for either adults or children.\u003c/p\u003e","manuscriptTitle":"HPLC-MS/MS Monitoring and Health Risk Assessment of Carbosulfan and its Metabolites in Date Palm Fruit (Phoenix dactylifera)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-08 07:17:53","doi":"10.21203/rs.3.rs-5022517/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-18T05:08:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-19T04:55:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"243981768226455999161326913939248799686","date":"2024-09-11T09:26:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122485501528937581178892679687794408241","date":"2024-09-11T08:36:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-11T08:31:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-11T08:27:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-09-10T13:54:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-10T06:48:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-09-03T06:49:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"56f0d3d9-043b-4b4d-ab8b-7868952ee7e9","owner":[],"postedDate":"November 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":39104536,"name":"Physical sciences/Chemistry/Analytical chemistry"},{"id":39104537,"name":"Physical sciences/Chemistry/Chemical safety"},{"id":39104538,"name":"Physical sciences/Chemistry/Environmental chemistry"}],"tags":[],"updatedAt":"2024-11-18T19:16:12+00:00","versionOfRecord":{"articleIdentity":"rs-5022517","link":"https://doi.org/10.1038/s41598-024-79871-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-11-14 15:56:58","publishedOnDateReadable":"November 14th, 2024"},"versionCreatedAt":"2024-11-08 07:17:53","video":"","vorDoi":"10.1038/s41598-024-79871-5","vorDoiUrl":"https://doi.org/10.1038/s41598-024-79871-5","workflowStages":[]},"version":"v1","identity":"rs-5022517","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5022517","identity":"rs-5022517","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}