The occurrence of pesticide residues in representative samples collected from imported dates palm fruits during 2020 to United Arab Emirates (UAE) was investigated to ensure compliance with the standard specifications and requirements by the regulatory and supervisory authorities, maintain the health and safety of consumers and improve food safety. An accurate, rapid, and reliable method for the simultaneous determination of pesticide multi-residues in 230 samples imported dates by liquid chromatography coupled with tandem mass spectrometry (LC–ESI (+)-MS/MS) operating in multiple reaction monitoring (MRM) mode and modified quick, easy, cheap, effective, rugged, safe (QuEChERS) method was used. The performance of the analytical method was validated in accordance with EU SANCO guidelines (SANTE/12682/2019) for monitoring pesticide multi-residues to check compliance with existing regulations, especially for European Community. Residues level of 343 compounds were determined in 230 samples. Results indicated that the percentage of samples with residues above the maximum residue levels (MRL) was 4.34% in dates samples, whereas samples with residues within MRL were 7.39% in dates samples. A total of 230 samples of 88.26% were free from detectable residues. Out of the 343 pesticides tested, 11 pesticides were found above the limit of detection, according to UAE, Codex, and European regulations. The main purpose of this work is to inform citizens and traders who have concerns about food safety on the capability of the MOCCAE on quality assurance regarding pesticide residue in imported food.

Food contamination with pesticide residues is a serious concern. In United Arab Emirates, ministry of climate change and environment (MOCCAE) carries out incidence/level monitoring in order to acquire data on the presence and amounts of pesticide residues in particular commodity/chemical combinations. This monitoring aimed to provide the necessary information on quantitative and qualitative pesticide multiresidues in imported legume crops. Sampling plan of 2375 selected legume imported into the UAE has been examined as part of an official surveillance program, these samples include beans, peas, peanuts, lupine and lentils, they were collected from across United Arab Emirates (UAE) ports of entry during 2020 and 2021 by certified staff. These samples were analyzed by modified QuEChERS method for pesticide residue screening based on multi-reaction monitoring (MRM) mode with gas and/or liquid chromatography tandem mass spectrometry for monitoring more than 400 pesticides residues in these legume crops. The method used in this study was validated following the European Commission guidelines achieving good recovery values in the range 70–120% with relative standard deviation values lower than 20% and providing limits of quantification of the method in the low mg/kg range, in accordance with the maximum residue limits set by European policies and CODEX. The results showed that the majority (98.8%) of legume crops samples analyzed had compliance with the legislation in force in UAE and 29 samples (1.2%) contained residues above MRLs established by the Codex Committee on pesticide residues as well as by the European Union. This monitoring is a part of a surveillance study for pesticide control in food samples. Based on the results current monitoring program provide a valuable source of information for estimating dietary exposure of UAE consumers to pesticide residues, and to check compliance with the national maximum residue levels in legume samples.

This study aimed to optimize and validate a multi-residue method for identifying and quantifying pesticides in honey by using an accurate, rapid and reliable method for the simultaneous determination of 101 pesticide residues in honey by liquid chromatography coupled with tandem mass spectrometry LC–ESI (+)-MS/MS operating in multiple reaction monitoring (MRM) mode. The performance of the analytical method was validated in accordance with EU SANCO guidelines (SANTE/12682/2019). Acceptable values were obtained for the following parameters: linearity, recoveries, precision (reproducibility and repeatability) and measurement uncertainty tests (<50.0%). A highly efficient approach for determining pesticide residues in honey with good recoveries was developed. The recovery values obtained at two fortification levels: 0.01 and 0.1 mgkg−1, were 73.2% and 119.7% respectively, with an average RSD<17% for all the tested compounds. The estimated linearity measured at five concentration levels presented good correlation coefficients (r2) average 0.99, all residue contaminants were detected at acceptable MRLs.

Assessing the contamination of cereals and their manufactured products with pesticide residues is a topic of global importance, and monitoring studies are needed to analyze multiple residues at trace levels. Current study was conducted to monitor pesticide residues in various cereals (corn, oats, rice, barley, sorghum and wheat) imported into the UAE as part of official surveillance. A total of 1,440 samples were collected during 2020 and 2021. Modified QuEChERS method for pesticide residue screening based on multi-reaction monitoring (MRM) mode with advanced gas and/or liquid chromatography tandem mass spectrometry were optimized for monitoring 400 pesticides residues in cereals, and the method was validated for oats, rice, barley and corn matrices, following the European Commission guidelines achieving good recovery values in the range 70–120% with relative standard deviation values lower than 20% and providing limits of quantification of the method in the low mg/kg range, in accordance to the maximum residue limits set by European policies and CODEX. Results from monitoring showed that among the Cereals Grains samples, 903 samples (62.7%) were free from detectable residues, while 419 samples (29.09%) contained residues and 121 samples (8.4%) had residues exceeded the MRLs allowed by the EU legislation and/or COEDX. Tricyclazole, Thiamethoxam, Carbendazim and Buprofesin were the most frequently detected exceeded the MRLs in samples.