Development and validation of an analytical methodology based on solvent extraction and gas chromatography for determining pesticides in royal jelly and propolis

We propose a new analytical methodology to determine seven pesticides (atrazine, chlorpyrifos, chlorfenvinphos, α-endosulfan, bromopropylate, coumaphos, and τ-fluvalinate) in royal jelly and propolis products using gas chromatography-mass spectrometry. Sample treatment, with minor modifications for propolis, consisted of a solvent extraction with a hexane and isopropanol mixture, and a further clean-up step. Meanwhile, chromatographic analysis (<25 min) was performed in a DB-5MS column under programmed temperature conditions. In all cases we validated the method in terms of selectivity, limits of detection (0.1-2.8 μg kg-1) and quantification (0.3-9.2 μg kg-1), linearity, matrix effect (<±20 %), trueness (recoveries between 93 % and 118 %), and precision (relative standard deviation < 11 %). All royal jelly liquid dietary supplements were positive for chlorfenvinphos and, in the case of one of them, for α-endosulfan; chlorfenvinphos was determined in some fresh royal jelly samples, and no pesticide residues were detected in the propolis samples analysed.

Free amino acid profile in Mimosa scabrella honeydew honey from Brazil and chemometric analysis for geographical discrimination

In this study, twenty free amino acids (FAA) were investigated in samples of bracatinga (Mimosa scabrella) honeydew honey (BHH) from Santa Catarina (n = 15) and Paraná (n = 13) states (Brazil), followed by chemometric analysis for geographic discrimination. The FAA determination was performed by gas chromatography-mass spectrometry (GC-MS) after using a commercial EZ:faast™ kits for GC. Eight FAA were determined, being proline, asparagine, aspartic and glutamic acids found in all BHH, with significant differences (p < 0.05). In addition, with the exception of proline, the others FAA (asparagine, aspartic and glutamic) normally showed higher concentrations in samples from Santa Catarina state, being that in these samples it was also observed higher FAA sums (963.41 to 2034.73 mg kg-1) when compared to samples from Paraná state. The variability in the results did not show a clear profile of similarity when the heatmap and hierarchical grouping were correlated with the geographic origin and the concentration of eight determined FAA. However, principal component analysis (PCA) demonstrated that serine, asparagine, glutamic acid, and tryptophan were responsible for the geographic discrimination among samples from Santa Catarina and Paraná states, since they were the dominant variables (r > 0.72) in the PCA. Therefore, these results could be useful for the characterization and authentication of BHH based on their FAA composition and geographic origin.

Contamination of Honeybee (Apis mellifera L.) Royal Jelly by Pesticides and Sample Preparation Methods for Its Determination: A Critical Appraisal

Pesticides can easily enter the food chain, harming bee populations and ecosystems. Exposure of beehive products to various contaminants has been identified as one of the factors contributing to the decline in bee populations, and multiple food alerts have been reported. Despite this fact, royal jelly, a valuable bee product with nutritional and functional properties, has received less attention in this context. Pesticide residues of different chemical class can contaminate royal jelly when foraging bees collect pollen or nectar from pesticide-treated flowers, or in some cases, due to its frequent and inappropriate use in the treatment of mites in beehives. To monitor this issue and also make it more reliable, it is crucial to develop effective sample preparation methods for extracting pesticides from royal jelly for subsequent analysis. In this context, this review provides information about sample preparation methods (solid-phase extraction, solvent extraction, and QuEChERS-quick, easy, cheap, effective, rugged and safe) and analytical methods that have been validated or improved to extract and analyze pesticides, respectively, in royal jelly samples of different origins. Finally, future perspectives are discussed. With this background, we aim to provide data that can guide future research related to this topic.

Determination of acaricides in honeys from different botanical origins by gas chromatography-mass spectrometry

An analytical method has been proposed and validated to determine seven acaricides (atrazine, chlorpyrifos, chlorfenvinphos, α-endosulfan, bromopropylate, coumaphos, and τ-fluvalinate) in honeys from different botanical origins (multifloral, heather and rosemary) by means of gas chromatography-mass spectrometry. An efficient and simple sample treatment was proposed that involved a solvent extraction with an ethyl acetate and cyclohexane (50:50, v/v) mixture. Chromatographic analysis (<25 min) was performed in a DB-5MS column under programmed temperature conditions. The method was validated in terms of selectivity, limits of detection (0.2-2.0 µg kg^-1) and quantification (0.5-7.6 µg kg^-1), linearity (limit of quantification-700 (heather) or 800 (multifloral and rosemary) µg kg^-1), matrix effect (<20 % in most cases), trueness (recoveries between 81 % and 108 %), and precision (relative standard deviation < 15 %). Finally, of the seven acaricides investigated in several honey samples only τ-fluvalinate residues (<limit of quantification - 23 µg kg^-1) were found.

Development and Validation of a Gas Chromatography-Mass Spectrometry Method for Determining Acaricides in Bee Pollen

Pesticides can be found in beehives for several reasons, including contamination from surrounding crops or for their use by beekeepers, which poses a risk to bee ecosystems and consumers. Therefore, efficient and sensitive methods are needed for determining pesticide residues in bee products. In this study, a new analytical method has been developed and validated to determine seven acaricides (atrazine, chlorpyrifos, chlorfenvinphos, α-endosulfan, bromopropylate, coumaphos, and τ-fluvalinate) in bee pollen using gas chromatography coupled to mass spectrometry. After an optimization study, the best sample treatment was obtained when using a modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method employing an ethyl acetate and cyclohexane as the extractant mixture, and a mixture of salts for the clean-up step. A chromatographic analysis (<21 min) was performed in an Agilent DB-5MS column, and it was operated under programmed temperature conditions. The method was fully validated in terms of selectivity, limits of detection (0.2–3.1 µg kg−1) and quantification (0.6–9.7 µg kg−1), linearity, matrix effect (<20% in all cases), trueness (recoveries between 80% and 108%), and precision. Finally, the proposed method was applied to analyze commercial bee pollen samples, and some of the target pesticides (chlorfenvinphos, α-endosulfan, coumaphos, and τ-fluvalinate) were detected.

MONITORING CHANGES IN THE VOLATILE FRACTION OF ROASTED NUTS AND SEEDS BY USING COMPREHENSIVE TWO-DIMENSIONAL GAS CHROMATOGRAPHY AND MATRIX TEMPLATES

Static headspace coupled with comprehensive two-dimensional gas chromatography and a flame ionization detector (HS-GC × GC-FID), has been applied to monitor changes in the volatile fraction of commercial edible nuts and seeds (peanuts, almonds, hazelnuts, and sunflower seeds). Effects of the roasting conditions (time, 5-40 min; temperature, 150-170 °C), which were employed under different combinations by using a ventilated oven, on target volatile fraction were examined to identify potential differences in relation to the roasting treatment of raw samples. In addition, reference templates were created, from the HS-GC × GC-FID method, for each of the four food matrices analyzed, and they were applied to characterize the samples according to the presence or absence of volatile compounds. Finally, these templates were successfully employed to make a quick distinction between different roasting conditions.•HS-GC × GC-FID was applied to study the volatile profile of edible nuts and seeds.•Reference templates (GC × GC-FID) were created for each of the four food matrices.•Rapid discrimination between raw and roasted samples was achieved.