Simultaneous detection of ten kinds of insecticide residues in honey and pollen using UPLC-MS/MS with graphene and carbon nanotubes as adsorption and purification materials

An analytical method of simultaneous detection of ten insecticide residues in honey and pollen was established. The samples were purified with QuEChERS approach using new adsorbents and analyzed with UPLC-MS/MS. The results showed that both of graphene and carbon nanotubes were highly efficient adsorbents for the dSPE clean up to eliminate coextractives in the samples, and graphene was superior to carbon nanotubes for the detection of pesticide residues in honey and pollen samples. The proposed method was used to detect pesticide residues in 25 honey samples and 30 pollen samples which were randomly collected from more than ten provinces in China. All honey samples contain 1-27 mu g/kg of chlorpyrifos residues. Only 4% of the honey samples were detected containing acetamiprid and imidacloprid, while the other seven pesticides were not detected. Chlorpyrifos residues were found in all pollen samples (5-66 mu g/kg), among which twenty percent exceeded the maximum residue limits (MRLs, 50 mu g/kg, European Commission Regulation). Most of the pollen samples containing pesticide concentrations higher than MRLs were collected from rape, followed by lotus, camellia, and rose. Besides, 36.7% and 33.3% of the pollen samples had imidacloprid and flupyradifurone higher than 5 mu g/kg. A total of 26.7% pollen samples were detected containing bifenthrin, while none of the other six pesticides were detected in pollen samples.

Automated summary

A method for simultaneous detection of ten insecticide residues in honey and pollen was developed, using graphene and carbon nanotubes as efficient adsorbents. The method was applied to detect pesticide residues in honey and pollen samples collected from various provinces in China, showing chlorpyrifos residues in all honey samples and chlorpyrifos residues exceeding maximum limits in twenty percent of pollen samples.