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Agricultural products, such as foodstuffs and herbal medicines, may be contaminated by pesticides. Therefore, developing sensitive methods for pesticide detection are urgently needed for the assurance of food safety. In this study, a ratiometric fluorescent sensing system based on blue-emitted nitrogen-doped carbon quantum dots (N-CQDs) and red-emitted copper nanoclusters (CuNCs) complex was fabricated for pesticide detection. The selective detection of thiram and paraquat, two typical widely used pesticides, can be easily realized by changing the solvent environment. The detection limit can be reached as low as 7.49 nM and 3.03 nM, respectively. A good linear correlation was found over the concentration range from 10 to 500 nM for thiram and 5 to 100 nM for paraquat. More interestingly, fast and visual detection of thiram and paraquat can be achieved via smartphone-based colorimetric analysis, which has provided an effective implementation for on-site monitoring of the levels of pesticide residues in food.

The aim of this study was to evaluate the combination of fatty acid profile and fatty acid δ

The aim of this study was to evaluate the combination of fatty acid profile and fatty acid δ13C fingerprinting to identify the origins of scallops. Fatty acid contents, as well as fatty acid δ13C values of 300 samples of three scallop species (Patinopecten yessoensis, Chlamys farreri, and Argopecten irradians) from seven sites in China were determined. Principal component analysis was performed on datasets to evaluate their performance of classification. Moreover, 75 samples were tested by discrimination analysis to estimate the accuracy of origin prediction. The results show that the accuracy rate of fatty acid profile and fatty acid δ13C fingerprinting for origin prediction was 92% and 85.3%, respectively. The combination of these two methods improved the identification, with an accuracy rate of 100.0%. These results indicate that the combination of fatty acid profile and fatty acid δ13C fingerprinting can be a precise and promising tool for origin traceability of scallops.

Traceability and authenticity is crucial to the food safety of scallop. The present study investigated the possibility of using stable isotope analysis to identify the origins and species of scallops (Patinopecten yessoensis, Chlamys farreri, and Argopecten irradians) in the coastal areas of China. The δ13C and δ15N values of a total of 575 samples from seven sites around China were determined and additional 150 samples were tested by fisher linear discrimination analysis (LDA) to estimate the accuracy of origin identification and species prediction. The results show that the stable C and N isotope composition differed significantly depending on the origin, season and species of scallops. Meanwhile, the LDA shows that 92% of the samples were correctly classified for origin prediction, and an accuracy of 98.3% was obtained for species prediction. This study reveals that stable isotope ratio is an effective technique to trace the geographical origin and identify the species of scallops.