A sensitive and effective method, using gas chromatography (GC) and an electron capture detector (ECD), for the simultaneous quantitative determination of bifenthrin, chlorothalonil, cyfluthrin, cypermethrin, difenoconazole, fenvalerate, procymidone and pyridaben residues in cowpea was developed and validated. The method involved extracting with acetonitrile, purification with a graphitized carbon black/amino solid phase extraction cartridge, and then determining by GC–ECD. Recovery studies were carried out at three spiked levels (0.01, 0.1 and 0.5 mg/kg). The average recoveries at the three spiked levels ranged from 76.6 to 107.0% with relative standard deviations in the range of 1.2–5.6% for all analytes. The quantification limit was 0.01 mg/kg for each pesticide and was less than or equal to the relevant MRLs set by China, the Codex Alimentarius or the European Union. The developed analyzing method was convenient, time and cost saving, environment-friendly and readily available than the traditional methods.

The nutritional quality of bananas and their geographical origin authenticity are very important for trade. There is an urgent need for rapid, non-destructive testing to improve the origin and quality assurance for importers, distributors, and consumers. In this study, 99 banana samples from a range of producing countries were collected. Hyperspectral data were combined with chemometric methods to construct quantitative and qualitative models for bananas, predicting soluble solids content (SSC), potassium content (K), and country of origin. A second derivative analysis combined with competitive adaptive weighted sampling (CARS) and random frog jumping (RF) was selected as the best pre-treatment method for the prediction of SSC and K content, respectively. Partial least squares (PLS) models achieved R²_p values of 0.8012 and 0.8606 for SSC and K content, respectively. Chinese domestic and imported bananas were classified with a prediction accuracy of 95.83% using partial least squares-discriminant analysis (PLS-DA) and an RF method that screened the spectral variables after a second pretreatment. These results showed that hyperspectral imaging technology could be effectively used to non-destructively predict the nutrient contents of bananas and identify their geographical origin. In the future, this technology can be applied to determine the nutritional quality composition and geographical origin of bananas from other countries.