Rapid Determination of Prochloraz in Orange Juice by Near-Infrared Spectroscopy

Detection of Profenofos in Chinese Kale, Cabbage, and Chili Spur Pepper Using Fourier Transform Near-Infrared and Fourier Transform Mid-Infrared Spectroscopies

Different types of quantitative technology based on infrared spectroscopy to detect profenofos were compared based on Fourier transform near-infrared (FT-NIR; 12,500-4000 cm^-1) and Fourier transform mid-infrared (FT-MIR; 4000-400 cm^-1) spectroscopies. Standard solutions in the range of 0.1-100 mg/L combined with the dry-extract system for infrared (DESIR) technique were analyzed. Based on partial least-squares regression (PLSR) to develop a calibration equation, FT-NIR-PLSR produced the best prediction of profenofos residues based on the values for R ² (0.87), standard error of prediction or SEP (11.68 mg/L), root-mean-square error of prediction or RMSEP (11.50 mg/L), bias (-0.81 mg/L), and ratio performance to deviation or RPD (2.81). In addition, FT-MIR-PLSR produced the best prediction of profenofos residues based on the values for R ² (0.83), SEP (13.10 mg/L), RMSEP (13.00 mg/L), bias (1.46 mg/L), and RPD (2.49). Based on the ease of use and appropriate sample preparation, FT-NIR-PLSR combined with DESIR was chosen to detect profenofos in Chinese kale, cabbage, and chili spur pepper at concentrations of 0.53-106.28 mg/kg. The quick, easy, cheap, effective, rugged, and safe technique coupled with gas chromatography-mass spectrometry was used to obtain the actual values. The best FT-NIR-PLSR equation provided good profenofos detection in all vegetables based on values for R ² (0.88-0.97), SEP (5.27-11.07 mg/kg), RMSEP (5.25-11.00 mg/kg), bias (-1.39 to 1.30 mg/kg), and RPD (2.91-5.22). These statistics revealed no significant differences between the FT-NIR predicted values and actual values at a confidence interval of 95%, with agreeable results presented at pesticide residue levels over 30 mg/kg. FT-NIR spectroscopy combined with DESIR and PLSR should be considered as a promising screening method for pesticide detection in vegetables.

Determination of Adenosine and Cordycepin Concentrations in Cordyceps militaris Fruiting Bodies Using Near-Infrared Spectroscopy

Near-infrared (NIRS) spectroscopy, coupled with partial least squares regression, was used to predict adenosine and cordycepin concentrations in fruiting bodies of Cordyceps militaris. The fruiting body samples were prepared in four different sample formats, which were intact fruiting bodies, chopped fruiting bodies, dried powder, and dried crude extract. The actual amount of the adenosine and cordycepin concentrations in fresh fruiting bodies was analyzed by high-performance liquid chromatography. Results showed that the prediction models developed from the chopped samples provided excellent accuracy in both parameters with minimal sample preparation. These optimum models provided a coefficient of determination of prediction, standard error of prediction, bias, and residual predictive deviation, which were respectively 0.95, 16.60 mg kg^-1, -8.57 mg kg^-1, and 5.04 for adenosine prediction, and 0.98, 181.56 mg kg^-1, -1.05 mg kg^-1, and 8.9 for cordycepin prediction. The accuracy and performance of the model were determined by ISO12099:2017(E). It was found that these two equations can be considered to be acceptable at a probability level of 95% confidence. The NIRS technique, therefore, has the potential to be an objective method for determining the adenosine and cordycepin concentrations in C. militaris fruiting bodies.

Residue Dynamics and Risk Assessment of Prochloraz and Its Metabolite 2,4,6-Trichlorophenol in Apple

The residue dynamics and risk assessment of prochloraz and its metabolite 2,4,6-trichlorophenol (2,4,6-TCP) in apple under different treatment concentrations were investigated using a GC-ECD method. The derivatization percent of prochloraz to 2,4,6-TCP was stable and complete. The recoveries of prochloraz and 2,4,6-TCP were 82.9–114.4%, and the coefficients of variation (CV) were 0.7–8.6% for the whole fruit, apple pulp, and apple peel samples. Under the application of 2 °C 2.0 g/L, 2 °C 1.0 g/L, 20 °C 2.0 g/L, and 20 °C 1.0 g/L treatment, the half-life for the degradation of prochloraz was 57.8–86.6 d in the whole fruit and apple peel, and the prochloraz concentration in the apple pulp increased gradually until a peak (0.72 mg·kg⁻¹) was reached. The concentration of 2,4,6-TCP was below 0.1 mg·kg⁻¹ in four treatment conditions and not detected (<LOD) in apple pulp. Finally, based on the detection of market samples in Hefei (China), we believe that the residual level of prochloraz in apples meets the requirements of the Chinese standards.