Detection And Analysis Of Pesticide Residues Of Procymidone In Edible Vegetable Oil Based On Near Infrared Spectroscopy

With the developing of Chinese agriculture, the amount of pesticides applied is increasing, at the same time,the pesticide poisoning incidents occur frequently. The edible vegetable oil is a necessity for human survival, so explore the quickly and nondestructive detection of pesticide residues in edible vegetable oil is of great significance.In this research, refer to the regulations in “Food safety national standards of pesticide maximum residue in food”, the maximum residue limits of procymidone pesticides in edible vegetable oil is 0.5mg/kg, so near infrared spectral analysis technology combined with chemometrics methods was used to exploratory the pesticide residue detection method in edible vegetable oil. Pesticide procymidone was used as the research object, and the Golden dragon fish soybean oil, the Daodaoquan soybean oil, the Five lake soybean oil,the Fulinmen soybean oil, the Golden dragon fish peanut oil, the Jinding peanut oil, the Fulinmen peanut oil, the Luhua peanut oil, the Business days rapeseed oil, the Daodaoquan rapeseed oil, the Golden dragon fish rapeseed oil, the Aoxing rapeseed oil, a total of 12 kinds of edible vegetable oil were chose for represent, carried out of research.For qualitative discrimination, the edible vegetable oil samples which containing procymidone pesticide concentration between 0-0.4mg/kg were classified as category 0;and the samples which containing procymidone pesticide concentration between1-1000mg/kg were classified as category 1. The qualitative analysis model developed with different qualitative identification method, different wavelengths, different pretreatment methods for all kinds of edible vegetable oil were compared. The LDA model without pretreatment is the best qualitative identification method for edible vegetable oil. The optimal wavelength range of qualitative discriminant model for peanut oil samples is350~1800 nm, the calibration accuracy is 100%, and the prediction accuracy is 94.74%.The optimal wavelength range of qualitative discriminant model for soybean oil samples is500~1650 nm, the calibration accuracy is 100%, and the prediction accuracy is 100%. The optimal wavelength range of qualitative discriminant model for rapeseed oil samples are750~1150 nm,1250~1350 nm,1500~1700 nm, the calibration accuracy is 100%, and the prediction accuracy is 100%.For quantitative analysis, the real value of procymidone pesticide concentration in each samples was calculated, then the quantitave analysis models developed with different qualitative identification method, different wavelengths, different pretreatment methods for all kinds of edivle vegetable oil were compared. PLS is the best quantitative correction methods for edible vegetable oil. Without pretreatment, the optimal wavelenth range of quantitative analysis model for peanut oil samples is 550~1650nm, the RMSEC is96.654961, the R2 of calibration is 0.9116384, the RMSEP is 75.870956, the R2 ofprediction is 0.92421. With MA pretreatment, the optimal wavelength range of quantitative analysis model for soybean oil samples is 600~1600nm, the RMSEC is 85.50515, the R2 of calibration is 0.9329157, the RMSEP is 57.115135, R2 of prediction is 0.9564602.Without pretreatment, the optimal wavelength range of quantitative analysis model for rapeseed oil samples are 800~1150nm and 1500~1700nm, the RMSEC is 178.48836, the R2 of calibration is 0.7078086, the RMSEP is 113.42947, the R2 of prediction is0.8288952。...