Study Of Rapid Detection Of Pesticide Residues In Tea Using Spectroscopy Technology

Tea is a kind of functional health drink, which is loved by people all over the world,. But the global people are also paying more attention to the problem of pesticide residue in tea. The state supervises the rational application and residue control in pesticides laxly, which lead to some problems such as pesticides residue exceeding standard in tea. In order to ensure the drink safety of consumers, it is imperative to study the method of rapid detection of pesticides residue in tea. Spectroscopy technologies have some advantages such as easy to handle, rapid detection, real-time, etc. And they have been widely used in the field of food safety. In this paper, the rapid detection methods of pesticides residue in tea were studied based on fluorescent hyperspectral image and surface-enhanced Raman spectroscopy(SERS) technolgy. The main contents are as follows:(1) Fluorescent hyperspectral image technology combined with spectral angle algorithm was used to fast and nondestructive detection of pesticide residues on fresh tea in this study. Distilling water was used to dilute the commercial carbendazim pesticide and the gradient pesticide dilution of 1: 200, 1: 500 and 1: 1000 were gained. Then the dilutions were respectively dropped on the surface of fresh tea leaves. Hyperspectral images were acquired after dried naturally using laser induced fluorescence hyperspectral device. Principal component analysis(PCA) method was used to optimize the feature wavelength and the characteristic images under 768.74 nm were extracted. Spectral angle mappe(SAM) method was used to identify the pesticide information on the leaves. The results showed that the pixels of pesticides and the pixels of leaves(1: 200) could be clearly distinguished. But for the pixels of pesticides and the the pixels of leaves(1: 500 and 1: 1000), part of the pixels on the petiole and leaf stems were mistaken for the pixels of pesticides. The study indicated that fluorescent hyperspectral image technology could be used to nondestructively and effectively detect high concentration of pesticide residues on fresh leaves. But for the low concentration needs, the detection accuracy must be further improved.(2) Surface-enhanced Raman spectroscopy(SERE) combined with the fast solvent pretreatment method was used to rapidly detect the difenoconazole residues in tea. Firstly, difenoconazole standard solution was sprayed on negative dry tea leaves, and made them dry naturally, so the tea samples containing pesticide residues were prepared. Then acetonitrile was used to extract the tea containing difenoconazole residues. Magnesium sulfate anhydrous, PSA and Nano Bamboo Charcoal(NBC) were used to remove the fluorescent materials such as chlorophyll, plant alkaloid and organic acid, etc. The dosages of PSA and NBC fillers were optimized. The results showed that Raman signals were best when PSA was 80 mg and NBC was 20 mg. The rate of recovery of this pretreatment method was 86.41%~93.61%, and the relative standard deviation(RSD) was between 2.49%~3.38%, it showed that the rate of the method for difenoconazole extraction was high. Gold colloid(OTR202) was used to enhance Raman signal. Raman spectroscopy of difenoconazole solid and SERS of its standard solution were analyzed and attributed. And six characteristic peaks of difenoconazole such as 696、808、1087、1127、1159 and 1193cm-1were identified, which could be used to qualitative and quantitative analysis the difenoconazole. Partial least squares(PLS) method was used to develop the prediction model for predicting the difenoconazole residues in tea. For the prediction set sample, the correlation coefficient and root mean square error of prediction(RMSEP) were 0.9749 and 2.98mg/kg, predict recoveries were 92.7%~106.14% and the absolute values of relative errors were below 8%. T-test result indicated that there was no significant difference between the reference values and the prediction values. The minimum detection concentration of difenoconazole standard solution was 0.2mg/L. The minimum detection concentration of difenoconazole residues in tea was below 5.0157mg/kg, and it was suitable for the state of monitoring the maximum residue limits(GB 2763-2014,10 mg/kg) of difenoconazole in tea.(3) SERE combined with the fast solvent pretreatment method was used to rapidly detect the chlorpyrifos residues in tea. It was the same way to prepared the tea samples containing pesticide residues, and the acetonitrile was used to extracted and the PSA with NBC were used to purified the samples. The rate of recovery of the optimized pretreatment method was 91.22%~96.86%, and the relative standard deviation(RSD) was between 1.77%~4.77%, it showed that the rate of the method for chlorpyrifos extraction was high. Gold colloid(OTR202) was used to enhance Raman signal. Raman spectroscopy of chlorpyrifos solid and SERS of its standard solution were analyzed and attributed. And six characteristic peaks of difenoconazole such as: 525、560、605、673、1095 and 1264cm-1, which could be used to qualitative and quantitative analysis the chlorpyrifos. Partial least squares(PLS) method was used to develop the prediction model for predicting the chlorpyrifos residues in tea. For the prediction set sample, the correlation coefficient and root mean square error of prediction(RMSEP) were 0.9838 and 1.83mg/kg, predict recoveries were 93.98%~103.95% and the absolute values of relative errors were below 7%. T-test result indicated that there was no significant difference between the reference values and the prediction values. The minimum detection concentration of chlorpyrifos standard solution was 0.5mg/L. The minimum detection concentration of chlorpyrifos residues in tea was below 8.6385mg/kg, and it wasn’t suitable for the state of monitoring the maximum residue limits(GB 2763-2014,1 mg/kg)chlorpyrifos of in tea, so the method need to be futher optimized.The research showed that the rapid detection methods of pesticides residue in tea using fluorescent hyperspectral image and SERS was feasible, the single sample only spent 20 minutes in whole process, which could be used to lay the foundation for developing the devices of the rapid detection of pesticide residues in tea.