Tea leaf pesticide residue detection system and method based on tea leaf pretreatment

Abstract

The invention relates to the technical field of pesticide detection, and particularly discloses a tea leaf pesticide residue detection system and method based on tea leaf pretreatment, a data acquisition module is used for acquiring interferent content data influencing pesticide detection accuracy in pretreated tea leaves; by combining the content data of the interferent in the tea leaves, the pesticide residue detection accuracy influence coefficient of the tea leaves in different batches can be calculated, the data can reflect the influence degree of the interferent in the tea leaves in the current batch on the pesticide detection result, so that whether pesticide residue detection operation is carried out or not is decided, and then the detection accuracy of the pesticide residues in the tea leaves is determined by combining the data. According to the method, the actually detected data can be corrected and calculated, so that the processed pesticide residue values of different batches of tea leaves are obtained, the data are closer to the real value after being corrected, the condition and the content of pesticide residues can be truly reflected, and the accuracy of the detection result of the pesticide residues of the tea leaves is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of XX, and in particular to a tea pesticide residue detection system and method based on tea pretreatment. Background Art

[0002] The tea pesticide residue detection system is a device or system specifically used to detect the pesticide residue in tea. It can quickly and accurately detect the pesticide residue in tea, ensure the safety and quality of tea, and ensure safe production of tea.

[0003] The tea pesticide residue detection system usually uses the GC / MS detection method for detection. This method combines the advantages of gas chromatography (GC) and mass spectrometry (MS). Gas chromatography is mainly used to separate and determine the components in gases or volatile liquids, while mass spectrometry is used to determine the mass and structural information of molecules. By observing the peak shape, retention time and comparison with the standard spectrum in the mass spectrum, the type of compound present in the sample can be determined, and the relative content of the compound can be calculated based on the peak intensity in the mass spectrum. Therefore, this method is often used to monitor pesticide residues in tea.

[0004] In the prior art, the tea pesticide residue detection system is usually used for detection by GC / MS detection method. However, during the detection process, the tea leaves are usually not pretreated, and the interfering substances present in the tea leaves may interact with the pesticide molecules, resulting in low accuracy of the detection results, which cannot truly reflect the pesticide residue situation and cannot ensure the safety and quality of the tea leaves. Summary of the invention

[0005] The purpose of the present invention is to provide a tea pesticide residue detection system and method based on tea pretreatment to solve the following technical problems:

[0006] How to improve the accuracy of tea pesticide residue detection results.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A tea pesticide residue detection system and method based on tea pretreatment, the system comprising:

[0009] The data collection module is used to collect data on the content of interfering substances in pre-treated tea leaves that affect the accuracy of pesticide detection;

[0010] The data processing module is used to calculate the accuracy influence coefficient of different batches of tea pesticide residue detection based on the data collected by the data collection module;

[0011] The data evaluation module is used to compare the accuracy influence coefficients of different batches of tea pesticide residue detection with the preset influence coefficient threshold, and evaluate the accuracy of the current pesticide detection based on the comparison results;

[0012] The pesticide residue detection module is used to detect the pesticide residue values ​​of different batches of tea by GC / MS detection method when the accuracy of pesticide detection is evaluated to be high, and to calculate the pesticide residue values ​​of different batches of tea after treatment in combination with the accuracy influence coefficient of pesticide residue detection of different batches of tea, and to judge whether different batches of tea are qualified in combination with the data;

[0013] The risk analysis module is used to calculate the dispersion coefficient of the pesticide residue values ​​of all tested batches of tea, and use this data to monitor and evaluate the risks of all tested batches of tea.

[0014] Furthermore, the interference content data collected by the data collection module includes the polyphenol content, caffeine content and pigment content in the tea leaves.

[0015] Furthermore, the processing process of the data processing module includes:

[0016] By formula Calculate the influence coefficient k of the detection accuracy of the i-th batch of tea pesticide residues i ;

[0017] Among them, i is any batch of tea, df i is the content of polyphenols in the i-th batch of tea, df y is the preset polyphenol content, ss i is the content of pigment substances in the i-th batch of tea, ss y is the preset pigment content, μ is the error influence coefficient, which is set according to empirical fitting, a is any type of tea, b is the total number of types of all teas in the same batch, kf ai is the caffeine content of the a-th type of tea in the i-th batch of tea, kf 01 kf ai is the standard value of , x1 and x2 are weight coefficients.

[0018] Furthermore, the evaluation process of the data evaluation module includes:

[0019] By calculating the influence coefficient k of the detection accuracy of the i-th batch of tea pesticide residues i and the preset influence coefficient threshold k 01 Make a comparison;

[0020] If k i ≤k 01, the system judges that the accuracy influence coefficient of pesticide residue detection of this batch of tea is low, which means that the interference in this batch of tea has little effect on the pesticide residue detection results, and pesticide residue detection can be carried out;

[0021] If k i >k 01 The system determines that the accuracy influence coefficient of pesticide residue detection of this batch of tea is high, which means that the interference in this batch of tea has a great influence on the detection results of pesticide residues. It is necessary to add reasonable analytical protective agents to reduce the influence of interference.

[0022] Furthermore, the detection process of the pesticide residue detection module includes:

[0023] By formula Calculate the pesticide residue value r of the i-th batch of tea after treatment i ;

[0024] Among them, r 01 is the pesticide residue value r of the i-th batch of tea detected by GC / MS detection method 01 , wd i is the room temperature of the i-th batch of tea leaves during testing, wd y is the preset room temperature, nd i is the concentration of the i-th batch of tea in the mixed standard solution, nd y is the preset concentration, nd b nd i The standard value, f t To adjust the coefficient comparison table function, according to The influence of the range of calculated results on the pesticide residue values ​​is obtained based on testing.

[0025] Furthermore, the detection process of the pesticide residue detection module also includes:

[0026] By taking the pesticide residue value r of the i-th batch of tea after treatment i and the preset pesticide residue threshold r 01 Make a comparison;

[0027] If r i ≥r 01 , the system judges that the pesticide residue value of the batch of tea after treatment is high, indicating that the batch of tea is unqualified;

[0028] Otherwise, the system determines that the pesticide residue value of the processed batch of tea is low, indicating that the batch of tea is qualified, and further analyzes it through the risk analysis module.

[0029] Furthermore, the analysis process of the risk analysis module includes:

[0030] By formula Calculate the dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea;

[0031] Where n is the total number of all test batches, For all r i The average value of For all k i The average value of , g is the proportionality coefficient;

[0032] The dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea is compared with the preset fluctuation value threshold s 01 Make a comparison;

[0033] If s≥s 01 ,The system judged that the pesticide residue values ​​of all tested batches of tea had large fluctuations, indicating that the pesticide residue values ​​among tea samples varied greatly;

[0034] Otherwise, the system determines that the volatility of the pesticide residue values ​​of all tested batches of tea is small, which means that the difference in pesticide residue values ​​between tea samples is small, that is, the pesticide residue levels of different tea samples are relatively stable.

[0035] Furthermore, a method for detecting pesticide residues in tea leaves based on tea pretreatment comprises:

[0036] S1: Collect data on the content of interfering substances that affect the accuracy of pesticide detection in pre-treated tea leaves through a data acquisition module;

[0037] S2: Calculate the accuracy influence coefficient of different batches of tea pesticide residue detection by combining the data collected by the data acquisition module with the data processing module;

[0038] S3: Compare the accuracy influence coefficients of different batches of tea pesticide residue detection with the preset influence coefficient threshold through the data evaluation module, and evaluate the accuracy of the current pesticide detection according to the comparison results;

[0039] S4: When the accuracy of pesticide detection is evaluated to be high, the pesticide residue values ​​of different batches of tea leaves are tested by GC / MS detection method;

[0040] S5: Calculate the pesticide residue values ​​of different batches of tea leaves after treatment through the pesticide residue detection module, and make a judgment on whether the different batches of tea leaves are qualified based on the data;

[0041] S6: The risk analysis module calculates the coefficient of dispersion of the pesticide residue values ​​of all tested batches of tea, and uses this data to monitor and evaluate the risks of all tested batches of tea.

[0042] Beneficial effects of the present invention:

[0043] (1) The present invention can calculate the accuracy influence coefficient of pesticide residue detection of different batches of tea by combining the interference content data in tea. The data can reflect the degree of influence of the interference in the current batch of tea on the pesticide detection results, so as to decide whether to perform pesticide residue detection operations. After that, by combining the data, the actually detected data can be corrected and calculated to obtain the pesticide residue values ​​of different batches of tea after processing. After correction, the data will be closer to the true value and can truly reflect the situation and content of pesticide residues, thereby improving the accuracy of the tea pesticide residue detection results.

[0044] (2) The present invention calculates the accuracy influence coefficient k of the i-th batch of tea pesticide residue detection i and the preset influence coefficient threshold k 01 By comparing, through this comparison method, an accurate judgment can be made on the impact of interferences in batches of tea on the results of pesticide residue detection. The judgment result can provide data support for the detection personnel to decide whether to conduct pesticide residue detection, thereby avoiding pesticide residue detection when there are many interferences in the tea, resulting in a large difference between the test results and the actual situation, and failing to truly reflect the actual pesticide residue situation, thereby ensuring the safety and quality of the tea.

[0045] (3) The present invention calculates the pesticide residue value r of the i-th batch of tea leaves after treatment. i and the preset pesticide residue threshold r 01 Through this comparison method, combined with the preset pesticide residue value threshold, the pesticide residue value of the processed batch of tea can be accurately judged, and further judged whether the batch of tea is qualified. Moreover, since the calculation result of the pesticide residue value of the i-th batch of tea after processing is obtained by correction based on diversified data, the accuracy of the judgment result can be improved to ensure that the pesticide residue situation is truly reflected and the accuracy of the tea pesticide residue detection result is improved.

[0046] (4) The present invention compares the dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea with the preset fluctuation value threshold s 01 By making such a comparison, the difference in pesticide residue values ​​between tea samples can be judged based on the size of the discrete coefficient of the pesticide residue values ​​of all tested batches of tea. This data can reflect the pesticide residue levels of different tea samples, thereby providing additional data for reference for the staff in the pesticide residue detection of tea, further improving the accuracy of the pesticide residue detection results of tea and ensuring the safety and quality of tea.

[0047] (5) The present invention first calculates the detection accuracy influence coefficient of pesticide residues in different batches of tea leaves, and then corrects the pesticide residue value results of different batches of tea leaves, thereby obtaining the pesticide residue values ​​of different batches of tea leaves after processing. The data can reflect the real and accurate pesticide residue content, thereby improving the accuracy of the detection results of pesticide residues in tea leaves and ensuring the safety and quality of tea leaves. After that, the discrete coefficients of the pesticide residue values ​​of all the detected batches of tea leaves are calculated, which can provide additional data for analysis and further improve the accuracy of the detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described below in conjunction with the accompanying drawings.

[0049] Figure 1 It is a schematic block diagram of a tea pesticide residue detection system based on tea pretreatment in the present invention;

[0050] Figure 2 It is a flow chart of the method for detecting tea pesticide residues based on tea pretreatment in the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1 As shown, in one embodiment, the present application provides a tea pesticide residue detection system and method based on tea pretreatment, the system comprising:

[0053] The data collection module is used to collect data on the content of interfering substances in pre-treated tea leaves that affect the accuracy of pesticide detection;

[0054] The data processing module is used to calculate the accuracy influence coefficient of different batches of tea pesticide residue detection based on the data collected by the data collection module;

[0055] The data evaluation module is used to compare the accuracy influence coefficients of different batches of tea pesticide residue detection with the preset influence coefficient threshold, and evaluate the accuracy of the current pesticide detection based on the comparison results;

[0056] The pesticide residue detection module is used to detect the pesticide residue values ​​of different batches of tea by GC / MS detection method when the accuracy of pesticide detection is evaluated to be high, and to calculate the pesticide residue values ​​of different batches of tea after treatment in combination with the accuracy influence coefficient of pesticide residue detection of different batches of tea, and to judge whether different batches of tea are qualified in combination with the data;

[0057] The risk analysis module is used to calculate the dispersion coefficient of the pesticide residue values ​​of all tested batches of tea, and use this data to monitor and evaluate the risks of all tested batches of tea;

[0058] Through the above technical scheme, this embodiment provides a data acquisition module for collecting data on the content of interference substances that affect the accuracy of pesticide detection in pre-treated tea leaves. When detecting pesticide residues in tea leaves, firstly, the data processing module is combined with the data collected by the data acquisition module to calculate the accuracy influence coefficients of different batches of tea leaves. Then, the accuracy influence coefficients of different batches of tea leaves are compared with the preset influence coefficient threshold through the data evaluation module, and the accuracy of the current pesticide detection is evaluated according to the comparison result. In this process, when the accuracy of the current batch of tea leaves is evaluated to be high, the pesticide residue values ​​of different batches of tea leaves are detected by the pesticide residue detection module using the GC / MS detection method, and the pesticide residue values ​​of different batches of tea leaves are calculated in combination with the accuracy influence coefficients of different batches of tea leaves. In combination with the data, it is judged whether different batches of tea leaves are qualified.

[0059] Through such settings, the system can calculate the accuracy influence coefficient of different batches of tea pesticide residue detection by combining the interference content data in tea. This data can reflect the degree of influence of the interference in the current batch of tea on the pesticide detection results, so as to decide whether to perform the pesticide residue detection operation. After that, by combining this data, the actual detected data can be corrected and calculated to obtain the pesticide residue values ​​of different batches of tea after processing. After correction, the data will be closer to the true value, which can truly reflect the situation and content of pesticide residues, thereby improving the accuracy of the tea pesticide residue detection results;

[0060] The risk analysis module is then used to calculate the discrete coefficients of the pesticide residue values ​​of all tested batches of tea, and the data is used to monitor and evaluate the risks of all tested batches of tea. The overall risk of all batches of tea can be analyzed and evaluated, thereby providing managers with additional data for reference, further improving the accuracy of tea pesticide residue detection results, and ensuring the safety and quality of tea.

[0061] The interference content data collected by the data collection module include the polyphenol content, caffeine content and pigment content in the tea leaves;

[0062] Through the above technical solution, this embodiment provides interference content data collected by the data acquisition module, including the polyphenol content, caffeine content and pigment content in tea. These three substances have the same characteristic, that is, they are easy to interact with pesticides, thereby affecting the accuracy of tea pesticide residue detection results. Therefore, by collecting this data information, it is possible to provide accurate and reliable data support for the subsequent calculation of the tea pesticide residue detection accuracy influence coefficient and the cleaning and correction of the pesticide detection value, thereby ensuring the accuracy of tea pesticide residue detection.

[0063] The processing process of the data processing module includes:

[0064] By formula Calculate the influence coefficient k of the detection accuracy of the i-th batch of tea pesticide residues i ;

[0065] Among them, i is any batch of tea, df i is the content of polyphenols in the i-th batch of tea, df y is the preset polyphenol content, ss i is the content of pigment substances in the i-th batch of tea, ss y is the preset pigment content, μ is the error influence coefficient, which is set according to empirical fitting, a is any type of tea, b is the total number of types of all teas in the same batch, kf ai is the caffeine content of the a-th type of tea in the i-th batch of tea, kf 01 kf ai The standard value of , which can be set based on the allowable error in empirical data, x1 and x2 are weight coefficients, which can be set based on experience;

[0066] Through the above technical solution, this embodiment provides the accuracy influence coefficient k of the i-th batch of tea pesticide residue detection i , can be obtained by formula It is calculated that since pigments, polyphenols and caffeine will interact with pesticides, resulting in errors in the test results, it can be seen from the above formula that the more pigments, polyphenols and caffeine there are in the i-th batch of tea, the greater the influence coefficient of the i-th batch of tea pesticide residue detection accuracy will be, indicating that this batch of tea will be greatly affected when undergoing pesticide residue detection, resulting in a large error in the test results. Conversely, the less pigments, polyphenols and caffeine there are in the i-th batch of tea, the smaller the influence coefficient of the i-th batch of tea pesticide residue detection accuracy will be, indicating that this batch of tea will be greatly affected when undergoing pesticide residue detection, resulting in a small error in the test results. Through this calculation method, it can be reflected whether different batches of tea have a good testing environment, thereby ensuring the accuracy of the test results.

[0067] The evaluation process of the data evaluation module includes:

[0068] By calculating the influence coefficient k of the detection accuracy of the i-th batch of tea pesticide residues i And the preset influence coefficient threshold k 01 Make a comparison;

[0069] If k i ≤k 01 , the system judges that the accuracy influence coefficient of pesticide residue detection of this batch of tea is low, which means that the interference in this batch of tea has little effect on the pesticide residue detection results, and pesticide residue detection can be carried out;

[0070] If k i >k 01 The system determines that the accuracy influence coefficient of the pesticide residue detection of this batch of tea is high, which means that the interference in this batch of tea has a great influence on the pesticide residue detection results. It is necessary to add a reasonable analytical protective agent to reduce the influence of the interference;

[0071] Through the above technical solution, this embodiment is to set the accuracy influence coefficient k of the i-th batch of tea pesticide residue detection i And the preset influence coefficient threshold k 01 By comparing, the influence of the interference substances in the batch of tea on the pesticide residue test results can be accurately judged through this comparison method. The judgment result can provide data support for the test personnel to decide whether to conduct pesticide residue testing, thereby avoiding the test of pesticide residues when there are many interference substances in the tea, resulting in a large difference between the test results and the actual situation, and failing to truly reflect the actual pesticide residue situation, thereby ensuring the safety and quality of the tea;

[0072] It should be noted that the above preset influence coefficient threshold k 01 It can be set based on experience fitting.

[0073] The detection process of the pesticide residue detection module includes:

[0074] By formula Calculate the pesticide residue value r of the i-th batch of tea after treatment i ;

[0075] Among them, r 01 is the pesticide residue value r of the i-th batch of tea detected by GC / MS detection method 01 , wd i is the room temperature of the i-th batch of tea leaves during testing, wd y is the preset room temperature, nd i is the concentration of the i-th batch of tea in the mixed standard solution, nd y is the preset concentration, nd b nd i The standard value of f can be selected and set according to the allowable error in empirical data. t To adjust the coefficient comparison table function, according to The influence of the range of values ​​of the calculated results on the pesticide residue values ​​is obtained based on the test results;

[0076] Through the above technical solution, this embodiment provides the pesticide residue value r of the i-th batch of tea after treatment. i , can be obtained by formula Calculated, through this calculation method, combined with the i-th batch of tea pesticide residue detection accuracy influence coefficient k i , together with the temperature and concentration of the mixed standard solution during the test, the pesticide residue value r of the i-th batch of tea detected by the GC / MS test method can be 01 Correction is made so that the calculated pesticide residue value r of the i-th batch of tea after treatment is i It is closer to the true value, so that the data can more accurately and truly reflect the pesticide residue content in the i-th batch of tea, which is convenient for staff to analyze the data and improve the accuracy of the tea pesticide residue detection results.

[0077] The detection process of the pesticide residue detection module also includes:

[0078] By taking the pesticide residue value r of the i-th batch of tea after treatment i and the preset pesticide residue threshold r 01 Make a comparison;

[0079] If r i ≥r 01 , the system judges that the pesticide residue value of the batch of tea after treatment is high, indicating that the batch of tea is unqualified;

[0080] Otherwise, the system determines that the pesticide residue value of the processed batch of tea is low, indicating that the batch of tea is qualified, and further analyzes it through the risk analysis module;

[0081] Through the above technical solution, this embodiment calculates the pesticide residue value r of the i-th batch of tea leaves after treatment. i and the preset pesticide residue threshold r 01 By comparing, through this comparison method, after combining with the preset pesticide residue value threshold, it is possible to make an accurate judgment on the pesticide residue value of the processed batch of tea, and further judge whether the batch of tea is qualified, and because the calculation result of the pesticide residue value of the i-th batch of tea after processing is obtained by correction in combination with diversified data, the accuracy of the judgment result can be improved to ensure that the pesticide residue situation is truly reflected, and the accuracy of the tea pesticide residue detection result is improved;

[0082] It should be noted that the above preset pesticide residue threshold r 01 It can be set based on experience fitting.

[0083] The analysis process of the risk analysis module includes:

[0084] By formula Calculate the dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea;

[0085] Where n is the total number of all test batches, For all r i The average value of For all k i The average value of , g is the proportionality coefficient;

[0086] The dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea is compared with the preset fluctuation value threshold s 01 Make a comparison;

[0087] If s≥s 01 ,The system judged that the pesticide residue values ​​of all tested batches of tea had large fluctuations, indicating that the pesticide residue values ​​among tea samples varied greatly;

[0088] Otherwise, the system judges that the volatility of the pesticide residue values ​​of all tested batches of tea is small, which means that the difference in the pesticide residue values ​​between tea samples is small, that is, the pesticide residue levels of different tea samples are relatively stable;

[0089] Through the above technical solution, this embodiment provides the dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea, which can be calculated by the formula Calculate and compare the dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea with the preset fluctuation value threshold s01 By making such a comparison, the difference in pesticide residue values ​​between tea samples can be judged according to the size of the dispersion coefficient of the pesticide residue values ​​of all tested batches of tea. This data can reflect the pesticide residue levels of different tea samples, thereby providing additional data for reference for the staff in the pesticide residue detection of tea, further improving the accuracy of the tea pesticide residue detection results, and ensuring the safety and quality of tea.

[0090] It should be noted that the above preset fluctuation value threshold s 01 It can be set based on experience fitting.

[0091] See also Figure 2 As shown, a method for detecting pesticide residues in tea leaves based on tea pretreatment, the method comprising:

[0092] S1: Collect data on the content of interfering substances that affect the accuracy of pesticide detection in pre-treated tea leaves through a data acquisition module;

[0093] S2: Calculate the accuracy influence coefficient of different batches of tea pesticide residue detection by combining the data collected by the data acquisition module with the data processing module;

[0094] S3: Compare the accuracy influence coefficients of different batches of tea pesticide residue detection with the preset influence coefficient threshold through the data evaluation module, and evaluate the accuracy of the current pesticide detection based on the comparison results;

[0095] S4: When the accuracy of pesticide detection is evaluated to be high, the pesticide residue values ​​of different batches of tea leaves are tested by GC / MS detection method;

[0096] S5: Calculate the pesticide residue values ​​of different batches of tea leaves after treatment through the pesticide residue detection module, and make a judgment on whether the different batches of tea leaves are qualified based on the data;

[0097] S6: Calculate the dispersion coefficient of the pesticide residue values ​​of all tested batches of tea through the risk analysis module, and use the data to monitor and evaluate the risks of all tested batches of tea;

[0098] Through the above technical scheme, this embodiment provides a method for detecting pesticide residues in tea leaves based on tea pretreatment, firstly, the data of the content of interference substances affecting the accuracy of pesticide detection in the pretreated tea leaves is collected through the data acquisition module, when the tea leaves are subjected to pesticide residue detection, the accuracy influence coefficients of pesticide residue detection of different batches of tea leaves are calculated by the data processing module in combination with the data collected by the data acquisition module, and then the accuracy influence coefficients of pesticide residue detection of different batches of tea leaves are compared with the preset influence coefficient threshold value through the data evaluation module, and the accuracy of the current pesticide detection is evaluated according to the comparison result, and then when the accuracy of the pesticide detection is evaluated to be high, the pesticide residue values ​​of different batches of tea leaves are detected by the GC / MS detection method, and the pesticide residue values ​​of different batches of tea leaves after treatment are calculated by the pesticide residue detection module, and the different batches of tea leaves are judged to be qualified in combination with the data, and finally the discrete coefficients of the pesticide residue values ​​of all detected batches of tea leaves are calculated by the risk analysis module, and the risks of all detected batches of tea leaves are monitored and evaluated in combination with the data;

[0099] With such an arrangement, when conducting tea pesticide residue detection, by first calculating the detection accuracy influence coefficient of tea pesticide residue of different batches, the pesticide residue value results of different batches of tea can be corrected subsequently, so as to obtain the pesticide residue values ​​of different batches of tea after processing. This data can reflect the true and accurate pesticide residue content, thereby improving the accuracy of tea pesticide residue detection results and ensuring the safety and quality of tea. Afterwards, the discrete coefficients of pesticide residue values ​​of all tested batches of tea are calculated, which can provide additional data for analysis and further improve the accuracy of the detection results.

[0100] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A tea pesticide residue detection system based on tea pretreatment, It is characterized in that The system comprises: The data collection module is used to collect data on the content of interfering substances in pre-treated tea leaves that affect the accuracy of pesticide detection; The data processing module is used to calculate the accuracy influence coefficient of different batches of tea pesticide residue detection based on the data collected by the data collection module; The data evaluation module is used to compare the accuracy influence coefficients of different batches of tea pesticide residue detection with the preset influence coefficient threshold, and evaluate the accuracy of the current pesticide detection based on the comparison results; The pesticide residue detection module is used to detect the pesticide residue values ​​of different batches of tea by GC / MS detection method when the accuracy of pesticide detection is evaluated to be high, and to calculate the pesticide residue values ​​of different batches of tea after treatment in combination with the accuracy influence coefficient of pesticide residue detection of different batches of tea, and to judge whether different batches of tea are qualified in combination with the data; The risk analysis module is used to calculate the dispersion coefficient of the pesticide residue values ​​of all tested batches of tea, and use this data to monitor and evaluate the risks of all tested batches of tea.

2. A tea pesticide residue detection system based on tea pretreatment according to claim 1, It is characterized in that The interference content data collected by the data collection module include the polyphenol content, caffeine content and pigment content in the tea leaves.

3. A tea pesticide residue detection system based on tea pretreatment according to claim 1, It is characterized in that The processing process of the data processing module includes: By formula Calculate the influence coefficient k of the detection accuracy of the i-th batch of tea pesticide residues i ; Among them, i is any batch of tea, df i is the content of polyphenols in the i-th batch of tea, df y is the preset polyphenol content, ss i is the content of pigment substances in the i-th batch of tea, ss y is the preset pigment content, μ is the error influence coefficient, which is set according to empirical fitting, a is any type of tea, b is the total number of types of all teas in the same batch, kf ai is the caffeine content of the a-th type of tea in the i-th batch of tea, kf 01 kf ai is the standard value of , x1 and x2 are weight coefficients.

4. A tea pesticide residue detection system based on tea pretreatment according to claim 3, It is characterized in that The evaluation process of the data evaluation module includes: By calculating the influence coefficient k of the detection accuracy of the i-th batch of tea pesticide residues i And the preset influence coefficient threshold k 01 Make a comparison; If k i ≤k 01 , the system judges that the accuracy influence coefficient of pesticide residue detection of this batch of tea is low, which means that the interference in this batch of tea has little effect on the pesticide residue detection results, and pesticide residue detection can be carried out; If k i >k 01 The system determines that the accuracy influence coefficient of pesticide residue detection of this batch of tea is high, which means that the interference in this batch of tea has a great influence on the detection results of pesticide residues. It is necessary to add reasonable analytical protective agents to reduce the influence of interference.

5. A tea pesticide residue detection system based on tea pretreatment according to claim 4, It is characterized in that The detection process of the pesticide residue detection module includes: By formula Calculate the pesticide residue value r of the i-th batch of tea after treatment i ; Among them, r 01 is the pesticide residue value r of the i-th batch of tea detected by GC / MS detection method 01 , wd i is the room temperature of the i-th batch of tea leaves during testing, wd y is the preset room temperature, nd i is the concentration of the i-th batch of tea in the mixed standard solution, nd y is the preset concentration, nd b nd i The standard value of f t To adjust the coefficient comparison table function, according to The influence of the range of calculated results on the pesticide residue values ​​is obtained based on testing.

6. A tea pesticide residue detection system based on tea pretreatment according to claim 5, It is characterized in that The detection process of the pesticide residue detection module also includes: By taking the pesticide residue value r of the i-th batch of tea after treatment i and the preset pesticide residue threshold r 01 Make a comparison; If r i ≥r 01 , the system judges that the pesticide residue value of the batch of tea after treatment is high, indicating that the batch of tea is unqualified; Otherwise, the system determines that the pesticide residue value of the processed batch of tea is low, indicating that the batch of tea is qualified, and further analyzes it through the risk analysis module.

7. A tea pesticide residue detection system based on tea pretreatment according to claim 6, It is characterized in that The analysis process of the risk analysis module includes: By formula Calculate the dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea; Where n is the total number of all test batches, For all r i The average value of For all k i The average value of , g is the proportionality coefficient; The dispersion coefficient s of the pesticide residue values ​​of all tested batches of tea is compared with the preset fluctuation value threshold s 01 Make a comparison; If s≥s 01 ,The system judged that the pesticide residue values ​​of all tested batches of tea had large fluctuations, indicating that the pesticide residue values ​​among tea samples varied greatly; Otherwise, the system determines that the volatility of the pesticide residue values ​​of all tested batches of tea is small, which means that the difference in pesticide residue values ​​between tea samples is small, that is, the pesticide residue levels of different tea samples are relatively stable.

8. A method for detecting tea pesticide residues based on tea pretreatment, the method using a tea pesticide residue detection system based on tea pretreatment as described in claims 1-7, It is characterized in that The method comprises: S1: Collect data on the content of interfering substances that affect the accuracy of pesticide detection in pre-treated tea leaves through a data acquisition module; S2: Calculate the accuracy influence coefficient of different batches of tea pesticide residue detection by combining the data collected by the data acquisition module with the data processing module; S3: Compare the accuracy influence coefficients of different batches of tea pesticide residue detection with the preset influence coefficient threshold through the data evaluation module, and evaluate the accuracy of the current pesticide detection based on the comparison results; S4: When the accuracy of pesticide detection is evaluated to be high, the pesticide residue values ​​of different batches of tea leaves are tested by GC / MS detection method; S5: Calculate the pesticide residue values ​​of different batches of tea leaves after treatment through the pesticide residue detection module, and make a judgment on whether the different batches of tea leaves are qualified based on the data; S6: The risk analysis module calculates the coefficient of dispersion of the pesticide residue values ​​of all tested batches of tea, and uses this data to monitor and evaluate the risks of all tested batches of tea.

Images