Sampling method and system for agricultural product detection

Abstract

The invention is suitable for the technical field of agricultural product detection, and provides a sampling method and system for agricultural product detection, and the method comprises the following steps: receiving agricultural product types, agricultural product producing areas, planting modes and agricultural product quantity, and determining conventional detection information; calling a pesticide use condition, and determining first additional detection information according to the pesticide use condition; therefore, the first additional detection information considers the influence of the pesticide use condition on the quality and safety of agricultural products. Besides, keywords for retrieval can be automatically determined, retrieval is performed according to the keywords to determine the corresponding agricultural product network public opinion information, and the second additional detection information is determined, so that the second additional detection information considers the network public opinion information, and the qualified detection result can timely eliminate the concern of consumers and maintain the reputation of good agricultural products. The detection result obtained by the invention can comprehensively reflect the actual condition of the agricultural product, and is comprehensive in consideration, high in flexibility and strong in pertinence.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural product detection, and in particular to a sampling method and system for agricultural product detection. Background Art

[0002] In the process of agricultural product production and sales, quality and safety are crucial links. In order to ensure the quality and safety of agricultural products, agricultural product testing has become an indispensable link. Traditional agricultural product sampling and testing methods are often based on fixed testing items and sampling ratios, lacking flexibility and pertinence. With the continuous development of agricultural production, the types, origins, planting methods and pesticide use of agricultural products are becoming increasingly diversified. Traditional sampling and testing methods can no longer meet the current needs of agricultural product quality and safety testing. In addition, with the popularization of the Internet, the impact of agricultural product network public opinion information on agricultural product quality and safety is becoming increasingly significant. Traditional sampling and testing methods lack consideration of network public opinion information, resulting in the test results may not be able to reflect the reputation of agricultural products in a timely manner, and cannot dispel consumers' concerns. Therefore, it is necessary to provide a sampling method and system for agricultural product testing to solve the above problems. Summary of the invention

[0003] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a sampling method and system for agricultural product testing to solve the problems existing in the above-mentioned background technology.

[0004] The present invention is implemented as follows: a sampling method for agricultural product detection, the method comprising the following steps:

[0005] Receive the types of agricultural products, origins of agricultural products, planting methods and quantities of agricultural products, and determine routine testing information. Routine testing information includes several testing items, and each testing item has a corresponding sampling ratio;

[0006] Retrieving the pesticide usage situation, and determining the first additional testing information according to the pesticide usage situation, wherein the first additional testing information includes a plurality of testing items, and each testing item corresponds to a sampling ratio;

[0007] Determine keywords, search and determine corresponding agricultural product network public opinion information based on the keywords, and determine second additional testing information, where the second additional testing information includes several testing items, and each testing item corresponds to a sampling ratio;

[0008] The sampling information is determined according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information. The sampling information includes several sampling groups, and each sampling group corresponds to a detection item and a sampling quantity.

[0009] As a further solution of the present invention: the step of determining the conventional detection information specifically includes:

[0010] Input the types of agricultural products, their origins and planting methods into the regular sampling project database for matching;

[0011] Output several test items and corresponding sampling ratios, and determine routine test information based on the test items and sampling ratios.

[0012] As a further solution of the present invention: the step of determining the first additional detection information according to the pesticide usage situation specifically includes:

[0013] Retrieve the pesticide type and corresponding dosage D from the pesticide usage information;

[0014] Determine the corresponding test items according to the type of pesticide, and determine the toxicity level E and residual concentration coefficient K of each pesticide;

[0015] The residual risk score R of each pesticide is calculated, R=D×E×K, and the sampling ratio of the corresponding test items is determined according to the residual risk score R to obtain the first additional test information.

[0016] As a further solution of the present invention: the step of determining keywords, searching and determining corresponding agricultural product network public opinion information according to the keywords, and determining the second additional detection information specifically includes:

[0017] Determine keywords based on the types of agricultural products, their origins, and their planting methods, and determine the online public opinion information on agricultural products based on web crawler technology and keywords;

[0018] Retrieve food safety incidents and public opinion heat from agricultural product online public opinion information, and extract the causes and severity of food safety;

[0019] The testing items are determined based on food safety reasons, and the corresponding sampling ratio is determined based on the heat and severity of public opinion to obtain the second additional testing information.

[0020] As a further solution of the present invention: the step of determining the sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information specifically includes:

[0021] Summarize the conventional test information, the first additional test information, and the second additional test information. When multiple test items are repeated, only the one with the highest sampling ratio is retained;

[0022] Determine the number of random inspections for each inspection item based on the number of agricultural products and the random inspection ratio;

[0023] Arrange all the test items in descending order according to the number of random inspections, create a new sampling group, and move the first-ranked test item in the arrangement to the sampling group;

[0024] The detection items moved to the sampling group are deleted from the arrangement, and the detection items ranked first in the updated arrangement are moved to the existing sampling group or a new sampling group is created. This step is repeated until all detection items are moved.

[0025] As a further solution of the present invention: the step of moving the first-ranked detection item in the updated arrangement to an existing sampling group or creating a new sampling group specifically includes:

[0026] Inputting the first-ranked test item in the updated arrangement and the test items of the existing sampling group into the item conflict library;

[0027] Output the existing sampling groups that do not conflict with the first-ranked detection item. When the number of the output existing sampling groups is greater than zero, randomly move the detection items to the output existing sampling groups; when the number of the output existing sampling groups is zero, create a new sampling group.

[0028] Another object of the present invention is to provide a sampling system for agricultural product detection, the system comprising:

[0029] The routine testing information module is used to receive the types of agricultural products, the origin of agricultural products, the planting methods and the quantity of agricultural products, and determine the routine testing information. The routine testing information includes several testing items, and each testing item corresponds to a sampling ratio;

[0030] A first additional detection module is used to retrieve the pesticide usage situation and determine the first additional detection information according to the pesticide usage situation. The first additional detection information includes a number of detection items, and each detection item corresponds to a sampling ratio;

[0031] The second additional detection module is used to determine keywords, search and determine corresponding agricultural product network public opinion information according to the keywords, and determine second additional detection information. The second additional detection information includes several detection items, and each detection item corresponds to a sampling ratio;

[0032] The sampling information determination module is used to determine the sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information, wherein the sampling information includes several sampling groups, each sampling group corresponding to a detection item and a sampling quantity.

[0033] As a further solution of the present invention: the first additional detection module includes:

[0034] A pesticide information retrieval unit, used to retrieve the pesticide type and corresponding usage dosage D in the pesticide usage information;

[0035] The toxicity concentration coefficient unit is used to determine the corresponding test items according to the type of pesticide, and determine the toxicity level E and residual concentration coefficient K of each pesticide;

[0036] The residual risk scoring unit is used to calculate the residual risk score R of each pesticide, R=D×E×K, determine the sampling ratio of the corresponding test item according to the residual risk score R, and obtain the first additional test information.

[0037] As a further solution of the present invention: the second additional detection module includes:

[0038] Network public opinion information unit, used to determine keywords based on agricultural product types, agricultural product origins and planting methods, and to determine agricultural product network public opinion information based on web crawler technology and keywords;

[0039] Public opinion information analysis unit, used to retrieve food safety events and public opinion heat from agricultural product network public opinion information, and extract the causes and severity of food safety;

[0040] The additional testing information unit is used to determine the testing items based on food safety reasons, determine the corresponding sampling ratio based on the heat and severity of public opinion, and obtain the second additional testing information.

[0041] As a further solution of the present invention: the sampling information determination module includes:

[0042] A test information summary unit, used to summarize the conventional test information, the first additional test information, and the second additional test information, and when multiple test items are repeated, only the one with the highest sampling ratio is retained;

[0043] A sampling quantity calculation unit is used to determine the sampling quantity of each test item according to the quantity of agricultural products and the sampling ratio;

[0044] A test item arrangement unit, used to arrange all test items in descending order according to the number of random inspections, create a new sampling group, and move the first-ranked test item in the arrangement to the sampling group;

[0045] The sampling group determination unit is used to delete the detection items moved to the sampling group in the arrangement, move the detection item ranked first in the updated arrangement to the existing sampling group or create a new sampling group, and repeat this step until all the detection items are moved.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention determines conventional detection information by the type of agricultural products, the origin of agricultural products and the planting method, and determines the first additional detection information according to the use of pesticides. In this way, the first additional detection information takes into account the impact of the use of pesticides on the quality and safety of agricultural products. In addition, the keywords used for retrieval are automatically determined, and the corresponding agricultural product network public opinion information is determined by searching according to the keywords, and the second additional detection information is determined. In this way, the second additional detection information takes into account the network public opinion information. Qualified test results can promptly dispel consumers' concerns and maintain the reputation of good agricultural products. The test results obtained by the sampling information of the present invention can fully reflect the actual situation of agricultural products, with comprehensive considerations and high flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 The figure is a flow chart of a sampling method for agricultural product testing.

[0049] Figure 2 A flow chart for determining routine testing information in a sampling method for agricultural product testing.

[0050] Figure 3 The present invention is a flow chart for determining first additional testing information in a sampling method for testing agricultural products.

[0051] Figure 4 The present invention is a flow chart for determining second additional testing information in a sampling method for testing agricultural products.

[0052] Figure 5 A flow chart for determining sampling information in a sampling method for agricultural product testing.

[0053] Figure 6 The present invention is a flow chart for moving test items to an existing sampling group or creating a new sampling group in a sampling method for agricultural product testing.

[0054] Figure 7 The figure is a schematic diagram of the structure of a sampling system for agricultural product testing. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0056] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0057] like Figure 1 As shown, an embodiment of the present invention provides a sampling method for agricultural product detection, the method comprising the following steps:

[0058] S100, receiving the type of agricultural products, the origin of agricultural products, the planting method and the quantity of agricultural products, and determining the routine testing information, where the routine testing information includes a number of testing items, and each testing item corresponds to a sampling ratio;

[0059] S200, retrieve the pesticide usage situation, and determine first additional detection information according to the pesticide usage situation, where the first additional detection information includes a plurality of detection items, and each detection item corresponds to a sampling ratio;

[0060] S300, determining a keyword, searching and determining corresponding agricultural product network public opinion information according to the keyword, and determining second additional testing information, where the second additional testing information includes a number of testing items, and each testing item corresponds to a sampling ratio;

[0061] S400, determining sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information, wherein the sampling information includes a plurality of sampling groups, each sampling group corresponding to a detection item and a sampling quantity.

[0062] It should be noted that, with the continuous development of agricultural production, the types, origins, planting methods and pesticide usage of agricultural products are becoming increasingly diversified, and traditional sampling detection methods can no longer meet the current needs of agricultural product quality and safety testing. In addition, with the popularization of the Internet, the impact of agricultural product network public opinion information on agricultural product quality and safety is becoming increasingly significant. Traditional sampling detection methods lack consideration of network public opinion information, resulting in the test results may not be able to reflect the reputation of agricultural products in a timely manner, and cannot dispel consumers' concerns. The embodiments of the present invention are intended to solve the above problems.

[0063] In the embodiment of the present invention, before the formal test, the purchaser needs to determine the type of agricultural products, the origin of agricultural products, the planting method, the quantity of agricultural products and the use of pesticides. The use of pesticides includes the type of pesticides and the corresponding dosage. Based on the above information, the embodiment of the present invention will automatically determine the conventional detection information, and the conventional detection information includes several detection items, and each detection item corresponds to a sampling ratio. In addition, the embodiment of the present invention will also determine the first additional detection information according to the use of pesticides. The first additional detection information includes several detection items, and each detection item corresponds to a sampling ratio. In this way, the first additional detection information takes into account the impact of the use of pesticides on the quality and safety of agricultural products. In addition, the embodiment of the present invention will also automatically determine the keywords for retrieval, and determine the corresponding agricultural product network public opinion information according to the keywords, and determine the second additional detection information. The second additional detection information includes several detection items, and each detection item corresponds to a sampling ratio. In this way, the second additional detection information takes into account the network public opinion information, and the qualified test results can dispel consumers' concerns in time and maintain the reputation of good agricultural products. Finally, the embodiment of the present invention determines the sampling information based on the quantity of agricultural products, conventional detection information, the first additional detection information and the second additional detection information. The sampling information includes several sampling groups, each sampling group corresponds to a detection item and a sampling quantity. The detection results obtained through the final sampling information can fully reflect the actual situation of the agricultural products, with comprehensive considerations and high flexibility.

[0064] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of determining the conventional detection information specifically includes:

[0065] S101, input the types of agricultural products, their origins and planting methods into the regular sampling project database for matching;

[0066] S102, outputting a number of test items and corresponding sampling ratios, and determining routine test information according to the test items and the sampling ratios.

[0067] In the embodiment of the present invention, a conventional sampling inspection project library is constructed in advance, and the conventional sampling inspection project library contains a large number of agricultural product types, each agricultural product type corresponds to a number of agricultural product origins, each agricultural product origin corresponds to a number of planting methods, and each planting method corresponds to a number of detection items and corresponding sampling inspection ratios. When the agricultural product type, agricultural product origin and planting method are input into the conventional sampling inspection project library, a number of matching detection items and corresponding sampling inspection ratios will be automatically output, thereby obtaining conventional detection information.

[0068] like Figure 3 As shown, as a preferred embodiment of the present invention, the step of determining the first additional detection information according to the pesticide usage situation specifically includes:

[0069] S201, retrieve the pesticide type and corresponding usage dosage D in the pesticide usage status;

[0070] S202, determining corresponding test items according to the type of pesticide, and determining the toxicity level E and residual concentration coefficient K of each pesticide;

[0071] S203, calculating the residual risk score R of each pesticide, R = D × E × K, determining the sampling ratio of the corresponding test item according to the residual risk score R, and obtaining the first additional test information.

[0072] In the embodiment of the present invention, a pesticide information database is also constructed in advance, and the pesticide information database includes a large number of pesticide types, and each pesticide type corresponds to a detection item, a toxicity level, and a residual concentration coefficient. In this way, the detection items, toxicity level E, and residual concentration coefficient K corresponding to each pesticide can be determined according to the use of the pesticide, and then the residual risk score R of each pesticide is calculated, R = D × E × K, and the sampling ratio of the corresponding detection item is determined according to the residual risk score R. Each detection item is set with several residual risk score ranges in advance, and each residual risk score range corresponds to a sampling ratio. All detection items and sampling ratios are summarized to obtain the first additional detection information.

[0073] like Figure 4 As shown, as a preferred embodiment of the present invention, the steps of determining keywords, searching and determining corresponding agricultural product network public opinion information according to the keywords, and determining the second additional detection information specifically include:

[0074] S301, determining keywords based on the types of agricultural products, the origin of agricultural products, and the planting methods, and determining the network public opinion information of agricultural products based on the web crawler technology and keywords;

[0075] S302, retrieve food safety events and public opinion heat in agricultural product network public opinion information, and extract the causes and severity of food safety;

[0076] S303, determine the inspection items according to food safety reasons, determine the corresponding sampling ratio according to the heat and severity of public opinion, and obtain the second additional inspection information.

[0077] In the embodiment of the present invention, keywords are determined based on the types of agricultural products, the origin of agricultural products, and the planting methods, such as "corn in region A". Then, based on the web crawler technology, public opinion information related to the keywords is captured on social media, news reports, forums and other platforms. Then, food safety events and public opinion heat in the agricultural product network public opinion information are retrieved, and the food safety reasons and severity in the public opinion information are extracted in combination with NLP technology. The severity can be determined based on the number of people affected and the severity of the disease. Finally, the test items are determined based on the reasons for food safety, such as what is tested for what content exceeds the standard, and the corresponding sampling ratio is determined based on the public opinion heat and severity. The higher the public opinion heat and the higher the severity, the higher the sampling ratio will be.

[0078] like Figure 5 As shown, as a preferred embodiment of the present invention, the step of determining the sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information specifically includes:

[0079] S401, summarizing the conventional test information, the first additional test information, and the second additional test information, and when multiple test items are repeated, only retaining the one with the highest sampling ratio;

[0080] S402, determining the number of random inspections for each inspection item according to the number of agricultural products and the random inspection ratio;

[0081] S403, arranging all the test items in descending order according to the number of random inspections, creating a new sampling group, and moving the first-ranked test item in the arrangement to the sampling group;

[0082] S404, deleting the detection items moved to the sampling group from the arrangement, moving the detection item ranked first in the updated arrangement to the existing sampling group or creating a new sampling group, and repeating this step until all detection items are moved.

[0083] In an embodiment of the present invention, in order to determine the final sampling information, the conventional detection information, the first additional detection information and the second additional detection information are first summarized. When multiple detection items are repeated, only the one with the highest sampling ratio is retained. For example, if two B item detections appear, only the B item detection with a higher sampling ratio is retained. Then, according to the number of agricultural products and the sampling ratio, the number of samplings for each detection item is determined, and all detection items are arranged in descending order according to the number of samplings, a new sampling group is created, and the detection item ranked first in the arrangement is moved to the sampling group, and then the detection item moved to the sampling group is deleted in the arrangement, and the arrangement is updated, and the detection item ranked first in the updated arrangement is moved to the existing sampling group or a new sampling group is created, and this step is repeated until all detection items are moved. Several sampling groups will be obtained, and then sampling information will be obtained.

[0084] like Figure 6 As shown, as a preferred embodiment of the present invention, the step of moving the first-ranked detection item in the updated arrangement to an existing sampling group or creating a new sampling group specifically includes:

[0085] S4041, inputting the first-ranked test item in the updated arrangement and the test items of the existing sampling group into the item conflict library;

[0086] S4042, output the existing sampling groups that do not conflict with the first-ranked detection item. When the number of the output existing sampling groups is greater than zero, randomly move the detection item to the output existing sampling groups; when the number of the output existing sampling groups is zero, create a new sampling group.

[0087] In the embodiment of the present invention, in order to reduce the total number of samples as much as possible and ensure the quality of detection, it is necessary to construct a project conflict library, which contains a large number of detection items, and each detection item corresponds to a number of conflicting detection items, such as the conflict between project B and project C, indicating that the same raw material cannot be used when performing the detection of project B and project C. If several projects do not conflict, the same raw material can be used. In the embodiment of the present invention, the detection items ranked first in the updated arrangement and the detection items of the existing sampling group are input into the project conflict library, and the existing sampling group that does not conflict with the detection items ranked first is determined. When the number of existing sampling groups outputted is greater than zero, the detection items are randomly moved to any existing sampling group outputted; when the number of existing sampling groups outputted is zero, a new sampling group is created, so that it is ensured that multiple detection items in each sampling group can use the same batch of raw materials, reducing the total number of samples.

[0088] like Figure 7 As shown, an embodiment of the present invention further provides a sampling system for agricultural product detection, the system comprising:

[0089] The conventional testing information module 100 is used to receive the type of agricultural products, the origin of agricultural products, the planting method and the quantity of agricultural products, and determine the conventional testing information. The conventional testing information includes a number of testing items, and each testing item corresponds to a sampling ratio;

[0090] The first additional detection module 200 is used to retrieve the pesticide usage situation and determine the first additional detection information according to the pesticide usage situation. The first additional detection information includes a plurality of detection items, and each detection item corresponds to a sampling ratio;

[0091] The second additional detection module 300 is used to determine keywords, search and determine corresponding agricultural product network public opinion information according to the keywords, and determine second additional detection information, where the second additional detection information includes several detection items, and each detection item corresponds to a sampling ratio;

[0092] The sampling information determination module 400 is used to determine the sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information. The sampling information includes several sampling groups, each sampling group corresponds to a detection item and a sampling quantity.

[0093] As a preferred embodiment of the present invention, the first additional detection module 200 includes:

[0094] A pesticide information retrieval unit, used to retrieve the pesticide type and corresponding usage dosage D in the pesticide usage information;

[0095] The toxicity concentration coefficient unit is used to determine the corresponding test items according to the type of pesticide, and determine the toxicity level E and residual concentration coefficient K of each pesticide;

[0096] The residual risk scoring unit is used to calculate the residual risk score R of each pesticide, R=D×E×K, determine the sampling ratio of the corresponding test item according to the residual risk score R, and obtain the first additional test information.

[0097] As a preferred embodiment of the present invention, the second additional detection module 300 includes:

[0098] Network public opinion information unit, used to determine keywords based on agricultural product types, agricultural product origins and planting methods, and to determine agricultural product network public opinion information based on web crawler technology and keywords;

[0099] Public opinion information analysis unit, used to retrieve food safety events and public opinion heat from agricultural product network public opinion information, and extract the causes and severity of food safety;

[0100] The additional testing information unit is used to determine the testing items based on food safety reasons, determine the corresponding sampling ratio based on the heat and severity of public opinion, and obtain the second additional testing information.

[0101] As a preferred embodiment of the present invention, the sampling information determination module 400 includes:

[0102] A test information summary unit, used to summarize the conventional test information, the first additional test information, and the second additional test information, and when multiple test items are repeated, only the one with the highest sampling ratio is retained;

[0103] A sampling quantity calculation unit is used to determine the sampling quantity of each test item according to the quantity of agricultural products and the sampling ratio;

[0104] A test item arrangement unit, used to arrange all test items in descending order according to the number of random inspections, create a new sampling group, and move the first-ranked test item in the arrangement to the sampling group;

[0105] The sampling group determination unit is used to delete the detection items moved to the sampling group in the arrangement, move the detection item ranked first in the updated arrangement to the existing sampling group or create a new sampling group, and repeat this step until all the detection items are moved.

[0106] The above only describes in detail the preferred embodiments of the present invention, which is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0107] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0108] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0109] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A sampling method for agricultural product detection, characterized in that: The method comprises the following steps: Receive the types of agricultural products, origins of agricultural products, planting methods and quantities of agricultural products, and determine routine testing information. Routine testing information includes several testing items, and each testing item has a corresponding sampling ratio; Retrieving the pesticide usage situation, and determining the first additional testing information according to the pesticide usage situation, wherein the first additional testing information includes a plurality of testing items, and each testing item corresponds to a sampling ratio; Determine keywords, perform a search based on the keywords to determine the corresponding agricultural product network public opinion information, and determine the second additional testing information, the second additional testing information includes a number of testing items, and each testing item corresponds to a sampling ratio; The sampling information is determined according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information. The sampling information includes several sampling groups, and each sampling group corresponds to a detection item and a sampling quantity.

2. The sampling method for agricultural product detection according to claim 1, characterized in that: The step of determining routine detection information specifically includes: Input the types of agricultural products, their origins and planting methods into the regular sampling project database for matching; Output several test items and corresponding sampling ratios, and determine routine test information based on the test items and sampling ratios.

3. The sampling method for agricultural product detection according to claim 1, characterized in that: The step of determining the first additional detection information according to the pesticide usage situation specifically includes: Retrieve the pesticide type and corresponding dosage D from the pesticide usage information; Determine the corresponding test items according to the type of pesticide, and determine the toxicity level E and residual concentration coefficient K of each pesticide; The residual risk score R of each pesticide is calculated, R=D×E×K, and the sampling ratio of the corresponding test items is determined according to the residual risk score R to obtain the first additional test information.

4. The sampling method for agricultural product detection according to claim 1, characterized in that: The step of determining keywords, searching and determining corresponding agricultural product network public opinion information according to the keywords, and determining the second additional detection information specifically includes: Determine keywords based on the types of agricultural products, their origins, and their planting methods, and determine the online public opinion information on agricultural products based on web crawler technology and keywords; Retrieve food safety incidents and public opinion heat from agricultural product online public opinion information, and extract the causes and severity of food safety; The testing items are determined based on food safety reasons, and the corresponding sampling ratio is determined based on the heat and severity of public opinion to obtain the second additional testing information.

5. The sampling method for agricultural product detection according to claim 1, characterized in that: The step of determining the sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information specifically includes: Summarize the conventional test information, the first additional test information, and the second additional test information. When multiple test items are repeated, only the one with the highest sampling ratio is retained; Determine the number of random inspections for each inspection item based on the number of agricultural products and the random inspection ratio; Arrange all the test items in descending order according to the number of random inspections, create a new sampling group, and move the first-ranked test item in the arrangement to the sampling group; The detection items moved to the sampling group are deleted from the arrangement, and the detection items ranked first in the updated arrangement are moved to the existing sampling group or a new sampling group is created. This step is repeated until all detection items are moved.

6. The sampling method for agricultural product detection according to claim 5, characterized in that: The step of moving the first-ranked detection item in the updated arrangement to an existing sampling group or creating a new sampling group specifically includes: Inputting the first-ranked test item in the updated arrangement and the test items of the existing sampling group into the item conflict library; Output the existing sampling groups that do not conflict with the first-ranked detection item. When the number of the output existing sampling groups is greater than zero, randomly move the detection items to the output existing sampling groups; when the number of the output existing sampling groups is zero, create a new sampling group.

7. A sampling system for agricultural product testing, characterized in that: The system comprises: The routine testing information module is used to receive the types of agricultural products, the origin of agricultural products, the planting methods and the quantity of agricultural products, and determine the routine testing information. The routine testing information includes several testing items, and each testing item corresponds to a sampling ratio; A first additional detection module is used to retrieve the pesticide usage situation and determine the first additional detection information according to the pesticide usage situation. The first additional detection information includes a number of detection items, and each detection item corresponds to a sampling ratio; The second additional detection module is used to determine keywords, search and determine corresponding agricultural product network public opinion information according to the keywords, and determine second additional detection information. The second additional detection information includes several detection items, and each detection item corresponds to a sampling ratio; The sampling information determination module is used to determine the sampling information according to the quantity of agricultural products, conventional detection information, first additional detection information and second additional detection information, wherein the sampling information includes several sampling groups, each sampling group corresponding to a detection item and a sampling quantity.

8. The sampling system for agricultural product detection according to claim 7, characterized in that: The first additional detection module comprises: A pesticide information retrieval unit, used to retrieve the pesticide type and corresponding usage dosage D in the pesticide usage information; The toxicity concentration coefficient unit is used to determine the corresponding test items according to the type of pesticide, and determine the toxicity level E and residual concentration coefficient K of each pesticide; The residual risk scoring unit is used to calculate the residual risk score R of each pesticide, R=D×E×K, determine the sampling ratio of the corresponding detection item according to the residual risk score R, and obtain the first additional detection information.

9. The sampling system for agricultural product detection according to claim 7, characterized in that: The second additional detection module comprises: Network public opinion information unit, used to determine keywords based on agricultural product types, agricultural product origins and planting methods, and to determine agricultural product network public opinion information based on web crawler technology and keywords; Public opinion information analysis unit, used to retrieve food safety events and public opinion heat from agricultural product network public opinion information, and extract the causes and severity of food safety; The additional testing information unit is used to determine the testing items based on food safety reasons, determine the corresponding sampling ratio based on the heat and severity of public opinion, and obtain the second additional testing information.

10. The sampling system for agricultural product detection according to claim 7, characterized in that: The sampling information determination module comprises: A test information summary unit, used to summarize the conventional test information, the first additional test information, and the second additional test information, and when multiple test items are repeated, only the one with the highest sampling ratio is retained; A sampling quantity calculation unit is used to determine the sampling quantity of each test item according to the quantity of agricultural products and the sampling ratio; A test item arrangement unit, used to arrange all test items in descending order according to the number of random inspections, create a new sampling group, and move the first-ranked test item in the arrangement to the sampling group; The sampling group determination unit is used to delete the detection items moved to the sampling group in the arrangement, move the detection item ranked first in the updated arrangement to the existing sampling group or create a new sampling group, and repeat this step until all the detection items are moved.

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