A method and system for tracing the origin of agricultural and sideline products throughout their life cycle

Abstract

The present application relates to the field of data processing technology, and specifically to a method and system for tracing the entire life cycle of agricultural and sideline products, the method comprising: obtaining monitoring data of the entire life cycle of agricultural and sideline products, the entire life cycle including N stages, and any stage Pi including Mi batches; for stage Pi, determining the first parameter value of agricultural and sideline products of any batch Bj based on the monitoring data of Mi batches of agricultural and sideline products; for batch Bj, determining the second parameter value based on R first parameter values ​​corresponding to R stages; determining abnormal agricultural and sideline products based on the second parameter value of each batch. Based on the monitoring information of agricultural and sideline products, the present application determines the probability of each batch of agricultural and sideline products being of abnormal quality and the changing trend of the probability in the historical stage, and accurately determines the authenticity of the monitoring data of agricultural and sideline products.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for tracing the origin of agricultural and sideline products throughout their entire life cycle. Background Art

[0002] Agricultural and sideline products traceability refers to a system that records and stores information about agricultural products and agricultural by-products (i.e. agricultural and sideline products) throughout the entire process of agricultural and sideline products supply to ensure the quality of agricultural and sideline products. The agricultural and sideline products traceability system usually includes the production, circulation, storage, secondary processing and sales of agricultural and sideline products. Through the agricultural and sideline products traceability system, the source of agricultural and sideline products can be determined, the quality and safety of the production and processing process can be guaranteed, the responsibility for quality problems can be investigated, and a rapid recall mechanism can be established.

[0003] Agricultural and sideline products traceability systems usually use centralized traceability systems to collect data from various stages of agricultural and sideline products, and reorganize them so that various data of the entire life cycle of agricultural and sideline products can be obtained at consumer terminals. In the above process, the centralized traceability system is prone to the problem of agricultural and sideline product data being tampered with, which cannot ensure the authenticity of the traceability data of agricultural and sideline products, resulting in abnormal quality agricultural and sideline products entering the market and consumers' trust in the agricultural and sideline product traceability system declining. Summary of the invention

[0004] In order to determine the authenticity of relevant data in the agricultural and sideline products traceability process and improve users' trust in the agricultural and sideline products traceability system, the purpose of the present invention is to provide a method and system for tracing the entire life cycle of agricultural and sideline products. The technical solutions adopted are as follows:

[0005] On the one hand, the present application provides a method for tracing the entire life cycle of agricultural and sideline products, including: obtaining monitoring data of the entire life cycle of agricultural and sideline products, the entire life cycle includes N stages, any stage Pi includes Mi batches, N and Mi are both integers greater than or equal to 1, and i is an integer greater than or equal to 1 and less than or equal to N; for stage Pi, according to the monitoring data of Mi batches of agricultural and sideline products, determine the first parameter value of agricultural and sideline products of any batch Bj, the first parameter value represents the probability that the agricultural and sideline products of batch Bj are of abnormal quality, j is an integer greater than or equal to 1 and less than or equal to Mi; for batch Bj, according to R first parameter values ​​corresponding to R stages, determine the second parameter value, the second parameter value represents the probability that the monitoring data of agricultural and sideline products of batch Bj has been tampered with, R is less than or equal to N, and the Rth stage is the stage where the agricultural and sideline products are at the current moment; according to the second parameter value of each batch, determine the abnormal agricultural and sideline products.

[0006] In a possible example, for stage Pi, based on the monitoring data of Mi batches of agricultural and sideline products, determining the first parameter value of any batch Bj of agricultural and sideline products includes: for stage Pi, based on the monitoring data of Mi batches of agricultural and sideline products, determining the third parameter value between any two batches in Mi batches, the third parameter value representing the consistency between the monitoring data of the corresponding two batches of agricultural and sideline products; classifying each batch of agricultural and sideline products according to the third parameter value and the first threshold value to obtain a first category and a second category, the first category being the category of agricultural and sideline products of normal quality, and the second category being the category of agricultural and sideline products of abnormal quality; determining the first parameter value of the agricultural and sideline products of batch Bj according to the number of batches in the category to which batch Bj belongs.

[0007] In a possible example, any two batches of stage Pi are the first batch and the second batch, the monitoring data of the agricultural and sideline products of stage Pi include monitoring data of Xi dimensions of the agricultural and sideline products, the third parameter value is related to the sum of Xi fourth parameter values, and the fourth parameter value represents the similarity between the monitoring data of one dimension of the agricultural and sideline products of the first batch and the monitoring data of the corresponding dimension of the agricultural and sideline products of the second batch.

[0008] In one possible example, all batches in the first category are chained based on a third parameter value greater than or equal to a first threshold.

[0009] In a possible example, the batch quantity of the category to which batch Bj belongs is negatively correlated with the first parameter value of the agricultural and sideline products of batch Bj.

[0010] In a possible example, for batch Bj, determining the second parameter value according to R first parameter values ​​corresponding one-to-one to the R stages includes: for batch Bj, determining a fifth parameter value according to the R first parameter values ​​corresponding one-to-one to the R stages, the fifth parameter value representing the fluctuation trend of the R first parameter values; determining the second parameter value according to the fifth parameter value.

[0011] In one possible example, the fifth parameter value is related to the sixth parameter value and / or the sum of (R-1) seventh parameter values, the sixth parameter value represents the ratio of the number of stages in which the first parameter value decreases to R, and among the (R-1) seventh parameter values, the kth seventh parameter value represents the absolute value of the difference between the first parameter value of the kth stage Pk and the first parameter value of the (k-1)th stage Pk-1, where k is an integer greater than or equal to 2 and less than R.

[0012] In a possible example, determining abnormal agricultural and sideline products based on the second parameter value of each batch includes: when the second parameter value of batch Bj is greater than or equal to the second threshold, determining the agricultural and sideline products of batch Bj as candidate abnormal agricultural and sideline products; obtaining secondary detection results, which are obtained by secondary detection of the candidate abnormal agricultural and sideline products; and determining the abnormal agricultural and sideline products based on the secondary detection results.

[0013] In one possible example, the monitoring data of agricultural and sideline products includes secondary detection results.

[0014] On the one hand, the present application provides a full life cycle traceability system for agricultural and sideline products, including: a module for executing the full life cycle traceability method for agricultural and sideline products as described above.

[0015] In summary, the present application provides a method and system for tracing the origin of agricultural and sideline products throughout their life cycle, which can determine the probability (i.e., the first parameter value) of each batch of agricultural and sideline products being of abnormal quality based on the monitoring information of the agricultural and sideline products throughout their life cycle, and determine the probability that the monitoring data of the agricultural and sideline products has been tampered with in combination with the changing trend of the first parameter value in the historical stage, so as to automatically judge the authenticity of the monitoring data of the agricultural and sideline products and improve the user's trust in the agricultural and sideline products traceability system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flowchart of a method for tracing the origin of agricultural and sideline products throughout their life cycle provided by one embodiment of the present application;

[0018] Figure 2 A schematic diagram of classifying each batch of agricultural and sideline products in a method for tracing the origin of agricultural and sideline products throughout their life cycle provided in one embodiment of the present application.

[0019] Figure 3 A block diagram of a full life cycle traceability system for agricultural and sideline products provided in one embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined purpose, the following is a detailed description of the method and system for tracing the source of agricultural and sideline products throughout the life cycle proposed in the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0021] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0022] The specific scheme of a method and system for tracing the entire life cycle of agricultural and sideline products provided by the present application is described in detail below with reference to the accompanying drawings.

[0023] See also Figure 1 , a flowchart of a method for tracing the entire life cycle of agricultural and sideline products provided by an embodiment of the present application.

[0024] like Figure 1 As shown, a method for tracing the origin of agricultural and sideline products throughout their entire life cycle according to an embodiment of the present application includes operations S110 to S140.

[0025] In operation S110, monitoring data of the entire life cycle of agricultural and sideline products is obtained.

[0026] The whole life cycle includes N stages, and any stage Pi includes Mi batches. N and Mi are both integers greater than or equal to 1, and i is an integer greater than or equal to 1 and less than or equal to N.

[0027] The following will take the five stages of the entire life cycle, namely the production stage, circulation stage, storage stage, secondary processing stage and sales stage as an example to illustrate.

[0028] The number of stages in the life cycle of agricultural and sideline products and the number of batches of agricultural and sideline products at any stage may be fixed or variable. The number of stages in the life cycle of different agricultural and sideline products may be the same or different, and the number of stages in the life cycle of the same agricultural and sideline product may be fixed or variable in different scenarios.

[0029] Taking the production stage as an example, agricultural and sideline products in the production stage can be divided into several batches according to different production times. After the agricultural and sideline products are divided into batches and stages, they can be traced back to any stage and any batch.

[0030] In a possible embodiment, monitoring data of the entire life cycle of agricultural and sideline products can be collected through the Internet of Things technology, and the monitoring data of the entire life cycle of the agricultural and sideline products can be uploaded to a traceability platform. The monitoring data of the entire life cycle of agricultural and sideline products can be obtained by obtaining authorization from the traceability platform and through the interface provided by the traceability platform. The traceability platform can be pre-built.

[0031] Exemplarily, the Internet of Things technology may be, for example, radio frequency identification (RFID) technology. Specifically, RFID tags may be hung on seedlings of crops, and monitoring data of each stage and batch of agricultural and sideline products may be collected through RFID reading and writing equipment. Monitoring data of each stage and batch of agricultural and sideline products may be associated with corresponding RFID tags, and monitoring data of each stage and batch of agricultural and sideline products may also be uploaded to a traceability platform. The traceability platform may be pre-built, for example.

[0032] The purpose of agricultural and sideline product traceability is to ensure the quality of agricultural and sideline products. The monitoring data of agricultural and sideline products has been tampered with, making the monitoring data of agricultural and sideline products untrue, and appearing on agricultural and sideline products of abnormal quality. Therefore, in order to determine the authenticity of the monitoring data of agricultural and sideline products, the quality of agricultural and sideline products can be determined first.

[0033] Normally, agricultural and sideline products at each stage are divided into batches. For agricultural and sideline products of normal quality, the difference between the monitoring data of each batch of agricultural and sideline products at any stage is small. However, the difference between the monitoring data of the batch of agricultural and sideline products with abnormal quality and the monitoring data of other batches is large.

[0034] Therefore, the embodiment of the present application can determine the probability of agricultural and sideline products being of abnormal quality in batches through the following operation S120, so that agricultural and sideline products with a higher probability of abnormal quality can be identified later.

[0035] In operation S120, for stage Pi, a first parameter value of agricultural and sideline products of any batch Bj is determined according to monitoring data of Mi batches of agricultural and sideline products.

[0036] The first parameter value represents the probability that the agricultural and sideline products of batch Bj are of abnormal quality, and j is an integer greater than or equal to 1 and less than or equal to Mi.

[0037] Generally, the number of agricultural and sideline products of normal quality is greater than the number of agricultural and sideline products of abnormal quality. In another embodiment of the present application, the probability of the agricultural and sideline products being of abnormal quality can be more accurately determined based on the quantity characteristic.

[0038] Specifically, in a possible embodiment, operation S120 may include operations S121 to S123.

[0039] In operation S121, for stage Pi, a third parameter value between any two batches of Mi batches is determined according to the monitoring data of Mi batches of agricultural and sideline products.

[0040] The third parameter value represents the consistency between the monitoring data of two corresponding batches of agricultural and sideline products.

[0041] Exemplarily, the monitoring data of agricultural and sideline products include monitoring data of Xi dimensions of agricultural and sideline products, where Xi is an integer greater than or equal to 1.

[0042] Taking any two batches, namely the first batch and the second batch, as an example, when Xi takes a value of 1, the corresponding third parameter value can be determined based on the consistency of the monitoring data of the dimension between the first batch and the second batch. When Xi takes a value greater than or equal to 2, the corresponding third parameter value can be determined based on the sum of the consistency of the monitoring data of each dimension between the first batch and the second batch.

[0043] For example, the consistency can be characterized by similarity. Specifically, the similarity can be characterized by similarity coefficients such as Pearson correlation coefficient and Spearman rank similarity coefficient, and the value of the similarity coefficient is positively correlated with the similarity. Alternatively, the similarity can be characterized by distances such as Euclidean distance and Manhattan distance, and the value of the distance is negatively correlated with the similarity.

[0044] For example, the following formula (1) can be used to determine the third parameter value between any two batches (i.e., the first batch B1 and the second batch B2) in the i-th stage: .

[0045] (1)

[0046] Indicates the consistency of monitoring data of agricultural and sideline products of the first batch B1 and the second batch B2 in the i-th stage in the N stages of the whole life cycle; Indicates the number of dimensions of the monitoring data of agricultural and sideline products in the i-th phase. The dimensions here include, for example, temperature, humidity, etc.; represents the monitoring data of the xth dimension of the agricultural and sideline products of the first batch B1 of the i-th phase; represents the monitoring data of the xth dimension of the agricultural and sideline products of the second batch B2 of the i-th phase; Represents the normalization function; DTW() represents the calculation of DTW distance using the dynamic time warping algorithm, which is used to measure the similarity between two time series. The monitoring data of each dimension corresponds to a time series. The smaller the DTW distance, the greater the similarity.

[0047] In operation S122, each batch of agricultural and sideline products is classified according to the third parameter value and the first threshold value to obtain a first category and a second category.

[0048] Taking the DTW distance calculated by the above DTW algorithm as the basis of similarity as an example, when the third parameter value between two batches is greater than or equal to the first threshold, the agricultural and sideline products of the two batches can be classified into the first category. The first category is the category where agricultural and sideline products of normal quality are located. When the third parameter value between two batches is less than the first threshold, the agricultural and sideline products of the two batches can be classified into the second category. The second category is the category where agricultural and sideline products of abnormal quality are located.

[0049] In one possible embodiment, all batches in the first category are chained based on a third parameter value greater than or equal to a first threshold.

[0050] Taking the third parameter value calculated by the above formula (1) as an example, when the third parameter value is a value greater than or equal to 0 and less than or equal to 1, the first threshold value can be, for example, within a numerical range of greater than or equal to 0.6 and less than or equal to 0.95. For example, the first threshold value can be 0.8.

[0051] The following will be combined Figure 2 , taking the first threshold value of 0.8 as an example to illustrate the process of classifying each batch of agricultural and sideline products.

[0052] like Figure 2 As shown, among the total 4 batches, namely batch Ba, batch Bb, batch Bc and batch Bd, the third parameter value between batch Ba and batch Bb is 0.8, the third parameter value between batch Ba and batch Bc is 0.9, the third parameter value between batch Ba and batch Bd is 0.78, the third parameter value between batch Bb and batch Bc is 0.72, the third parameter value between batch Bb and batch Bd is 0.7, and the third parameter value between batch Bc and batch Bd is 0.82.

[0053] The third parameter value between batch Ba and batch Bb, the third parameter value between batch Ba and batch Bc, and the third parameter value between batch Bc and batch Bd all satisfy the condition of being greater than or equal to the first threshold, and batch Bb, batch Ba, batch Bc and batch Bd form a chain relationship. Therefore, the agricultural and sideline products of batch Ba, batch Bb, batch Bc and batch Bd can be classified into the first category.

[0054] exist Figure 2In the example, when the third parameter values ​​of two batches are less than the first threshold, the line between the two batches is a dotted line, and when the third parameter values ​​of two batches are greater than or equal to the first threshold, the line between the two batches is a solid line. When a batch is taken as the starting point (i.e., the first batch), and another batch at the end (i.e., the last batch) can be reached based on an uninterrupted solid line, the first batch, the last batch, and the batch in between (in Figure 1 In the example, when the first batch is Bb, the last batch is Bd, and the batches in between are batch Ba and batch Bc), all can be classified into the first category.

[0055] In this way, all batches of agricultural and sideline products in any stage can be classified.

[0056] Generally, the number of agricultural and sideline products with abnormal quality is less than that of agricultural and sideline products with normal quality. Therefore, the probability that the agricultural and sideline products of any batch Bj are of abnormal quality can also be determined according to the number of batches of the category to which the agricultural and sideline products of the batch Bj belong.

[0057] Specifically, in operation S123, the first parameter value of the agricultural and sideline products of the batch Bj is determined according to the batch quantity of the category to which the batch Bj belongs.

[0058] Exemplarily, the number of batches in the category to which batch Bj belongs is negatively correlated with the first parameter value of the agricultural and sideline products of batch Bj.

[0059] For example, the following formula (2) can be used to determine the first parameter value of the jth batch of agricultural and sideline products in the i-th stage: .

[0060] (2)

[0061] in, is the number of batches in the category of the jth batch.

[0062] Therefore, an accurate first parameter value can be obtained through the above operations S121 to S123, that is, the probability that any batch of agricultural and sideline products is of abnormal quality can be accurately determined.

[0063] The processing methods of agricultural and sideline products at each stage are usually relatively simple and generally do not change their original properties. Therefore, the production stage, transportation stage, processing stage and sales stage in the whole life cycle will not significantly affect the quality of agricultural and sideline products. Therefore, the authenticity of the monitoring data of agricultural and sideline products can be determined based on the first parameter values ​​of several historical stages.

[0064] Specifically, in operation S130, for the batch Bj, the second parameter value is determined according to the R first parameter values ​​corresponding one-to-one to the R stages.

[0065] The second parameter value represents the probability that the monitoring data of the agricultural and sideline products of the batch Bj has been tampered with.

[0066] R is less than or equal to N, and the Rth stage is the stage that the agricultural and sideline products are in at the current moment.

[0067] For the real monitoring data of agricultural and sideline products of normal quality, the first parameter value at each stage is relatively stable. For the monitoring data of agricultural and sideline products of abnormal quality, if the monitoring data of agricultural and sideline products is tampered with at a certain stage so that the monitoring data of agricultural and sideline products is not true, the first parameter value will show a large fluctuation at this stage.

[0068] Therefore, in the embodiment of the present application, the second parameter value can be determined according to the fluctuation trend of the first parameter value.

[0069] Specifically, operation S130 may include: operation S131 and operation S132.

[0070] In operation S131 , for the batch Bj, a fifth parameter value is determined according to R first parameter values ​​corresponding one-to-one to the R stages.

[0071] The fifth parameter value represents the fluctuation trend of the R first parameter values.

[0072] For batch Bj, if the fluctuation trend of the R first parameter values ​​corresponding to the R stages is relatively slow, the probability that the monitoring data of agricultural and sideline products has been tampered is low, that is, the authenticity of the monitoring data of agricultural and sideline products is high. If the fluctuation trend of the R first parameter values ​​corresponding to the R stages is relatively violent, and the number of stages in which the first parameter value decreases in the R stages is larger, the probability that the monitoring data of agricultural and sideline products has been tampered is higher, that is, the authenticity of the monitoring data of agricultural and sideline products is low.

[0073] Exemplarily, the fifth parameter value is related to the sixth parameter value and / or the sum of (R-1) seventh parameter values.

[0074] The sixth parameter value represents the ratio of the number of stages in which the first parameter value decreases to N, that is, the proportion of the number of stages in which the first parameter value decreases in the R stages.

[0075] Among the (R-1) seventh parameter values, the kth seventh parameter value represents the absolute value of the difference between the first parameter value of the kth stage Pk and the first parameter value of the (k-1)th stage Pk-1, and k is an integer greater than or equal to 2 and less than R. The (R-1)th seventh parameter values ​​can represent the fluctuation trend of the R first parameter values.

[0076] In operation S132, a second parameter value is determined according to the fifth parameter value.

[0077] Exemplarily, the following formula (3) can be used to determine the second parameter value of the jth batch in the i-th stage: .

[0078] (3)

[0079] Among them, The first stage is the stage that agricultural and sideline products are in at the current moment. represents the number of stages in which the value of the first parameter decreases; represents the first parameter value of the jth batch in the kth stage, represents the first parameter value of the j-th batch in the (k-1)-th stage.

[0080] In formula (3), That is, the sixth parameter value, That is, the sum of (R-1) seventh parameter values.

[0081] In summary, through the above operations S131 and S132, the second parameter value can be accurately determined according to the fluctuation trend of the first parameter value.

[0082] In operation S140, abnormal agricultural and sideline products are determined according to the second parameter value of each batch.

[0083] Abnormal agricultural and sideline products refer to agricultural and sideline products whose monitoring data are more likely to be tampered with. Correspondingly, normal agricultural and sideline products refer to agricultural and sideline products whose monitoring data are less likely to be tampered with.

[0084] Therefore, in the embodiment of the present application, the above operations can accurately identify abnormal agricultural and sideline products whose monitoring data has been tampered with, so as to improve the user's trust in the agricultural and sideline products traceability system.

[0085] In a possible embodiment, operation S140 may include operations S141 to S143.

[0086] In operation S141 , when the second parameter value of the batch Bj is greater than or equal to the second threshold value, the agricultural and sideline products of the batch Bj are determined as candidates for abnormal agricultural and sideline products.

[0087] In operation S142, a secondary detection result is obtained.

[0088] The secondary detection result is obtained by performing secondary detection on the candidate abnormal agricultural and sideline products. Specifically, the secondary detection result can be obtained by relevant personnel performing manual detection on the monitoring data of the candidate abnormal agricultural and sideline products.

[0089] Exemplarily, the monitoring data of agricultural and sideline products may include secondary test results. For example, the secondary test results may be uploaded to a traceability platform.

[0090] In operation S143, abnormal agricultural and sideline products are determined according to the secondary detection result.

[0091] In the embodiment of the present application, through the above-mentioned operations S141 to S143, the agricultural and sideline products whose second parameter values ​​are greater than the second threshold value can be subjected to secondary detection, and the final abnormal agricultural and sideline products can be determined based on the second detection results to accurately judge the authenticity of the monitoring data of the agricultural and sideline products.

[0092] In a possible embodiment, between operation S142 and operation S143, for stage Pi, when the second detection result is qualified, the second parameter value of the candidate abnormal agricultural and sideline product can be determined as the second parameter value of stage Pi-1.

[0093] In summary, the present application provides a method and system for tracing the origin of agricultural and sideline products throughout their life cycle, which can determine the probability (i.e., the first parameter value) of each batch of agricultural and sideline products being of abnormal quality based on the monitoring information of the agricultural and sideline products throughout their life cycle, and determine the probability that the monitoring data of the agricultural and sideline products has been tampered with in combination with the changing trend of the first parameter value in the historical stage, so as to automatically judge the authenticity of the monitoring data of the agricultural and sideline products and improve the user's trust in the agricultural and sideline products traceability system.

[0094] like Figure 3 As shown, the embodiment of the present application also provides a block diagram of a system for tracing the entire life cycle of agricultural and sideline products.

[0095] The agricultural and sideline products full life cycle traceability system may include: a first module 310 , a second module 320 , a third module 330 and a fourth module 340 .

[0096] The first module 310 is used to obtain monitoring data of the entire life cycle of agricultural and sideline products.

[0097] The entire life cycle includes N stages. Any stage Pi includes Mi batches. N and Mi are both integers greater than or equal to 1, and i is an integer greater than or equal to 1 and less than or equal to N.

[0098] The second module 320 is used to determine the first parameter value of any batch Bj of agricultural and sideline products according to the monitoring data of Mi batches of agricultural and sideline products in stage Pi, where the first parameter value represents the probability that the agricultural and sideline products of batch Bj are of abnormal quality, and j is an integer greater than or equal to 1 and less than or equal to Mi.

[0099] The third module 330 is used to determine the second parameter value for batch Bj based on R first parameter values ​​corresponding to R stages, the second parameter value represents the probability that the monitoring data of the agricultural and sideline products of batch Bj has been tampered with, R is less than or equal to N, and the Rth stage is the stage that the agricultural and sideline products are in at the current moment.

[0100] The fourth module 340 is used to determine abnormal agricultural and sideline products according to the second parameter value of each batch.

[0101] An embodiment of the present application also provides an electronic device, including a storage device and a processor, wherein the storage device is used to store executable program code, and the processor can be used to call and run the executable program code from the storage device, so that the electronic device executes the above-mentioned agricultural and sideline products full life cycle traceability method.

[0102] In other embodiments, a computer program product is also provided. When the computer program product is run on an electronic device such as a computer, the electronic device executes the above-mentioned related steps to implement a method for tracing the entire life cycle of agricultural and sideline products provided in the above-mentioned embodiment.

[0103] In other embodiments, a computer-readable storage medium is also provided, in which a computer program code is stored. When the computer program code is run on a computer, the computer executes the above-mentioned related method steps to implement the agricultural and sideline products full life cycle traceability method provided in the above-mentioned embodiment.

[0104] Among them, the provided systems, devices, computer program products, and computer-readable storage media are all used to execute the agricultural and sideline products full life cycle traceability method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the agricultural and sideline products full life cycle traceability method provided above, and will not be repeated here.

[0105] It should be noted that the sequence of the above embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0106] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for tracing the origin of agricultural and sideline products throughout their entire life cycle, characterized in that: include: Obtain monitoring data of the entire life cycle of agricultural and sideline products, where the entire life cycle includes N stages, and any stage P i Including M i batches, N and M i are all integers greater than or equal to 1, i is an integer greater than or equal to 1 and less than or equal to N; For the stage P i , according to M i The monitoring data of the agricultural and sideline products of batches are used to determine any batch B j The first parameter value of the agricultural and sideline products, wherein the first parameter value characterizes the batch B j The probability that the agricultural and sideline products are of abnormal quality, j is greater than or equal to 1 and less than or equal to M i integer; For the batch B j , according to the R first parameter values ​​corresponding to the R stages, determine the second parameter value, the second parameter value characterizing the batch B j The probability that the monitoring data of the agricultural and sideline products has been tampered with, R is less than or equal to N, and the Rth stage is the stage that the agricultural and sideline products are in at the current moment; determining abnormal agricultural and sideline products according to the second parameter value of each batch; For the batch B j , according to the R first parameter values ​​corresponding to the R stages one by one, determining the second parameter value includes: For the batch B j , determining a fifth parameter value according to the R first parameter values ​​corresponding to the R stages, wherein the fifth parameter value represents a fluctuation trend of the R first parameter values; The second parameter value is determined according to the fifth parameter value.

2. The method for tracing the origin of agricultural and sideline products throughout their life cycle according to claim 1, characterized in that: The phase P i , according to M i The monitoring data of the agricultural and sideline products of batches are used to determine any batch B j The first parameter values ​​of the agricultural and sideline products include: For the stage P i , according to M i The monitoring data of the agricultural and sideline products of batches are used to determine M i a third parameter value between any two batches in the batches, wherein the third parameter value represents the consistency between the monitoring data of the agricultural and sideline products of the corresponding two batches; According to the third parameter value and the first threshold, each batch of agricultural and sideline products is classified to obtain a first category and a second category, wherein the first category is the category of the agricultural and sideline products of normal quality, and the second category is the category of the agricultural and sideline products of abnormal quality; According to the batch B j The number of batches in the category, determine the batch B j The first parameter value of the agricultural and sideline products.

3. The method for tracing the origin of agricultural and sideline products throughout their life cycle according to claim 2, characterized in that: The stage P i Any two batches are the first batch and the second batch, the stage P i The monitoring data of agricultural and sideline products include X i The monitoring data of the dimension, the third parameter value is related to X i The fourth parameter value represents the similarity between the monitoring data of one dimension of the agricultural and sideline products of the first batch and the monitoring data of the corresponding dimension of the agricultural and sideline products of the second batch.

4. The method for tracing the origin of agricultural and sideline products throughout their life cycle according to claim 2, characterized in that: All batches in the first category are chained based on the third parameter value being greater than or equal to the first threshold.

5. The method for tracing the origin of agricultural and sideline products throughout their life cycle according to claim 2, characterized in that: The batch B j The number of batches in the category is the same as the batch B j is negatively correlated with the first parameter value of the agricultural and sideline products.

6. The method for tracing the origin of agricultural and sideline products throughout their life cycle according to claim 1, characterized in that: The fifth parameter value is related to the sixth parameter value and / or the sum of (R-1) seventh parameter values, the sixth parameter value represents the ratio of the number of stages of decreasing the first parameter value to R, and among the (R-1) seventh parameter values, the kth seventh parameter value represents the kth stage P k The first parameter value and the (k-1)th stage P k-1 The absolute value of the difference between the first parameter values, k is an integer greater than or equal to 2 and less than R.

7. The method for tracing the source of agricultural and sideline products throughout their life cycle according to any one of claims 1 to 5, characterized in that: Determining abnormal agricultural and sideline products according to the second parameter value of each batch includes: In the batch B j If the second parameter value is greater than or equal to the second threshold, the batch B j The agricultural and sideline products are determined as candidate abnormal agricultural and sideline products; Obtaining secondary detection results, where the secondary detection results are obtained by secondary detection of the candidate abnormal agricultural and sideline products; The abnormal agricultural and sideline products are determined according to the secondary detection results.

8. The method for tracing the origin of agricultural and sideline products throughout their life cycle according to claim 7, characterized in that: The monitoring data of the agricultural and sideline products includes the secondary detection results.

9. A full life cycle traceability system for agricultural and sideline products, characterized in that: include: A module for executing the agricultural and sideline products full life cycle traceability method as described in any one of claims 1-8.

Images