Chain type traceability management method, system and terminal for cultivation of gastrodia elata

Abstract

The application belongs to the field of cultivation of Gastrodia elata, and discloses a chain type traceability management method, system and terminal for cultivation of Gastrodia elata. The method manages traceability information based on a main chain composed of key nodes and a secondary chain composed of patrol nodes. The method comprises: when it is determined that the main chain and the secondary chain are in an asynchronous state, performing a main chain correction operation; the main chain correction operation comprises identifying an abnormal affiliated node in the main chain, and determining a docking node based on the secondary chain to replace the abnormal affiliated node, so as to restore the synchronization state of the main chain. The application improves traceability efficiency by constructing the main chain composed of key nodes, realizes dynamic data repair by using the double-chain monitoring and node replacement mechanism of the main chain and the secondary chain, guarantees the quality of traceability information by performing a merging operation on the affiliated nodes, and enhances the robustness and credibility of the traceability system.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cultivation of Gastrodia elata, and particularly relates to a chain traceability management method, system and terminal for cultivation of Gastrodia elata. BACKGROUND

[0002] With the deep development of modern agriculture towards intelligence and refinement, scientific management of the cultivation process of high-value-added Chinese medicinal materials such as Gastrodia elata has become the key to improving the yield and quality of the Chinese medicinal materials. Through integration of various sensors and automatic control equipment, real-time regulation and control of key parameters such as temperature, humidity, light and carbon dioxide concentration in the growth environment have become a basic technical means to ensure the stable growth of the Chinese medicinal materials, and have important value for promoting the modernization of the Chinese medicinal material industry.

[0003] However, the existing technology still has the following problems in the cultivation and management practice of crops such as Gastrodia elata: the existing technology only focuses on the instantaneous environmental data of a specific growth stage, lacks the ability to associate and integrate the longitudinal data from seed source treatment, germination, growth to harvesting throughout the entire cultivation period, resulting in the data of each stage being disconnected from each other, so that when quality problems or yield fluctuations occur, effective root cause tracing and attribution analysis cannot be performed, limiting the iterative optimization of the cultivation process. Moreover, the traditional recording method or centralized database management mode has the risk of data being tampered with, lost or recorded inconsistently, and cannot build a reliable chain of trust, which weakens the public credibility and market value of the product in the Chinese medicinal material market with high product traceability requirements.

[0004] Based on the above problems, the application provides a chain traceability management method, system and terminal for cultivation of Gastrodia elata. SUMMARY

[0005] The purpose of the application is to provide a chain traceability management method for cultivation of Gastrodia elata, which can track and monitor the entire process of cultivation of Gastrodia elata.

[0006] To achieve the above purpose, the application adopts the following technical solutions:

[0007] A chain traceability management method for cultivation of Gastrodia elata, comprising:

[0008] The method manages traceability information based on a main chain composed of key nodes and a secondary chain composed of patrol nodes, comprising:

[0009] When it is determined that the main chain and the secondary chain are in an out-of-sync state, a main chain correction operation is performed;

[0010] The step of determining that the main chain and the secondary chain are in an out-of-sync state comprises:

[0011] determining the effective state of the secondary chain, comprising: calculating the collection deviation of the second key parameter corresponding to the patrol node in the secondary chain in a continuous time period, and determining that the secondary chain is in an effective state if the collection deviation is less than a first preset threshold value;

[0012] under the condition that the secondary chain is in an effective state, if the deviation between the first key parameter corresponding to the key node in the primary chain and the second key parameter corresponding to the patrol node in the secondary chain is greater than a second preset threshold value, it is determined that the primary chain and the secondary chain are in an out-of-sync state;

[0013] the primary chain correction operation comprises:

[0014] identifying an abnormal affiliated node in the primary chain associated with the deviation;

[0015] determining a docking node based on the secondary chain, and replacing the abnormal affiliated node with the docking node to restore the synchronization state of the primary chain.

[0016] Preferably, the generation steps of the primary chain and the secondary chain comprise:

[0017] obtaining traceability information including planting information, environmental information and harvesting information, and setting a plurality of affiliated nodes based on the traceability information;

[0018] performing a merging operation on the plurality of affiliated nodes to construct a plurality of data sub-chains;

[0019] calculating the correlation degree between each node in the data sub-chain, and selecting a node with a correlation degree satisfying a preset condition from each data sub-chain as a key node, and connecting the plurality of key nodes in time sequence to generate a primary chain;

[0020] defining the patrol point set in the cultivation process of Gastrodia as a patrol node, and connecting the patrol nodes in time sequence to generate a secondary chain.

[0021] Preferably, the step of performing a merging operation on the plurality of affiliated nodes to construct a plurality of data sub-chains comprises:

[0022] performing value review, time check and geographic location verification on the affiliated nodes;

[0023] determining and removing the affiliated nodes with abnormal sampling frequency to determine the remaining affiliated nodes as effective affiliated nodes for constructing the data sub-chains.

[0024] Preferably, the step of determining a docking node based on the secondary chain comprises:

[0025] taking the timestamp of the abnormal affiliated node as a time reference point;

[0026] In the secondary chain, we find patrol nodes whose timestamp is less than a preset time threshold and whose content parameters are less than a preset content threshold compared to the content parameters of the abnormal subordinate nodes, and these nodes are used as docking nodes.

[0027] Preferably, the step of selecting nodes whose correlation meets preset conditions as key nodes from each data sub-chain includes:

[0028] Using a collation model, the information deviation value between a node and its temporally adjacent nodes is calculated, and the correlation degree is calculated based on the information deviation value.

[0029] Nodes with a correlation degree greater than a preset correlation degree threshold are identified as key nodes.

[0030] Preferably, the step of generating the secondary chain further includes:

[0031] For each key node in the main chain, select a subordinate node with the same timestamp as the key node and designate it as a patrol node, so as to connect all patrol nodes to form a sub-chain.

[0032] This invention also discloses a chain-based traceability management system for Gastrodia elata cultivation, comprising:

[0033] The link generation module is used to generate a main chain consisting of key nodes and a secondary chain consisting of patrol nodes based on the traceability information.

[0034] The link status determination module is used to determine whether the main chain is out of sync by comparing the data of the main chain and the secondary chain.

[0035] The main chain correction module is used to respond to the link status determination module's determination of the asynchronous state, identify abnormal subsidiary nodes in the main chain, and determine the docking node based on the secondary chain to replace the abnormal subsidiary node in order to restore the synchronization state of the main chain.

[0036] Preferably, the link status determination module is configured as follows:

[0037] The effective state of the sub-chain is determined by the following method: if the collection deviation of the second key parameter corresponding to the patrol node in the sub-chain is less than the first preset threshold within a continuous time period, the sub-chain is determined to be in an effective state.

[0038] Preferably, the link status determination module is further configured to:

[0039] If the deviation between the first key parameter corresponding to the key node in the main chain and the second key parameter corresponding to the patrol node in the sub-chain is greater than the second preset threshold when the sub-chain is in an asynchronous state, the main chain and the sub-chain are determined to be in an asynchronous state.

[0040] The application further discloses a chain traceability management terminal for Gastrodia cultivation.

[0041] Beneficial effects

[0042] 1、The application sets the traceability information as multiple subsidiary nodes, performs a merging operation on the subsidiary nodes according to content parameters, timestamps and spatial positions, thereby constructing multiple data sub-chains, further selects a key node with the largest correlation degree from each data sub-chain by calculating the correlation degrees between nodes, and connects the key nodes to generate a simplified main chain, so that the complex and discrete original cultivation data can be reconstructed into a structured and high-correlation chain data system, compared with the mode of directly recording all traceability information, the main chain is generated by constructing data sub-chains and extracting key nodes, which significantly reduces data redundancy, improves data retrieval and traceability efficiency under the premise of ensuring traceability integrity, and makes the traceability of the whole process of Gastrodia cultivation faster and more focused.

[0043] 2、The application constructs an independent sub-chain by using a patrol node at the same time of constructing the main chain, forms a double-chain monitoring mechanism of the main chain and the sub-chain, identifies an abnormal subsidiary node in the main chain when determining that the main chain is in an out-of-sync state, and finds a docking node with similar timestamps and content parameters from the sub-chain, performs a replacement operation on the abnormal subsidiary node, through the double-chain monitoring and node replacement mechanism, the application realizes dynamic repair of traceability information, can accurately identify and correct the abnormal subsidiary node without interrupting the traceability process and without the need of re-collecting all data, and overcomes the defect that the traditional single-chain traceability system is prone to cause the credibility of all-chain data to decrease or even fail when encountering data abnormalities, thereby enhancing the robustness and data continuity of the traceability management system.

[0044] 3、The application performs a merging operation on the subsidiary nodes before constructing the data sub-chains, the operation includes value review, time check and geographic position check on node information, and through single deviation and continuous deviation determination, identifies and removes nodes with abnormal sampling frequency, and only uses effective subsidiary nodes for subsequent chain construction, so that the application guarantees the quality of the in-chain data from the source, effectively filters out invalid or error data caused by equipment failure or network fluctuation and the like by setting multi-dimensional check and screening barriers before data chaining, ensures the accuracy and reliability of the subsidiary nodes constituting the main chain and the sub-chain, and further fundamentally improves the final credibility of the whole chain traceability system. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is one of flowcharts of embodiment 1 of the application.

[0046] Figure 2 is a flowchart of embodiment 1 of the present application;

[0047] Figure 3 is a structural diagram of embodiment 2 of the present application. DETAILED DESCRIPTION

[0048] In the following description, certain specific details are set forth in order to provide a thorough understanding of different embodiments of the application. However, persons of ordinary skill in the art will appreciate that the application can be practiced without many of these details.

[0049] Embodiment one

[0050] Referring to Figures 1-2 The present embodiment provides a chain traceability management method for Gastrodia cultivation, comprising the following steps:

[0051] In the Gastrodia cultivation management system, traceability information related to the whole life cycle of Gastrodia cultivation is obtained. The traceability information refers to a collection of data used to trace the source, production process, quality status and other related information of products in the whole life cycle of production, processing, circulation and consumption. Specifically, it covers planting information such as sowing time, variety, planting location, fertilization record, pesticide use record, environmental information such as temperature, humidity, light intensity, soil pH value, and harvesting information such as harvesting date, harvesting amount, harvesting personnel. All the obtained traceability information is regarded as an independent event or data point, and based on the obtained traceability information, a plurality of discrete nodes are automatically set, i.e. the minimum unit representing an independent event, state or data record occurring at a specific time point in the traceability chain. Each node represents a specific event or state on the traceability chain.

[0052] The plurality of discrete nodes set above are divided into data nodes and subsidiary nodes. The data nodes usually represent key stages or important events in the Gastrodia cultivation process, such as sowing, growth critical period, harvesting, etc. The data content of the data nodes is usually more macroscopic or general. The subsidiary nodes represent more detailed and frequent observation or operation data generated between or around the key stages or events, such as daily environmental monitoring data, periodic fertilization records.

[0053] The data node performs a merging operation on the affiliated nodes. The merging operation first classifies the affiliated nodes in detail according to the data type, content parameters such as measurement indicators, a timestamp representing a recording time accurate to seconds or milliseconds, and a spatial position representing specific geographic coordinates or planting area numbers of the affiliated nodes. The merging operation specifically refers to a data processing process of classifying, checking, and integrating the affiliated nodes with similar characteristics in data content, timestamps, spatial positions, and the like to form a structured and high-quality data set.

[0054] In the process of classifying the affiliated nodes in detail, a series of data quality checks are performed. Specifically, the process refers to a systematic inspection and verification process of data, aiming to identify and correct errors, inconsistencies, or missing data in the data to ensure the accuracy, integrity, and reliability of the data. The process includes performing value review, time check, and geographic position check on the information of the affiliated nodes to ensure the accuracy and consistency of the data. The value review includes but is not limited to checking whether the data is within a reasonable range, whether there are obvious errors or missing data. The time check includes but is not limited to checking the logical order and validity of the timestamp. The geographic position check includes but is not limited to checking whether the position information matches the actual planting area.

[0055] At the same time, it is determined whether there are nodes with abnormal sampling frequency in the affiliated nodes. The node with abnormal sampling frequency refers to a node whose data collection frequency does not meet the preset standard. Specifically, the preset standard requires temperature data to be collected once an hour, but a certain node has not collected data for several consecutive hours or the collection frequency is much higher than the preset standard. For the node determined to have abnormal sampling frequency, it is excluded from the data set to avoid interference of low-quality data on subsequent analysis. The determination of abnormal sampling frequency includes:

[0056] An affiliated node with a sampling frequency lower than the average sampling frequency of all affiliated nodes in the same batch is determined to have abnormal sampling frequency.

[0057] The determination of abnormal sampling frequency also includes single deviation determination and continuous deviation determination. The single deviation determination includes: taking an affiliated node as a reference node, calculating the time difference between the reference node and its adjacent previous node in time, and the time difference between the reference node and its adjacent subsequent node in time, and comparing it with a preset deviation threshold to determine whether the sampling frequency of the node is abnormal. The continuous deviation determination includes: counting the sampling time intervals of a plurality of consecutive affiliated nodes to generate a time interval sequence, and comparing it with a preset deviation threshold to determine whether the sampling frequency is abnormal.

[0058] The single deviation determination and the continuous deviation determination are both performed by comparing the calculated value with a preset deviation threshold value, if the calculated value exceeds the preset deviation threshold value, the corresponding auxiliary node is determined as a sampling frequency abnormal node, the remaining auxiliary nodes which pass the quality check and are not rejected are determined as effective auxiliary nodes, and are logically associated with the data node; wherein the preset deviation threshold value refers to a predetermined numerical limit for judging whether the sampling frequency is abnormal.

[0059] The effective auxiliary nodes which pass the classification and quality check are connected according to the chronological order of their time stamps, thereby constructing a plurality of independent data sub-chains, each data sub-chain representing a detailed traceability record of a specific aspect or stage in the cultivation process of Gastrodia elata.

[0060] After the data sub-chain is constructed, the correlation degree between the nodes in the data sub-chain is calculated, which is a quantitative index for measuring the information correlation or logical closeness between two nodes, for example, it can be calculated by comparing the similarity of node content parameters, the closeness of time stamps and the overlap of spatial positions, from each data sub-chain, the node with the maximum correlation degree is selected and determined as a key node, the key node represents the most representative or information richest link in the data sub-chain, and the steps of generating the main chain specifically include:

[0061] The content values of the data nodes and the auxiliary nodes are input into a processing module specially used for data checking and correlation degree calculation, the processing module calculates the information deviation value between a node and its adjacent node in time through a set of preset logical rules, specifically, by comparing the numerical difference, change trend of two nodes on a specific parameter, quantifying the index of information inconsistency degree;

[0062] Based on the information deviation value, the processing module further calculates the correlation degree between the nodes, sets a preset correlation degree threshold value for screening the key nodes, and determines the nodes with a correlation degree greater than the preset correlation degree threshold value as key nodes, connects the plurality of key nodes according to the chronological order of their time stamps, and generates a main chain which runs through the whole process of Gastrodia elata cultivation, the main chain is used for macro and efficient traceability of the whole process of Gastrodia elata cultivation.

[0063] In order to enhance the reliability of traceability and provide a backup verification path, at least one patrol point is set in the Gastrodia elata cultivation process, the patrol point refers to a physical location or logical marker set in the Gastrodia elata cultivation process for manual inspection, third party sampling inspection or independent data acquisition by a specific sensor, and at least one patrol point is defined as a patrol node, the patrol node is a special auxiliary node, its data usually comes from manual inspection, third party sampling inspection or independent acquisition by a specific sensor, and is designed to provide information which is mutually verified or supplemented with the main chain data, and the steps of generating the secondary chain specifically include:

[0064] For each key node in the main chain, among the above generated effective affiliated nodes, select the affiliated node with the same or approximate timestamp as the key node and determine it as a patrol node. The patrol node can contain the same or different type of data as the key node, but its time dimension is consistent with the key node of the main chain. Connect all selected patrol nodes in the order of their timestamps to form an independent patrol path, which is determined as a secondary chain. Its main function is to serve as a backup comparison channel for the main chain for subsequent data comparison and state judgment. In this way, the main chain and the secondary chain are defined as two independent monitoring paths based on traceability data, each carrying different verification functions.

[0065] In a specified time period, the first key parameter corresponding to the key node in the main chain and the second key parameter corresponding to the patrol node in the secondary chain are collected in parallel. The first key parameter is the core data indicator represented by the key node in the main chain, such as the growth cycle and yield prediction of Gastrodia elata. The second key parameter is an auxiliary or verification data indicator represented by the patrol node in the secondary chain, such as the growth conditions recorded by the patrol personnel and the independent measurement values of environmental parameters. The collected first key parameter data is recorded as first sampling data, and the collected second key parameter data is recorded as second sampling data.

[0066] To evaluate the reliability of the secondary chain, the collection deviation of the second sampling data in a continuous time period is calculated. This collection deviation is an indicator that measures the continuity and stability of the secondary chain data in the time dimension. For example, it can be determined by calculating the time interval difference between consecutive sampling points and the data fluctuation range. The steps for determining the secondary chain as an effective state include:

[0067] A specific time period for continuously collecting patrol data of the secondary chain and evaluating its reliability is set as a patrol interval, such as every 24 hours or every week. Within the patrol interval, the patrol data in the secondary chain is continuously collected and arranged in chronological order to form a sampling sequence. The sampling sequence is then input into a difference analysis module specifically designed for difference analysis. The difference analysis module analyzes the data in the sampling sequence according to pre-set logical rules and outputs the collection deviation. For example, the module can calculate the difference between adjacent data points in the sampling sequence and the deviation of the data from the average value. A first pre-set threshold is set to determine whether the secondary chain is in an effective state. If the collection deviation is less than the first pre-set threshold, the secondary chain is determined to be in an effective state, indicating that the data collection process of the secondary chain is stable and reliable, and can serve as an effective reference for the main chain.

[0068] Under the condition that the secondary chain is determined to be in the valid state, the synchronization state of the primary chain is further determined, the synchronization state refers to the consistency or coordination of the primary chain data and the secondary chain data in key parameters, if the deviation between the first sampling data from the primary chain and the second sampling data from the valid secondary chain is greater than a second preset threshold value for judging whether the primary chain is in the synchronization state, the primary chain is determined to be in the out-of-sync state, which indicates that some data in the primary chain may be abnormal or inconsistent with the actual situation, and the second preset threshold value can be set according to the tolerance of Gastrodia at different growth stages, thereby realizing the differentiation of the valid secondary chain or the primary chain abnormality, for example, in the seedling stage of Gastrodia, the tolerance of the deviation of the environmental parameters may be lower, and in the mature stage, the tolerance may be higher.

[0069] When the primary chain is determined to be in the out-of-sync state, the affiliated node in the primary chain that produces the deviation is determined to be an abnormal affiliated node, the abnormal affiliated node refers to a node whose data is significantly different from the secondary chain data, thereby causing the primary chain to be out of sync, for the abnormal affiliated node, a docking node is found and determined in the secondary chain, and the docking node is a node in the secondary chain that has a high matching degree in time and content with the abnormal affiliated node and has reliable data quality, and the steps of determining the abnormal affiliated node and replacing the abnormal affiliated node with the docking node specifically include:

[0070] The patrol deviation is calculated, the patrol deviation is the difference between the first sampling data and the second sampling data, and is used to quantify the inconsistency degree of the primary chain and the secondary chain data;

[0071] The continuous deviation judgment is performed, if the cumulative occurrence number of the patrol deviation of an affiliated node in a continuous determination interval exceeds a monitoring threshold value, the affiliated node is marked as an abnormal affiliated node of the primary chain, and a patrol node is selected from the secondary chain as a docking node to replace the abnormal affiliated node, and the selected patrol node needs to satisfy the following conditions:

[0072] The absolute value of the difference between the timestamp of the patrol node and the timestamp of the abnormal affiliated node is less than a preset time threshold value, and the absolute value of the difference between the content parameter of the patrol node and the content parameter of the abnormal affiliated node is less than a preset content threshold value, the preset content threshold value refers to a predetermined content parameter difference absolute value limit for screening the docking node, and the present application replaces the abnormal affiliated node in the primary chain with the docking node to correct the data abnormality of the primary chain. The continuous determination interval refers to a continuous time period for counting the cumulative occurrence number of the patrol deviation, and the monitoring threshold value refers to a predetermined numerical limit for judging whether the affiliated node is an abnormal affiliated node.

[0073] After the replacement is completed, the docking node is logically accessed to the primary chain and becomes part of the primary chain, which aims to use the reliable data verified in the secondary chain to correct the abnormality in the primary chain, thereby providing more accurate and reliable data support for the traceability data of the primary chain, and the steps of determining the docking node specifically include:

[0074] A time reference point of the abnormal affiliated node is determined, and all patrol nodes in the secondary chain that meet the following condition are searched: the absolute value of the difference between the time stamp of the patrol node and the time reference point is less than a preset time threshold; the time reference point is the time stamp of the abnormal affiliated node, which is used as a time reference point for searching a matching docking node in the secondary chain.

[0075] A difference between the content parameter of the found patrol node and the content parameter of the abnormal affiliated node is calculated, and if the difference is less than a preset content threshold, the patrol node is determined as the docking node and is imported into the primary chain, and a new round of verification is started to ensure the consistency of the replaced primary chain data.

[0076] The determination of the sampling frequency anomaly can include continuous monitoring of the sampling interval of the node, and if the sampling interval exceeds the preset standard, the node is determined as a node with abnormal sampling frequency and is excluded from the construction process of the data sub-chain. In addition, after the construction of the data sub-chain is completed, a deviation test can be performed on the nodes inside the sub-chain, and only the nodes that pass the deviation test are included in the generation process of the primary chain to ensure the accuracy and reliability of the data chain. When calculating the information deviation value between adjacent nodes, a time density coefficient can be combined, i.e., a coefficient for quantifying the density of data sampling in the time dimension, to obtain a composite correlation score for more accurately evaluating the correlation between nodes to adapt to the scene of multi-parameter coupled fluctuations in production. During the generation of the secondary chain, an environmental parameter disturbance test can be introduced to artificially interfere with environmental factors to make the sampling nodes of the secondary chain fluctuate under control, thereby forming a contrast analysis path to improve the corresponding ability of subsequent faults.

[0077] If abnormal affiliated nodes appear continuously in the primary chain, a replacement mechanism is started, at which time a multi-node joint comparison mechanism can be started to select multiple candidate nodes in the patrol nodes of the secondary chain for parallel verification, and then the most suitable node is selected as the docking node to access the primary chain.

[0078] In addition, when determining the docking node, a multi-parameter weighted scoring mode can be selected for the difference calculation between the patrol node and the abnormal affiliated node to improve the adaptation accuracy of the docking node. The multi-parameter weighted scoring mode refers to a scoring mode that calculates the differences between multiple content parameters of the patrol node and the abnormal affiliated node to comprehensively evaluate the adaptation accuracy when determining the docking node.

[0079] Through the above scheme, the present application realizes systematic tracing and fault-tolerant management of the whole growth period data of Gastrodia elata, and improves the real-time performance and reliability of the traceability system.

[0080] Embodiment two

[0081] Reference Figure 3The embodiment provides a chain traceability management system for Gastrodia cultivation, which can efficiently manage the traceability information of the whole process of Gastrodia cultivation by constructing a main chain and a vice chain, and can automatically correct the main chain by using the vice chain when data deviation occurs, so as to ensure the accuracy and reliability of the traceability information. In specific implementation, the system can be deployed on a server, a cloud platform or a dedicated data processing terminal, and communicates with various sensors, mobile terminals, cameras and manual input interfaces deployed on the Gastrodia cultivation site through a network interface, wherein the sensors include temperature and humidity sensors, soil component analyzers and illumination sensors. The system specifically comprises the following modules.

[0082] A link generation module

[0083] The module is responsible for initializing and constructing a main chain and a vice chain for traceability management, and the work flow thereof specifically includes:

[0084] The traceability information of the whole process of Gastrodia cultivation is acquired from multiple data sources, the traceability information includes planting information such as sowing time and seed source batch, environmental information such as real-time temperature, humidity and soil pH value, and harvesting information such as harvesting time, weight and grade, each data record acquired and having a time stamp and a geographical position is constructed into a basic subsidiary node;

[0085] A merging operation is performed on all collected subsidiary nodes to screen out valid subsidiary nodes, the operation includes: the values in the nodes are reviewed to eliminate abnormal values obviously beyond the reasonable range; time checking is performed to ensure the continuity and logic of the node time stamp; geographical position checking is performed to confirm that the data comes from the specified cultivation area, the module further analyzes the sampling frequency of the node, and determines and eliminates the nodes with abnormal sampling frequency caused by equipment failure or network problems;

[0086] The valid subsidiary nodes obtained through the merging operation are grouped according to data sources or types, and multiple data sub-chains are constructed, for each data sub-chain, an information deviation value between each node and its adjacent node in time is calculated by using a proofreading model, and the correlation degree between the nodes is further calculated based on the deviation value, and from each data sub-chain, a node with a correlation degree greater than a preset correlation degree threshold is selected as a key node;

[0087] All selected key nodes are connected in time sequence to generate the final main chain, and also responsible for generating the secondary chain as a reference benchmark. In a specific implementation, the pre-set inspection points in the cultivation process of Gastrodia elata, such as weekly manual on-site inspection, fertilization, pest control and other key operation nodes, are defined as inspection nodes, and these inspection nodes are connected in time sequence to generate the secondary chain. In another optional implementation, the module selects an auxiliary node with the same timestamp as the key node in the original auxiliary node set for each key node in the main chain, and determines it as an inspection node, thereby constructing a secondary chain that completely corresponds to the main chain in time point.

[0088] Link state determination module

[0089] The core task of this module is to periodically or upon receiving a trigger instruction, determine whether the main chain is in data accurate synchronization state by comparing the data of the main chain and the secondary chain. Its determination logic follows a double verification process:

[0090] Determine the secondary chain effective state of the secondary chain. The module calculates the collection deviation of the second key parameter corresponding to the continuous inspection nodes in the secondary chain in the continuous time period. The second key parameter includes but is not limited to the temperature value manually recorded by the experienced technician at the inspection point. If the collection deviation is less than a first preset threshold, it indicates that the data of the secondary chain is stable and reliable, and the secondary chain is determined to be in the secondary chain effective state and can be used as a proofreading benchmark.

[0091] Under the condition that the secondary chain is in the secondary chain effective state, the synchronization of the main and secondary chains is compared. The first key parameter corresponding to the key node in the main chain, such as the temperature value automatically collected by the sensor at the corresponding time, is extracted and compared with the second key parameter corresponding to the closest inspection node in the secondary chain. If the deviation between the two is greater than a second preset threshold, the module determines that the main chain and the secondary chain are out of synchronization, and generates an abnormal event signal to be transmitted to the main chain correction module.

[0092] Main chain correction module

[0093] The module is activated after receiving the abnormal event signal from the link state determination module, and performs main chain correction operation to restore the data accuracy of the main chain. The specific operation steps are as follows:

[0094] According to the information contained in the abnormal event signal, one or more abnormal auxiliary nodes associated with the deviation in the main chain are accurately identified;

[0095] The docking node for replacement is determined based on a reliable secondary chain, which takes the time stamp of the identified abnormal affiliated node as a time reference point, and then searches in the secondary chain to find a patrol node satisfying the following two conditions: first, the difference between the time stamp of the patrol node and the time reference point is less than a preset time threshold; second, the difference between the content parameter of the patrol node and the content parameter of the abnormal affiliated node is less than a preset content threshold, and the first patrol node satisfying the conditions is determined as the docking node.

[0096] The replacement operation is performed to replace the corresponding abnormal affiliated node in the primary chain with the just determined docking node, and through the operation, the error data in the primary chain is corrected by the correct data from the reliable secondary chain, so that the primary chain is restored to the synchronization state synchronized with the secondary chain.

[0097] Through the cooperative work of the above link generation module, link state determination module and primary chain correction module, the chain type traceability management system for Gastrodia cultivation of the present application can construct a double-chain traceability model with self-checking and repairing capabilities, which not only can record various traceability information in the cultivation process of Gastrodia, but also can actively identify and correct data abnormalities caused by sensor failure, data transmission error or human input error, etc., thereby significantly improving the credibility of traceability data and the robustness of the system, and is suitable for modern agricultural production management scenarios with extremely high requirements for product quality and safety traceability.

[0098] Embodiment three

[0099] A chain type traceability management terminal for Gastrodia cultivation, comprising at least one processor and a memory in communication connection with the processor, wherein the memory stores a computer program, and when the program is loaded and run on the processor, the processor executes the chain type traceability management method for Gastrodia cultivation.

[0100] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A chain-based traceability management method for Gastrodia elata cultivation, characterized in that, The method manages traceability information based on a main chain composed of key nodes and a secondary chain composed of patrol nodes, including: When it is determined that the main chain and the secondary chain are out of sync, a main chain correction operation is performed. The steps to determine if the main chain and the secondary chain are out of sync include: Determining the effective state of the sub-chain includes: calculating the collection deviation of the second key parameter corresponding to the patrol node in the sub-chain within a continuous time period; if the collection deviation is less than the first preset threshold, the sub-chain is determined to be in an effective state. If the deviation between the first key parameter corresponding to the key node in the main chain and the second key parameter corresponding to the patrol node in the sub-chain is greater than the second preset threshold when the sub-chain is in an asynchronous state, the main chain and the sub-chain are determined to be in an asynchronous state. Main chain correction operations include: Identify anomalous subsidiary nodes in the main chain that are associated with the occurrence of deviations; The docking node is determined based on the secondary chain, and the abnormal auxiliary node is replaced by the docking node to restore the synchronization state of the main chain; Among them, a node is the smallest unit of an independent event, state or data record that occurs at a specific point in time, and each node represents a specific event or state on the traceability chain; Key nodes refer to nodes selected from the data sub-chain whose relevance meets preset conditions, representing the most representative or information-rich links in the data sub-chain; Inspection nodes refer to the inspection points set in the cultivation process of Gastrodia elata, which are used for manual inspection, third-party sampling inspection or independent sensor data collection. Subsidiary nodes refer to detailed and frequent observation or operational data nodes generated around key stages or events; A docking node is a patrol node selected from the sub-chain that matches the abnormal subsidiary node in terms of time and content parameters.

2. The chain-based traceability management method for Gastrodia elata cultivation according to claim 1, characterized in that, The steps for generating the main chain and sub-chains include: Acquire traceability information including planting, environmental, and harvesting information, and set up multiple auxiliary nodes based on the traceability information; Perform a merge operation on multiple subsidiary nodes to construct multiple data subchains; Calculate the correlation between nodes in the data subchain, and select nodes whose correlation meets the preset conditions from each data subchain as key nodes. Connect multiple key nodes in chronological order to generate the main chain. The inspection points set in the cultivation process of Gastrodia elata are defined as inspection nodes, and the inspection nodes are connected in chronological order to generate a secondary chain.

3. The chain-based traceability management method for Gastrodia elata cultivation according to claim 2, characterized in that, The steps for performing a merge operation on multiple subsidiary nodes to construct multiple data subchains include: Perform value verification, time verification, and geographical location validation on the subordinate nodes; Identify and remove dependent nodes with abnormal sampling frequencies, and determine the remaining dependent nodes as valid dependent nodes for constructing the data subchain.

4. The chain-based traceability management method for Gastrodia elata cultivation according to claim 1, characterized in that, The steps for determining the docking node based on the secondary chain include: Use the timestamp of the abnormal subsidiary node as the time reference point; In the secondary chain, we find patrol nodes whose timestamp is less than a preset time threshold and whose content parameters are less than a preset content threshold compared to the content parameters of the abnormal subordinate nodes, and these nodes are used as docking nodes.

5. A chain-based traceability management method for Gastrodia elata cultivation according to claim 2, characterized in that, The steps for selecting nodes whose correlation meets preset conditions as key nodes from each data sub-chain include: Using a collation model, the information deviation value between a node and its temporally adjacent nodes is calculated, and the correlation degree is calculated based on the information deviation value. Nodes with a correlation degree greater than a preset correlation degree threshold are identified as key nodes.

6. A chain-based traceability management method for Gastrodia elata cultivation according to claim 2, characterized in that, The steps for generating secondary chains also include: For each key node in the main chain, select a subordinate node with the same timestamp as the key node and designate it as a patrol node, so as to connect all patrol nodes to form a sub-chain.

7. A chain-based traceability management system for Gastrodia elata cultivation, characterized in that, include: The link generation module is used to generate a main chain consisting of key nodes and a secondary chain consisting of patrol nodes based on the traceability information. The link status determination module is used to determine whether the main chain is out of sync by comparing the data of the main chain and the secondary chain. The main chain correction module is used to respond to the link status determination module's determination of the asynchronous state, identify abnormal auxiliary nodes in the main chain, and determine the docking node based on the secondary chain to replace the abnormal auxiliary node in order to restore the synchronization state of the main chain. Specifically, the determination of asynchronous states by the response link status determination module includes: Calculate the collection deviation of the second key parameter corresponding to the patrol node in the sub-chain within a continuous time period. If the collection deviation is less than the first preset threshold, the sub-chain is determined to be in a valid state. Under the condition that the sub-chain is in a valid state, if the deviation between the first key parameter corresponding to the key node in the main chain and the second key parameter corresponding to the patrol node in the sub-chain is greater than the second preset threshold, the main chain and the sub-chain are determined to be in an asynchronous state. Among them, a node is the smallest unit of an independent event, state or data record that occurs at a specific point in time, and each node represents a specific event or state on the traceability chain; Key nodes refer to nodes selected from the data sub-chain whose relevance meets preset conditions, representing the most representative or information-rich links in the data sub-chain; Inspection nodes refer to the inspection points set in the cultivation process of Gastrodia elata, which are used for manual inspection, third-party sampling inspection or independent sensor data collection. Subsidiary nodes refer to detailed and frequent observation or operational data nodes generated around key stages or events; A docking node is a patrol node selected from the sub-chain that matches the abnormal subsidiary node in terms of time and content parameters.

8. A chain-type traceability management terminal for Gastrodia elata cultivation, characterized in that, It includes at least one processor and a memory communicatively connected to the processor, wherein the memory stores a computer program that, when loaded and run on the processor, causes the processor to execute a chain traceability management method for Gastrodia elata cultivation as described in any one of claims 1 to 6.

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