A chain type agricultural whole industry chain comprehensive management system and management and control method

Abstract

The application relates to the technical field of intelligent agriculture, and discloses a chain type agricultural whole-industry-chain comprehensive management system, which comprises a graph construction module, a chain type data merging and accounting module, a collection and exchange processing module, a link breakpoint analysis module and a cross-level scheduling execution module. The graph construction module is used for constructing a node operation distribution graph about the whole-industry-chain. The chain type data merging and accounting module is used for extracting flow data bound with one-code identification in chain operation data, performing merging and accounting processing on the flow data, and obtaining a node flow data set. The collection and exchange processing module is used for performing jurisdiction area mapping and collection and exchange processing on the node flow data set and the node operation distribution graph, and obtaining a node flow statistics account book. The link breakpoint analysis module is used for generating an industry coordination regulation list of administrative supervision nodes based on link flow breakpoints. The cross-level scheduling execution module is used for performing link repair and resource redistribution processing on the whole-industry-chain, and obtaining a management result of link penetration. The application can improve the coordination of the chain type agricultural whole-industry-chain comprehensive management.

Description

Technical Field

[0001] This invention relates to a comprehensive management system and control method for the entire chain of agriculture, belonging to the field of smart agriculture technology. Background Technology

[0002] With the continuous advancement of agricultural modernization and digital governance, integrated and collaborative management across the entire agricultural industry chain has become an important direction for improving the operational efficiency of the agricultural industry. Existing agricultural information management platforms are mostly built independently by a single link or a single entity, such as environmental monitoring at the planting end, production records at the processing end, and logistics query systems at the distribution end. Each entity relies on its own channels to collect and store data, achieving limited interoperability only through manual aggregation or simple interfaces. This decentralized construction model can only reflect the local operational status and cannot fully represent the overall connectivity of the entire agricultural industry chain in cross-linked flows.

[0003] In actual production, agricultural input supply, planting, storage, processing, logistics, and sales belong to different management and data systems. Significant differences in data collection standards, storage formats, and update timeliness lead to severe data silos, information gaps between links, and even regional flow blockages. This deficiency makes it difficult for county-level, township-level, and village-level administrative regulatory nodes to obtain a real-time view of the entire chain's operation. Regulatory instructions often rely on outdated manual reports, failing to accurately identify breakpoints in the flow. If a blockage occurs in a link without being detected by upstream and downstream in a timely manner, it will lead to mismatches between production and sales, idle resources, and agricultural product losses. Therefore, current technology lacks a method to effectively integrate administrative regulatory grids with full-chain flow data, enabling cross-node analysis and cross-level collaborative control, thereby ensuring the integrity of the industrial chain and the rational allocation of resources. Summary of the Invention

[0004] This invention provides a comprehensive management system for the entire chain of agricultural industry, the main purpose of which is to improve the synergy of the comprehensive management of the entire chain of agricultural industry.

[0005] To achieve the above objectives, the present invention provides a chain-based agricultural full-industry chain integrated management system, the system comprising: The map construction module is used to obtain the operation calibration data of each administrative supervision node in the entire agricultural industry chain, and construct a node operation distribution map of the entire agricultural industry chain based on the operation calibration data. The chain data merging and accounting module is used to collect chain operation data of the entire agricultural industry chain, extract the circulation data bound with one item one code identifier in the chain operation data, and perform merging and accounting processing on the circulation data to obtain node circulation dataset; The aggregation and processing module is used to perform hierarchical parsing of the chain operation data based on a preset administrative division coding system to obtain regulatory benchmarks, and to perform jurisdictional mapping and aggregation processing on the node flow dataset and the node operation distribution map based on the regulatory benchmarks to obtain a node flow statistical ledger. The link breakpoint analysis module is used to perform cross-node connectivity analysis on the node flow statistics ledger, obtain the link flow breakpoints, and generate the industrial collaborative regulation list of the administrative supervision node based on the link flow breakpoints. The cross-level scheduling and execution module is used to convert the industry collaborative regulation list into cross-level scheduling and execution instructions and send them to the corresponding administrative supervision nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, so as to obtain the management result of link connectivity.

[0006] Optionally, constructing a node operation distribution map of the entire agricultural industry chain based on the operation calibration data includes: Spatial coordinate registration and administrative division coding are performed on the calibration data to form a calibration dataset with geographic labels; Identify the industry category code and capacity lower limit parameter of each administrative regulatory node from the calibration dataset; Based on the industry category coding, the calibration dataset is divided into calibration subsets of different industry dimensions; Based on the lower limit of production capacity and the calibration subset, capacity density clustering and spatial adjacency modeling are performed on each administrative regulatory node to generate a node operation distribution map.

[0007] Optionally, the step of dividing the calibration dataset into calibration subsets with different industry dimensions based on the industry category coding includes: Identify the field structure template corresponding to the calibration dataset; Analyze the matching mapping relationship between the industry category code and the field structure template; Based on the matching mapping relationship, the calibration dataset is divided into calibration subsets of different industry dimensions.

[0008] Optionally, the step of extracting the circulation data bound to a unique item-code identifier from the chain-like operation data includes: The chained running data is subjected to time window alignment processing to obtain time-aligned link data; The time-aligned link data is parsed and validated using a unique identifier for each item, resulting in a transfer record with a verification mark. The node affiliation of the flow records is determined to obtain node-associated flow data; Based on the node-associated flow data, flow data bound to a one-item-one-code identifier is extracted from the chain-like operation data.

[0009] Optionally, the step of merging and calculating the transferred data to obtain a node transfer dataset includes: Construct the node inflow tensor and node outflow tensor corresponding to the flow data; Based on the node inflow tensor and the node outflow tensor, calculate the node inventory of the flowing data; The data flow is grouped and categorized according to administrative supervision nodes to obtain node grouping results; Based on the node grouping results, the number of inter-node transfers for each node is calculated. The node inventory, node inflow, node outflow, and number of inter-node transfers are mapped to the coordinate positions of the corresponding node grouping results to obtain the node transfer dataset.

[0010] Optionally, the step of performing hierarchical parsing of the chain-like operational data based on a preset administrative division coding system to obtain regulatory benchmarks includes: Extract the node encoding field from the chained running data; The node coding field is matched hierarchically with the administrative division coding system to obtain the node hierarchical affiliation result; Based on the node hierarchy attribution results, county-level nodes, township-level nodes, and village-level nodes in the chain-like operation data are identified. Select nodes where the levels intersect from the county-level nodes, township-level nodes, and village-level nodes to obtain regulatory benchmarks.

[0011] Optionally, the step of mapping and converging the node flow dataset with the node operation distribution map based on the regulatory benchmark to obtain a node flow statistical ledger includes: Obtain the spatial boundary data in the node operation distribution map; Based on the aforementioned regulatory benchmark, the node flow dataset is mapped to the corresponding spatial boundary to obtain the flow data within the boundary; The data flowing within the boundary is linked to the spatial boundary data by attribute association to obtain the linked data flowing within the boundary. The linked and transferred data are summarized level by level according to administrative divisions to obtain the node transfer statistics ledger.

[0012] Optionally, the step of summarizing the linked data at each administrative level to obtain a node transfer statistics ledger includes: Construct the village-level summary matrix corresponding to the linked and transferred data; Based on the village-level summary matrix, calculate the township-level convergence value; Based on the township-level convergence values, the county-level convergence values ​​are calculated. The village-level summary matrix, the township-level convergence values, and the county-level convergence values ​​are mapped to the corresponding administrative division's register structure to obtain the node flow statistics ledger.

[0013] Optionally, the step of performing cross-node connectivity analysis on the node flow statistics ledger to obtain the link flow breakpoint includes: Extract the inter-node transfer records from the node transfer statistics ledger to obtain node pairing transfer data; Determine the set of administrative regulatory nodes participating in the flow of node-paired data, and construct a link connection matrix between the administrative regulatory node sets based on the node-paired data. The continuity of the throughput values ​​in the link connection matrix is ​​reviewed to identify weak links whose throughput values ​​are lower than a preset normal operation threshold. The causes of the weak links were traced to identify the breakpoints in the link flow.

[0014] A management and control method for integrated management of the entire chain of agricultural industry, characterized in that the method includes: Obtain operational calibration data for each administrative regulatory node in the entire agricultural industry chain, and construct a node operational distribution map of the entire agricultural industry chain based on the operational calibration data; Collect chain operation data of the entire agricultural industry chain, extract the circulation data bound to one item one code in the chain operation data, and perform merging and accounting processing on the circulation data to obtain node circulation dataset; Based on the preset administrative division coding system, the chain operation data is parsed hierarchically to obtain the regulatory benchmark point. Based on the regulatory benchmark point, the node flow dataset and the node operation distribution map are mapped and converged by jurisdiction area to obtain the node flow statistical ledger. Cross-node connectivity analysis is performed on the node flow statistics ledger to obtain the link flow breakpoints, and an industry collaborative regulation list of the administrative supervision node is generated based on the link flow breakpoints. The industrial collaborative regulation list is converted into cross-level scheduling and execution instructions and sent to the corresponding administrative supervision nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, so as to obtain the management result of link connectivity.

[0015] This invention, by collecting and mapping operational data from various administrative regulatory nodes, eliminates data fragmentation across different administrative divisions in terms of industry base, operational standards, and spatial positioning. It establishes precise node anchors for the consolidation and accounting of chain-like operational data and lays a dual geographical and administrative reference foundation for cross-node interconnection analysis. By collecting chain-like operational data across the entire agricultural industry chain, this invention captures the flow of goods and operational connections at each administrative regulatory node in planting, breeding, processing, warehousing, logistics, and waste disposal stages, providing raw data support for the generation of subsequent node flow statistical ledgers. Furthermore, by performing hierarchical parsing of the chain-like operational data based on a pre-set administrative division coding system, this invention establishes a hierarchical relationship between administrative regulatory nodes and geographic space. The hierarchical affiliation provides a unified administrative reference for subsequent jurisdictional mapping and convergence processing. This invention, through cross-node interconnection analysis of the node flow statistics ledger, can track the complete path of goods flow in the entire agricultural industry chain and identify the connection status between various administrative regulatory nodes. By identifying chain flow breakpoints, the specific location and cause of logistics interruptions, capacity mismatches, or flow stagnation in the entire agricultural industry chain can be clearly identified, providing a targeted basis for generating an industry collaborative control list. This invention converts the industry collaborative control list into cross-level scheduling and execution instructions, transforming the textual arrangements in the list into operational instructions that administrative regulatory nodes can directly identify and execute, solving the execution deviation problem caused by distorted hierarchical transmission or ambiguous instruction expression in traditional agricultural industry control. Therefore, this invention can improve the synergy of comprehensive management of the entire chain-like agricultural industry chain. Attached Figure Description

[0016] Figure 1 A schematic diagram of modules for implementing a chain-type agricultural whole-industry chain integrated management system according to an embodiment of the present invention; Figure 2 A flowchart illustrating the interconnectedness of a chain-based agricultural industry chain integrated management system, as provided in an embodiment of the present invention. Figure 3 A flowchart illustrating a control method for integrated management of the entire chain agricultural industry chain, provided in an embodiment of the present invention; Figure 4 A schematic diagram of a computer device for a chain-type agricultural whole-industry chain integrated management system provided in an embodiment of the present invention; The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0018] This application provides a comprehensive management system for the entire chain of agricultural industries. The implementing entity of this comprehensive management system includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the comprehensive management system for the entire chain of agricultural industries can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0019] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments.

[0020] like Figure 1 The diagram shown is a schematic diagram of the modules of a chain-type agricultural whole-industry chain integrated management system of the present invention.

[0021] The integrated management system 100 for the entire chain of agricultural industries described in this invention can be installed in an electronic device. Based on the functions implemented, the integrated management system includes a graph construction module 101, a chain data merging and accounting module 102, a convergence processing module 103, a link breakpoint analysis module 104, and a cross-level scheduling and execution module 105. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0022] The map construction module 101 is used to acquire the operation calibration data of each administrative supervision node in the entire agricultural industry chain, and construct a node operation distribution map of the entire agricultural industry chain based on the operation calibration data.

[0023] This invention, by collecting and mapping operational calibration data from various administrative regulatory nodes, can eliminate data fragmentation in terms of industrial base, operational standards, and spatial positioning dimensions across different administrative divisions. It establishes precise node anchors for the merging and accounting of chain-like operational data and lays a dual geographical and administrative reference foundation for cross-node interconnection analysis.

[0024] The administrative supervision nodes include at least one level of unit among county-level agricultural and rural affairs bureaus, township agricultural service centers, village-level industry coordinating points, and management committees of key agricultural industrial parks; the operation calibration data includes at least one industry type of data among planting operation calibration data, breeding operation calibration data, agricultural product processing operation calibration data, warehousing and logistics operation calibration data, and agricultural waste treatment operation calibration data.

[0025] Specifically, constructing a node operation distribution map of the entire agricultural industry chain based on the operation calibration data includes: Spatial coordinate registration and administrative division coding are performed on the calibration data to form a calibration dataset with geographic labels; Identify the industry category code and capacity lower limit parameter of each administrative regulatory node from the calibration dataset; Based on the industry category coding, the calibration dataset is divided into calibration subsets of different industry dimensions; Based on the lower limit of production capacity and the calibration subset, capacity density clustering and spatial adjacency modeling are performed on each administrative regulatory node to generate a node operation distribution map.

[0026] Specifically, the spatial coordinate registration refers to aligning the operational calibration data of each administrative regulatory node with the basic geographic information data of the national land space and ensuring boundary matching. The administrative division code linkage refers to associating and mapping the operational calibration data with the unified administrative division codes of the National Bureau of Statistics. The industry category code refers to the classification identifier used to distinguish the five major industry categories of planting, breeding, processing, logistics and waste treatment. The capacity lower limit parameter refers to the smallest operational unit area or capacity threshold for each administrative regulatory node to be included in the statistics under a specific industry category. The capacity density clustering refers to identifying hotspots and grading gradients based on the operational scale within a unit administrative division area. The spatial adjacency modeling refers to constructing a hierarchical network structure between nodes based on the affiliation and geographical adjacency of administrative divisions.

[0027] It should be understood that the administrative regulatory nodes covered by the entire agricultural industry chain exhibit high heterogeneity in terms of hierarchical span, spatial distribution, and industrial form. Furthermore, the operational calibration data for different industry types differ significantly in terms of measurement dimensions, collection cycles, and accuracy levels. If unified modeling is directly performed without spatial coordinate registration and administrative division coding, it is highly likely to cause ambiguity in the administrative boundaries of nodes and crosstalk between industry attributes. Therefore, this module prioritizes establishing a unified spatial and administrative reference framework, and then implements differentiated segmentation according to industry category coding, aiming to achieve a balance between spatial positioning accuracy and industry classification accuracy.

[0028] Furthermore, as an optional embodiment of the present invention, dividing the calibration dataset into calibration subsets of different industry dimensions based on the industry category code includes: Identify the field structure template corresponding to the calibration dataset; Analyze the matching mapping relationship between the industry category code and the field structure template; Based on the matching mapping relationship, the calibration dataset is divided into calibration subsets of different industry dimensions.

[0029] The field structure template refers to the composition pattern of key fields in the calibration record, which is used to characterize the differentiated structural features of different industry categories at the data field level; the matching mapping relationship refers to the correspondence rules between the preset industry category code and the field structure template, which is used to merge calibration records with specific field composition patterns into the corresponding industry dimension.

[0030] Furthermore, a field structure template corresponding to the calibration dataset can be identified using a field fingerprint extraction algorithm; a pattern comparison is performed between a preset industry category coding dictionary and the field structure template to analyze the matching mapping relationship between the industry category code and the field structure template. The preset industry category coding dictionary is a set of reference data pre-established based on authoritative standards such as agricultural industry standards or national economic industry classification, used to associate industry category codes with corresponding agricultural industry chain links, field structure templates, or business dimensions. Based on the matching mapping relationship, grouping aggregation and set merging operations are performed to divide the calibration dataset into calibration subsets of different industry dimensions.

[0031] The chain data merging and accounting module 102 is used to collect chain operation data of the entire agricultural industry chain, extract the circulation data bound to one item one code identifier in the chain operation data, and perform merging and accounting processing on the circulation data to obtain node circulation dataset.

[0032] This invention, by collecting chain-like operational data across the entire agricultural industry chain, can capture the status of cargo flow and operational connections generated by each administrative regulatory node in the planting, breeding, processing, warehousing, logistics, and waste disposal stages. This provides raw data support for the generation of subsequent node flow statistical ledgers. The chain-like operational data refers to the set of original flow records generated by each administrative regulatory node in the entire agricultural industry chain throughout the entire process, recording cargo categories, weights, volumes, start and end points, and operation timestamps.

[0033] Specifically, the extraction of the flow data bound to a unique item-code identifier from the chain-like operation data includes: The chained running data is subjected to time window alignment processing to obtain time-aligned link data; The time-aligned link data is parsed and validated using a unique identifier for each item, resulting in a transfer record with a verification mark. The node affiliation of the flow records is determined to obtain node-associated flow data; Based on the node-associated flow data, flow data bound to a one-item-one-code identifier is extracted from the chain-like operation data.

[0034] The time-aligned link data refers to a standardized set of transfer records that have been corrected with a unified time reference and whose timestamp discrepancies have been eliminated; the one-item-one-code identifier refers to an identity code that is uniquely bound to a single agricultural product batch or work unit, using a QR code or electronic tag as a carrier; and the node-associated transfer data refers to a subset of transfer records that have completed node attribution matching and have a clear administrative jurisdiction.

[0035] Furthermore, the chain-like operation data can be aligned to a time window using a timestamp correction algorithm based on global clock synchronization to obtain time-aligned link data, such as correcting the drift of the local clock of each IoT terminal node using the BeiDou time signal as a reference; the time-aligned link data can be parsed and validated using a composite decoding method based on character pattern matching and verification to obtain circulation records with verification marks, such as extracting the batch code from the QR code payload and comparing it with the check bit for confirmation; the circulation records with verification marks can be used to determine the node affiliation by using the longest prefix matching method based on the administrative division coding tree to obtain node-associated circulation data, such as comparing the start and end node codes in the circulation records with the administrative division coding tree layer by layer to determine the administrative supervision node to which it belongs.

[0036] This invention obtains a node flow dataset by merging and calculating the flow data. This dataset can provide the distribution of total inflow and outflow of goods and the frequency of operation connections for each administrative regulatory node within a specific statistical period, providing a basis for subsequent hierarchical analysis and jurisdictional mapping. The node flow dataset refers to a set of statistical results that includes node inflow, node outflow, node inventory, and the number of transfers between nodes, formed by grouping and summarizing the flow data according to administrative regulatory nodes and industry categories.

[0037] In detail, the process of merging and calculating the transferred data to obtain the node transfer dataset includes: Construct the node inflow tensor and node outflow tensor corresponding to the flow data; Based on the node inflow tensor and the node outflow tensor, calculate the node inventory of the flowing data; The data flow is grouped and categorized according to administrative supervision nodes to obtain node grouping results; Based on the node grouping results, the number of inter-node transfers for each node is calculated. The node inventory, node inflow, node outflow, and number of inter-node transfers are mapped to the coordinate positions of the corresponding node grouping results to obtain the node transfer dataset.

[0038] Wherein, the node inflow tensor refers to a one-dimensional set of values ​​arranged in chronological order, recording the number of each batch of goods entering the administrative supervision node; the node outflow tensor refers to a one-dimensional set of values ​​arranged in chronological order, recording the number of each batch of goods leaving the administrative supervision node; the node stock refers to the cumulative number of goods remaining in the node at the end of a specific statistical period, and the value is an integer greater than or equal to zero; the number of inter-node transfers refers to the statistical value of the number of times goods are transferred between two administrative supervision nodes; and the node grouping result refers to the classification result of the transfer records to the corresponding administrative supervision nodes according to the administrative division code.

[0039] Furthermore, the node inflow tensor and node outflow tensor can be constructed using a one-dimensional array construction method based on ascending timestamps. For example, the inflow quantity of all batches of the same node within the statistical period can be stored in a one-dimensional array according to the operation timestamp from earliest to latest. Based on the node inflow tensor and node outflow tensor, the node stock of the circulation data can be calculated by accumulating the difference between batches. The circulation data can be grouped and classified according to administrative supervision nodes using an equivalent grouping method based on precise matching of administrative division codes to obtain node grouping results. For example, the start and end node codes in the circulation records can be compared with the list of administrative division codes one by one. If the codes match, they can be grouped into the corresponding node group. The node stock, node inflow, node outflow, and number of transfers between nodes can be mapped to the coordinate positions of the corresponding node grouping results using a two-dimensional array filling method based on node pairing counts to obtain the node circulation dataset. For example, the inflow, outflow, and stock of each administrative supervision node can be imported into the corresponding row and column positions of the two-dimensional array according to its hierarchical index and adjacency index.

[0040] The first method involves constructing a one-dimensional array based on ascending timestamps. This method stores the inflow or outflow quantities of all batches within a statistical period for the same administrative regulatory node in the corresponding positions of a one-dimensional array according to their operation timestamps from earliest to latest, forming an ordered node flow tensor. This is a common method for agricultural IoT data processing. The second method involves using an equivalent grouping method based on precise matching of administrative division codes. This method compares the start and end node codes in the flow records with a pre-configured list of administrative division codes. If the codes match, the nodes are grouped into the corresponding node group. This comparison process requires no additional learning process and has low computational overhead. The third method involves filling a two-dimensional array based on node pairing and counting. This method stores the node stock, inflow, outflow, and number of transfers between each administrative regulatory node and other nodes in the corresponding row and column positions of a two-dimensional array according to the node's hierarchical index and adjacency index in the administrative division system. The resulting structured data set is the node flow dataset. This process is completely consistent with the hierarchical conventions of administrative division codes and will not cause misalignment of attribution mapping.

[0041] The aggregation and processing module 103 is used to perform hierarchical parsing of the chain operation data based on a preset administrative division coding system to obtain regulatory benchmarks, and to perform jurisdictional mapping and aggregation processing on the node flow dataset and the node operation distribution map based on the regulatory benchmarks to obtain a node flow statistical ledger.

[0042] This invention performs hierarchical parsing of the chain-like operational data based on a preset administrative division coding system, which can establish a hierarchical relationship between administrative regulatory nodes and geographic space, providing a unified administrative reference benchmark for subsequent jurisdictional mapping and convergence processing.

[0043] The administrative division coding system refers to the set of hierarchical codes issued by the National Bureau of Statistics to identify the unique identity of administrative divisions at all levels; the regulatory benchmark point refers to the coordinates of administrative nodes identified from the chain-like operation data, which serve as the starting point for the mapping and aggregation of jurisdictional areas; the node circulation statistical ledger refers to the statistical book that records the total volume of goods circulation and the distribution of operational scale of each administrative regulatory node after the node circulation dataset and the node operation distribution map are aggregated and integrated according to the administrative division level.

[0044] In detail, the process of performing hierarchical parsing of the chain-like operational data based on a preset administrative division coding system to obtain regulatory benchmarks includes: Extract the node encoding field from the chained running data; The node coding field is hierarchically matched with the administrative division coding system to obtain the node hierarchical affiliation result; Based on the node hierarchy attribution results, county-level nodes, township-level nodes, and village-level nodes in the chain-like operation data are identified. Select nodes where the levels intersect from the county-level nodes, township-level nodes, and village-level nodes to obtain regulatory benchmarks.

[0045] Wherein, the node coding field refers to the unique code used to identify the identity of the administrative supervision node in the chained operation data; the node hierarchical attribution result refers to the administrative level category to which the node coding field belongs in the administrative division coding system; the hierarchical intersection node refers to the key node that undertakes the function of data intersection and aggregation in multiple administrative levels.

[0046] Furthermore, the node code field in the chained operation data can be extracted using a field extraction algorithm; the node code field can be hierarchically matched with the administrative division coding system using a prefix matching method to obtain the node hierarchical affiliation result; county-level nodes, township nodes, and village-level nodes in the chained operation data can be identified using hierarchical judgment logic; and hierarchical intersection nodes can be selected from the county-level nodes, township nodes, and village-level nodes using node importance scoring.

[0047] This invention maps and converges the node circulation dataset with the node operation distribution map based on the regulatory benchmark to obtain a node circulation statistical ledger. It can spatially overlay and attribute-summarize cargo circulation data and operation spatial distribution according to administrative divisions to form a regional statistical view that combines circulation scale and operation density.

[0048] In detail, the process of mapping and converging the node flow dataset with the node operation distribution map based on the regulatory benchmark to obtain a node flow statistical ledger includes: Obtain the spatial boundary data in the node operation distribution map; Based on the aforementioned regulatory benchmark, the node flow dataset is mapped to the corresponding spatial boundary to obtain the flow data within the boundary; The data flowing within the boundary is linked to the spatial boundary data by attribute association to obtain the linked data flowing within the boundary. The linked and transferred data are summarized level by level according to administrative divisions to obtain the node transfer statistics ledger.

[0049] The spatial boundary data refers to the geographic boundary vector data corresponding to each administrative regulatory node in the node operation distribution map; the flow data within the boundary refers to the subset of node flow data falling within a specific spatial boundary range; the attribute linking refers to the operation of associating and matching the goods category, weight and volume attributes in the flow data with the administrative code and industry category attributes in the spatial boundary data; the hierarchical aggregation refers to the process of aggregating data from bottom to top according to the administrative level order of village level → township level → county level.

[0050] Furthermore, spatial boundary data in the node operation distribution map can be obtained through a geographic information system interface; the node circulation dataset can be mapped to the corresponding spatial boundary using a spatial point-surface inclusion determination algorithm with the regulatory benchmark as a reference, to obtain circulation data within the boundary; the circulation data within the boundary can be attribute-linked with the spatial boundary data using an attribute association engine, to obtain linked circulation data; and the linked circulation data can be aggregated level by level according to administrative divisions using hierarchical aggregation operations to obtain a node circulation statistical ledger.

[0051] Furthermore, as an optional embodiment of the present invention, the step of summarizing the linked and transferred data level by level according to administrative division to obtain the node transfer statistics ledger includes: Construct the village-level summary matrix corresponding to the linked and transferred data; Based on the village-level aggregation matrix, the township-level convergence value is calculated using the following formula: in, This represents the aggregated values ​​at the township level. This represents the total transfer value of the i-th administrative village in the village-level aggregation matrix. This represents the supplementary transfer value of the directly subordinate nodes at the township level, where m represents the number of administrative villages under the township's jurisdiction. Based on the township-level convergence values, the county-level convergence values ​​are calculated. The village-level summary matrix, the township-level convergence values, and the county-level convergence values ​​are mapped to the corresponding administrative division's register structure to obtain the node flow statistics ledger.

[0052] The village-level summary matrix refers to a two-dimensional set of values ​​that summarizes the inflow, outflow, and stock of goods by administrative village; the supplementary transfer value of the township-level directly affiliated nodes refers to the transfer volume generated by nodes that do not belong to any administrative village and are directly managed by the township agricultural service center; the register structure refers to a standardized table framework arranged according to the administrative division level to carry the data collected at each level.

[0053] Furthermore, the village-level summary matrix corresponding to the linked data can be constructed using a two-dimensional array construction method based on administrative code grouping; the township-level convergence value can be calculated using a summation algorithm based on traversing and accumulating administrative villages within the township jurisdiction; the county-level convergence value can be calculated using a summation algorithm based on traversing and accumulating townships within the county jurisdiction; and the village-level summary matrix, the township-level convergence value, and the county-level convergence value can be mapped to the corresponding administrative division's register structure using a register generation method based on hierarchical index nesting and filling to obtain the node flow statistics ledger.

[0054] The two-dimensional array construction method based on administrative code grouping refers to grouping the linked transfer data according to the administrative village code, storing the inflow, outflow, and stock of each administrative village in the corresponding positions of the two-dimensional array in row and column order to form a village-level summary matrix. This is a common method for collecting agricultural statistical data. The summation algorithm based on traversing and accumulating administrative villages within the township jurisdiction refers to traversing all administrative villages under the township's jurisdiction according to the township's administrative division code list, accumulating the corresponding values ​​in the summary matrix of each village, and superimposing the supplementary transfer values ​​of the township's directly subordinate nodes to obtain the township-level converged values. The calculation process does not require additional learning process support and has high reliability. The book generation method based on hierarchical index nesting and filling refers to filling the converged values ​​of the village, township, and county levels into the corresponding hierarchical columns of the book structure according to their hierarchical index and subordinate relationship in the administrative division system. The resulting hierarchical statistical book is the node transfer statistical ledger. This process is completely consistent with the hierarchical convention of administrative division codes and will not cause hierarchical misalignment problems.

[0055] This invention, by obtaining the node circulation statistics ledger, can provide a regional data foundation for the generation of an industrial collaborative regulation list. The node circulation statistics ledger is a comprehensive statistical result of the circulation scale and operational density of the entire agricultural industry chain from an administrative division perspective. Furthermore, based on the node circulation statistics ledger, the circulation load and operational saturation of each administrative regulatory node can be identified. If the circulation volume of a node consistently exceeds the operational capacity limit of its jurisdiction, the node is marked as a congested circulation node and included in the key regulatory scope. Combined with the industrial density distribution in the node operational distribution map, diversion and capacity allocation measures can be deployed in advance in areas of excessive industrial agglomeration. Based on the convergence results at the administrative division level, the circulation quotas and operational indicators of each township are coordinated at the county level, ultimately forming a regionalized industrial governance view covering both spatial and administrative dimensions.

[0056] The link breakpoint analysis module 104 is used to perform cross-node connectivity analysis on the node flow statistics ledger to obtain link flow breakpoints, and generate an industry collaborative regulation list for the administrative regulatory node based on the link flow breakpoints.

[0057] This invention, through cross-node interconnection analysis of the node flow statistics ledger, can track the complete path of goods flow in the entire agricultural industry chain and identify the connection status between various administrative regulatory nodes; by obtaining the link flow breakpoints, it can clarify the specific location and cause of logistics interruption, capacity mismatch or flow stagnation in the entire agricultural industry chain, and provide a targeted basis for the generation of industry collaborative regulation list.

[0058] The link flow interruption point is a segment in the agricultural industry chain where the volume of goods flow between adjacent administrative regulatory nodes is lower than the normal operating threshold or the flow is interrupted.

[0059] In detail, the cross-node connectivity analysis of the node flow statistics ledger to obtain the link flow breakpoints includes: Extract the inter-node transfer records from the node transfer statistics ledger to obtain node pairing transfer data; Determine the set of administrative regulatory nodes participating in the flow of node-paired data, and construct a link connection matrix between the administrative regulatory node sets based on the node-paired data. The continuity of the throughput values ​​in the link connection matrix is ​​reviewed to identify weak links whose throughput values ​​are lower than a preset normal operation threshold. The causes of the weak links were traced to identify the breakpoints in the link flow.

[0060] The node pairing and transfer data refers to a structured record set that records the volume and type of goods transferred between the starting and ending administrative regulatory nodes; the administrative regulatory node set refers to the complete set of nodes formed by deduplicating the regulatory grids of counties, townships, and villages involved in the node pairing and transfer data; the link connection matrix is ​​a two-dimensional numerical array with the elements in the administrative regulatory node set as row and column indices and the volume of goods transferred between corresponding nodes as matrix element values, used to characterize the tightness of connection between each administrative division node in the physical industrial chain; the weak link refers to the node connection segment in the link connection matrix whose transfer volume value is significantly lower than the average level of the same period in history or the capacity output of adjacent upstream and downstream nodes; the cause tracing refers to investigating the operation links corresponding to the weak link and identifying the root cause categories (such as administrative division barriers, logistics channel blockages, or seasonal fluctuations in capacity) that lead to the decrease or interruption of the transfer volume value.

[0061] Furthermore, the inter-node transfer records in the node transfer statistics ledger can be extracted using an association query algorithm; a matrix framework can be constructed using the adjacency matrix construction method with the deduplicated set of administrative supervision nodes, and the transfer volume values ​​in the node pairing transfer data can be filled into the corresponding node coordinates to construct a link connection matrix between the set of administrative supervision nodes; the transfer volume values ​​in the link connection matrix can be continuously reviewed using the sliding window threshold comparison method to identify weak links; the causes of the weak links can be traced using a knowledge graph-based reasoning algorithm, and the root causes can be located by associating and querying the operation calibration data and external event databases. Finally, the root cause categories and associated evidence obtained by reasoning are mapped to the corresponding matrix coordinates to accurately locate the physical location and administrative affiliation of the link transfer breakpoint, thus obtaining the link transfer breakpoint.

[0062] Furthermore, as an optional embodiment of the present invention, the step of performing a continuity review on the throughput values ​​in the link connection matrix to identify weak links whose throughput values ​​are lower than a preset normal operation threshold includes: Calculate the historical average throughput of each node's connection segment in the link connection matrix; Based on the historical average throughput, set the normal operation threshold for each node connection segment; Compare the current throughput value in the link connection matrix with the normal operation threshold; The node connection segments whose current throughput value is lower than the normal operation threshold are marked as weak links.

[0063] The historical average throughput refers to the arithmetic mean of the throughput of a specific node connection segment within past statistical periods; the normal operation threshold is a critical value determined based on the historical average throughput combined with the seasonal fluctuation coefficient, used to determine whether the link operation status is normal.

[0064] Furthermore, the historical average throughput of each node connection segment in the link connection matrix can be calculated using the sliding window averaging method; the normal operation threshold of each node connection segment can be set based on the historical average throughput using the benchmark value weighting method; the current throughput value can be compared with the normal operation threshold using the numerical comparison method; and segments below the threshold can be marked as weak links using the status marking method.

[0065] This invention generates an industry collaborative regulation list for the administrative regulatory nodes based on the broken links, thereby enabling targeted adjustment and connection repair of production capacity, inventory, and logistics resources in the entire agricultural industry chain, reducing industry losses caused by link interruptions and improving the overall operational efficiency of the chain. The industry collaborative regulation list is a structured arrangement table that records the industry collaborative operation items, resource adjustment amounts, and responsible entities that each administrative regulatory node needs to perform in response to the broken links.

[0066] Furthermore, an industry collaborative regulation list of the administrative regulatory nodes is generated based on the broken links. First, the set of administrative regulatory nodes to be regulated is determined according to the location and cause of the broken links. Then, the resource adjustment amount and operation priority are calculated according to the severity of the broken links and the capacity margin of upstream and downstream nodes. Finally, the industry collaborative regulation list of the administrative regulatory nodes is generated.

[0067] The cross-level scheduling and execution module 105 is used to convert the industry collaborative regulation list into cross-level scheduling and execution instructions and send them to the corresponding administrative supervision nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, so as to obtain the management result of link connectivity.

[0068] This invention converts the industrial collaborative regulation list into cross-level scheduling and execution instructions, transforming the textual arrangements in the list into operational instructions that can be directly identified and executed by administrative regulatory nodes. This solves the problem of execution deviation caused by distorted hierarchical transmission or ambiguous instruction expression in traditional agricultural industrial regulation. The cross-level scheduling and execution instructions refer to a set of structured instructions carrying the code of the regulation item, the amount of resource allocation, the execution time limit, and the information of the responsible entity. The management result of the link connection refers to the operational effectiveness record of the restoration of the continuous flow of goods between administrative regulatory nodes in the entire agricultural industry chain after link repair and resource reallocation.

[0069] Specifically, the process of converting the industry collaborative regulation list into cross-level scheduling execution instructions includes: Analyze the regulatory items and circulation gap information in the industrial collaborative regulation list to obtain the regulatory elements to be implemented; Extract the flow gap and node capacity surplus recorded in the control elements to be executed; Determine the outgoing and incoming nodes in the control elements to be executed; By combining the aforementioned flow gap and the node's capacity surplus, the amount of goods transferred from the outgoing node to the incoming node is calculated. Based on the cargo flow adjustment volume, the allocation quantity field in the adjustment element to be executed is completed to obtain the quantitative adjustment element; The quantitative control elements are encoded and formatted to obtain the original scheduling instructions. The original scheduling instructions are routed and distributed according to administrative levels to obtain cross-level scheduling execution instructions.

[0070] The "to be executed control elements" refer to structured data items extracted from the industrial collaborative control list, recording the categories of goods to be adjusted, the outgoing nodes, the incoming nodes, and the circulation gaps. The outgoing nodes refer to the administrative supervision nodes of the goods outgoing party, and the incoming nodes refer to the administrative supervision nodes of the goods receiving party. The circulation gap refers to the difference between the normal operating threshold of the weak link and the actual circulation volume. The node capacity margin refers to the unused capacity quota of the outgoing and incoming nodes in the current statistical period. The "quantified control elements" refer to the control data set with executable values ​​after converting the circulation gap in the to be executed control elements into specific goods circulation control amounts. The "original scheduling instructions" refer to the set of primary instructions that have not yet undergone hierarchical routing, formed by encoding and encapsulating the quantified control elements according to a preset instruction format. The "administrative hierarchical routing" refers to the path arrangement for the original scheduling instructions to be transmitted layer by layer from the county-level nodes to the township nodes and then to the village-level nodes according to the administrative division coding system. The "issuance sequence arrangement" refers to the arrangement of multiple original scheduling instructions in the order of execution according to the urgency of the link breakpoints.

[0071] Furthermore, the regulatory items and circulation gap information in the industrial collaborative regulation list can be parsed using text parsing based on regular expressions and keyword positioning to obtain the regulatory elements to be executed; the quantitative regulatory elements can be encoded and formatted using data encapsulation based on fixed field templates to obtain the original scheduling instructions; and the original scheduling instructions can be routed by administrative level and arranged in a sequential order using a step-by-step addressing method based on administrative division code level prefixes to obtain cross-level scheduling execution instructions.

[0072] Furthermore, as an optional embodiment of the present invention, the resource adjustment amount corresponding to the original scheduling instruction can be calculated using the following formula: in, This indicates the resource adjustment amount corresponding to the original scheduling instruction. This indicates the amount of flow gap at the point where the link flow breaks down. This represents the urgency coefficient determined based on the duration of the breakpoint. This indicates the available capacity margin of the node being transferred in. This represents the minimum production capacity of the system.

[0073] The flow gap refers to the difference between the normal operating threshold and the actual flow volume of the weak link; the urgency coefficient is a weight value that increases with the duration of the breakpoint, used to prioritize links with longer breakpoint durations when resources are scarce; the available capacity margin refers to the capacity quota that the transferred node has not yet occupied in the current statistical period; the system minimum capacity base refers to the minimum capacity reserve that the transferred node still needs to maintain in a zero-load state, used to avoid division by zero when the available capacity margin is zero, and its value is determined based on the minimum capacity margin of the node in the past three statistical periods.

[0074] Furthermore, the turnover gap can be calculated using an algorithm based on the difference in turnover volume during the same period in history; the urgency coefficient can be determined using a segmented incremental lookup table method based on the duration of the breakpoint; and the available capacity margin can be calculated using an algorithm based on the difference between the upper limit of capacity and the used capacity in the node operation distribution map.

[0075] This invention, by issuing cross-level scheduling execution instructions to the corresponding administrative regulatory nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, can transform the written arrangements in the industry collaborative control list into actual operational actions in the fields. This ensures that the overall decision-making of the county-level node can be accurately transmitted to the township and village-level nodes and implemented. Furthermore, by issuing the cross-level scheduling execution instructions to the corresponding administrative regulatory nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, a management result of link connectivity is obtained. For example, when a county-level node determines that there is a shortage of agricultural processing raw materials between village-level nodes under a township node, a cross-level scheduling execution instruction is generated, carrying the code of the sending node, the code of the receiving node, the category of goods as processing raw materials, and the quantity of the adjustment as fifty tons. This instruction is relayed through the township node to the corresponding village-level node, where the sending node organizes the shipment of goods, the receiving node organizes the receipt and warehousing, and after the circulation is completed, execution confirmation information is sent back to the county-level node, resulting in a management result of link connectivity. For details, please refer to the following. Figure 2 This is a flowchart illustrating the link connection of a chain-based agricultural full-industry chain integrated management system according to an embodiment of the present invention. The flowchart details the complete closed-loop process of cross-level scheduling execution instructions from generation to implementation: The county-level node first detects and determines the problem of raw material supply interruption between village-level nodes, and then generates a scheduling instruction containing the code of the sending / receiving node, the type of goods, and the quantity of the adjustment; the instruction is relayed to the corresponding village-level node through the township node, and the sending node organizes the shipment of goods, and the receiving node organizes the receipt and storage, for example, realizing the cross-node flow of fifty tons of raw materials; after the flow is completed, the village-level node relays the execution confirmation information back to the county level through the township node, and finally the county-level node summarizes and settles the data to obtain the management result of link connection and supply and demand restoration.

[0076] like Figure 3 The diagram shown is a flowchart illustrating a control method for integrated management of the entire chain agricultural industry chain according to an embodiment of the present invention. In this embodiment, the control method for integrated management of the entire chain agricultural industry chain includes: S1. Obtain the operation calibration data of each administrative supervision node in the entire agricultural industry chain, and construct a node operation distribution map of the entire agricultural industry chain based on the operation calibration data; S2. Collect chain operation data of the entire agricultural industry chain, extract the circulation data bound to one item one code in the chain operation data, and perform merging and accounting processing on the circulation data to obtain node circulation dataset; S3. Based on the preset administrative division coding system, the chain operation data is parsed hierarchically to obtain the regulatory benchmark point, and the node flow dataset and the node operation distribution map are mapped and converged in the jurisdiction based on the regulatory benchmark point to obtain the node flow statistical ledger. S4. Perform cross-node connectivity analysis on the node flow statistics ledger to obtain the link flow breakpoints, and generate the industrial collaborative regulation list of the administrative supervision node based on the link flow breakpoints; S5. Convert the industrial collaborative regulation list into cross-level scheduling execution instructions and issue them to the corresponding administrative supervision nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, and obtain the management result of link connectivity.

[0077] In one embodiment, a computer device is provided, which may be a server or a client, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a chain-based agricultural industry chain integrated management system on the server or client side.

[0078] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0079] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0080] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0081] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0082] Finally, it should be noted that in the above embodiments, each embodiment can be combined with each other or independent. Deleting any one of them will not affect the technical implementation of other embodiments. The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A comprehensive management system for the entire agricultural industry chain, characterized in that, The system includes: The map construction module is used to obtain the operation calibration data of each administrative supervision node in the entire agricultural industry chain, and construct a node operation distribution map of the entire agricultural industry chain based on the operation calibration data. The chain data merging and accounting module is used to collect chain operation data of the entire agricultural industry chain, extract the circulation data bound with one item one code identifier in the chain operation data, and perform merging and accounting processing on the circulation data to obtain node circulation dataset; The aggregation and processing module is used to perform hierarchical parsing of the chain operation data based on a preset administrative division coding system to obtain regulatory benchmarks, and to perform jurisdictional mapping and aggregation processing on the node flow dataset and the node operation distribution map based on the regulatory benchmarks to obtain a node flow statistical ledger. The link breakpoint analysis module is used to perform cross-node connectivity analysis on the node flow statistics ledger, obtain the link flow breakpoints, and generate the industrial collaborative regulation list of the administrative supervision node based on the link flow breakpoints. The cross-level scheduling and execution module is used to convert the industry collaborative regulation list into cross-level scheduling and execution instructions and send them to the corresponding administrative supervision nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, so as to obtain the management result of link connectivity.

2. The integrated management system for the entire chain of agricultural industry as described in claim 1, characterized in that, The step of constructing a node operation distribution map of the entire agricultural industry chain based on the operation calibration data includes: Spatial coordinate registration and administrative division coding are performed on the calibration data to form a calibration dataset with geographic labels; Identify the industry category code and capacity lower limit parameter of each administrative regulatory node from the calibration dataset; Based on the industry category coding, the calibration dataset is divided into calibration subsets of different industry dimensions; Based on the lower limit of production capacity and the calibration subset, capacity density clustering and spatial adjacency modeling are performed on each administrative regulatory node to generate a node operation distribution map.

3. The integrated management system for the entire chain of agricultural industry as described in claim 2, characterized in that, The step of dividing the calibration dataset into calibration subsets with different industry dimensions based on the industry category coding includes: Identify the field structure template corresponding to the calibration dataset; Analyze the matching mapping relationship between the industry category code and the field structure template; Based on the matching mapping relationship, the calibration dataset is divided into calibration subsets of different industry dimensions.

4. The integrated management system for the entire chain of agricultural industry as described in claim 1, characterized in that, The extraction of the flow data bound to a unique item-code identifier from the chain-like operation data includes: The chained running data is subjected to time window alignment processing to obtain time-aligned link data; The time-aligned link data is parsed and validated using a unique identifier for each item, resulting in a transfer record with a verification mark. The node affiliation of the flow records is determined to obtain node-associated flow data; Based on the node-associated flow data, flow data bound to a one-item-one-code identifier is extracted from the chain-like operation data.

5. The integrated management system for the entire chain of agricultural industry as described in claim 1, characterized in that, The process of merging and calculating the transferred data to obtain the node transfer dataset includes: Construct the node inflow tensor and node outflow tensor corresponding to the flow data; Based on the node inflow tensor and the node outflow tensor, calculate the node inventory of the flowing data; The data flow is grouped and categorized according to administrative supervision nodes to obtain node grouping results; Based on the node grouping results, the number of inter-node transfers for each node is calculated. The node inventory, node inflow, node outflow, and number of inter-node transfers are mapped to the coordinate positions of the corresponding node grouping results to obtain the node transfer dataset.

6. The integrated management system for the entire chain of agricultural industry as described in claim 1, characterized in that, The method, based on a preset administrative division coding system, performs hierarchical parsing of the chain-like operational data to obtain regulatory benchmarks, including: Extract the node encoding field from the chained running data; The node coding field is matched hierarchically with the administrative division coding system to obtain the node hierarchical affiliation result; Based on the node hierarchy attribution results, county-level nodes, township-level nodes, and village-level nodes in the chain-like operation data are identified. Select nodes where the levels intersect from the county-level nodes, township-level nodes, and village-level nodes to obtain regulatory benchmarks.

7. The integrated management system for the entire chain of agricultural industry as described in claim 1, characterized in that, The process of mapping and converging the node flow dataset with the node operation distribution map based on the regulatory benchmark to obtain a node flow statistical ledger includes: Obtain the spatial boundary data in the node operation distribution map; Based on the aforementioned regulatory benchmark, the node flow dataset is mapped to the corresponding spatial boundary to obtain the flow data within the boundary; The data flowing within the boundary is linked to the spatial boundary data by attribute association to obtain the linked data flowing within the boundary. The linked and transferred data are summarized level by level according to administrative divisions to obtain the node transfer statistics ledger.

8. The integrated management system for the entire chain of agricultural industry as described in claim 7, characterized in that, The process of summarizing the linked and transferred data level by level according to administrative divisions to obtain a node transfer statistics ledger includes: Construct the village-level summary matrix corresponding to the linked and transferred data; Based on the village-level summary matrix, calculate the township-level convergence value; Based on the township-level convergence values, the county-level convergence values ​​are calculated. The village-level summary matrix, the township-level convergence values, and the county-level convergence values ​​are mapped to the corresponding administrative division's register structure to obtain the node flow statistics ledger.

9. A chain-type agricultural whole-industry chain integrated management system as described in claim 1, characterized in that, The cross-node connectivity analysis of the node flow statistics ledger, to obtain the link flow breakpoints, includes: Extract the inter-node transfer records from the node transfer statistics ledger to obtain node pairing transfer data; Determine the set of administrative regulatory nodes participating in the flow of node-paired data, and construct a link connection matrix between the administrative regulatory node sets based on the node-paired data. The continuity of the throughput values ​​in the link connection matrix is ​​reviewed to identify weak links whose throughput values ​​are lower than a preset normal operation threshold. The causes of the weak links were traced to identify the breakpoints in the link flow.

10. A management and control method for integrated management of the entire chain of agricultural industry, characterized in that, The method includes: Obtain operational calibration data for each administrative regulatory node in the entire agricultural industry chain, and construct a node operational distribution map of the entire agricultural industry chain based on the operational calibration data; Collect chain operation data of the entire agricultural industry chain, extract the circulation data bound to one item one code in the chain operation data, and perform merging and accounting processing on the circulation data to obtain node circulation dataset; Based on the preset administrative division coding system, the chain operation data is parsed hierarchically to obtain the regulatory benchmark point. Based on the regulatory benchmark point, the node flow dataset and the node operation distribution map are mapped and converged by jurisdiction area to obtain the node flow statistical ledger. Cross-node connectivity analysis is performed on the node flow statistics ledger to obtain the link flow breakpoints, and an industry collaborative regulation list of the administrative supervision node is generated based on the link flow breakpoints. The industrial collaborative regulation list is converted into cross-level scheduling and execution instructions and sent to the corresponding administrative supervision nodes to perform the link repair and resource reallocation processing of the entire agricultural industry chain, so as to obtain the management result of link connectivity.

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