CN-122023057-A - Agricultural product production whole-flow data management and control and intelligent analysis system and method

CN122023057ACN 122023057 ACN122023057 ACN 122023057ACN-122023057-A

Abstract

The application discloses a full-flow data management and control and intelligent analysis system and method for agricultural product production, and relates to the technical field of data management and control, wherein the system comprises a data acquisition module, a data management module and a data analysis module, wherein the data acquisition module is used for deploying an Internet of things sensor and a multispectral unmanned aerial vehicle to generate a crop growth digital file; the system comprises a storage deduction module, a yield optimization module, a data record module, a data query module, a crop adaptation module and an automatic grading module, wherein the storage deduction module is used for carrying out simulated growth deduction in a mechanism growth digital model, the yield optimization module is used for generating a yield optimization scheme according to target yield influence factors, the data record module is used for obtaining a digital fingerprint ID of crops and generating a query two-dimensional code, the data query module is used for constructing a crop knowledge graph and constructing a natural language question-answer interface at the front end, the crop adaptation module is used for generating a crop/mode plug-in and expanding according to the crop/mode adaptation plug-in, and the automatic grading module is used for carrying out computer vision identification on crop fruits and carrying out automatic grading. The application has the effect of improving the efficiency and accuracy of the whole flow data management and analysis of agricultural product production.

Inventors

LIU JIAN
YU WENCHAO
ZENG WENHUI
He Manxiang
LU JUN

Assignees

大农科技股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (9)

1. Agricultural product production full-flow data management and control and intelligent analysis system, its characterized in that includes: The data acquisition module is used for deploying the Internet of things sensor and the multispectral unmanned aerial vehicle in the field, monitoring the growth of crops to obtain the growth situation data and the agronomic operation data of the crops, and generating a crop growth digital file; The storage deduction module is used for storing the crop growth digital files, establishing a mechanism growth digital model, substituting a plurality of preset different plans into the mechanism growth digital model to carry out simulated growth deduction, and recording deduction results and yield influence factors generated in the deduction process; the yield optimization module is used for screening a plurality of deduction results to obtain an optimal target plan, extracting target yield influence factors corresponding to the target plan, and generating a yield optimization scheme according to the target yield influence factors; the data record module is used for extracting digital fingerprints of the crop growth digital files of crops in different batches, obtaining digital fingerprint IDs of the crops in each batch, storing the digital fingerprint IDs into a blockchain, and generating a query two-dimensional code; The data query module is used for extracting a relation structure between different data in the crop growth digital file, constructing a crop knowledge graph according to the relation structure and the crop growth digital file, and constructing a natural language question-answering interface at the front end according to the crop knowledge graph; The crop adaptation module is used for extracting historical plant data and/or historical mode data of new crops and/or new planting modes introduced by the farm, generating crop/mode plug-ins according to the historical plant data and/or the historical mode data, and expanding according to the crop/mode plug-ins; And the automatic grading module is used for acquiring crop grading standards in the current market, carrying out computer vision identification on crop fruits according to the crop grading standards, and carrying out automatic grading.
2. The agricultural product production complete flow data management and intelligent analysis system of claim 1, wherein the data acquisition module comprises: A sensor unit and an unmanned aerial vehicle unit; the sensor unit is used for acquiring a field map, and uniformly dividing the field according to the field map to obtain a plurality of small-range plots; deploying an internet of things sensor in each small-range land block, wherein the internet of things sensor is used for monitoring the root of crops and recording agronomic operations to obtain first growth data and agronomic operation data; the unmanned aerial vehicle unit is used for deploying multispectral unmanned aerial vehicles around the field according to the field map, the multispectral unmanned aerial vehicles patrol field crops according to a preset time interval, and data acquisition is carried out on stems, leaves and fruits of the crops to obtain second growth data; And combining the first growth data and the second growth data to obtain growth situation data of crops, and combining the growth situation data and the agronomic operation data to generate a crop growth digital file.
3. The agricultural product production full-process data management and intelligent analysis system of claim 2, wherein the storage deduction module comprises: A data storage unit and a model deduction unit; the data storage unit is used for carrying out error data identification on the crop growth digital file, carrying out error correction, and carrying out long-term stable storage on the corrected crop growth digital file; the model deduction unit is used for acquiring local historical crop yield, historical meteorological data and current soil data and constructing a digital model frame according to the historical crop yield, the historical meteorological data and the current soil data; substituting data in the crop growth digital archive into the digital model frame based on the crop growth digital archive to construct a mechanism growth digital model of the crop; substituting a plurality of preset different plans into the mechanism growth digital model, and carrying out mechanism growth deduction by the mechanism growth digital model according to each different plan to obtain a plurality of deduction results; And recording deduction process information of each plan in the deduction process, transversely comparing a plurality of deduction results to obtain a deduction result good-bad sequence, and identifying the deduction process information according to the deduction result good-bad sequence to obtain yield influence factors influencing the final yield.
4. A full-process data management and intelligent analysis system for agricultural product production according to claim 3, wherein the yield optimization module comprises: a plan screening unit and a data analysis unit; The plan screening unit is used for extracting the yield data in each deduction result and extracting the factor quantity and the factor processing difficulty of the yield influence factors in each deduction process; Weight distribution is carried out on the yield data, the factor quantity and the factor processing difficulty, and optimal index evaluation is carried out to obtain an optimal target plan; The data analysis unit is used for extracting target yield influence factors corresponding to the target plans and identifying the occurrence time period, the influence range, the influence depth and the occurrence reason of the target yield influence factors; And generating a problem processing scheme by combining the occurrence time period, the occurrence reason, the influence range and the influence depth, and optimizing the target plan according to the problem processing scheme to generate a yield optimization scheme.
5. The agricultural product production complete flow data management and intelligent analysis system of claim 4, wherein the data historian module comprises: A digital fingerprint unit and a query unit; The digital fingerprint unit is used for extracting crop growth characteristic data in the crop growth digital files of different batches of crops; Based on the crop growth characteristic data, carrying out unique characteristic identification on the crop growth characteristic data to obtain a target unique characteristic; based on the unique target characteristics, digital fingerprint extraction is carried out to obtain the digital fingerprint ID of crops in each batch, and the digital fingerprint ID is stored in a blockchain; And the inquiring unit is used for generating an inquiring two-dimensional code of each digital fingerprint ID based on the digital fingerprint ID, and linking the inquiring two-dimensional code to the crop growth digital file corresponding to each digital fingerprint ID.
6. The agricultural product production complete flow data management and intelligent analysis system of claim 5, wherein the data query module comprises: a knowledge graph unit and a front-end question-answering interface; the knowledge graph unit is used for extracting plant data, plant disease and insect pest data, pesticide data and agronomic data in the crop growth digital file; Identifying a relationship structure among the plant data, the plant disease and insect pest data, the pesticide data and the agronomic data, and constructing a crop knowledge graph of each batch of crops based on the relationship structure and the crop growth digital file; the front-end question-answering interface is used for constructing a natural language question-answering interface which is connected with the crop knowledge graph information, receiving external natural language questions by the natural language question-answering interface, and carrying out semantic analysis on the natural language questions to obtain a query target; searching in the crop knowledge graph based on the query target to obtain a target output result; The natural language question-answering interface is also provided with a conditional combination query component, wherein the conditional combination query component comprises four conditions of farm product type, growth period, time period and data type.
7. The agricultural product production complete flow data management and intelligent analysis system of claim 6, wherein the crop adaptation module comprises: The plug-in generation unit and the adaptation expansion unit; A plug-in generating unit for extracting historical plant data and/or historical mode data of new works and/or new planting modes introduced in the farm; Carrying out data extraction on the historical plant data and/or the historical mode data to obtain plant growth information and/or mode operation information; constructing a crop/mode plug-in according to the plant growth information and/or the mode operation information; The adaptation expansion unit is used for extracting basic environment information of the field according to the crop growth digital file, and carrying out suitability evaluation on the crop/mode plug-in unit according to the basic environment information to obtain adaptation error information; and adjusting the crop/mode plug-in according to the adaptation error information to obtain a target crop/mode plug-in, and performing system adaptation and expansion according to the target crop/mode plug-in.
8. The agricultural product production complete flow data management and intelligent analysis system of claim 7, wherein the automatic classification module comprises: The system comprises a market monitoring unit, an automatic grading unit and a real-time adjusting unit; The market monitoring unit is used for monitoring the sales information of the same type of crops in the market to obtain real-time sales information, and obtaining crop grading standards according to the real-time sales information; the automatic grading unit is used for calling a preset camera to perform computer vision identification on the crop fruits to obtain appearance condition data of the crop fruits; grading the crop fruits according to the appearance condition data and the crop grading standard; The real-time adjusting unit is used for monitoring the crop grading standard and unsold crop fruits and judging whether the crop grading standard changes or not; and if the crop grading standard is judged to be changed, the automatic grading unit is adjusted in real time, grade label information of currently unsold crop fruits is recorded, and the grade label information is corrected in real time.
9. A method for controlling and intelligently analyzing whole-process data of agricultural product production, which uses the whole-process data of agricultural product production control and intelligently analyzing system according to any one of claims 1 to 8, characterized in that the method comprises: The method comprises the steps of deploying an Internet of things sensor and a multispectral unmanned aerial vehicle in a field, monitoring the growth of crops to obtain growth situation data and agronomic operation data of the crops, and generating a crop growth digital file; Storing the crop growth digital file, establishing a mechanism growth digital model, substituting a plurality of preset different plans into the mechanism growth digital model to carry out simulated growth deduction, and recording a deduction result and yield influence factors generated in the deduction process; Screening a plurality of deduction results to obtain an optimal target plan, extracting target yield influence factors corresponding to the target plan, and generating a yield optimization scheme according to the target yield influence factors; Carrying out digital fingerprint extraction on the crop growth digital files of crops in different batches to obtain digital fingerprint IDs of the crops in each batch, storing the digital fingerprint IDs into a blockchain, and generating a query two-dimensional code; extracting a relation structure among different data in the crop growth digital file, constructing a crop knowledge graph according to the relation structure and the crop growth digital file, and constructing a natural language question-answering interface at the front end according to the crop knowledge graph; Extracting historical plant data and/or historical mode data of new crops and/or new planting modes introduced by a farm, generating crop/mode plug-ins according to the historical plant data and/or the historical mode data, and expanding according to the crop/mode plug-ins; And acquiring crop grading standards in the current market, performing computer vision recognition on crop fruits according to the crop grading standards, and performing automatic grading.

Description

Agricultural product production whole-flow data management and control and intelligent analysis system and method Technical Field The application relates to the technical field of data management and control, in particular to a system and a method for managing and controlling whole-flow data and intelligent analysis of agricultural product production. Background With the improvement of the quality safety attention of consumers to the agricultural products and the large-scale development of fresh-keeping industry, the full-chain management and control demands of the agricultural products from planting to output are increasingly urgent. In the prior art, when the whole production process of agricultural products is subjected to data management and control, a traditional manual supervision mode is adopted for data acquisition, then the acquired data is utilized, and then the data analysis and management and control are performed in a manual mode, so that a target result is expected to be obtained. However, the problems of inaccurate and incomplete data acquisition are easy to generate in a manual mode, so that problems occur in the subsequent data analysis process. On the other hand, when manually analyzing and managing data, there may be data processing deviation, and it is very time-consuming and labor-consuming. In addition, in the process of manual analysis, people needing data analysis know agricultural products, the variety of agricultural products is various, the modes of carrying out data processing on different types of agricultural products are different, and the pressure is very high for staff. Therefore, how to efficiently and accurately manage and control the whole flow data of agricultural product production and analyze intelligently becomes a problem to be solved. Disclosure of Invention The invention aims to provide a system and a method for managing and controlling whole flow data of agricultural product production and intelligent analysis so as to solve the problems in the background technology. In a first aspect, the present application provides a system for controlling and intelligent analysis of whole process data of agricultural product production, the system comprising: The data acquisition module is used for deploying the Internet of things sensor and the multispectral unmanned aerial vehicle in the field, monitoring the growth of crops to obtain the growth situation data and the agronomic operation data of the crops, and generating a crop growth digital file; The storage deduction module is used for storing the crop growth digital files, establishing a mechanism growth digital model, substituting a plurality of preset different plans into the mechanism growth digital model to carry out simulated growth deduction, and recording deduction results and yield influence factors generated in the deduction process; the yield optimization module is used for screening a plurality of deduction results to obtain an optimal target plan, extracting target yield influence factors corresponding to the target plan, and generating a yield optimization scheme according to the target yield influence factors; the data record module is used for extracting digital fingerprints of the crop growth digital files of crops in different batches, obtaining digital fingerprint IDs of the crops in each batch, storing the digital fingerprint IDs into a blockchain, and generating a query two-dimensional code; The data query module is used for extracting a relation structure between different data in the crop growth digital file, constructing a crop knowledge graph according to the relation structure and the crop growth digital file, and constructing a natural language question-answering interface at the front end according to the crop knowledge graph; The crop adaptation module is used for extracting historical plant data and/or historical mode data of new crops and/or new planting modes introduced by the farm, generating crop/mode plug-ins according to the historical plant data and/or the historical mode data, and expanding according to the crop/mode plug-ins; And the automatic grading module is used for acquiring crop grading standards in the current market, carrying out computer vision identification on crop fruits according to the crop grading standards, and carrying out automatic grading. Preferably, the data acquisition module includes: A sensor unit and an unmanned aerial vehicle unit; the sensor unit is used for acquiring a field map, and uniformly dividing the field according to the field map to obtain a plurality of small-range plots; deploying an internet of things sensor in each small-range land block, wherein the internet of things sensor is used for monitoring the root of crops and recording agronomic operations to obtain first growth data and agronomic operation data; the unmanned aerial vehicle unit is used for deploying multispectral unmanned aerial vehicles around the field according to the field map,