With the rapid development of science and technology, the agricultural industry has gradually ushered in an era of digital transformation. In this process, agricultural big data has become one of the key factors to promote agricultural modernization. The widespread application of big data in agriculture can not only help improve agricultural production efficiency, but also reduce resource waste, optimize the supply chain of agricultural products, and promote sustainable agriculture.
01 Agricultural big data
1. Increase yield
Big data in agriculture provides farmers and agricultural practitioners with more basis for decision-making. By collecting, integrating, and analyzing various data in the agricultural production process, such as meteorological data, soil information, crop growth, etc., farmers can understand important information such as crop growth status, pest and disease risks, etc. in a timely manner. Based on this data, they can take appropriate measures, such as adjusting the amount of irrigation water, fertilizer application, pesticide use, etc., to optimally manage their farmland. In addition, big data in agriculture can also help farmers make more accurate market forecasts and choose the right crops to plant, thereby improving yields and economic benefits.
2. Information Collection
The application of big data in agriculture helps to optimize the supply chain management of agricultural products. In the traditional supply chain of agricultural products, problems such as poor information flow and information asymmetry often lead to a large gap between the supply and demand of agricultural products. Through the application of agricultural big data, a series of functions such as traceability management, logistics optimization and market monitoring of agricultural products can be realized, and the transparency and efficiency of the agricultural product supply chain can be improved. All kinds of data on the origin, planting, picking, processing and transportation of agricultural products can be recorded, tracked and shared, and consumers can learn about the production process and quality information of agricultural products by scanning the QR code on the goods or querying the database, which increases consumers' trust in agricultural products.
3. Sustainable development
The application of big data in agriculture will also help promote the sustainable development of agriculture. With the growth of the global population and the finite nature of resources, sustainable agriculture has become a top priority. Through the application of agricultural big data, the precise management of agricultural product production can be realized, the use of agricultural inputs such as pesticides and fertilizers can be reduced, and waste and environmental pollution can be avoided. In addition, agricultural big data can also help farmers choose crop varieties that are more suitable for local climate and soil conditions, improve the adaptability of crops, and reduce the impact of natural disasters on agriculture.
02 Agricultural big data
1. Data collection and recording
The agricultural big data system should be able to collect and record a variety of data related to agricultural production in real time and accurately, including meteorological data, soil information, crop growth data, etc. These data need to be collected automatically through sensors, monitoring equipment and other means to ensure the accuracy and timeliness of the data.
2. Data storage and management
Agricultural big data systems need to provide reliable data storage and management functions to ensure the safe and efficient acquisition of data. The data store should have a scalable architecture that supports large-scale data storage and processing, and has data backup and disaster recovery capabilities.
3. Data analysis and mining
The agricultural big data system should have strong data analysis and mining capabilities, and be able to extract valuable information from massive data and realize in-depth data mining. Data analysis can include data visualization, statistical analysis, machine learning and other methods to discover potential patterns and trends in the data and provide a scientific basis for agricultural decision-making.
4. Decision support and forecasting
Based on the results of data analysis, the agricultural big data system should be able to provide decision support and prediction functions, and provide accurate decision-making suggestions for farmers and agricultural practitioners. The system can help farmers optimize farmland management, crop planting, pest control and other decision-making through model prediction and scenario analysis to maximize agricultural production benefits.
5. Data sharing and interaction
The agricultural big data system should support the sharing and interaction of data to promote cooperation and information flow among all parties involved in agricultural production. Farmers, agricultural product processing enterprises, and supply chain managers can participate in the agricultural production process through data sharing, so as to realize information sharing and optimize resource utilization.
6. Intelligent perception and early warning
The agricultural big data system should be able to grasp the information of crop growth, meteorological changes, pest and disease risks in a timely manner through intelligent perception technology, and provide corresponding early warning functions. This can help farmers take timely measures to avoid losses and reduce agricultural risks.
7. Traceability and quality management
The agricultural big data system should have traceability and quality management functions, which can track and record the production process, source and quality information of agricultural products. Consumers can learn about the production process and quality information of agricultural products by scanning the QR code on the product or querying the database, and increase their trust in agricultural products.
03 Development trend
The application of agricultural big data in modern agriculture has broad prospects. Through the rational use and analysis of agricultural big data, we can realize the intelligent, precise and sustainable development of agricultural production, and inject new impetus into promoting agricultural modernization. However, the application of agricultural big data also faces some challenges, such as data security and privacy protection, so it is necessary to strengthen the formulation and supervision of relevant policies to ensure the safe and legal use of data in the process of promoting the application of agricultural big data. Only by giving full play to the advantages of agricultural big data can we achieve sustainable development and precise management of agriculture, and make greater contributions to global food security and farmers' well-being.
Research on the development strategy of agricultural big data and information infrastructure
I. Preface
Agricultural big data is the practice of big data concepts, technologies and methods in the field of agriculture. After entering the era of big data and information technology, agricultural big data and intelligent analysis technology have developed into a new type of modern agricultural production factor for agricultural practitioners to discover new knowledge, create new value and improve production capacity, and are also important new strategic resources of the country. Through the continuous transformation of agricultural production methods, business models and management service methods, agricultural big data can provide new impetus for the transformation and development of agricultural and rural economic structure. Agricultural informatization infrastructure refers to the basic information hardware, application terminals and basic equipment that provide informatization public services for agriculture and rural areas, mainly including agricultural data acquisition facilities, agricultural data storage and computing power, agricultural and rural network communication, agricultural information application terminals, and agricultural informatization integration infrastructure. Agricultural big data and information infrastructure is an important foundation for the development of modern agriculture and the fundamental premise for the construction of smart agriculture, which plays an important role as a bridge and cornerstone.
From a global perspective, the "new infrastructure" is promoting a new round of information revolution, and many countries have taken the development of big data, fifth-generation mobile communications (5G) and other new-generation information technology and infrastructure as the priority direction of strategic deployment, such as the United States has launched the "Big Data Research and Development Program", "National Broadband Plan", "Connect to America Fund" and other strategic plans, the United Kingdom has launched the "Agricultural Technology Strategy", and Germany has released "Industry 4.0", "Digital Agenda (2014-2017)" and "Digital Strategy 2025". Japan has launched its "Future Investment Strategy". In recent years, the mainland has attached great importance to and actively promoted the construction of agricultural big data and information infrastructure, and has successively issued the "Broadband China" Strategy and Implementation Plan, the Action Plan for Promoting Big Data Development, the Pilot Program for Agricultural and Rural Big Data, the Outline of the Digital Rural Development Strategy, and the Digital Agriculture and Rural Development Plan (2019-2025).
The "Outline of the 14th Five-Year Plan for National Economic and Social Development of the People's Republic of China and the Long-Range Objectives Through the Year 2035" proposes to accelerate the construction of a national integrated big data center system, build a number of national hub nodes and big data center clusters, and accelerate the development of smart agriculture. The implementation of a series of documents and major decision-making arrangements will further promote the development of agricultural big data and information infrastructure in the mainland. In terms of academic research, domestic researchers have carried out a series of studies on key technologies, platform architecture, and application practices of agricultural big data. On the whole, the technology and application of agricultural big data in mainland China have developed rapidly, and great progress has been made in the acquisition of "sky and ground" big data, big data modeling, analysis and prediction, and data-driven intelligent decision-making, and the application of big data is covering the whole process of the entire agricultural industry chain.
2 The development status of agricultural big data and information infrastructure construction
(1) The level of agricultural information monitoring technology, transmission technology and computing technology has been significantly improved, and the agricultural information infrastructure has been continuously improved
With the in-depth implementation of strategies such as "broadband villages", important achievements have been made in the development of agricultural informatization infrastructure in mainland China in terms of data acquisition capacity, data resource construction, data computing power, agricultural and rural network communication, and application terminals.
The level of agricultural data monitoring technology has been continuously improved. The mainland's first agricultural high-resolution observation satellite was successfully launched into orbit and put into application in 2018, breaking the long-term dependence on foreign suppliers for high-resolution earth observation data. In terms of ground Internet of Things sensors, a number of low-cost and practical agricultural sensors have been produced, covering meteorology, soil, water, plant life information, physiological and biochemical information, animal behavior recognition, etc., which have played an important role in agricultural information monitoring and data acquisition. The "sky and ground" digital agriculture technology has gradually taken shape, and an integrated observation system has been established by comprehensively using aerospace remote sensing, aerial remote sensing, and ground Internet of Things to realize high-precision, three-dimensional, and continuous acquisition of agricultural information in time and space.
The construction of the national agricultural big data collection system has been continuously improved, and the Internet of Things, intelligent equipment, mobile Internet and other information technologies have been used to collect agricultural and rural data, which has improved the efficiency and quality of data collection. The basic agricultural database has been gradually established and improved, and the centralized and unified management of basic agricultural survey data has been realized. The agricultural product market information platform has formed an agricultural big data resource pool, gathering the whole industrial chain data of 15 key agricultural products in 8 categories, such as grain, cotton, oil, sugar, livestock and poultry products, aquatic products, vegetables, fruits, etc., with more than 1×105 new data added every day, and about 21×109 agricultural data of various types have been accessed cumulatively, becoming the convergence center of agricultural product market information data in the mainland.
Agricultural and rural network facilities have been continuously improved. The mainland has initially built a ubiquitous, safe, and green broadband network environment, and has basically realized "urban fiber-to-the-building to the home, and rural broadband to the countryside and villages", and the era of "the same network and the same speed" between rural and urban areas is coming. By the end of 2020, the Internet penetration rate in rural areas was 55.9% and 79.8% in urban areas, and the gap between urban and rural Internet penetration rates has narrowed significantly. More than 98% of administrative villages across the country have access to optical fiber and fourth-generation mobile communications (4G), achieving the world's leading rural network in terms of coverage. By the end of 2020, the total number of rural broadband users in China reached 14,2×108, a year-on-year increase of 5.3%, accounting for 29.3% of the total number of Internet access users. The integration of the national cable television network and the construction of radio and television 5G have been integrated, and rural radio and television households have basically been connected.
Computing power in agriculture is constantly improving. After years of continuous accumulation, the mainland has made important progress in the field of artificial intelligence (AI), the number of international scientific and technological papers published and the number of invention patents authorized have ranked among the top in the world, and important breakthroughs have been made in core and key technologies in some directions. Adaptive self-learning, intuitive perception, integrated reasoning, hybrid intelligence, and swarm intelligence have initially developed by leaps and bounds, intelligent monitoring and biometric recognition have gradually entered practical applications, and new and efficient algorithms have promoted AI innovation and entrepreneurship to become increasingly active. With the in-depth integration of agriculture and AI technology, high-performance algorithms and intelligent models continue to be innovated and developed, and are efficiently applied in intelligent decision-making in all aspects of the entire industry chain such as agricultural production, circulation, and markets. Agricultural big data computing pays more attention to finding correlations and predictive analysis from massive data, and agricultural data processing is evolving from traditional data mining, machine learning, and statistical analysis to intelligent analysis and early warning model systems.
The "new infrastructure" of agriculture kicked off. The construction of new infrastructure such as agricultural and rural big data centers has been accelerated, new technologies, new products and new formats of digital agriculture have been emerging, and Beidou, 5G, the Internet of Things, agriculture-specific sensors and intelligent equipment have accelerated their application in rural areas to accelerate the development of smart agriculture. For example, Yangling Demonstration Zone in Shaanxi Province has actively promoted the construction of 5G informatization, relying on 5G technology to build an agricultural big data management and control center and an agricultural production operation control system based on the Internet of Things, and the Nanjing National Agricultural High-tech Industry Demonstration Zone in Jiangsu Province has cooperated with China Mobile Communications Group Co., Ltd. Jiangsu Branch to plan 3 During the year, "5G+4G" full coverage was achieved in the region, injecting new digital momentum into agricultural technology innovation.
5G-enabled information enters villages and households, and highlights such as "5G+" Yinong cloud e-commerce live broadcast, "5G+" smart farming, "5G+" smart planting, and 5G smart agricultural machinery frequently appear. In addition, the digital transformation of rural traditional infrastructure has accelerated, the digital transformation and upgrading of rural power grids, smart water conservancy, rural logistics, agricultural machinery and equipment have been accelerated, a map of national water conservancy, the basic attributes of national rural roads and an electronic map database have been completed, the pace of digitalization of agricultural machinery and equipment has accelerated, and the application of Beidou terminals has been continuously expanded.
(2) Breakthroughs have been made in the standardization, acquisition, analysis and processing, management and other technologies of agricultural information, and remarkable results have been achieved in the construction of agricultural big data
Agricultural big data in mainland China is in the historical stage of long-term continuous growth, and agricultural resources (such as atmosphere, soil, water, biomass, etc.), agricultural environment (such as meteorology, hydrology, soil moisture, temperature and humidity, etc.), agricultural crops (such as crop growth, yield, diseases and pests, etc.), agricultural processes (such as breeding, fertilization, harvesting, transportation, sales, etc.) and many other aspects are continuously generating massive data resources.
First, a complete framework for big data standardization has been established. Standards and standardization are the basic guarantee for the rapid analysis and application of big data, and they are also the inevitable choice for agriculture to enter the era of big data. In 2014, the National Information Technology Standardization Technical Committee set up a big data standards working group to formulate, revise and improve the big data standard specification system, proposing that the system should include seven categories: basic standards, data standards, technical standards, platform/tool standards, management standards, security standards, and industry application standards. On the basis of extensive research, the Chinese Academy of Agricultural Sciences analyzed the actual situation and needs of the current standardization and standardization of agricultural big data in mainland China, and formed a framework proposal for the standardization of agricultural big data (see Figure 1). According to statistics, the Ministry of Rural Agriculture has issued a total of 6,575 relevant standards and specifications, involving agricultural foundation, agricultural machinery, process technology, environmental requirements, product standards, grade specifications, food safety, quality inspection, disease prevention and control, labeling and other categories, providing method guidance for the acquisition, analysis and application of agricultural big data.
The second is to develop effective data management norms and multi-level agricultural and rural big data centers. Since the start of construction of the Golden Agriculture Project in 1994, after years of development and improvement, the mainland has initially formed a multi-level agricultural big data system. The Ministry of Agriculture and Rural Affairs, in conjunction with relevant departments, has steadily promoted the development of agricultural big data, and has successively established 23 sets of statistical survey systems (with a total of more than 300 reports and 5×104 indicators) focusing on agricultural resources and environment, agricultural production, agricultural product processing, and market operation, and has built 18 data marts with the themes of output, prices, imports and exports, and costs and benefits of major agricultural products, with about 3×105 daily updates. At present, the Ministry of Agriculture and Rural Affairs is organizing the construction of an agricultural and rural big data center and a national platform. The big data platform of China's seed industry integrates the seed industry management data at the national, provincial, prefecture (city) and county levels, and simultaneously collects the industry data of variety approval, registration, protection and promotion.
The China Agricultural Technology Extension Information Platform has gathered 2.4×105 grassroots agricultural technicians across the country, and the total number of requests on the platform has exceeded 3×109. The Guizhou Provincial Department of Agriculture and Rural Affairs has organized the construction of a unified management platform for agricultural big data, and has put into operation more than 20 agricultural information service systems such as animal disease monitoring, soil resource management, agricultural product quality traceability, agricultural dispatching, and agricultural machinery purchase. The big data platform of Bohai Granary Science and Technology Demonstration Project has the functions of massive data source diversity, multi-factor comprehensive analysis and decision-making, etc., and effectively guides the grain production management and decision-making process in the demonstration area, covering 30 counties and 1.5×107 mu of grain fields (1 mu ≈ 666.67 m2). The Agricultural Information Institute of the Chinese Academy of Agricultural Sciences has developed and established the China Agricultural Market Monitoring and Early Warning System, which covers the big data resources of the entire industrial chain of production, circulation and market of important agricultural products, supports the monitoring and early warning work of the agricultural market, and publishes the "China Agricultural Outlook Report" year by year.
Third, a series of agricultural big data technology application models have been formed. The integration of agricultural big data with information technologies such as the Internet, cloud computing, and AI has changed the traditional agricultural model and promoted the development of smart agriculture. In terms of efficient agricultural breeding, AI technologies such as big data mining, artificial neural networks, and deep learning are deeply integrated and applied with modern biotechnology to discover excellent genes and accelerate independent innovation in the whole chain of breeding. In terms of agricultural production management, a large number of data such as environmental factors, animal and plant growth collected in the production process are analyzed and processed, scientific and precise control is implemented, agricultural production is optimized, and the goal of improving efficiency and increasing income is achieved.
In terms of agricultural product market monitoring, the technical system of collection, analysis, release and service of information on the whole industrial chain of agricultural products supported by big data provides effective market information services for agricultural production and operation entities and promotes the accurate docking of production and marketing of agricultural products. In terms of rural management services, agricultural big data is combined with the sharing economy, and the integration and exchange of resources are realized through the "Internet +" big data platform, so as to maximize, optimize and accurately match rural resources and rural tourism consumption demand, and promote the high-quality development of leisure agriculture and rural tourism. In addition, the application of data service software and hardware carriers such as intelligent decision-making systems, information push services, and mobile intelligent terminals, as well as related big data service applications, has been gradually promoted in the agricultural field.
3. The main problems existing in the construction of agricultural big data and information infrastructure
(1) Rural network infrastructure is still weak
Although the mainland's informatization infrastructure has made a series of important achievements, it still faces problems such as the lag in the construction of rural network infrastructure, the obvious gap between urban and rural digital development, the lack of informatization infrastructure in planting and breeding bases, and the insufficient integration of traditional infrastructure and informatization. Compared with urban areas, there is still a large gap in the penetration rate and access speed of fiber broadband users in rural areas, and the proportion of rural Internet users is low. By the end of 2020, there was still a 23.9 percentage point gap between urban and rural areas in mainland China, and the digital divide between urban and rural areas had not yet been bridged. According to the questionnaire survey data distributed in this study, 27.2% of the planting and breeding bases have been opened to optical fiber broadband, about 13.6% of them use farmers' information terminals to monitor or control crop planting and production, and 19.7% of them believe that the network speed of the planting base cannot meet the needs of agricultural applications. Problems such as the low proportion of farmers connected to the Internet, the low proportion of optical fiber broadband in planting and breeding bases, and poor network signals have restricted the promotion and application of smart agriculture technology.
(2) Insufficient capacity to obtain, analyze, apply and share agricultural data
Digital resources are scattered, and the ability to obtain data from the "sky and ground" integration is not strong and the coverage rate is low. There is a big gap between the domestic sensor technology and the world's advanced level, among which there is a serious shortage of digital, intelligent and miniaturized technology products. The ability of agricultural data analysis and application is insufficient, and the value of data elements is still greatly limited, and many agricultural big data monitoring platforms still stay at the level of data collection, rough processing, and phenomenon display, especially in the "last mile" of agriculture and rural areas, and grassroots agricultural service enterprises that directly connect with small farmers usually do not have the ability to develop big data platform research and development technology and big data analysis and mining. There are still many barriers to agricultural data sharing, the sharing is seriously insufficient, and the data is mostly protected as personal or departmental wealth, and the level of development and utilization is still low due to data monopoly or monopoly. The legal guarantee mechanism for agricultural data sharing is not perfect, and most of the agriculture-related departments follow the principle of "good for me, prudent in numbers" and refuse to open share important agricultural data, resulting in low value elements of shared agricultural data and difficulty in meeting the needs of smart agriculture.
(3) The original innovation ability of key core technologies is insufficient
The original innovation of core technologies such as agricultural IoT life form perception, high-throughput acquisition of holographic information, and AI chips is insufficient. High-end computing chips and technical standards are still monopolized by foreign countries, and it is not easy to get rid of the situation of being controlled by others in the short term; there is a phenomenon of "stuck" in chip design and manufacturing, large-scale industrial software, and basic software for mobile operating systems (OS). There is a big gap between the new computing platform, distributed computing architecture, big data processing, analysis, and presentation and the world's advanced level, and the research and development of forward-looking technologies is in a state of follow-up, and the influence of big data core technology and ecosystem is weak [29]. The key technological innovation of big data in agriculture is inseparable from the breakthrough development of these basic information technologies. Developed countries have blockaded key technologies, making it difficult to buy them; most of the basic technologies and equipment used by the mainland come from outsourcing, and it is difficult to independently develop them, so it is necessary to continue to increase investment in the basic research and development of agricultural data.
(4) The scale of the professional talent team needs to be expanded
There is a shortage of senior professionals in agricultural big data. Although a large amount of agriculture-related data has been accumulated, due to the lack of professional data processing, analysis, and mining personnel, a large amount of data is in a "sleeping" state, and a deeper application has not yet been realized. There is a shortage of cross-border compound talents in big data and agriculture, computer talents do not understand agriculture, agricultural talents do not understand information technology, especially big data technology, and compound talents with interdisciplinary professional knowledge are scarce. The grass-roots information contingent is insufficient, lacks professional and regular professional training, and lacks the necessary financial support; the contingent is unstable, and the number and quality of personnel engaged in related work have failed to meet the requirements of the development of informatization in the new period.
4. Development goals and roadmap of agricultural big data and information infrastructure
(1) Development goals
Based on national conditions, agricultural conditions and practical needs, promote the construction of agricultural big data and information infrastructure. The agricultural information infrastructure system has been replaced by localization as a whole, and the gap between urban and rural networks has been basically reduced, forming a network space that integrates the Internet of Everything, human-computer interaction, and "sky, ground and sea"; major breakthroughs have been made in key core digital technologies in agriculture and an agricultural digital economic system has been built; a nationwide data sharing and exchange network has been gradually built to achieve integrated and standardized data sharing; and the application of agricultural big data has been continuously deepened and innovated, and "sky, ground and sea" have been built An integrated digital agriculture system, forming an agricultural big data industrial base and industrial application ecosystem jointly built and shared by the government and the market, and basically realizing the modernization of agricultural and rural governance systems and governance capabilities.
1. 2025 targets
The agricultural and rural information infrastructure system has been established and improved, and the basic data resource system has been basically completed. The "sky, ground and sea" integrated observation network and the national agricultural and rural big data center have been basically completed, and a panorama of national agricultural and rural digital resources has been initially formed, realizing the open sharing of data resources and strongly supporting the application of smart agriculture in various scenarios. 100% broadband coverage has been achieved in administrative villages across the country, innovative 5G applications have been implemented, and the "digital divide" between urban and rural areas has been significantly narrowed. The proportion of agricultural information application terminals has been greatly increased, with the rural Internet penetration rate reaching 70%, the proportion of agricultural Internet of Things technology application reaching 25%, and the coverage rate of village-level information service stations reaching 90%. The rural information service and digital governance system has been established and improved.
Form a standardized technology and data exchange mechanism system for agricultural big data, and build a national integrated data sharing and exchange network. Strengthen the construction of a standard and normative system, establish a standard and security system for agricultural data, and promote the intelligent and institutionalized management of agricultural data. Construct a "1+N" data sharing model, that is, build one agricultural big data general center, N sub-data service centers, and N innovative application demonstration bases, break the industry data barriers in the agricultural field, and realize internal, external, horizontal and vertical data sharing of agricultural business departments, so that data can better serve agriculture-related subjects. Build a demonstration base for the application of agricultural big data, and enrich the innovative application of big data in agricultural production, operation, management, and services.
2. 2035 targets
The overall agricultural information infrastructure system has achieved localization, independent and controllable, the popularization of 5G in rural areas has been deepened, the sixth-generation mobile communication (6G) network has been innovatively applied, and the gap between urban and rural networks has been basically reduced, which has strongly supported the development of smart agriculture and rural areas. Breakthroughs have been made in key core technologies and products such as brain-inspired computing, biometric recognition, digital twins, and simulations, and a large number of applications have been made. Information terminals play a significant role in serving farmers in production, management, management, and life. The Internet penetration rate in rural areas has reached 85 percent, the proportion of agricultural Internet of Things technology application has reached 35 percent, and village-level information service stations have achieved full coverage. The digital literacy of farmers has been significantly improved, and the equalization of basic public services in urban and rural areas has been basically realized.
Major breakthroughs have been made in the key core digital technologies of agriculture, and an agricultural digital economy system has been built. Agricultural data has been basically standardized and shared. The integrated digital agriculture system of "sky, ground and sea" has been completed, the digital management of all agricultural elements, all fields and the whole process has been basically realized, and the modernization of agricultural and rural governance system and governance capacity has been basically realized. Big data is deeply integrated with all links of the whole industrial chain such as modern agricultural production, circulation, market, and processing, and the application of agricultural big data has been continuously deepened and innovated, and new paths, new formats, and new models for the development of the agricultural industry are rich and diverse. Big data application products are constantly enriched, and agricultural big data customized service models are popularized.
3. 2050 targets
We will build a high-speed, mobile, safe and ubiquitous new generation of agricultural and rural information network, form a cyberspace with the interconnection of all things, human-computer interaction, and the integration of "sky, ground and sea", and lay an important foundation for becoming a world smart agricultural power. The rural Internet penetration rate has reached 95%, and the proportion of agricultural Internet of Things technology application has reached 50%. Agricultural and rural information terminals and agricultural robots support the large-scale and in-depth application of smart agriculture.
The whole chain of agricultural production, circulation and market has fully realized digital and intelligent management. Build an agricultural big data industrial base jointly built and shared by the government and the market, attract upstream and downstream enterprises in the agricultural big data industry chain to gather and settle in, and form an agricultural big data industry application ecosystem.
(2) Key tasks and technical routes
1. By 2025
Driven by digital agricultural and rural infrastructure projects, a new generation of agricultural information infrastructure system will be built. Comprehensively use multiple sensing systems such as space-based remote sensing, space-based, ground-based and marine platforms to build a national agricultural and rural information standardization monitoring system, and make overall use of information infrastructure such as urban and rural big data centers to build a unified, open and shared national agricultural and rural big data center. Accelerate the deployment of new agricultural infrastructure such as 5G networks and digital infrastructure in agriculture and rural areas, coordinate and promote the extension of 5G construction to key towns and agricultural parks where conditions permit, carry out pilot layout and innovative application of 5G networks in rural areas, and greatly narrow the digital divide between urban and rural areas.
In terms of R&D and application of agricultural big data technology, we should establish agricultural data standards, norms and security guarantee systems, promote the intelligent management and institutionalization of agricultural data management, build agricultural data standard systems such as data collection indicators, acquisition methods, analysis models, and release systems for the entire agricultural industry chain, integrate and gather data from agriculture-related departments, and build an agricultural big data resource center that is compatible with agricultural development in the new era. Implement the special research and development of data-driven agricultural intelligent analysis models/tools, develop special tools for intelligent analysis and processing of agricultural big data, develop deep learning models based on agricultural big data and high-performance algorithms for agricultural big data, and build a number of data-driven intelligent analysis and decision-making systems.
2. 2026-2035
Focus on overcoming key core technologies such as advanced agricultural sensors, agricultural AI chips, agricultural high-performance models and algorithms, break through problems such as human-computer interaction, biometric recognition, and brain-like computing, and significantly improve the computing power of agricultural big data. Develop an advanced agricultural information infrastructure system with independent intellectual property rights to ensure the information security of the agricultural information infrastructure network. Construct a panorama of agricultural and rural digital resources covering the whole country, and realize the digitization of agricultural and rural resources across the country. Implement the "5G+" agricultural and rural application demonstration project, deepen the popularization of 5G network coverage in rural areas, establish a 5G-supported smart agriculture technology system, and study the layout of 6G network pilot and innovative applications in rural areas, so as to promote the basic reduction of the gap between urban and rural networks. Strengthen the industrial application of information terminals and agricultural robots, and promote them to play a significant role. Efforts should be made to increase the penetration rate of the Internet in rural areas and the proportion of agricultural Internet of Things technology applications, so as to ensure the basic equalization of basic public services in urban and rural areas and the modernization of rural governance systems and governance capabilities.
We will build an integrated digital agriculture system of "sky, ground and sea", and promote the digital management of all elements, fields and processes of agriculture. Build an integrated agricultural and rural data sharing mechanism, promote data development and sharing, and continuously deepen and innovate the application of agricultural big data. Construct a "1+N" data sharing model, develop agricultural big data sharing, exchange and service platforms, break down industry data barriers in the agricultural field, and completely solve the waste of resources caused by different data standards and small data centers built by various departments. Overcome key technologies such as intelligent data computing, analysis and mining, deep learning, and data visualization, deeply integrate the new generation of information technology such as big data with traditional agriculture, and cultivate new paths, new formats, and new models for the development of the agricultural industry. Build a demonstration base for the application of agricultural big data, deeply integrate big data with the development of modern agriculture, and enrich the innovative application of big data in the direction of agricultural production, operation, management and service around the management of agricultural production process, agricultural resources and ecological environment management, agricultural product safety management, agricultural product trading and circulation, monitoring and prediction of agricultural market and consumption, and agricultural innovation services.
3. 2036-2050
We will build an agricultural and rural network space with the interconnection of all things, human-computer interaction, and the integration of "sky, ground and sea", and build an agricultural and rural communication network integrating satellite communication, ground communication, and marine communication, so as to lay an important foundation for the mainland to become a world smart agricultural power. Breakthroughs have been made in agricultural intelligent computing technologies and algorithms, and agricultural big data computing power has reached the world's leading level. Develop AI chips for agricultural scenarios that are replaced by localization, and promote the extensive and in-depth application of smart chips in agriculture and rural areas. Build a high-speed, mobile, safe and ubiquitous agricultural and rural information infrastructure, and realize seamless network coverage of rural production and living areas. Through the implementation of the agricultural and rural Internet of Everything project, we will create a digital world of agricultural communication with full connection of people, machines and things, promote the application of agricultural and rural information intelligent terminals in spatial communication, intelligent interaction, mixed reality and other scenarios, and support the large-scale and in-depth application of smart agriculture.
Promote the digital and intelligent management of the whole chain of agricultural production, circulation and market. Build an agricultural big data industry base and create an agricultural big data industry ecosystem. Focusing on the management of the whole process of agricultural production, the management of agricultural resources and ecological environment, the safety management of the whole chain of agricultural products, the trading and circulation of agricultural products, the monitoring and prediction of agricultural product markets, and agricultural information services, we will develop a series of big data application products such as agricultural smart production, agricultural disaster monitoring, prevention and control, information monitoring and early warning of the whole agricultural industry chain, and agricultural product quality and safety. Build an agricultural big data industrial base jointly built and shared by the government and the market, and quickly form industrial clusters and improve the agricultural big data industry ecosystem through the operation of the agricultural big data industrial base.
5. Countermeasures and suggestions
(1) Strengthen the top-level design and overall layout, and plan the chassis work path for the medium and long-term development of agricultural information infrastructure and big data
Facing the needs of building a smart agricultural power and the main battlefield of modern agricultural construction, we should strengthen the top-level design, and deeply plan the chassis work path for the medium and long-term development of agricultural informatization infrastructure and agricultural big data. It is suggested that the national agricultural authorities should take the lead, with the participation of agricultural research institutes, enterprises and operators, and establish a national agricultural big data alliance to jointly study and formulate the top-level design and implementation plan of agricultural big data. Research on the standard system of agricultural big data, and carry out system design and overall planning from the aspects of data sharing, data storage, data governance, and legal and regulatory guarantees, so as to build a basic chassis for the application of agricultural big data. Coordinate information infrastructure resources such as urban and rural data centers, unify the planning of new agricultural infrastructure and urban network construction, and build an integrated information infrastructure for urban and rural areas. Establish a comprehensive policy system to promote the upgrading and healthy development of agricultural information infrastructure.
(2) Strengthen investment in technological research, and break through the "bottleneck" technology of the key core commonality of agricultural big data
It is suggested to strengthen the basic research of agricultural big data, strengthen original and leading scientific and technological research, implement key core technologies of agricultural big data, and improve the strategic layout of agricultural big data scientific and technological forces. In view of the key links such as agricultural data acquisition, analysis and application, we will focus on the research and development of key technologies such as big data acquisition, massive data storage, data cleaning, analysis and mining, big data visualization, big data intelligence, big data deep learning, and virtual reality, and strengthen the research and development of information intelligent decision-making systems for the entire industrial chain of agricultural production, circulation and market, so as to form an international advanced agricultural big data technology system. Strengthen the research and development of original models and advanced algorithms, build an agricultural big data model development platform, carry out the research and development of key mechanism models and analysis and early warning models such as animal and plant growth models and agricultural product market models, and improve the efficiency of agricultural information monitoring and early warning supported by big data. Promote the formation of a market-oriented mechanism for the application of agricultural big data, and guide market entities to carry out value-added and public welfare technological innovation and service applications of agricultural big data.
(3) Strengthen collaborative innovation in systems and mechanisms, effectively solving difficult pain points such as data sharing and data services
Construct a mechanism for the co-construction and sharing of agricultural big data resources, promote government-led, market-oriented and other types of mechanisms, and make overall plans from the aspects of data rights confirmation, sharing mechanisms, and legal and regulatory safeguards, so as to solve urgent problems such as serious data barriers and weak awareness of data resources among agriculture-related management departments. In terms of data resource construction, we will pay attention to the collection of basic agricultural data and daily data, and introduce long-term and stable data collection supporting subsidies and platform facility maintenance policies. It is necessary to build a mechanism for linking the interests of all parties involved, explore effective ways for the government and social entities to cooperate in the construction of agricultural big data, and guide social capital to actively participate in the construction of agricultural big data through various modes such as public-private partnership (PPP) and service outsourcing. Fully respect the status of the main body of agricultural big data output, service and application, and accelerate the market-oriented mechanism of agricultural big data transactions. Improve the mechanism for the distribution of data benefits, establish systems and norms for confirming data property rights, accounting for data value, and data transactions, effectively mobilize the enthusiasm of all parties, improve the level of market-oriented operation, and promote the commercialization of agricultural big data achievements.
(4) Strengthen the construction of high-level talent teams and promote the mainland's agricultural big data technology to the forefront of the world
The first is to build a multi-level talent system for agricultural big data, and establish an agricultural big data talent team that integrates the research and development of common technologies of agricultural big data, key technological breakthroughs, promotion and application, and combines the old, middle and young, and multi-professional talents.
The second is to strengthen the cultivation of high-end talents, cultivate professional and compound talents in agricultural big data, build a high-level talent training and selection platform, focus on cultivating and supporting the construction of agricultural big data discipline leaders and innovative teams, and forge the hard skills of talent teams in response to the international scientific frontier and major national needs, and improve the breakthrough ability of major core technologies, the planning ability of strategic frontiers, and the ability to solve practical problems in the industry.
The third is to strengthen the training of big data knowledge for grassroots information personnel, and give full play to the role of big data technology in agricultural and rural management services.
Fourth, strengthen international exchanges and cooperation, establish a cooperation mechanism for cross-border and cross-domain flexible exchange of talents, establish an agricultural big data talent think tank and a "industry-university-research" alliance system, encourage the normalization of innovation achievements and talent exchange mechanisms, and continue to provide endogenous driving force for the innovation and application of agricultural big data.