Smart Agriculture: Empowering High-Quality Development of Modern Agriculture

Smart agriculture is considered another agricultural technological revolution following the revolution of plant breeding and genetics. It will fundamentally change the production, operation, and management methods of modern agriculture, leading agriculture into a digital, networked, and intelligent development stage. Smart agriculture is a new scenario for technological innovation in digital technology. The deep integration of technological innovation and agricultural industries will not only stimulate new driving forces for agricultural development but also lead to technological innovation in digital technology, data science, artificial intelligence, and blockchain.
Smart agriculture represents the advanced stage of agricultural informatization and is the inevitable direction of future agricultural development.
Human society is undergoing an information revolution. Information technology represents the direction of the development of today's advanced productive forces and has strong driving force, penetration, and diffusion capabilities. Since the 21st century, mankind has fully entered the information technology era centered on the Internet. With the rapid development of new generation information technology, agricultural informatization is developing from the traditional digital and networked to the high-end intelligent and smart directions. Global agricultural development is entering a new stage of smart agriculture development. Smart agriculture takes information and knowledge as its core and integrates remote sensing networks, sensor networks, big data, the Internet, cloud computing, artificial intelligence, and other modern information technologies, as well as intelligent equipment and robots, into all aspects of the agricultural industry chain, including production, processing, operation, management, and service. This achieves precise planting, internet-based sales, intelligent decision-making, and socialized services, forming a modern agricultural development model characterized by digitalization, automation, precision, and intelligence.
The report of the 19th National Congress of the Communist Party of China points out that "we must prioritize the development of agriculture and rural areas, following the general requirements of prosperous industries, livable ecology, civilized rural customs, effective governance, and affluent lives. We must establish and improve a system of policies and mechanisms for integrated urban-rural development and accelerate the modernization of agriculture and rural areas."
Smart agriculture is the advanced stage of agricultural informatization development and a brand-new concept of agricultural development. It is related to but different from computer agriculture, digital agriculture, and precision agriculture, other agricultural informatization development models. Computer agriculture, digital agriculture, and precision agriculture apply key information technologies to agricultural production to improve efficiency and benefits. Smart agriculture, however, aims to achieve intelligence across all elements, the entire chain, the entire industry, and all regions. It not only permeates agricultural production but also encompasses agricultural operations, management, and services. This is the biggest difference from other agricultural informatization development models. Smart agriculture has a broader connotation and wider scope, involving more comprehensive and complex theories, technologies, systems, and equipment.
Currently, China is in a crucial period of transition from traditional to modern agriculture. Agricultural development faces new challenges such as the "ceiling" of agricultural product prices and the rising "floor" of production costs. New problems such as constraints on agricultural resources and the environment, imbalances in agricultural production structure, and low quality and efficiency of agricultural development are becoming increasingly prominent. There is an urgent need to accelerate the transformation of agricultural development methods, shifting from extensive development to fine management and scientific decision-making, and pursuing a path of modern agriculture that is highly efficient in output, safe in products, resource-saving, and environmentally friendly. Agricultural informatization has become the inevitable choice for leading the development of modern agriculture in China, innovating agricultural management services, and solving problems in agricultural development.
The "13th Five-Year Plan" outline, the annual "Central No. 1 Document" since 2016, and recently issued documents such as the "Development Plan for New Generation Artificial Intelligence," the "Digital Village Development Strategic Outline," and the "Digital Agriculture and Rural Development Plan (2019-2025)" have all made top-level designs and systematic plans for the digital and intelligent development of agriculture. The development of smart agriculture is an urgent need to implement China's national strategy of "synchronous development of the four modernizations," accelerate the transformation of agricultural development methods, and promote the modernization of agriculture. It helps to promote the deep integration of informatization and agricultural modernization, promote the transformation and upgrading of the entire agricultural industry chain, optimize resource allocation and scientific management, effectively improve the efficiency of agricultural production and operation, and improve the agricultural ecological environment. It is of great significance to building a digital China, implementing the rural revitalization strategy, and promoting high-quality agricultural development.
The key to smart agriculture is data; it needs to address three major issues: data acquisition, processing, and application.
Data is a fundamental strategic resource, and the digital economy is a new driving force for modern economic development. For the first time, the Fourth Plenary Session of the 19th Central Committee of the Communist Party of China proposed that data should participate in income distribution as a factor of production. Data, as a new factor of production, runs through the input, output, and distribution stages. The goal of smart agriculture is to achieve intelligent agricultural processes; its essence is data-driven. Focusing on "data," this key factor of production, smart agriculture consists of key technologies, equipment, and integrated systems for data acquisition, data processing and analysis, and data application services, achieving the conversion from data to knowledge to decision-making. Each link has its key theoretical and technical methods. These theories and methods are highly integrated to form a complete smart agriculture system.
Data acquisition is the foundation of smart agriculture. Through innovations in precise sensing and data acquisition technologies, an integrated "sky-ground" agricultural and rural information acquisition technology system is constructed. Research is conducted on data acquisition, input, aggregation, application, and management technologies to improve the ability to acquire and process raw data, solving the basic problem of "where data comes from and how to manage it." The focus is on promoting the research and development of professional remote sensing satellites that meet the needs of agriculture and rural areas; breaking through the common key technologies for the application of unmanned aerial vehicles in agriculture; overcoming the manufacturing of special sensors for agricultural production environments and the physiological characteristics of plants and animals; achieving cross-regional, multi-element, and multi-level data collection of resources, environment, production, operation, management, and services in important agricultural and pastoral areas; developing an agricultural and rural big data management platform; and breaking through key technologies such as the "centralized + distributed" integrated cloud architecture and data security for agricultural and rural resources and assets.
Data processing and analysis are the support. Innovations in data mining and intelligent diagnostic technologies are conducted to build an intelligent processing and analysis technology system for agricultural big data. Advance layouts are strengthened in cutting-edge technologies such as artificial intelligence, virtual reality, blockchain + agriculture, and big data cognitive analysis to solve the problem of "how to process and analyze data." The focus is on carrying out technological breakthroughs; integrating agricultural knowledge and models, computer vision, and deep learning methods; developing proprietary models and algorithms for monitoring, identification, diagnosis, simulation, and control of plant and animal production; achieving digital and intelligent diagnosis of all elements and the entire process of agricultural production; focusing on rural digital services; strengthening the research and development of technologies such as data resource correlation mining, intelligent retrieval, intelligent matching, and deep learning in agriculture and rural areas; and meeting farmers' comprehensive information needs for convenient services and E-Business.
Data application services are crucial. Through precise control and technological innovation, a technology system for data-enabled intelligent decision-making and management in agriculture and rural areas is built. The digital transformation of industry management and service processes is accelerated to solve the problem of "how data can provide services." The focus is on strengthening the research on the integration of proprietary software and information systems in agriculture and rural areas; developing intelligent environmental control systems, rapid detection and cold chain logistics technology for agricultural products, and credible traceability technology for agricultural products; strengthening the independent research and development capabilities of intelligent equipment; creating a batch of equipment for agricultural intelligent sensing, intelligent control, and autonomous operation; focusing on breakthroughs in technologies such as agricultural robots, numerical control spraying, intelligent detection, intelligent handling, intelligent harvesting, and grading and sorting of fruits and vegetables; and conducting research and development of digital agriculture standards and specifications, establishing standards and specifications for data standards, data access and services, and software and hardware interfaces.
Smart agriculture is a complex system application requiring cross-disciplinary integration across multiple departments, fields, and disciplines.
In terms of Applications, smart agriculture technologies, platforms, and equipment have been widely applied to various fields such as planting, animal husbandry, processing, and circulation, forming new industrial development formats such as intelligent farmland, intelligent pastures, intelligent fish farms, intelligent orchards, intelligent plant factories, intelligent workshops for agricultural product processing, and green intelligent supply chains for agricultural products. Different smart agriculture development models and paths have been formed for different application entities. For example, smart agriculture applications for small farmers mainly focus on information skills training, technical entrustment and equipment sharing services, e-commerce platforms, and the application of small intelligent terminals; for new operating entities such as large-scale farmers, family farms, agricultural enterprises, and cooperatives, the focus is on improving production efficiency, enhancing product value-added, and achieving the intelligent transformation of the entire industry chain. At the same time, different smart agriculture application models are formed based on the industrial types and characteristics of different regions. For example, in Northeast China, the focus is on large-scale precision planting in farmland; in Southeast coastal areas, the focus is on smart fisheries and smart logistics; and in Southwest mountainous areas, the focus is on smart specialty agriculture.
Smart agriculture is a complex application of hardware and software systems. Through the integrated application of cutting-edge digital technologies and equipment, it automatically, precisely, and efficiently collects, extracts, and processes large agricultural data, connecting various data "islands." Using artificial intelligence methods such as image and video recognition, deep learning, and data mining, it rapidly obtains various types of information and knowledge, achieving high-quality development of agriculture that is high-yield, efficient, and environmentally friendly.
As a technology-intensive agricultural innovation system, smart agriculture requires the integrated development of technology, platforms, and ecosystems. Specifically, it not only requires the support of new infrastructure such as 5G, artificial intelligence, and data centers, but also fundamental research and theoretical breakthroughs in information technology, data science, agricultural science, and equipment science. The important driving force behind the future development of smart agriculture comes from the highly organic integration of agricultural information technology, agricultural science, and agricultural machinery, relying on the cross-integration of digital technology with agricultural science, resource and environmental science, genomics, agricultural economics, and social science. Only through a scientific understanding of the complex relationships and ecological connections between plant and animal production and water and soil resources and the environment can massive amounts of agricultural data be transformed into knowledge and decisions; only by combining it with the genomic information and microbiome of individual plants and animals can powerful machine learning, deep learning, and data mining technologies play a significant role, achieving the goal of data empowering agriculture. In addition, promoting technological innovation in smart agriculture must place importance on interdisciplinary and cross-industry knowledge exchange and technological integration, and on the cultivation of interdisciplinary agricultural talents.