On March 16, the Ministry of Agriculture and Rural Affairs held a cadre meeting to convey and study the spirit of the Two Sessions. The meeting emphasized that we must earnestly implement the major deployments for agriculture, rural areas, and farmers from the Two Sessions, focus on ensuring the stable and secure supply of grain and important agricultural products, effectively carry out spring plowing and field management, further boost the large-scale yield increase of grain and oil crops, promote the transformation and upgrading of the “vegetable basket” industry, strive to improve the quality of agricultural products, and achieve new improvements in the comprehensive agricultural production capacity, quality, and efficiency. We will also focus on achieving high-level self-reliance and self-improvement in agricultural science and technology, prioritize breakthroughs in key core technologies in critical fields such as the seed industry, continuously enhance the overall effectiveness of the agricultural science and technology innovation system, vigorously promote the integration of artificial intelligence (AI) and agriculture, develop and strengthen the rural talent team, and make new breakthroughs in fostering new quality productive forces in agriculture.
Agriculture is the foundation of a nation and the cornerstone of national strength. Advancing agricultural modernization is the core task of building a strong agricultural country and achieving all-around rural revitalization. Currently, as the core driving force of the new round of technological revolution and industrial transformation, AI is breaking through technological boundaries and industrial barriers, deeply integrating into the entire chain of agricultural production, operation, management, and services. It has become a key tool for solving the pain points of traditional agriculture, reshaping the agricultural development pattern, and cultivating new quality productive forces in agriculture.
The core of empowering agriculture with AI lies in building a closed-loop system of “data perception—intelligent analysis—precision decision-making—automatic execution,” realizing the digital and intelligent upgrading of the entire agricultural chain. On the production side, AI technologies have completely transformed traditional planting and breeding models. Applications such as drone remote sensing monitoring, intelligent soil moisture sensing, intelligent pest and disease identification, variable fertilization and irrigation, unmanned agricultural machinery operations, and intelligent breeding and feeding have been implemented. These technologies can precisely control every link of crop growth and livestock and poultry breeding, while significantly reducing the waste of water, fertilizer, pesticides, feed, and other resources, and lowering labor costs. Relevant practical data shows that intelligent irrigation systems can improve water use efficiency by 25%–30%, precision fertilization can reduce nitrogen fertilizer use by more than 18%, and simultaneously increase the yield of grain crops by 10%–15%, effectively consolidating the defense line of food security. At the back end of the industrial chain, AI facilitates intelligent sorting, quality grading, and full-chain traceability of agricultural products, optimizes cold chain logistics scheduling, reduces circulation losses, and relies on big data to analyze consumer market trends. This helps build agricultural product brands and carry out precision marketing, opening up the transformation channel from “good planting” to “good sales” and broadening farmers’ income channels.
Accelerating Seed Industry Innovation to Consolidate the Agricultural “Chip”
Relying on AI algorithms and big data technologies, we can quickly integrate massive data such as germplasm resources, gene sequencing, and field performance, breaking through the bottlenecks of long cycles, low efficiency, and poor precision in traditional breeding. This enables the intelligent upgrading of molecular design breeding and whole-genome selection breeding. Through intelligent modeling to analyze the correlation between crop genes and traits, we can precisely screen high-quality, high-yield, stress-resistant, and disease-resistant varieties, significantly shortening the breeding cycle, reducing R&D costs, and cultivating breakthrough varieties adapted to different regions and climates.
Realizing Intelligent Field Production to Reduce Costs, Increase Yields, and Ensure Harvests
Precision planting is the most mature application field of AI+ agriculture. Relying on satellite remote sensing, drone multispectral imaging, soil sensors, meteorological monitoring stations, and other equipment, we collect real-time data on soil nutrients, moisture, crop growth, meteorological conditions, and pest and disease occurrences. Through intelligent analysis by agricultural large models, personalized planting plans are generated, enabling the automatic execution of variable fertilization, precision pesticide spraying, and intelligent irrigation. Meanwhile, unmanned agricultural machinery integrating Beidou navigation and AI algorithms can independently complete operations such as sowing, plowing, harvesting, and plant protection without manual intervention, greatly improving operational efficiency. This is particularly suitable for major grain-producing areas and large-scale farms, effectively alleviating the shortage of rural labor and promoting the large-scale, intensive, and intelligent development of grain production.
Improving Breeding Efficiency and Consolidating the Epidemic Prevention Line
In the fields of livestock, poultry, and aquaculture, AI uses intelligent sensing equipment to monitor real-time indicators such as livestock and poultry behavior, physical signs, pen environment, and water quality changes, achieving precise feeding, automatic environmental regulation, and early epidemic warning. AI vision technology can quickly identify abnormal behaviors and disease symptoms of livestock and poultry, issue early warnings to avoid large-scale epidemic spread; intelligent aquaculture systems can regulate parameters such as water temperature and dissolved oxygen in real time, optimize the breeding environment, and improve the yield and quality of aquatic products. At the same time, AI enables digital traceability throughout the breeding process, realizing full supervision from breeding to the dining table, ensuring the quality and safety of livestock, poultry, and aquatic products, and promoting the transformation of the breeding industry from extensive free-range farming to standardized, intelligent, and green development.
Breaking Down Production-Marketing Barriers and Enhancing Industrial Added Value
The empowering value of AI extends to the entire agricultural industry chain. In agricultural product processing, AI vision sorting equipment can quickly complete quality inspection and classification of agricultural products, improving product commercialization rates; in circulation, intelligent algorithms optimize cold chain logistics routes and warehouse scheduling, reducing agricultural product circulation losses; in marketing and services, big data analyzes consumer demand, helps build brands for characteristic agricultural products, and realizes order-based agriculture and precision marketing; in risk prevention and control, AI combines meteorological, soil, and market data to carry out agricultural disaster warnings, yield forecasts, and price trend analysis, providing decision-making references for farmers and business entities. It also empowers precision agricultural insurance, simplifies loss assessment and claims settlement processes, and safeguards farmers’ incomes.
The key to agricultural modernization lies in the modernization of agricultural science and technology. AI has added technological wings to agricultural development, opening up a new track for building a strong agricultural country and achieving all-around rural revitalization.
