By Boluwatife Adedokun
China has launched its first open-source artificial intelligence model developed specifically for agriculture, marking a major step in the digital transformation of the sector.
The model, known as Sinong, was developed by Nanjing Agricultural University and is being described by experts as a technological breakthrough with the potential to reshape agribusiness management, agricultural research and innovation across the agri-food value chain.
Unlike general-purpose artificial intelligence tools, Sinong is a large language model designed exclusively for agricultural use. It is built to understand both everyday language and the technical terminology used by farmers, agroeconomists, plant breeders, veterinarians and agricultural engineers.
According to the developers, Sinong was trained entirely on agricultural data, setting it apart from conventional AI chatbots. Its database includes nearly 9,000 specialised books, over 240,000 academic research papers, about 20,000 policy documents and technical standards, as well as large volumes of agriculture-focused online data.
The model covers a wide range of agricultural fields, including horticulture, crop production and breeding, plant protection, livestock and veterinary medicine, agricultural economics, resource sustainability, smart farming and digital agriculture technologies.
As a result, Sinong is designed to provide structured, domain-specific responses rather than generic or abstract information, making it more suitable for real-world agricultural decision-making.
Developers also said special attention was paid to reducing inaccurate or misleading outputs, a common challenge with artificial intelligence systems. The training process incorporated logical reasoning frameworks, contextual data referencing and multi-dimensional agricultural datasets to improve accuracy and reliability.
Industry experts say the introduction of an open-source agricultural AI model could significantly impact global agribusiness. Farmers could gain access to more precise agronomic advice, agribusinesses may improve market and risk analysis, researchers could process scientific data more efficiently, and AgTech startups may develop new tools tailored to agricultural needs.
Sinong has been released as open source on platforms such as ModelScope and GitHub, allowing developers, researchers and companies worldwide to adapt the model to local farming systems, crops and markets.
Analysts say the move positions China as a key contributor to a growing global agricultural AI ecosystem, where collaboration and shared innovation could accelerate technological adoption.
The launch of Sinong also highlights a broader shift in global agriculture, where competitiveness is increasingly driven not only by physical infrastructure and machinery but by intelligent systems capable of managing and applying knowledge.
Experts note that the effective use of artificial intelligence in production, analysis and farm management is rapidly becoming a decisive factor in the long-term sustainability and competitiveness of the agricultural sector.
