Translation. Region: Russian Federal
Source: People’s Republic of China in Russian –
Source: People’s Republic of China – State Council News
CHENGDU, June 7 (Xinhua) — Under the golden rays of the June sun, a “high-risk” agricultural experiment is unfolding in the emerald rice fields of the “Tianfu Breadbasket” key demonstration area in Chongzhou City, southwest China’s Sichuan Province.
Three weeks into the second AI rice-growing competition, organizers are faced with a key question: Can AI surpass centuries of farming wisdom?
The competition, which runs from May 15 to September 30, features six traditional farming teams and four AI-enabled teams on 1,000 mu (about 66.7 hectares) of high-quality rural fields. Each team cultivates 100 mu using elite rice varieties. This modern duel between tradition and technology offers insight into China’s advancement toward smart agriculture.
The AI teams use an intelligent agent for rice cultivation decision-making developed by the Institute of Urban Agriculture of the Chinese Academy of Agricultural Sciences (CAAS) using a sky-earth-space data network. The system collects information on crop growth, farming operations, diseases, pests and weeds in real time, processes the data through a cloud-based AI agent, generates detailed reports and professional recommendations that are instantly sent to the smartphones of the AI participants.
Based on these recommendations, AI participants carry out field work, and the monitoring system continuously collects operational data, forming a closed decision-making loop to ensure the accuracy and intelligence of the growing process.
Gao Ying, a participant from Qingqiao Shared Land Cooperative in Chongzhou City, said that compared with traditional farming, AI farming can quickly master key knowledge and production skills. “In addition, the system provides effective recommendations in response to queries,” she added.
Lessons from the first competition
This is not Gao Ying’s first experience. Last year’s competition showed the reality of the situation: the AI system from ASNC, which guided the newcomer Gao Ying in the 100 mu section, helped her team to take seventh place among nine teams.
“AI needs field practice,” said Wang Ran, a leading researcher at ASNC for urban agriculture strategy, whose team developed the system.
“When we created the algorithm, we had fragmentary data. Now we have created a comprehensive data set covering the entire rice growing process: start and end dates, photos of crop growth, relevant weather and soil data,” said Wang Ran.
“The power of AI is in processing 10,000 data points from each mu through our monitoring network, but converting them into practical actions requires deeper synergy between farmers and algorithms,” Wang explained. He noted that the AI-based decision-making rate reached 73 percent last year, but there were challenges with the timing of pest control.
“This year, the goal is to achieve more than 80 percent decision making to ensure that AI recommendations are consistent with farmers’ actions,” he said.
Harmony between humans and AI
The organizers view the competition not as a confrontation, but as an integration of humans and AI.
“AI is a help, not a replacement for humans. We aim to provide more accurate support to urban producers and decision makers through AI computing power,” Wang Ran said of the initial goal of applying AI in agriculture.
“The key value of the system is to create a bridge between innovators and farmers’ needs, improving the quality of decision-making by farmers and providing data for government sector planning,” he stressed.
Now, in the midst of summer harvesting and planting, Qingqiao Village in Chongzhou City, Chengdu Plain, is demonstrating the results of technological transformation of traditional agriculture: an intelligent rice planting system works in tandem with farmers, creating a highly efficient symbiosis of smart technology and human labor. -0-