BEIJING, Nov. 8 (Xinhua) -- A small drone flew low over a sugarcane field in Sanya, south China's Hainan Province, collecting crop data that artificial intelligence (AI) can analyze to identify potential disease risks.
Wang Xiaoding, a researcher at the Chinese Academy of Tropical Agricultural Sciences, said AI can help detect signs of sugarcane diseases before obvious symptoms appear, while smartphone-based tools provide farmers with crop management advice.
AI is also being used to identify genes linked to higher yields and sugar content, and to improve harvesting efficiency.
"Breeding a new sugarcane variety used to take eight to 10 years. AI can substantially shorten this timeline," Wang noted.
Similar applications are emerging across other tropical crops, with AI helping analyze genetic data for banana breeding, detect pests and diseases in cassava, and monitor oil palm plantations and rubber forests.
These developments reflect China's broader push toward smarter agriculture. Last year, China had more than 300,000 agricultural drones in use, the largest fleet in the world, with an annual operating area exceeding 460 million mu (about 30.7 million hectares).
China has issued a plan for agricultural and rural modernization for the 2026-2030 period, aiming to raise the contribution rate of sci-tech progress to agricultural development to 67 percent by 2030. The plan also calls for broader AI applications in agriculture and breakthroughs in developing new quality productive forces in the sector.
For tropical agriculture, the potential extends beyond China, particularly to Southeast Asia, where countries grow many of the same crops and face similar pest, disease and extreme-weather challenges.
"We are exploring these technologies not only to address challenges in tropical crop breeding and cultivation in China, but also to strengthen cooperation with Southeast Asian countries, including Thailand, Indonesia and Malaysia," said Hao Chaoyun, director of the Institute of Tropical Bioscience and Biotechnology at the Chinese Academy of Tropical Agricultural Sciences.
"We hope to share technological advances and farming experience to improve the quality and efficiency of tropical agriculture worldwide," Hao added.
Such cooperation is already taking shape.
In Cambodia's Kampong Chhnang Province, an AI-powered platform developed by JJR Science & Technology Group Co., Ltd. helps manage sprinkler and drip irrigation systems in vegetable greenhouses. In Pakse, Laos, more than 4,000 mu of banana plantations are managed with greater precision using the company's technology.
Weather forecasting is another area of cooperation. China's MAZU early-warning system combines meteorological satellite data and AI forecasting models to support disaster warnings, with several products already providing services to ASEAN countries.
Dai Kan, deputy director of China's National Meteorological Center, said China and ASEAN countries are both located in monsoon climate zones. He expressed hope that the two sides would strengthen data sharing and jointly develop sustained early-warning services tailored to key regional disaster risks and agricultural production needs.
Still, expanding such technologies across the region requires more than equipment and software. Reliable data, local expertise and affordable access to digital tools remain essential, particularly for smaller farms.
The opportunities and challenges extend beyond agriculture.
A 2025 report by the United Nations Development Programme says Asia and the Pacific region, home to over 55 percent of the world's population, is at the center of the AI transition. The region hosts more than half of global AI users and is rapidly expanding its innovation footprint.
AI could lift annual GDP growth in the region by around 2 percentage points and raise productivity by up to 5 percent in sectors like health and finance. ASEAN economies, meanwhile, could see nearly 1 trillion U.S. dollars in additional GDP over the next decade, the report said.
Against this backdrop, experts at the International Forum on China Reform, recently held in Haikou, capital of Hainan, called for closer regional cooperation to ensure that more economies can benefit from AI.
Peng Sen, former president of the China Society of Economic Reform, said AI is emerging as a new driver of growth and productivity, offering Asia-Pacific economies opportunities to leverage their complementary strengths and reshape regional value chains.
Peng also stressed the need to address the digital divide, fragmented rules and barriers to cross-border flows of data, AI models and talent.
A background report prepared for the forum highlighted complementary strengths among members of the Regional Comprehensive Economic Partnership (RCEP). These include China's large AI application market, Japan and the Republic of Korea's expertise in semiconductor materials and chip manufacturing, and ASEAN economies' growing capabilities in data annotation, service outsourcing and smart city applications.
To turn these strengths into practical cooperation, the report proposed establishing an AI industrial cooperation working group under the RCEP framework and developing demonstration projects in agricultural AI, smart manufacturing, health care and other fields, drawing on existing platforms.
For agriculture, such cooperation could help make AI technologies more accessible to farmers through demonstration projects and tools adapted to local needs.
Ye Tun Win, Myanmar's deputy minister of agriculture, livestock and irrigation, expressed hope for expanded cooperation with China in AI, infrastructure and logistics to develop more efficient agricultural value chains. ■
