A drone captures a picture of the Yazhou Bay Science and Technology City in Sanya, Hainan province, on July 29. YANG GUANYU/XINHUA
In the huge, sun-drenched fields of Yazhou Bay in Sanya, Hainan province, a quiet however monumental shift is happening. Here, the follow of crop breeding is being rewritten not with a hoe, however with laptop algorithms.
For generations, growing a superior seed selection was typically an inexact science — a decade-long pursuit typically relying closely on a breeder’s hunch. Now, a brand new initiative powered by synthetic intelligence guarantees to slash that timeline in half, aiming to ship resilient, high-yield crops in simply three to 4 years.
Officially referred to as the Future Agriculture Nexus, or Fan, the venture is a joint creation of the Yazhou Bay National Laboratory and Chinese tech firm Huawei Technologies Co. The hub goals to remodel breeding right into a exact, predictive science — a vital transfer for a nation safeguarding its meals safety in an period of local weather uncertainty.
The aim is according to China’s strategic wants, with seeds seen as the “chips” of worldwide agriculture.
During an inspection of the Yazhou Bay laboratory in April 2022, President Xi Jinping harassed the significance of pursuing agricultural technological breakthroughs to attain self-dependence in the seed sector. “We should rely on Chinese seeds to ensure China’s food security,” he stated.
Yuan Xiaohui, a senior scientist at the Yazhou Bay National Laboratory, stated that “as the only national-level laboratory in China’s agricultural sector, our lab’s mission is to develop major strategic crop varieties to meet real demand”.
“We are fully aware that AI holds immense potential to empower agricultural science, but data remains the core bottleneck hindering its practical application,” Yuan stated.
“There is an urgent need for us to build a system capable of integrating global field and laboratory data while providing intelligent analytical capabilities.”
Chen Fan, deputy director of the laboratory, outlined the basic shift required.
“Traditional breeding work relies heavily on experience. Moving from traditional to precision breeding requires analyzing correlations between massive amounts of data on crop traits and genotypes,” Chen stated.
Connecting information islands
For generations, breeders have operated like explorers in an enormous, uncharted organic wilderness. The course of of choosing father or mother vegetation, crossbreeding, and evaluating hundreds of progeny over a number of rising seasons is painstakingly gradual, with the success fee typically beneath 1 %, consultants stated.
This problem, Chen added, is compounded by deeply entrenched “data silos”.
“Data on genotype, phenotype, environment, and even soil are all kept separate. This fragmentation creates a critical bottleneck,” he stated.
Yuan stated: “Researchers often know neither the source and quality of data, nor can they discern which data AI can understand. This causes AI to falter — or worse, produce erroneous results.”
It is that this exact drawback that the Fan venture is engineered to resolve, appearing as a “central nervous system” to attach disparate information islands — a full-chain AI technical system constructed on Huawei’s AI information answer.
Yuan Yuan, vice-president of Huawei’s information storage product line, stated the Fan platform tackles the drawback in 3 ways. First, it aggregates and standardizes multisource information on atmosphere, traits, phenotype, and genotype from throughout the nation.
Second, it makes use of specialised instruments to allow the fast building of custom-made, industry-specific AI giant language fashions, which may minimize mannequin growth time from 15 days to 5, Yuan stated.
Finally, its core “breeding AI agent” can intelligently display this unified information, automate complicated evaluation workflows, and validate fashions to establish optimum breeding pathways, he stated.
“The impact is transformative,” Yuan stated.
“It can shorten the traditional 20-generation cultivation cycle for crops like rice, which usually takes eight to 10 years, to just five generations, or three to four years.”
This represents a 50 % discount in the breeding cycle and may enhance total effectivity by an estimated 30 %.
The venture represents greater than a technical development. It can be a press release of strategic intent aligned with a nationwide blueprint. “This intelligent system currently does not exist globally,” stated Chen.
The aim is to quickly advance the building of the “Nanfan Silicon Valley” and set up a number one hub for future agriculture.
“Nanfan” refers to a novel breeding technique utilizing Hainan’s heat winters as a pure method to speed up the course of. According to a nationwide plan, the Nanfan breeding base, positioned in Hainan, is ready to evolve into the “Silicon Valley” of China’s seed {industry} by 2030, serving as a complete hub for agricultural analysis, {industry}, and expertise change.
This ambition mirrors high-level nationwide directives. On Nov 13, 2025,China’s Ministry of Agriculture and Rural Affairs convened a nationwide convention to advance the seed {industry} revitalization motion, charting the course for the fifteenth Five-Year Plan interval (2026-30). The convention referred to as for accelerating the realization of self-reliance and self-improvement in seed expertise and securing a agency grip on seed sources.
At the {industry} stage, the plan emphasizes upgrading the Nanfan Silicon Valley scientific base right into a nationwide seed innovation hub that integrates analysis, commercialization, and software.
“Digitalization and intelligence are undoubtedly the future directions for building the Nanfan Silicon Valley,” Chen stated. “We must use advanced technology to serve and transform both agricultural production and research.”
This initiative is a part of a broader push to harness AI for agricultural progress throughout the nation. In 2024,Yazhou Bay National Laboratory researchers, in collaboration with China Agricultural University and the Shanghai Artificial Intelligence Laboratory, developed China’s first giant language mannequin for seed design, referred to as SeedLLM, or Fengdeng.
This AI platform supplies professional insights on breeding, cultivation and {industry} traits — empowering farmers and researchers with sensible data.
In July 2025, Fengdeng was upgraded to an AI agent with three core analysis features, stated Yang Fan, a scientist at the laboratory.
The first perform is data summarization, which addresses key questions like “which traits are regulated by what type of genes”. It does this by mechanically integrating over 98 % of related world crop analysis literature to construct a gene-trait-environment affiliation map.
The second is gene-trait affiliation prediction, enabling autonomous genome-wide screening of key genes past conventional reasoning.
The third is experimental reasoning and design optimization, the place it simulates professional logic to automate the whole analysis cycle from speculation technology and experimental design to outcome evaluation, Yang stated.
Agricultural researchers examine agronomic traits of rice at Nanfan breeding base, Yazhou Bay, on Feb 10. ZHAO YINGQUAN/XINHUA
Nationwide effort
Agricultural innovation can be advancing at different Chinese establishments and analysis our bodies.
At the China National Seed Group, researchers use an AI-powered, cloud-based system to remotely monitor fields and accumulate real-time information on crop well being, enabling immediate intervention.
The Chinese Academy of Agricultural Sciences can be exploring the transition from experience-driven to data-driven breeding.
In the previous, breeders examined hundreds of combos to discover a single superior hybrid. Now, AI-powered genomic evaluation predicts high-yield combos earlier than subject trials start, stated Li Huihui, deputy director of the National Nanfan Research Institute of the Chinese Academy of Agricultural Sciences.
Li Jiayang, an academician at the Chinese Academy of Sciences, spoke extremely of the idea of “intelligent creation of intelligent varieties”, underscoring the potential of integrating AI, biotechnology and knowledge expertise to develop crops that autonomously adapt to environmental challenges.
Despite these developments, challenges stay.
“Our country’s total number of research papers in the seed field has surpassed that of the United States,” stated Wan Jianmin, an academician of the Chinese Academy of Engineering and former vice-president of the Chinese Academy of Agricultural Sciences.
“However, the connection between basic research and breeding application is not tight enough, and the innovation capacity in breeding theory and methodology is relatively weak,” Wan stated.
Wan additionally highlighted gaps in frontier biotechnology.
“Our R&D capability and level in biotechnology still lag noticeably behind the US. This is evident in core patents. While China’s core patent quantity ranks second globally, the US holds far more high-value patents and controls the majority of core biotechnology patents,” he added.
China’s sensible breeding sector additionally trails world seed giants when it comes to data-sharing infrastructure and commercialization, stated Qian Qian, one other Chinese Academy of Sciences academician.
“Given the complexity of crop traits, understanding the relationship between genes and traits requires computational power and advanced algorithms,” Qian stated.
“Accelerating the development of high-yield, high-quality and climate-resilient ‘super varieties’ is crucial,” Qian stated, calling for interdisciplinary collaboration amongst breeding establishments, AI researchers and agribusinesses, to drive improvements in sensible breeding.
Experts look at bananas at a trial plantation in Yazhou Bay science and expertise metropolis in July. YANG GUANYU/XINHUA
Global quest
These endeavors have been constructed on a basis of immense organic assets.
China hosts the world’s largest and most structurally numerous repository of agricultural germplasm, in response to the Ministry of Agriculture and Rural Affairs.
The newest nationwide census of agricultural germplasm assets collected 139,000 new crop germplasm assets, offering a wealthy “source supply” for future breeding innovation.
The {industry}’s scale can be increasing. The home seed market worth surpassed 150 billion yuan ($21.51 billion) for the first time in 2023, whereas R&D spending reached 7.6 billion yuan, a 20 % improve from 2021, in response to People’s Daily.
The use of AI in agriculture just isn’t confined to China. Scientists and entrepreneurs worldwide are utilizing algorithms to construct a extra resilient and productive meals system.
In the US, the drive is spearheaded by a vibrant ecosystem of startups rising from prime analysis hubs.
Heritable Agriculture, a spin-off from Google X’s moonshot manufacturing unit, applies machine studying to investigate plant genomes, aiming to establish genetic combos that improve yield, scale back water use, and improve soil carbon storage — all with out direct genetic modification.
Researchers from Longping Biotechnology (Hainan) Co work on corn hybridization in Yazhou Bay science and expertise metropolis in February. ZHAO YINGQUAN/XINHUA
To share the technological progress it has made, the Yazhou Bay National Laboratory can be deepening worldwide cooperation. In December, it signed a cooperation memorandum of understanding with agricultural analysis establishments from Colombia, Peru, Ecuador, and Chile.
“It is positive to strengthen Global South collaboration, integrating experience and knowledge from both sides to tackle food security and sustainability issues,” stated Agustin Zsogon, a professor at Brazil’s Federal University of Vicosa.
Santiago Signorelli, a biochemistry professor at the University of the Republic in Uruguay, stated China’s superior applied sciences maintain nice potential for contributing to scientific work in Uruguay.
From the experimental fields of Hainan to farms worldwide, a typical narrative is rising. The daunting challenges of local weather change and useful resource shortage are being met with the converging energy of superior biology and AI.
Huawei’s Yuan stated: “Our future collaboration prospects are very broad; this is just the beginning.”
(Web editor: Wang Xiaoping, Liang Jun)