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Journal of Integrative Agriculture
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Cotton science and production in China: A decade of progress and prospects

Lei Fang1*#, Guanjing Hu2*, Yanjun Zhang3*, Chengzhen Liang4*, Juyun Zheng5*, Shangkun Jin1, Lei Shao1, Yabing Li2, Mirza Muhammad Ahad Baig4, Wangfeng Zhang6#, Hezhong Dong3#, Xiongfeng Ma2#, Tianzhen Zhang1#

1 Key Laboratory of Speed Breeding in Plant Factory, Ministry of Agriculture and Rural Affairs/Zhejiang Key Laboratory of Crop Germplasm Innovation &Utilization/Advanced Seed Institute, Zhejiang University, Hangzhou 300058, China
2 Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
3 State Key Laboratory of Nutrient Use and Management/Institute of Industrial Crops, Shandong Academy of Agricultural Sciences, Jinan 250100, China
4 Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
5 Xinjiang Key Laboratory of Cotton Genetic Improvement and Intelligent Production/Cotton Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830091, China
6 Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps/Shihezi University, Shihezi 832003, China
Highlights
Industry & Policy dynamics: Key shifts in planting layouts, cultivar development, consumption trends, and policy impacts.
Genomics & Molecular breeding: Breakthroughs in telomere-to-telomere/pan-genomes, trait gene cloning (quality, yield, resistance), and functional marker systems.
Regional cultivation & Smart agriculture: Innovations in Xinjiang mechanization and river valley resilient models, advancing toward data-driven, sensor-integrated farming.  

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摘要  

棉花(Gossypium spp.)是全球最重要的天然纤维作物之一,也是保障我国纺织工业稳定运行的重要战略物资。过去十年,高通量测序、全基因组关联分析、多组学整合、基因组选择与基因编辑等技术不断发展,推动棉花研究由传统经验育种向数据驱动、定向设计改良转型。本文综述近十年来我国棉花生产格局、区域布局与消费结构的变化;总结基因组学领域重大进展,包括从祖先基因组到端粒-端粒无缺口基因组组装与泛基因组研究,以及功能标记开发、产量、纤维品质、抗病性和非生物胁迫耐受性等关键农艺性状基因克隆方面的成果。栽培技术层面,我国构建了以集中成熟为核心、适配不同区域的高效栽培体系。新疆棉区通过精量单粒播种、干播湿出、膜下滴灌水肥一体化、密度与化控塑造株型、机采配套脱叶等技术,实现全程机械化生产,同时减少水、肥与人工投入;黄河流域与长江流域棉区采用精播或后茬直播、增密、化学打顶、高效脱叶等简化栽培模式,提升劳动生产率与生产稳定性。展望未来,棉花改良将朝着整合设计育种与智慧栽培方向发展,融合基因编辑、人工智能、大数据、数字化表型与自动化管理技术。解析复杂农艺性状调控网络、高效利用野生资源与未充分发掘的种质材料,以及将遗传改良和智能生产技术相结合,将是推动我国棉花产业可持续高质量发展的关键。



Abstract  Cotton (Gossypium spp.) is a globally important natural fiber crop and a cornerstone of China’s textile industry security.  Over the past decade, advances in high-throughput sequencing, genome-wide association studies, multi-omics integration, genomic selection, and gene editing have accelerated the transition of cotton research from traditional, experience-based breeding to data-driven, design-oriented improvement.  This review examines changes in China’s cotton production patterns, regional distribution, and consumption structure over the last 10 years.  We summarize major breakthroughs in genomics, from progenitor genomes to telomere-to-telomere gap-free assemblies and pan-genomes, along with progress in functional marker development and the cloning of genes that govern critical agronomic traits, including yield, fiber quality, disease resistance, and abiotic stress tolerance.  In cultivation, China has developed regionally adapted high-efficiency systems centered on concentrated maturity.  In Xinjiang, precision monoseeding, dry sowing-wet emergence, mulched drip fertigation, density–chemical architecture regulation, and harvest-oriented defoliation have jointly enabled fully mechanized production while reducing water, fertilizer, and labor inputs.  In the Yellow and Yangtze River valleys, simplified systems based on precision sowing or post-harvest direct seeding, higher density, chemical topping, and efficient defoliation have improved labor productivity and production resilience.  Looking forward, cotton improvement is expected to move toward integrated design breeding and smart cultivation, combining genome editing, artificial intelligence, big data, digital phenotyping, and automated management.  The systematic dissection of complex agronomic networks, the effective use of wild resources and underutilized germplasm, and the integration of genetic improvement with intelligent production technologies will be critical to advancing China’s cotton industry toward sustainable, high-quality development.
Keywords:  cotton       genomics              functional marker              cultivation              artificial intelligence  
Online: 14 September 2026  
Fund: This work was financially supported in part by the Project of Fund for Stable Support to Finance Science and Technology Project of Xinjiang Uyghur Autonomous Region, China (2023A01), the National Natural Science Foundation of China (32341024), and the Xinjiang Talent Development Fund Project, China (XJRC-2025-KJ-YJ-CXPT-172).
About author:  Lei Fang, E-mail: fangl@zju.edu.cn; Guanjing Hu, E-mail: huguanjing@caas.cn; Yanjun Zhang, E-mail: zhangyanjunche@163.com; Chengzhen Liang, E-mail: liangchengzhen@caas.cn; Juyun Zheng, E-mail: zjypp8866@126.com; #Correspondence Lei Fang, E-mail: fangl@zju.edu.cn; Tianzhen Zhang, E-mail: cotton@zju.edu.cn; Xiongfeng Ma, E-mail: maxiongfeng@caas.cn; Hezhong Dong, E-mail: donghezhong@163.com; Wangfeng Zhang, E-mail: zhwf_agr@shzu.edu.cn * These authors contributed equally to this study.

Cite this article: 

Lei Fang, Guanjing Hu, Yanjun Zhang, Chengzhen Liang, Juyun Zheng, Shangkun Jin, Lei Shao, Yabing Li, Mirza Muhammad Ahad Baig, Wangfeng Zhang, Hezhong Dong, Xiongfeng Ma, Tianzhen Zhang. 2026. Cotton science and production in China: A decade of progress and prospects. Journal of Integrative Agriculture, Doi:10.1016/j.jia.2026.09.028

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