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市场调查报告书
商品编码
1897496
数位农业市场规模、份额和成长分析(按产品、技术、营运、类型和地区划分)-2026-2033年产业预测Digital Agriculture Market Size, Share, and Growth Analysis, By Offering (Advisory Services, Precision Agriculture & Farm Management), By Technology (Peripheral Technology, Core Technology), By Operation, By Type, By Region - Industry Forecast 2026-2033 |
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预计到 2024 年,全球数位农业市场规模将达到 246.6 亿美元,到 2025 年将达到 272.8 亿美元,到 2033 年将达到 610.7 亿美元,预测期(2026-2033 年)的复合年增长率为 10.6%。
数位农业领域正日益受到精密农业快速发展的影响。精准农业是一种创新方法,能够在提高作物产量的同时降低投入成本。它利用感测器和无人机等先进技术收集温度、养分含量和土壤湿度等关键数据。透过分析这些讯息,农民可以优化田间管理、监测作物健康状况,并更精准地施用肥料和农药。此外,物联网 (IoT) 技术与精密农业软体的整合正在改变整个产业,使农民能够更有效地追踪作物健康状况和土壤状况。总而言之,对数位化工具的日益依赖正在显着提高农业生产力,赋予全球农民,并促进更永续的农业实践。
全球数位农业市场驱动因素
全球数位农业市场正经历一场由人工智慧 (AI) 和物联网 (IoT) 技术在农业实践中融合所驱动的显着变革。这些先进技术使农民能够利用数据分析来优化产量、及早发现植物病害并准确预测天气,从而提高整体效率。智慧物联网感测器即时监测土壤湿度和养分水平等关键因素,实现精准灌溉和施肥。此外,自主机器、用于作物监测的人工智慧无人机以及机器人收割机的出现,正透过大幅减少对人力的依赖,改变着农业格局。
全球数位农业市场面临的限制因素
采用数位化农业技术需要大量资金投入,这对中小农场,尤其是发展中地区的农场来说,构成了严峻的挑战。人工智慧驱动的农业机械、精准灌溉和云端管理平台等先进解决方案通常需要高额的前期投资,这阻碍了许多农民采用这些创新技术。已开发地区的大型农业公司可以轻鬆地将资源投入到自动驾驶拖拉机和机器人收割机等先进技术中,而东南亚、非洲和拉丁美洲等地区的农民往往面临资金障碍。融资管道有限和政府支持不足进一步加剧了向现代农业转型的困难。
全球数位农业市场趋势
全球数位农业市场正经历一场变革,人工智慧技术的融合显着提升了农业实践的效率、生产力和永续性。精密农业的兴起正利用人工智慧驱动的工具,例如电脑视觉、机器学习、卫星影像、无人机和物联网感测器,来加强作物监测和资源管理。农民正利用预测分析来解读历史数据和环境因素,从而做出明智的决策,优化作物产量并降低风险。此外,自动化技术的应用,例如自动驾驶拖拉机和机器人收割机,在简化操作流程的同时降低了人事费用,进一步推动了生产力的成长。人工智慧聊天机器人和虚拟助理也为农民提供即时资讯,进一步巩固了市场的成长潜力。
Global Digital Agriculture Market size was valued at USD 24.66 Billion in 2024 and is poised to grow from USD 27.28 Billion in 2025 to USD 61.07 Billion by 2033, growing at a CAGR of 10.6% during the forecast period (2026-2033).
The digital agriculture landscape is increasingly shaped by the surge in precision farming, a revolutionary approach that enhances crop yields while reducing input costs. This method leverages advanced technologies like sensors and drones to collect critical data on temperature, nutrient levels, and soil moisture. By analyzing this information, farmers can optimize field management, monitor crop growth, and apply fertilizers and pesticides with greater precision. Furthermore, the integration of Internet of Things (IoT) technology and precision agriculture software is transforming the sector, enabling farmers to track crop progress and soil conditions more effectively. Overall, the growing reliance on digital tools is significantly improving agricultural productivity and empowering farmers globally, leading to more sustainable farming practices.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Digital Agriculture market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Digital Agriculture Market Segments Analysis
Global Digital Agriculture Market is segmented by Offering, Technology, Operation, Type and region. Based on Offering, the market is segmented into Advisory Services, Precision Agriculture & Farm Management, Quality Management & Traceability, Digital Procurement, Agri Ecommerce and Financial Services. Based on Technology, the market is segmented into Peripheral Technology and Core Technology. Based on Operation, the market is segmented into Farming & Feeding, Monitoring & Scouting and Marketing & Demand Generation. Based on Type, the market is segmented into Hardware, Software and Services. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Digital Agriculture Market
The Global Digital Agriculture market is experiencing a remarkable transformation driven by the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) in farming practices. These advanced technologies empower farmers to utilize data analytics for optimizing crop yields, early detection of plant diseases, and accurate weather predictions, enhancing overall efficiency. Smart IoT sensors facilitate real-time monitoring of critical factors such as soil moisture and nutrient levels, enabling precise irrigation and fertilization techniques. Moreover, the emergence of autonomous machinery, AI-equipped drones for crop surveillance, and robotic harvesters are significantly reducing reliance on manual labor, reshaping the agricultural landscape.
Restraints in the Global Digital Agriculture Market
The significant financial demands associated with the adoption of digital agriculture technologies present a considerable challenge, particularly for small and mid-sized farms located in developing regions. Advanced solutions such as AI-driven farming equipment, precision irrigation, and cloud-based management platforms often require high initial investments, hindering the ability of many farmers to embrace these innovations. While larger agribusinesses in more developed areas may easily allocate resources for cutting-edge tools like autonomous tractors and robotic harvesters, farmers in regions such as Southeast Asia, Africa, and Latin America frequently encounter financial barriers. Limited access to affordable financing options and insufficient government support further complicate the transition to modern agricultural practices.
Market Trends of the Global Digital Agriculture Market
The Global Digital Agriculture market is experiencing a transformative shift, propelled by the integration of AI technologies that significantly boost efficiency, productivity, and sustainability in farming practices. The rise of precision farming harnesses AI-driven tools like computer vision, machine learning, satellite imagery, drones, and IoT sensors for enhanced crop monitoring and resource management. Farmers leverage predictive analytics to interpret historical data and environmental factors, enabling informed decisions that optimize crop yield and mitigate risks. Furthermore, the adoption of automation, including autonomous tractors and robotic harvesters, streamlines operations while reducing labor costs, reinforcing a trend toward greater productivity. Additionally, AI chatbots and virtual assistants empower farmers with real-time insights, further solidifying the market's growth potential.