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市場調査レポート
商品コード
1651668
農業ロボットの市場規模、シェア、成長分析:コンポーネント別、タイプ別、農業環境別、用途別、地域別 - 産業予測 2025~2032年Agricultural Robots Market Size, Share, and Growth Analysis, By Component (Hardware, Software), By Type (Unmanned Aerial Vehicles/Drones, Milking Robots), By Farming Environment, By Application, By Region - Industry Forecast 2025-2032 |
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農業ロボットの市場規模、シェア、成長分析:コンポーネント別、タイプ別、農業環境別、用途別、地域別 - 産業予測 2025~2032年 |
出版日: 2025年02月05日
発行: SkyQuest
ページ情報: 英文 202 Pages
納期: 3~5営業日
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農業ロボットの世界市場規模は2023年に76億7,000万米ドルと評価され、2024年の106億9,000万米ドルから2032年には1,524億6,000万米ドルに成長し、予測期間(2025-2032年)のCAGRは39.4%で成長する見通しです。
世界の農業ロボット市場は、人口増加と持続可能な農法へのシフトに伴う食糧需要の増加により、力強い成長軌道に乗っています。農家が労働力を最小限に抑えながら効率性を高めようとする中、農業ロボットは圃場作業、酪農管理、種子選別、土壌管理など様々な作業に欠かせないものとなっています。気候の変動や室内農業の増加傾向といった動向は、この市場の拡大をさらに後押ししています。しかし、農家の意識が限定的であることや、ロボットが人間の手先の器用さを再現できないといった課題が、採用の妨げになる可能性があります。とはいえ、テレマティクスセンサーの採用による機会も存在します。欧州連合(EU)による自動化プロジェクト支援などの政府の取り組みや、研究開発への多額の投資は、特に今後数年間で持続的な成長が見込まれる米国市場において、市場の成長を後押しする構えです。
Global Agricultural Robots Market size was valued at USD 7.67 billion in 2023 and is poised to grow from USD 10.69 billion in 2024 to USD 152.46 billion by 2032, growing at a CAGR of 39.4% during the forecast period (2025-2032).
The global agricultural robots market is on a robust growth trajectory, driven by increasing food demand amidst rising populations and a shift towards sustainable farming practices. As farmers seek to enhance efficiency while minimizing labor, agricultural robots have become essential for various tasks, including field operations, dairy management, seed sorting, and soil care. Factors such as climate variability and the growing trend of indoor farming further fuel this market's expansion. However, challenges like limited farmer awareness and robots' inability to replicate human dexterity may hinder adoption. Yet, opportunities exist through the adoption of telematics sensors. Government initiatives, such as the European Union's support for automation projects, and significant investments in R&D are poised to bolster market growth, particularly in the U.S. market, anticipated to grow sustainably in the coming years.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Agricultural Robots 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 Agricultural Robots Market Segments Analysis
Global Agricultural Robots Market is segmented by Component, Type, Farming Environment, Application and region. Based on Component, the market is segmented into Hardware, Software, and Services. Based on Type, the market is segmented into Unmanned Aerial Vehicles/Drones, Milking Robots, Driverless Tractors, Automated Harvesting Systems, and Others. Based on Farming Environment, the market is segmented into Indoor and Outdoor. Based on Application, the market is segmented into Harvest Management, Dairy & Livestock Management, Inventory Management, Soil & Irrigation Management and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Agricultural Robots Market
The global agricultural robots market is largely driven by the ongoing difficulties in securing sufficient manpower for farming operations across various regions. Contributing factors include the trend of rural-to-urban migration, an aging farmer demographic, and the decreasing appeal of manual agricultural work. In response to these challenges, agricultural robots present an effective alternative by automating essential tasks, thereby minimizing dependence on human labor and enhancing overall operational efficiency. These robotic systems are capable of executing tasks such as planting, harvesting, and crop monitoring with remarkable precision, ultimately leading to heightened productivity and lowered labor expenses for farmers.
Restraints in the Global Agricultural Robots Market
The Global Agricultural Robots market faces significant restraints primarily due to the high expenses associated with adopting this technology. Implementing agricultural robots necessitates substantial financial investments in essential components, such as the robots themselves, sensor systems, and necessary infrastructure improvements. Furthermore, the costs associated with research and development, along with the integration of cutting-edge technologies like artificial intelligence and machine learning, contribute to the overall financial burden. These upfront costs can be particularly daunting for small and medium-sized farms, acting as a major hurdle to their implementation. Ongoing maintenance, training, and integration challenges also exacerbate the overall cost of ownership.
Market Trends of the Global Agricultural Robots Market
The Global Agricultural Robots market is witnessing a prominent trend characterized by the integration of artificial intelligence (AI) and machine learning (ML) technologies. These advancements significantly enhance the operational efficiency of agricultural robots by facilitating sophisticated data analysis and interpretation. As robots gather insights about crucial factors such as crop health, soil conditions, weather patterns, and pest infestations, farmers can leverage this information for informed decision-making, optimizing resource allocation, and adopting precision farming practices. Moreover, the adaptive capabilities enabled by AI and ML allow these robots to evolve based on continuous data feedback, driving improved performance and efficiency in agricultural operations.