市場調查報告書
商品編碼
1441205
全球農業機器人市場規模、佔有率、成長分析、按產品類型、按應用分類 - 產業預測,2023-2030 年Global Agricultural Robots Market Size, Share, Growth Analysis, By Product Type(Unmanned aerial vehicles (UAVs), milking Robots), By Application(Field Farming, dairy Management) - Industry Forecast 2023-2030 |
2022年全球農業機器人市場規模預計為55億美元,從2023年的76.7億美元成長到2031年的1,099.6億美元,預測期間(2024-2031年)複合年成長率為39.49%。
全球農業機器人市場正在全球範圍內經歷顯著成長。我們的綜合報告包括詳細的價值鏈分析,製造商可以利用這些分析在預測期內獲得競爭優勢。由於迫切需要提高農業生產力,同時確保永續性,農業機器人越來越受到農民的歡迎。這些機器人執行田間耕作、酪農、種子分選和土壤管理等任務,在以最少的人為干預加快農業進程方面發揮關鍵作用。農業機器人市場的成長要素包括全球人口增加、食品供應需求增加、對室內農業的興趣日益濃厚、氣候變遷頻繁以及對自動化技術的接受程度不斷提高。儘管有這些積極的趨勢,但預計全球農業機器人領域仍面臨挑戰,例如農民對農業機器人的了解有限以及機器人無法再現人類的靈活性。然而,遠端資訊處理感測器的採用為全球市場帶來了巨大的機會。世界各國政府正在採取積極措施,提供補貼和支持以提高產量,並進行對農民進行農業機器人教育的宣傳活動。例如,歐盟 (EU) 支持 GRAPE 和 MARS 等舉措,旨在以先進的自動化技術取代集中任務。此外,現有和新的農業相關企業正在投資研發活動並引進尖端的農業機器人系列,進一步推動預測期內的市場成長。
Global Agricultural Robots Market size was valued at USD 5.5 Billion in 2022 and is poised to grow from USD 7.67 Billion in 2023 to USD 109.96 Billion by 2031, at a CAGR of 39.49% during the forecast period (2024-2031).
The global agricultural robots market is witnessing substantial growth on a worldwide scale. Our comprehensive report includes a detailed value chain analysis that manufacturers can leverage to attain a competitive advantage in the anticipated period. The increasing popularity of agricultural robots among farmers is driven by the imperative to enhance agricultural productivity while ensuring sustainability. These robots play a crucial role in expediting farming processes with minimal human intervention, performing tasks such as field farming, dairy farming, seed sorting, and soil management. Factors contributing to the growth of the agricultural robots market include a rising global population, heightened demand for food supply, growing interest in indoor farming, frequent climatic fluctuations, and an increased acceptance of automation technologies. Despite these positive trends, the global agricultural robotics sector is expected to encounter challenges, including farmers' limited understanding of agricultural robots and the robots' inability to replicate human-like dexterity. However, the adoption of telematics sensors presents a significant global market opportunity. Governments worldwide are taking proactive measures, such as providing subsidies and assistance to enhance output, as well as launching campaigns to educate farmers about agricultural robots. For instance, the European Union is supporting initiatives like GRAPE and MARS, aiming to replace labour-intensive tasks with advanced automated technology. Additionally, both existing and new agricultural companies are investing in research and development activities to introduce cutting-edge lines of agricultural robots, further fuelling the market's growth throughout the forecast period.
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 analysed to get the final quantitative and qualitative data.
Global Agricultural Robots Market Segmental Analysis
Global Agricultural Robots Market is segmented on the basis of product type, application and region. By product type, the market is segmented into unmanned aerial vehicles (UAVs), milking robots, driverless tractors, automated harvesting systems. By application, the market is segmented into field farming, dairy management, horticulture, livestock management. By region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
Drivers of the Global Agricultural Robots Market
Numerous global regions are grappling with the difficulty of securing a sufficient workforce for agricultural activities. Challenges like rural-to-urban migration, an aging farming demographic, and the lack of appeal in manual labour within agriculture have exacerbated this issue. Agricultural robots emerge as a practical solution, automating diverse tasks, diminishing dependence on human labour, and enhancing operational efficiency. Capable of executing precise activities such as planting, harvesting, and crop monitoring, these robots contribute to heightened productivity and decreased labour expenses.
Restraints in the Global Agricultural Robots Market
The implementation of agricultural robots typically involves significant financial commitments, encompassing the acquisition of robots, sensor technologies, and infrastructure enhancements. The inclusion of research and development costs, along with the integration of sophisticated technologies like AI and machine learning, contributes to the overall expenditure. This upfront financial outlay may pose a considerable obstacle to adoption, especially for small and medium-sized farms. Moreover, ongoing expenses related to maintenance, training, and potential difficulties in integration can further elevate the total cost of ownership.
Market Trends of the Global Agricultural Robots Market
The integration of AI and ML technologies provides advanced capabilities for data analysis and interpretation in the realm of agricultural robots. This allows these robots to collect valuable insights on aspects such as crop health, soil conditions, weather patterns, and pest infestations. Leveraging this information empowers farmers to make data-driven decisions, optimize resource allocation, and implement precision farming practices. The adaptive and learning capabilities enabled by AI and ML enable robots to continuously analyze data and refine their operations based on feedback. This iterative process contributes to a continual improvement in the performance of agricultural robots over time.