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1617119

2030年智慧農業市場預測：按農場規模、技術、應用和地區進行的全球分析

Intelligent Agriculture Market Forecasts to 2030 - Global Analysis By Farm Size, Technology (Internet of Things, Artificial Intelligence, Robotics and Automation, Cloud Computing and Other Technologies), Application and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據Stratistics MRC預測，2024年全球智慧農業市場規模將達到180.8億美元，預計2030年將達到349.3億美元，預測期內複合年成長率為11.6%。

智慧農業，也稱為智慧農業，是指利用先進技術、資料分析和自動化來最佳化農業實踐。它結合了物聯網 (IoT) 設備、無人機、感測器、人工智慧 (AI) 和機器學習等工具來監控和管理農業的各個方面，從種植作物到管理牲畜。這些技術使農民能夠做出更明智的決策，提高作物產量，減少資源浪費並提高永續性。

據世界銀行稱，基於技術的農業系統（包括智慧農業技術）可以顯著增加小規模農民的收入。世界銀行估計，數位農業可以幫助撒哈拉以南非洲和南亞等地區超過5億人減少貧窮。

糧食安全需求不斷成長

全球糧食安全需求的不斷成長正在推動智慧農業的快速成長。智慧農業是一種利用科技提高農業生產力和永續性的創新方法。預計到 2050 年，世界人口將達到近 100 億，確保穩定、高效的糧食供應成為關鍵問題。智慧農業利用人工智慧 (AI)、物聯網 (IoT)、機器人技術和資料分析等先進技術來最佳化農業運作。這些技術可以即時監測土壤健康、作物狀況和天氣模式，幫助農民做出有關灌溉、施肥和病蟲害防治的明智決策。透過提高資源效率和減少浪費，智慧農業可以提高產量，同時最大限度地減少對環境的影響。

初期投資成本高

高昂的初始投資成本是智慧農業技術廣泛採用的主要障礙。這些先進的農業解決方案，包括自動化機械、無人機、感測器、人工智慧（AI）系統等，需要在設備和基礎設施方面進行大量初步投資。對許多中小農戶來說，這種沉重的經濟負擔令人望而卻步，特別是在獲得貸款和補貼的機會有限的地區。除了購買技術本身之外，農民還經常面臨培訓、維護以及與現有系統整合的額外成本。因此，對於沒有足夠財力的農民來說，向更有效率、資料主導的耕作方法過渡變得更加困難。

農業技術與金融服務一體化

農業技術和金融服務的融合為農民提供了先進的工具和金融產品，從而提高了生產力和永續性，並正在徹底改變智慧農業。物聯網感測器、人工智慧主導的分析和精密農業工具等農業技術創新即時收集作物健康、土壤狀況和天氣模式的資料。這些資料對於農民做出明智的決策非常有價值。結合數位付款管道、農作物保險和信貸系統等金融服務，農民可以獲得技術投資所需的資金，降低風險並提高效率。

缺乏技術純熟勞工

缺乏技術純熟勞工是智慧農業發展的關鍵挑戰，智慧農業嚴重依賴技術和自動化來改善農業實踐。隨著各行業採用人工智慧、物聯網、無人機和資料分析等更先進的系統，對能夠操作、維護和最佳化這些技術的技術純熟勞工的需求不斷增加。然而，許多農民缺乏這些高科技領域的必要專業知識。這種差距導致效率低下，農民難以充分利用現代工具的潛力。勞動力老化以及農業職業對年輕一代的吸引力有限，加劇了勞動力短缺。

COVID-19 的影響：

COVID-19 大流行擾亂了全球供應鏈、勞動力供應和市場進入，對智慧農業產生了重大影響。農業部門至關重要，但限制和關閉造成了勞動力短缺，特別是在種植、收割和包裝等工作中，這些工作通常依賴季節性工人和農民工。勞動力短缺阻礙了農作物的及時生產和分配，影響了糧食供應。這場大流行促使人們對農業技術的依賴，包括精密農業、無人機和基於物聯網的監控系統，以填補勞動力短缺並提高效率。

預計中型農場在預測期內將是最大的

由於採用先進技術來最佳化生產力、永續性和資源管理，中型農場預計在預測期內將佔據最大佔有率。這些農場比小型家庭農場大，但比大型工業農場小，並將物聯網 (IoT) 設備、感測器、無人機和人工智慧 (AI) 整合到其農業作業中，這種趨勢越來越明顯。這些技術有助於即時監測作物健康、土壤濕度和天氣狀況，使農民能夠做出資料主導的決策，提高產量，同時最大限度地減少浪費。

作物監測產業預計在預測期內複合年成長率最高。

預計作物監測領域將在預測期內快速成長。作物監測是智慧農業的重要方面，大大提高了現代農業的效率和生產力。利用衛星影像、無人機和物聯網感測器等先進技術，農民可以持續即時監測作物健康、土壤濕度、溫度和其他關鍵因素。這種資料主導的方法使農民能夠做出更好的決策，最佳化灌溉，有效施用化學肥料和農藥，並檢測疾病和蟲害的早期徵兆。此外，作物監測系統通常結合人工智慧和機器學習演算法來分析大量資料並提供預測見解和建議以改善作物管理。

比最大的地區

預計亞太地區將在整個估計期間保持最大的市場佔有率。隨著農業部門的快速成長以及氣候變遷、人口成長和資源稀缺等日益嚴峻的挑戰，各國政府正在優先考慮智慧農業解決方案。人們正在製定政策和投資，以加速物聯網 (IoT)、人工智慧 (AI)、無人機和機器人等技術的採用。這些創新有助於最佳化資源利用、提高作物產量、改善供應鏈管理並減少對環境的影響。政府也促進官民合作關係，提供補貼、津貼和稅收優惠，並鼓勵農民採用科技。

複合年成長率最高的地區：

據估計，歐洲地區在預測期內的複合年成長率最高。隨著技術不斷重塑農業部門，歐洲農民和新興企業正在轉向精密農業、人工智慧主導的分析和物聯網設備等創新，以最佳化作物生產、減少資源消耗並提高效率，這種趨勢日益明顯。投資激增正在推動尖端解決方案的出現，這些解決方案可提高永續性、改善供應鏈管理並加強糧食安全。這些資本的湧入正在支持老牌農業科技公司和新興新興企業，使它們能夠擴大業務規模並擴大市場範圍。隨著資金籌措管道的增加，歐洲農業正變得更加資料主導和技術先進，從而實現更智慧、更有彈性的農業實踐。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 研究資訊來源
    • 主要研究資訊來源
    • 二次研究資訊來源
    • 先決條件

第3章市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 新興市場
  • COVID-19 的影響

第4章波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章全球智慧農業市場：依農場規模分類

  • 小農場
  • 中型農場
  • 大農場

第6章全球智慧農業市場：依技術分類

  • 物聯網 (IoT)
  • 人工智慧（AI）
  • 機器人和自動化
  • 雲端運算
  • 其他秤

第7章全球智慧農業市場：依應用分類

  • 精密農業
  • 牲畜監測
  • 作物監測
  • 智慧溫室
  • 農業無人機

第8章全球智慧農業市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東/非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第9章 主要進展

  • 合約、夥伴關係、合作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第 10 章 公司概況

  • AG Leader Technology
  • AGCO Corporation
  • BASF Agricultural Solutions
  • Bayer AG
  • John Deere
  • Kubota Corporation
  • Raven Industries
  • Syngenta AG
  • Trimble Inc
  • Topcon Positioning Systems
  • KUKA AG
  • JH Robotics, Inc
  • Kawasaki Heavy Industries
Product Code: SMRC27997

According to Stratistics MRC, the Global Intelligent Agriculture Market is accounted for $18.08 billion in 2024 and is expected to reach $34.93 billion by 2030 growing at a CAGR of 11.6% during the forecast period. Intelligent agriculture, also known as smart farming, refers to the use of advanced technologies, data analytics, and automation to optimize agricultural practices. It incorporates tools such as Internet of Things (IoT) devices, drones, sensors, artificial intelligence (AI), and machine learning to monitor and manage various aspects of farming, from crop growth to livestock management. These technologies enable farmers to make more informed decisions, improve crop yields, reduce resource wastage and enhance sustainability.

According to the World Bank, technology-based agriculture systems (including smart farming techniques) can significantly increase smallholder farmers' income. In regions such as Sub-Saharan Africa and South Asia, the World Bank estimates that digital agriculture could help reduce poverty for over 500 million people.

Market Dynamics:

Driver:

Rising demand for food security

Rising global demand for food security is driving the rapid growth of Intelligent Agriculture, an innovative approach that leverages technology to enhance agricultural productivity and sustainability. With the world's population projected to reach nearly 10 billion by 2050, ensuring a stable and efficient food supply has become a critical concern. Intelligent Agriculture uses advanced technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), robotics, and data analytics to optimize farming practices. These technologies enable real-time monitoring of soil health, crop conditions, and weather patterns, helping farmers make informed decisions on irrigation, fertilization, and pest control. By improving resource efficiency and reducing waste, Intelligent Agriculture can increase yields while minimizing environmental impact.

Restraint:

High initial investment costs

High initial investment costs are a significant barrier to the widespread adoption of intelligent agriculture technologies. These advanced farming solutions, which include automated machinery, drones, sensors, and artificial intelligence (AI) systems, require substantial upfront capital for both the equipment and infrastructure. For many small and medium-sized farmers, this high financial burden is prohibitive, especially in regions where access to financing or subsidies is limited. In addition to the purchase of the technologies themselves, farmers often face additional costs for training, maintenance, and integration with existing systems. As a result, the shift towards more efficient, data-driven farming practices becomes more challenging for those without sufficient financial resources.

Opportunity:

Integration of Agri-tech with financial services

The integration of agri-tech with financial services is revolutionizing intelligent agriculture by providing farmers with access to advanced tools and financial products that improve productivity and sustainability. Agri-tech innovations, such as IoT sensors, AI-driven analytics, and precision farming tools, collect real-time data on crop health, soil conditions, and weather patterns. This data is valuable for farmers to make informed decisions. When coupled with financial services like digital payment platforms, crop insurance, and credit systems, farmers can access the necessary capital to invest in technology, reduce risks, and increase efficiency.

Threat:

Shortage of skilled labor

The shortage of skilled labor is a significant challenge in the advancement of intelligent agriculture, which relies heavily on technology and automation to improve farming practices. As the industry adopts more advanced systems such as AI, IoT, drones, and data analytics, there is a growing need for skilled workers who can operate, maintain, and optimize these technologies. However, many agricultural workers lack the necessary expertise in these high-tech fields. This gap results in inefficiencies, as farmers struggle to fully harness the potential of modern tools. The labor shortage is further compounded by an aging workforce and the limited appeal of agricultural careers among younger generations.

Covid-19 Impact:

The COVID-19 pandemic significantly impacted intelligent agriculture by disrupting global supply chains, labor availability, and market access. While the agriculture sector is essential, the restrictions and lockdowns led to labor shortages, especially in tasks like planting, harvesting, and packaging, which were often reliant on seasonal or migrant workers. This labor deficit hindered the timely production and distribution of crops, affecting food supply. The pandemic prompted a greater reliance on technology in agriculture, such as precision farming, drones, and IoT-based monitoring systems, to compensate for the workforce shortage and improve efficiency.

The Medium Scale Farms segment is expected to be the largest during the forecast period

Medium Scale Farms segment is expected to dominate the largest share over the estimated period, by adopting advanced technologies to optimize productivity, sustainability, and resource management. These farms, which are larger than small family-run operations but smaller than large industrial farms, are increasingly integrating Internet of Things (IoT) devices, sensors, drones, and artificial intelligence (AI) into their farming practices. These technologies help in real-time monitoring of crop health, soil moisture, and weather conditions, allowing farmers to make data-driven decisions that improve yields while minimizing waste.

The Crop Monitoring segment is expected to have the highest CAGR during the forecast period

Crop Monitoring segment is estimated to grow at a rapid pace during the forecast period. Crop monitoring is a key aspect of intelligent agriculture, significantly enhancing the efficiency and productivity of modern farming. Through the use of advanced technologies such as satellite imagery, drones, and IoT sensors, farmers can continuously monitor crop health, soil moisture, temperature, and other vital factors in real-time. This data-driven approach allows for precise decision-making, enabling farmers to optimize irrigation, apply fertilizers and pesticides more efficiently, and detect early signs of diseases or pest infestations. Furthermore, crop monitoring systems often incorporate AI and machine learning algorithms to analyze large volumes of data, providing predictive insights and recommendations for improved crop management.

Region with largest share:

Asia Pacific region is poised to hold the largest share of the market throughout the extrapolated period. With the rapid growth of the agricultural sector and increasing challenges like climate change, population growth, and resource scarcity, governments are prioritizing smart farming solutions. Policies and investments are being made to promote the adoption of technologies such as Internet of Things (IoT), Artificial Intelligence (AI), drones, and robotics. These innovations help optimize resource use, enhance crop yields, improve supply chain management, and reduce environmental impacts. Governments are also fostering public-private partnerships, providing subsidies, grants, and tax incentives to encourage technological adoption among farmers.

Region with highest CAGR:

Europe region is estimated to witness the highest CAGR during the projected time frame. As technology continues to reshape the agricultural sector, European farmers and startups are increasingly adopting innovations like precision farming, AI-driven analytics, and IoT-enabled devices to optimize crop production, reduce resource consumption, and increase efficiency. The surge in investment has facilitated the emergence of cutting-edge solutions that enhance sustainability, improve supply chain management, and boost food security. This capital influx supports both established AgTech companies and emerging startups, enabling them to scale their operations and expand their market reach. With increased access to funding, European agriculture is becoming more data-driven and technologically advanced, allowing for smarter, more resilient farming practices.

Key players in the market

Some of the key players in Intelligent Agriculture market include AG Leader Technology, AGCO Corporation, BASF Agricultural Solutions, Bayer AG, John Deere, Kubota Corporation, Raven Industries, Syngenta AG, Trimble Inc, Topcon Positioning Systems, KUKA AG, JH Robotics, Inc and Kawasaki Heavy Industries.

Key Developments:

In July 2024, AGCO to Launch Autonomous Tractor Retrofit Kits for Mixed-fleets. The retrofit kits will enable select Fendt and John Deere tractors to autonomously perform grain cart and tillage functions, with more tractor compatibility and functions coming in the future.

In March 2024, Kubota Launches RTV520 Crossroads Edition. This refresh to the 2020 model adds a handful of factory-installed features based on popular request. This new limited edition of the RTV520 comes with a package of factory-installed creature comforts.

Farm Sizes Covered:

  • Small Scale Farms
  • Medium Scale Farms
  • Large Scale Farms

Technologies Covered:

  • Internet of Things (IoT)
  • Artificial Intelligence (AI)
  • Robotics and Automation
  • Cloud Computing
  • Other Technologies

Applications Covered:

  • Precision Farming
  • Livestock Monitoring
  • Crop Monitoring
  • Smart Greenhouses
  • Agricultural Drones

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Intelligent Agriculture Market, By Farm Size

  • 5.1 Introduction
  • 5.2 Small Scale Farms
  • 5.3 Medium Scale Farms
  • 5.4 Large Scale Farms

6 Global Intelligent Agriculture Market, By Technology

  • 6.1 Introduction
  • 6.2 Internet of Things (IoT)
  • 6.3 Artificial Intelligence (AI)
  • 6.4 Robotics and Automation
  • 6.5 Cloud Computing
  • 6.6 Other Technologies

7 Global Intelligent Agriculture Market, By Application

  • 7.1 Introduction
  • 7.2 Precision Farming
  • 7.3 Livestock Monitoring
  • 7.4 Crop Monitoring
  • 7.5 Smart Greenhouses
  • 7.6 Agricultural Drones

8 Global Intelligent Agriculture Market, By Geography

  • 8.1 Introduction
  • 8.2 North America
    • 8.2.1 US
    • 8.2.2 Canada
    • 8.2.3 Mexico
  • 8.3 Europe
    • 8.3.1 Germany
    • 8.3.2 UK
    • 8.3.3 Italy
    • 8.3.4 France
    • 8.3.5 Spain
    • 8.3.6 Rest of Europe
  • 8.4 Asia Pacific
    • 8.4.1 Japan
    • 8.4.2 China
    • 8.4.3 India
    • 8.4.4 Australia
    • 8.4.5 New Zealand
    • 8.4.6 South Korea
    • 8.4.7 Rest of Asia Pacific
  • 8.5 South America
    • 8.5.1 Argentina
    • 8.5.2 Brazil
    • 8.5.3 Chile
    • 8.5.4 Rest of South America
  • 8.6 Middle East & Africa
    • 8.6.1 Saudi Arabia
    • 8.6.2 UAE
    • 8.6.3 Qatar
    • 8.6.4 South Africa
    • 8.6.5 Rest of Middle East & Africa

9 Key Developments

  • 9.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 9.2 Acquisitions & Mergers
  • 9.3 New Product Launch
  • 9.4 Expansions
  • 9.5 Other Key Strategies

10 Company Profiling

  • 10.1 AG Leader Technology
  • 10.2 AGCO Corporation
  • 10.3 BASF Agricultural Solutions
  • 10.4 Bayer AG
  • 10.5 John Deere
  • 10.6 Kubota Corporation
  • 10.7 Raven Industries
  • 10.8 Syngenta AG
  • 10.9 Trimble Inc
  • 10.10 Topcon Positioning Systems
  • 10.11 KUKA AG
  • 10.12 JH Robotics, Inc
  • 10.13 Kawasaki Heavy Industries

List of Tables

  • Table 1 Global Intelligent Agriculture Market Outlook, By Region (2022-2030) ($MN)
  • Table 2 Global Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
  • Table 3 Global Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
  • Table 4 Global Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
  • Table 5 Global Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
  • Table 6 Global Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
  • Table 7 Global Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
  • Table 8 Global Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
  • Table 9 Global Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
  • Table 10 Global Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
  • Table 11 Global Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
  • Table 12 Global Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
  • Table 13 Global Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
  • Table 14 Global Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
  • Table 15 Global Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
  • Table 16 Global Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
  • Table 17 Global Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
  • Table 18 North America Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
  • Table 19 North America Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
  • Table 20 North America Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
  • Table 21 North America Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
  • Table 22 North America Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
  • Table 23 North America Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
  • Table 24 North America Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
  • Table 25 North America Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
  • Table 26 North America Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
  • Table 27 North America Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
  • Table 28 North America Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
  • Table 29 North America Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
  • Table 30 North America Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
  • Table 31 North America Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
  • Table 32 North America Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
  • Table 33 North America Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
  • Table 34 North America Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
  • Table 35 Europe Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
  • Table 36 Europe Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
  • Table 37 Europe Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
  • Table 38 Europe Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
  • Table 39 Europe Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
  • Table 40 Europe Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
  • Table 41 Europe Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
  • Table 42 Europe Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
  • Table 43 Europe Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
  • Table 44 Europe Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
  • Table 45 Europe Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
  • Table 46 Europe Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
  • Table 47 Europe Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
  • Table 48 Europe Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
  • Table 49 Europe Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
  • Table 50 Europe Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
  • Table 51 Europe Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
  • Table 52 Asia Pacific Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
  • Table 53 Asia Pacific Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
  • Table 54 Asia Pacific Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
  • Table 55 Asia Pacific Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
  • Table 56 Asia Pacific Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
  • Table 57 Asia Pacific Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
  • Table 58 Asia Pacific Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
  • Table 59 Asia Pacific Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
  • Table 60 Asia Pacific Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
  • Table 61 Asia Pacific Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
  • Table 62 Asia Pacific Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
  • Table 63 Asia Pacific Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
  • Table 64 Asia Pacific Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
  • Table 65 Asia Pacific Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
  • Table 66 Asia Pacific Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
  • Table 67 Asia Pacific Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
  • Table 68 Asia Pacific Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
  • Table 69 South America Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
  • Table 70 South America Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
  • Table 71 South America Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
  • Table 72 South America Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
  • Table 73 South America Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
  • Table 74 South America Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
  • Table 75 South America Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
  • Table 76 South America Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
  • Table 77 South America Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
  • Table 78 South America Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
  • Table 79 South America Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
  • Table 80 South America Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
  • Table 81 South America Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
  • Table 82 South America Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
  • Table 83 South America Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
  • Table 84 South America Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
  • Table 85 South America Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)
  • Table 86 Middle East & Africa Intelligent Agriculture Market Outlook, By Country (2022-2030) ($MN)
  • Table 87 Middle East & Africa Intelligent Agriculture Market Outlook, By Farm Size (2022-2030) ($MN)
  • Table 88 Middle East & Africa Intelligent Agriculture Market Outlook, By Small Scale Farms (2022-2030) ($MN)
  • Table 89 Middle East & Africa Intelligent Agriculture Market Outlook, By Medium Scale Farms (2022-2030) ($MN)
  • Table 90 Middle East & Africa Intelligent Agriculture Market Outlook, By Large Scale Farms (2022-2030) ($MN)
  • Table 91 Middle East & Africa Intelligent Agriculture Market Outlook, By Technology (2022-2030) ($MN)
  • Table 92 Middle East & Africa Intelligent Agriculture Market Outlook, By Internet of Things (IoT) (2022-2030) ($MN)
  • Table 93 Middle East & Africa Intelligent Agriculture Market Outlook, By Artificial Intelligence (AI) (2022-2030) ($MN)
  • Table 94 Middle East & Africa Intelligent Agriculture Market Outlook, By Robotics and Automation (2022-2030) ($MN)
  • Table 95 Middle East & Africa Intelligent Agriculture Market Outlook, By Cloud Computing (2022-2030) ($MN)
  • Table 96 Middle East & Africa Intelligent Agriculture Market Outlook, By Other Technologies (2022-2030) ($MN)
  • Table 97 Middle East & Africa Intelligent Agriculture Market Outlook, By Application (2022-2030) ($MN)
  • Table 98 Middle East & Africa Intelligent Agriculture Market Outlook, By Precision Farming (2022-2030) ($MN)
  • Table 99 Middle East & Africa Intelligent Agriculture Market Outlook, By Livestock Monitoring (2022-2030) ($MN)
  • Table 100 Middle East & Africa Intelligent Agriculture Market Outlook, By Crop Monitoring (2022-2030) ($MN)
  • Table 101 Middle East & Africa Intelligent Agriculture Market Outlook, By Smart Greenhouses (2022-2030) ($MN)
  • Table 102 Middle East & Africa Intelligent Agriculture Market Outlook, By Agricultural Drones (2022-2030) ($MN)