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市场调查报告书
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1617119

2030年智慧农业市场预测：按农场规模、技术、应用和地区进行的全球分析

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个工作天内

价格

根据Stratistics MRC预测，2024年全球智慧农业市场规模将达到180.8亿美元，预计2030年将达到349.3亿美元，预测期内复合年增长率为11.6%。

智慧农业，也称为智慧农业，是指利用先进技术、资料分析和自动化来优化农业实践。它结合了物联网 (IoT) 设备、无人机、感测器、人工智慧 (AI) 和机器学习等工具来监控和管理农业的各个方面，从种植作物到管理牲畜。这些技术使农民能够做出更明智的决策，提高作物产量，减少资源浪费并提高永续性。

据世界银行称，基于技术的农业系统（包括智慧农业技术）可以显着增加小规模农民的收入。世界银行估计，数位农业可以帮助撒哈拉以南非洲和南亚等地区超过5亿人减少贫穷。

粮食安全需求不断成长

全球粮食安全需求的不断增长正在推动智慧农业的快速成长。智慧农业是一种利用科技提高农业生产力和永续性的创新方法。预计到 2050 年，世界人口将达到近 100 亿，确保稳定、高效的粮食供应成为关键问题。智慧农业利用人工智慧 (AI)、物联网 (IoT)、机器人技术和资料分析等先进技术来优化农业运作。这些技术可以即时监测土壤健康、作物状况和天气模式，帮助农民做出有关灌溉、施肥和病虫害防治的明智决策。透过提高资源效率和减少浪费，智慧农业可以提高产量，同时最大限度地减少对环境的影响。

初期投资成本高

高昂的初始投资成本是智慧农业技术广泛采用的主要障碍。这些先进的农业解决方案，包括自动化机械、无人机、感测器、人工智慧（AI）系统等，需要在设备和基础设施方面进行大量初步投资。对许多中小农户来说，这种沉重的经济负担令人望而却步，特别是在获得贷款和补贴的机会有限的地区。除了购买技术本身之外，农民还经常面临培训、维护以及与现有系统整合的额外成本。因此，对于没有足够财力的农民来说，向更有效率、资料主导的耕作方法过渡变得更加困难。

农业技术与金融服务一体化

农业技术和金融服务的融合为农民提供了先进的工具和金融产品，从而提高了生产力和永续性，并正在彻底改变智慧农业。物联网感测器、人工智慧主导的分析和精密农业工具等农业技术创新即时收集作物健康、土壤状况和天气模式的资料。这些资料对于农民做出明智的决策非常有价值。结合数位付款管道、农作物保险和信贷系统等金融服务，农民可以获得技术投资所需的资金，降低风险并提高效率。

缺乏技术纯熟劳工

缺乏技术纯熟劳工是智慧农业发展的关键挑战，智慧农业严重依赖技术和自动化来改善农业实践。随着各行业采用人工智慧、物联网、无人机和资料分析等更先进的系统，对能够操作、维护和优化这些技术的技术纯熟劳工的需求不断增加。然而，许多农民缺乏这些高科技领域的必要专业知识。这种差距导致效率低下，农民难以充分利用现代工具的潜力。劳动力老化以及农业职业对年轻一代的吸引力有限，加剧了劳动力短缺。

COVID-19 的影响：

COVID-19 大流行扰乱了全球供应链、劳动力供应和市场进入，对智慧农业产生了重大影响。农业部门至关重要，但限制和关闭造成了劳动力短缺，特别是在种植、收割和包装等工作中，这些工作通常依赖季节性工人和农民工。劳动力短缺阻碍了农作物的及时生产和分配，影响了粮食供应。这场大流行促使人们对农业技术的依赖，包括精密农业、无人机和基于物联网的监控系统，以填补劳动力短缺并提高效率。

预计中型农场在预测期内将是最大的

由于采用先进技术来优化生产力、永续性和资源管理，中型农场预计在预测期内将占据最大份额。这些农场比小型家庭农场大，但比大型工业农场小，并将物联网 (IoT) 设备、感测器、无人机和人工智慧 (AI) 整合到其农业作业中，这种趋势越来越明显。这些技术有助于即时监测作物健康、土壤湿度和天气状况，使农民能够做出资料主导的决策，提高产量，同时最大限度地减少浪费。

作物监测产业预计在预测期内复合年增长率最高。

预计作物监测领域将在预测期内快速成长。作物监测是智慧农业的重要方面，大大提高了现代农业的效率和生产力。利用卫星影像、无人机和物联网感测器等先进技术，农民可以持续即时监测作物健康、土壤湿度、温度和其他关键因素。这种资料主导的方法使农民能够做出更好的决策，优化灌溉，有效施用化学肥料和农药，并检测疾病和虫害的早期征兆。此外，作物监测系统通常结合人工智慧和机器学习演算法来分析大量资料并提供预测见解和建议以改善作物管理。

比最大的地区

预计亚太地区将在整个估计期间保持最大的市场份额。随着农业部门的快速成长以及气候变迁、人口成长和资源稀缺等日益严峻的挑战，各国政府正在优先考虑智慧农业解决方案。人们正在製定政策和投资，以加速物联网 (IoT)、人工智慧 (AI)、无人机和机器人等技术的采用。这些创新有助于优化资源利用、提高作物产量、改善供应链管理并减少对环境的影响。政府也促进官民合作关係，提供补贴、津贴和税收优惠，并鼓励农民采用科技。

复合年增长率最高的地区：

据估计，欧洲地区在预测期内的复合年增长率最高。随着技术不断重塑农业部门，欧洲农民和新兴企业正在转向精密农业、人工智慧主导的分析和物联网设备等创新，以优化作物生产、减少资源消耗并提高效率，这种趋势日益明显。投资激增正在推动尖端解决方案的出现，这些解决方案可提高永续性、改善供应链管理并加强粮食安全。这些资本的涌入正在支持老牌农业科技公司和新兴新兴企业，使它们能够扩大业务规模并扩大市场范围。随着资金筹措管道的增加，欧洲农业正变得更加资料主导和技术先进，从而实现更智慧、更有弹性的农业实践。

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  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
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    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 研究资讯来源
    • 主要研究资讯来源
    • 二次研究资讯来源
    • 先决条件

第三章市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 新兴市场
  • COVID-19 的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第五章全球智慧农业市场：依农场规模分类

  • 小农场
  • 中型农场
  • 大农场

第六章全球智慧农业市场：依技术分类

  • 物联网 (IoT)
  • 人工智慧（AI）
  • 机器人和自动化
  • 云端运算
  • 其他秤

第七章全球智慧农业市场：依应用分类

  • 精密农业
  • 牲畜监测
  • 作物监测
  • 智慧温室
  • 农业无人机

第八章全球智慧农业市场：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第九章 主要进展

  • 合约、伙伴关係、合作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第 10 章 公司概况

  • 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)