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市场调查报告书
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农业人工智慧 -精密农业市场预测（至2032年）：按农场规模、组件、技术、应用、最终用户和地区进行的全球分析

AI in Agriculture - Precision Farming Market Forecasts to 2032 - Global Analysis By Farm Size (Small Farms, Mid-Sized Farms and Large Farms), Component, Technology, Application, End User 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 的数据，全球人工智慧精密农业市场预计在 2025 年达到 59 亿美元，到 2032 年将达到 304 亿美元，预测期内的复合年增长率为 26.3%。

农业中的人工智慧 -精密农业是指将人工智慧技术融入农业实践，以提高农业的精准度和管理水平。这涉及使用数据驱动演算法、模式识别和自主系统来分析和处理特定田地的变数。这种方法透过即时处理环境和生物数据来增强农业决策能力。这意味着从传统的大规模耕作方法转向精细化、高解析度、因地制宜的耕作方法。

根据NASSCOM预测，到2025年，数据和人工智慧技术将为印度农业部门增加约900亿美元的价值。

人工智慧和物联网技术的进步

人工智慧与物联网 (IoT) 设备的融合正在彻底改变精密农业，使其能够在田间层面实现数据主导的决策。在卫星影像、土壤感测器和人工智慧演算法的融合推动下，农民现在可以即时监测作物健康状况、灌溉需求和病虫害威胁。在政府和私部门对农业创新投资的支持下，人工智慧在已开发经济体和新兴经济体的应用都在加速。在全球粮食安全挑战的推动下，人工智慧赋能的精密农业正成为实现可扩展、永续农业的关键。

农民缺乏技术专业知识

人工智慧精密农业的推广应用受到农民有限的数位素养和技术知识的限制。受代沟和变革阻力的影响，许多农民不愿从传统做法转向资料密集型模式。由于部分农业地区智慧型手机和网路普及率有限，人工智慧所需的数位基础设施仍欠缺发展。鑑于这些差距，弥合知识差距对于精密农业解决方案的广泛应用至关重要。

提高作物产量和效率

人工智慧驱动的精密农业在提高作物产量的同时，最大限度地降低投入成本和环境影响，带来了巨大的机会。即时数据分析和自适应学习模型使农民能够以前所未有的精度调整施肥、灌溉和农药施用。在云端基础仪錶板和农场管理软体的推动下，即使是小农户也开始受益于人工智慧的最佳化潜力。在精准演算法的指导下，田间决策的精细调整，产量成长正变得可衡量且可复製。

农业系统可能遭受网路攻击

透过人工智慧和物联网技术实现农业数位化，使农业系统面临网路安全漏洞。智慧型设备和云端平台的互联互通使骇客能够利用漏洞破坏业务或操纵资料。自动化机械和自主无人机的日益普及也引发了越来越多的威胁，如果系统遭到入侵，可能会造成更大的田间损害和经济损失。这些风险促使相关人员将强大的网路防御机制纳入其精密农业策略。

COVID-19的影响：

新冠疫情再形成了全球农业格局。在劳动力短缺和供应链中断的背景下，人工智慧主导的精密农业正日益受到青睐。受出行限制和劳动力减少的推动，农民越来越多地转向自动化和远端监控工具。为了确保粮食生产不间断，人工智慧平台促进了及时介入和投入调整。在危机期间提供的弹性人工智慧工具的推动下，后疫情时代精密农业系统的整合度正在提高。

预计小型农场市场在预测期内将占最大份额

由于不断加强促进小农户数位包容性，预计小农农业领域将在预测期内占据最大市场占有率。人工智慧技术为小农户提供了经济高效的解决方案，从而提高了产量和效率。行动应用程式和感测器等可扩展人工智慧工具的价格实惠，正在推动其应用。政府对小农户的补贴增强了其获得精密农业技术的机会。小规模农业对永续实践的需求将推动市场成长。这些解决方案透过提高生产力，使小农户能够与大规模经营竞争。

预计硬体领域在预测期内将实现最高复合年增长率

预计硬体领域将在预测期内实现最高成长率，这得益于精密农业对感测器、无人机和自动化设备日益增长的需求。先进的硬体能够精确监测土壤、天气和作物状况，从而提高农业产量。现代农业硬体的经济性和扩充性正在推动市场扩张。耐用节能设备的技术进步将推动其普及。硬体与人工智慧软体的融合将增强精密农业的能力。对智慧农业设备的投资不断增加将支持该领域的快速成长。

占比最大的地区：

在预测期内，亚太地区预计将占据最大的市场占有率，这得益于其对农业的高度依赖以及政府对智慧农业技术的支持力度不断增加。中国和印度等国家正大力投资人工智慧和物联网，以提高粮食产量。印度「数位农业计画」等政府倡议正在推动人工智慧的应用。无人机和感测器在农业领域的日益普及，正在巩固该地区的市场地位。都市化和不断增长的粮食需求将进一步推动亚太地区市场的成长。

复合年增长率最高的地区：

由于农业创新水平高且先进农业设备的广泛应用，预计北美地区在预测期内的复合年增长率最高。美国在人工智慧主导的农业解决方案和研究方面投入巨资，处于领先地位。精密农业对优化产量和降低成本的需求将推动成长。政府支持永续农业的政策将推动市场扩张。先进硬体和软体解决方案的采用将推动北美市场的快速成长。

免费客製化服务：

此报告的订阅者可以从以下免费自订选项中选择一项：

  • 公司简介
    • 对最多三家其他市场公司进行全面分析
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 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
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买家的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球人工智慧精密农业市场（依农场规模）

  • 小型农场
  • 中型农场
  • 大型农场

6. 全球农业人工智慧-精密农业市场（按组成部分）

  • 硬体
  • 软体
  • 人工智慧服务

7. 全球农业人工智慧-精密农业市场（按技术）

  • 机器学习和深度学习
  • 预测分析
  • 电脑视觉

8. 全球农业人工智慧-精密农业市场（按应用）

  • 天气追踪
  • 精密农业
  • 农业机器人
  • 牲畜监控
  • 劳动力管理
  • 其他用途

9. 全球人工智慧精密农业市场（按最终用户）

  • 农民
  • 农业业务
  • 农业研究所
  • 政府机构
  • 农业技术公司

10. 全球农业人工智慧-精密农业市场（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
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • Deere & Company
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • The Climate Corporation
  • Farmers Edge Inc.
  • Granular Inc.
  • AgEagle Aerial Systems Inc.
  • Descartes Labs, Inc.
  • Raven Industries Inc.
  • AGCO Corporation
  • Gamaya SA
  • Bayer AG
  • Trimble Inc.
  • Topcon Positioning Systems, Inc.
  • Taranis
  • CropX Technologies
  • PrecisionHawk Inc.
  • Prospera Technologies Ltd.
  • OneSoil
Product Code: SMRC30106

According to Stratistics MRC, the Global AI in Agriculture - Precision Farming Market is accounted for $5.9 billion in 2025 and is expected to reach $30.4 billion by 2032 growing at a CAGR of 26.3% during the forecast period. AI in Agriculture - Precision Farming refers to the integration of artificial intelligence technologies into farming practices to improve agricultural accuracy and control. It involves the use of data-driven algorithms, pattern recognition, and autonomous systems to analyze and act upon field-specific variables. This approach enhances decision-making in farming operations by enabling the real-time processing of environmental and biological data. It represents a shift from traditional broad-scale agricultural practices to fine-tuned, high-resolution, and site-specific farming techniques.

According to NASSCOM, by 2025, approximately USD 90 billion of value will be added to the agriculture sector through data and AI technologies in India.

Market Dynamics:

Driver:

Advancements in AI and IoT technologies

The convergence of artificial intelligence with Internet of Things (IoT) devices is revolutionizing precision farming by enabling data-driven decision-making at the field level. Spurred by the integration of satellite imagery, soil sensors, and AI algorithms, farmers can now monitor crop health, irrigation needs, and pest threats in real-time. Backed by government and private sector investments in agri-tech innovation, AI adoption is accelerating across both developed and emerging economies. Motivated by the global food security challenge, AI-enabled precision farming is becoming essential for scalable and sustainable agriculture.

Restraint:

Lack of technological expertise among farmers

The adoption of AI-based precision agriculture is constrained by the limited digital literacy and technical know-how among a significant portion of the farming community. Driven by generational gaps and resistance to change, many farmers are hesitant to shift from traditional practices to data-intensive models. Backed by insufficient smartphone and internet penetration in certain agricultural zones, the digital infrastructure required for AI functionality remains underdeveloped. Fueled by these gaps, addressing the knowledge divide is crucial for widespread adoption of precision agriculture solutions.

Opportunity:

Increased crop yield and efficiency

AI-powered precision farming unlocks significant opportunities for enhancing crop productivity while minimizing input costs and environmental impact. Spurred by real-time data analytics and adaptive learning models, farmers can tailor fertilization, irrigation, and pesticide application with unprecedented precision. Fueled by cloud-based dashboards and farm management software, even smallholders are beginning to benefit from AI's optimization potential. Guided by precision algorithms that fine-tune decisions at the plot level, yield improvements are becoming both measurable and repeatable.

Threat:

Potential for cyberattacks on farming systems

The digitalization of agriculture through AI and IoT technologies exposes farming systems to increasing cybersecurity vulnerabilities. Driven by the interconnectivity of smart devices and cloud platforms, hackers can exploit weak points to disrupt operations or manipulate data. Spurred by the rising use of automated machinery and autonomous drones, any system breach could result in significant field-level damage or financial loss. Motivated by these risks, stakeholders must integrate robust cyber-defense mechanisms as part of their precision farming strategies.

Covid-19 Impact:

The COVID-19 pandemic reshaped global agriculture, with AI-driven precision farming gaining traction amid labor shortages and supply chain disruptions. Spurred by mobility restrictions and reduced workforce availability, farmers increasingly turned to automation and remote monitoring tools. Driven by the urgency to ensure uninterrupted food production, AI platforms facilitated timely interventions and input adjustments. Motivated by the resilience AI tools offered during the crisis, the post-COVID era is seeing deeper integration of precision farming systems.

The small farms segment is expected to be the largest during the forecast period

The small farms segment is expected to account for the largest market share during the forecast period, owing to widespread initiatives promoting digital inclusion among smallholder farmers.AI technologies offer cost-effective solutions for small farms, improving yields and efficiency. The affordability of scalable AI tools, such as mobile apps and sensors, supports adoption. Government subsidies for small farmers enhance access to precision farming technologies. The need for sustainable practices in small-scale farming drives market growth. These solutions empower small farms to compete with larger operations through enhanced productivity.

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

Over the forecast period, the hardware segment is predicted to witness the highest growth rate, impelled by rising demand for sensors, drones, and automated equipment in precision agriculture. Advanced hardware enables precise monitoring of soil, weather, and crop conditions, improving farming outcomes. The affordability and scalability of modern farming hardware fuel market expansion. Technological advancements in durable and energy-efficient devices drive adoption. The integration of hardware with AI software enhances precision farming capabilities. Growing investments in smart farming equipment support the segment's rapid growth.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, driven by strong agricultural dependence and rising government support for smart farming technologies. Countries like China and India are investing heavily in AI and IoT to boost food production. Government initiatives, such as India's Digital Agriculture Mission, promote AI adoption. The growing use of drones and sensors in agriculture strengthens the region's market position. Rising urbanization and food demand further fuel market growth in Asia Pacific.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR attributed to high levels of agri-tech innovation and widespread use of advanced farming equipment. The U.S. leads with significant investments in AI-driven farming solutions and research. High demand for precision farming to optimize yields and reduce costs drives growth. Government policies supporting sustainable agriculture accelerate market expansion. The adoption of advanced hardware and software solutions boosts North America's rapid market growth.

Key players in the market

Some of the key players in AI in Agriculture - Precision Farming Market include Deere & Company, IBM Corporation, Microsoft Corporation, Google LLC, The Climate Corporation, Farmers Edge Inc., Granular Inc., AgEagle Aerial Systems Inc., Descartes Labs, Inc., Raven Industries Inc., AGCO Corporation, Gamaya SA, Bayer AG, Trimble Inc., Topcon Positioning Systems, Inc., Taranis, CropX Technologies, PrecisionHawk Inc., Prospera Technologies Ltd., and OneSoil.

Key Developments:

In June 2025, Deere & Company launched an AI-powered precision farming platform integrating satellite imagery and IoT sensors. It provides real-time crop health monitoring, enabling farmers to optimize yields and reduce resource waste through data-driven insights and automated field management.

In May 2025, IBM Corporation introduced Watson AgriSense, an AI-driven solution for predictive analytics. It analyzes soil data to optimize management practices, enhancing yield forecasts and reducing costs through precise resource allocation for sustainable farming operations.

In April 2025, Microsoft Corporation unveiled Azure FarmSync, a cloud-based AI tool for automated irrigation and pest detection. It leverages real-time data to optimize water use and protect crops, improving efficiency and sustainability for precision agriculture.

In February 2025, Trimble Inc. unveiled an AI-based variable-rate seeding system to maximize planting efficiency based on soil conditions.

Farm Sizes Covered:

  • Small Farms
  • Mid-Sized Farms
  • Large Farms

Components Covered:

  • Hardware
  • Software
  • AI-as-a-Service

Technologies Covered:

  • Machine Learning & Deep Learning
  • Predictive Analytics
  • Computer Vision

Applications Covered:

  • Weather Tracking
  • Precision Farming
  • Agriculture Robots
  • Livestock Monitoring
  • Labor Management
  • Other Applications

End Users Covered:

  • Farmers
  • Agribusinesses
  • Agriculture Research Institutes
  • Government Agencies
  • Agritech Companies

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 2024, 2025, 2026, 2028, and 2032
  • 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 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 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 AI in Agriculture - Precision Farming Market, By Farm Size

  • 5.1 Introduction
  • 5.2 Small Farms
  • 5.3 Mid-Sized Farms
  • 5.4 Large Farms

6 Global AI in Agriculture - Precision Farming Market, By Component

  • 6.1 Introduction
  • 6.2 Hardware
  • 6.3 Software
  • 6.4 AI-as-a-Service

7 Global AI in Agriculture - Precision Farming Market, By Technology

  • 7.1 Introduction
  • 7.2 Machine Learning & Deep Learning
  • 7.3 Predictive Analytics
  • 7.4 Computer Vision

8 Global AI in Agriculture - Precision Farming Market, By Application

  • 8.1 Introduction
  • 8.2 Weather Tracking
  • 8.3 Precision Farming
  • 8.4 Agriculture Robots
  • 8.5 Livestock Monitoring
  • 8.6 Labor Management
  • 8.7 Other Applications

9 Global AI in Agriculture - Precision Farming Market, By End User

  • 9.1 Introduction
  • 9.2 Farmers
  • 9.3 Agribusinesses
  • 9.4 Agriculture Research Institutes
  • 9.5 Government Agencies
  • 9.6 Agritech Companies

10 Global AI in Agriculture - Precision Farming Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Deere & Company
  • 12.2 IBM Corporation
  • 12.3 Microsoft Corporation
  • 12.4 Google LLC
  • 12.5 The Climate Corporation
  • 12.6 Farmers Edge Inc.
  • 12.7 Granular Inc.
  • 12.8 AgEagle Aerial Systems Inc.
  • 12.9 Descartes Labs, Inc.
  • 12.10 Raven Industries Inc.
  • 12.11 AGCO Corporation
  • 12.12 Gamaya SA
  • 12.13 Bayer AG
  • 12.14 Trimble Inc.
  • 12.15 Topcon Positioning Systems, Inc.
  • 12.16 Taranis
  • 12.17 CropX Technologies
  • 12.18 PrecisionHawk Inc.
  • 12.19 Prospera Technologies Ltd.
  • 12.20 OneSoil

List of Tables

  • Table 1 Global AI in Agriculture - Precision Farming Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI in Agriculture - Precision Farming Market Outlook, By Farm Size (2024-2032) ($MN)
  • Table 3 Global AI in Agriculture - Precision Farming Market Outlook, By Small Farms (2024-2032) ($MN)
  • Table 4 Global AI in Agriculture - Precision Farming Market Outlook, By Mid-Sized Farms (2024-2032) ($MN)
  • Table 5 Global AI in Agriculture - Precision Farming Market Outlook, By Large Farms (2024-2032) ($MN)
  • Table 6 Global AI in Agriculture - Precision Farming Market Outlook, By Component (2024-2032) ($MN)
  • Table 7 Global AI in Agriculture - Precision Farming Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 8 Global AI in Agriculture - Precision Farming Market Outlook, By Software (2024-2032) ($MN)
  • Table 9 Global AI in Agriculture - Precision Farming Market Outlook, By AI-as-a-Service (2024-2032) ($MN)
  • Table 10 Global AI in Agriculture - Precision Farming Market Outlook, By Technology (2024-2032) ($MN)
  • Table 11 Global AI in Agriculture - Precision Farming Market Outlook, By Machine Learning & Deep Learning (2024-2032) ($MN)
  • Table 12 Global AI in Agriculture - Precision Farming Market Outlook, By Predictive Analytics (2024-2032) ($MN)
  • Table 13 Global AI in Agriculture - Precision Farming Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 14 Global AI in Agriculture - Precision Farming Market Outlook, By Application (2024-2032) ($MN)
  • Table 15 Global AI in Agriculture - Precision Farming Market Outlook, By Weather Tracking (2024-2032) ($MN)
  • Table 16 Global AI in Agriculture - Precision Farming Market Outlook, By Precision Farming (2024-2032) ($MN)
  • Table 17 Global AI in Agriculture - Precision Farming Market Outlook, By Agriculture Robots (2024-2032) ($MN)
  • Table 18 Global AI in Agriculture - Precision Farming Market Outlook, By Livestock Monitoring (2024-2032) ($MN)
  • Table 19 Global AI in Agriculture - Precision Farming Market Outlook, By Labor Management (2024-2032) ($MN)
  • Table 20 Global AI in Agriculture - Precision Farming Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 21 Global AI in Agriculture - Precision Farming Market Outlook, By End User (2024-2032) ($MN)
  • Table 22 Global AI in Agriculture - Precision Farming Market Outlook, By Farmers (2024-2032) ($MN)
  • Table 23 Global AI in Agriculture - Precision Farming Market Outlook, By Agribusinesses (2024-2032) ($MN)
  • Table 24 Global AI in Agriculture - Precision Farming Market Outlook, By Agriculture Research Institutes (2024-2032) ($MN)
  • Table 25 Global AI in Agriculture - Precision Farming Market Outlook, By Government Agencies (2024-2032) ($MN)
  • Table 26 Global AI in Agriculture - Precision Farming Market Outlook, By Agritech Companies (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.