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2030 年农业市场人工智慧 (AI) 预测：按产品、技术、用途和地区分類的全球分析
市场调查报告书
商品编码
1358974

2030 年农业市场人工智慧 (AI) 预测：按产品、技术、用途和地区分類的全球分析

Artificial Intelligence in Agriculture Market Forecasts to 2030 - Global Analysis By Offering, Technology, 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 的数据，2023 年全球农业人工智慧 (AI) 市场规模将达到 21 亿美元，预计预测期内年复合成长率为 21.1%，到 2030 年将达到 79 亿美元。

人工智慧是指创造智慧电脑系统，能够模拟或显示自然智慧（人类智慧）并在无需人为干预的情况下执行分析、判断和决策等任务的科学与工程科学与工程，具有学术性。由于人工智慧 (AI)，农业发生了重大转变，彻底改变了农业和相关任务的执行方式。机器学习、电脑视觉和资料分析等人工智慧技术正被用来配合措施这些问题并充分发挥农业的潜力。农业中的人工智慧超越了标准耕作方法，可以帮助农民和农业相关人员做出资料主导的洞察和智慧决策，以提高产量、最佳化资源利用并改善众多农艺方面，帮助您解决问题。

不断增长的粮食需求和人口

随着世界人口的成长，对粮食生产的需求增加。借助人工智慧技术，农民可以提高农业产量并最大限度地利用资源，以可持续地满足不断增长的粮食需求。例如，2022年11月中旬地球人口为80亿。预计世界人口将从现在的80亿人增加到2050年的97亿人，世界人口将增加约20亿人。随着人口的增长，更快生产农作物的需求也在增加，但人工智慧可能会以多种方式减缓农业活动。

非熟练劳动力和高成本

高昂的初始实施成本是该领域发展的主要障碍。根据要求，低收入家庭，特别是农村地区的低收入家庭将智慧农业的成本视为难以逾越的障碍，阻碍了此类尖端设备的普及。但由于土地碎片化、初始成本较高，海量累积资料没有标准化，导致资源配置效率低下，严重限制了分析期间的市场拓展。

政府推动人工智慧在小型农场管理中使用的配合措施

全球有超过5.7亿个农场，其中95%是5公顷及以下的小型农场。 100公顷以上的农业用地大部分采用了人工智慧技术。开发人工智慧系统所需的大量初始投资就证明了这一点。一般来说，拥有 100 公顷或更多土地的农民可以投资以人工智慧为基础的农场管理和其他用途解决方案。然而，随着世界各国政府支持人工智慧在农业用途中的使用并帮助小农，解决方案提供者也有机会专注于小于 5 公顷的农场。

新兴经济体大规模技术的局限性

人工智慧和与第四次工业革命相关的其他技术将以日益互动和复杂的方式实现各种流程的自动化。这些发展预计将为低度开发国家的经济和社会发展创造多种前景，例如透过提高粮食生产。它也可能加强和扩大发展中国家内部以及开发中国家地区与已开发地区之间业已存在的差距。

COVID-19 的影响：

COVID-19的迅速爆发促使许多国家采取了严格的封锁法，并暂时停止了许多农业活动，对全球农业人工智慧市场产生了负面影响。这次疫情凸显了农业自动化维持粮食供应和减少人为错误的必要性。全球供应链受到新冠肺炎 (COVID-19) 的影响，影响了化肥、农药和机械等农业用品的供应。这项障碍重新优先考虑减少废弃物和最佳化製造效率。

软体部分预计将在预测期内成为最大的部分

由于易于整合到农业机械、节省劳动力成本和即时资料收集，软体领域在预测期内占据了最大的市场占有率。此外，云端中产生和储存的大量资料以及分析工具的使用可以帮助农民识别和管理农业作业的各个方面。该计划的使用将大大提高农民适应不断变化的需求的能力。

预测分析领域预计在预测期内年复合成长率最高

据估计，预测分析领域在整个预测期内将呈现良好的成长。人工智慧的一个领域称为预测分析，它使用历史资料、机器学习演算法和统计方法来预测未来的事件和结果。此外，预测分析在农业中发挥越来越大的作用，帮助农民改善业务、做出资讯的决策并降低风险。预测分析模型检查有关作物产量、天气模式、土壤条件和其他重要变数的历史资讯。

占比最大的地区：

由于中国和印度等新兴国家的需求不断增加，亚太地区在预测期内占最大份额。农业人工智慧市场预计将受到机械技术和物联网设备在农业中越来越多使用的推动。农业领域的各种尖端发展和产品正在推动市场扩张。此外，该地区的人工智慧农业是由人口成长、气候变迁和水资源短缺要素的。该地区的市场成长将受到自动化程度提高、人工智慧和机器学习等技术进步以及土壤品质下降等要素的推动。

复合年复合成长率最高的地区：

由于北美农民和农业经营者采用人工智慧技术来提高生产力、改善资源配置和增强决策流程，预计北美在预测期内将出现良好的成长。此外，人工智慧在该地区的农业应用包括自动化农业系统、遥感、作物监测和精密农业。在现代科技的帮助下，农民可以提高产量、最大限度地减少开支、降低风险并做出资料主导的决策。

免费客製化服务：

订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和年复合成长率（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1章执行摘要

第2章前言

  • 概述
  • 利害关係人
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 调查来源
    • 主要调查来源
    • 二次调查来源
    • 先决条件

第3章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 新兴市场
  • 新型冠状病毒感染疾病（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
  • 替代的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第5章全球农业市场人工智慧（AI）：依产品分类

  • 服务
    • 支援与维护
    • 部署与整合
  • 软体
    • 人工智慧解决方案
    • 人工智慧平台
    • 其他软体
  • 硬体
    • 通讯网路
    • 储存设备
    • 处理器
    • 其他硬体
  • 其他产品

第6章全球农业人工智慧 (AI) 市场：依技术分类

  • 预测分析
  • 电脑视觉
  • 机器学习
  • 其他技术

第7章全球农业人工智慧 (AI) 市场：按用途

  • 农业机器人
  • 无人机分析
  • 劳动管理
  • 牲畜监控
  • 精密农业
    • 灌溉管理
    • 气象追踪与预报
    • 作物调查
    • 现场测绘
    • 产量监控
  • 水产养殖管理
  • 智慧温室管理
  • 土壤管理
    • 养分监测
    • 湿度监测
  • 智慧喷雾
  • 自动除草
  • Plantix 应用程式
  • 其他用途

第8章全球人工智慧（AI）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

第9章进展

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

第10章公司简介

  • aWhere Inc.
  • Cainthus Corp
  • Climate LLC（The Climate Corporation）
  • Corteva
  • Descartes Labs, Inc
  • Gamaya
  • Granular Inc.
  • IBM Corporation
  • Microsoft Corporation
  • PrecisionHawk Inc
  • Taranis
  • Valmont Industries（Prospera Technologies）
Product Code: SMRC23846

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Agriculture Market is accounted for $2.1 billion in 2023 and is expected to reach $7.9 billion by 2030 growing at a CAGR of 21.1% during the forecast period. Artificial intelligence is the study of the science and engineering involved in creating intelligent computer systems capable of simulating or displaying natural intelligence (human intelligence) and performing tasks like analysis, judgment, and decision-making without the need for human intervention. The agricultural industry has been transformed by artificial intelligence (AI), which has completely changed the ways farming and associated tasks are carried out. To tackle these issues and realize agriculture's full potential, AI technologies like machine learning, computer vision, and data analytics are being used. Beyond standard farming methods, AI in agriculture enables farmers and agricultural stakeholders to use data-driven insights and intelligent decision-making to improve production, optimize resource use, and handle numerous agronomic concerns.

According to UN Food and Agriculture Organization, the population will rise by 9.8 billion by 2050.

Market Dynamics:

Driver:

Growing food demand and population

The demand for food production is rising as the world's population expands. With the help of AI technologies, farmers can increase agricultural yields and maximize resource use to sustainably satisfy rising food demand. For instance, there were 8.0 billion people on earth in mid-November 2022. From the current 8 billion to 9.7 billion in 2050, the estimated increase in world population is around 2 billion people. A growing population increases the need for crops to produce more rapidly, yet AI can slow down agricultural activity in a number of different ways.

Restraint:

Unskilled labor and high cost

The high initial cost of implementation is an important obstacle to the growth of this sector. According to the requirements, low-income households in rural areas, among others, believe the cost of smart agriculture to be an insurmountable barrier, which prevents the widespread adoption of such cutting-edge equipment. However, due to land fragmentation and expensive beginning costs, there is no standardization of the massive amount of cumulative data, which causes an inefficient distribution of resources and severely restricts market expansion over the course of the analysis period.

Opportunity:

Government initiatives promoting the use of AI to manage small farms

There are more than 570 million farms around the globe, and 95 percent of these are smaller than 5 hectares. The majority of farms with more than 100 hectares of land use AI technology. This is demonstrated by the substantial initial outlay needed to develop AI systems. In general, farmers with land holdings larger than 100 hectares are able to invest in AI-based solutions for farm management and other uses. However, there is a chance for solution providers to concentrate on farms with fewer than 5 hectares of land because governments all over the world support the use of AI for agricultural applications and give aid to farmers with small farms.

Threat:

Limitations of large-scale technology in developing economies

Artificial intelligence and other Fourth Industrial Revolution-related technologies enable the automation of a wide range of processes in increasingly interactive and complex ways. By improving food production, for instance, these developments are expected to generate several prospects for economic and social development in underdeveloped nations. They could reinforce and amplify already existing disparities within developing nations and between those nations and more developed regions.

COVID-19 Impact:

The rapid COVID-19 pandemic breakout prompted the adoption of strict lockdown laws across a number of countries, which temporarily halted a number of agricultural activities and had a detrimental effect on the worldwide market for AI in agriculture. The epidemic has brought to light the necessity for agriculture automation to maintain the food supply and reduce human error. Global supply networks have been affected by COVID-19, which has an impact on the accessibility of agricultural supplies like fertilizer, pesticides, and machinery. Due to this disturbance, waste reduction and manufacturing efficiency optimization are again prioritized.

The software segment is expected to be the largest during the forecast period

Due to its ease of integration into agricultural machinery, labor cost savings, and real-time data collection, the software segment held the largest market share over the forecast period. Moreover, together with the use of analytical tools, the large amount of data being generated and stored in the cloud helps the farmer identify and manage every aspect of farming. The use of the program substantially improves farmers' capacity to adapt to shifting demands.

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

Predictive Analytics segment is estimated to witness lucrative growth throughout the extrapolated period. A branch of AI called predictive analytics uses historical data, machine learning algorithms, and statistical methods to forecast upcoming events or outcomes. Furthermore, predictive analytics is playing an increasing role in agriculture, assisting farmers to improve their operations, make informed decisions, and reduce risks. Models for predictive analytics examine past information on crop yields, weather patterns, the condition of the soil, and other important variables.

Region with largest share:

Due to the increased demand from emerging nations like China and India, Asia-Pacific held the largest portion during the projection period. The market for artificial intelligence in agriculture is predicted to be driven by the growing use of mechanical technology and IoT devices in agriculture. The wide variety of cutting-edge developments and products in the agriculture sector are associated with driving the market's expansion. Additionally, the region's AI agriculture industry is being driven primarily by population growth, climate change, and shortages of water. The market's growth in this region will be fueled by factors including rising automation, technological advancements like AI and ML, and decreasing soil quality.

Region with highest CAGR:

Owing to the adoption of AI technology by farmers and agricultural businesses in North America to boost productivity, improve resource allocation, and strengthen decision-making processes, North America is predicted to experience lucrative growth over the extrapolated period. Moreover, a few of the agricultural applications of AI in the area include automated farming systems, remote sensing, crop monitoring, and precision agriculture. With the help of modern technology, farmers may improve yields, minimize expenses, reduce risks, and make data-driven decisions.

Key players in the market:

Some of the key players in Artificial Intelligence (AI) in Agriculture market include: aWhere Inc., Cainthus Corp, Climate LLC (The Climate Corporation), Corteva, Descartes Labs, Inc, Gamaya, Granular Inc., IBM Corporation, Microsoft Corporation , PrecisionHawk Inc, Taranis and Valmont Industries (Prospera Technologies).

Key Developments:

In April 2023, IBM and Texas A&M AgriLife collaborated to provide farmers with water consumption insights, which can boost agricultural productivity while lowering economic and environmental expenses. Texas A&M AgriLife and IBM will deploy and grow Liquid Prep, a technology solution that helps farmers decide "when to water" in dry parts of the U.S.

In October 2022, Microsoft announced, FarmVibes open-sourced by Microsoft Research.AI, a collection of machine-learning models and technologies for sustainable agriculture. FarmVibes. AI comprises data processing methods for merging spatiotemporal and geographic data, such as weather data and satellite and drone footage.

Offerings Covered:

  • Service
  • Software
  • Hardware
  • Other Offerings

Technologies Covered:

  • Predictive Analytics
  • Computer Vision
  • Machine Learning
  • Other Technologies

Applications Covered:

  • Agriculture Robots
  • Drone Analytics
  • Labor Management
  • Livestock Monitoring
  • Precision Farming
  • Fish Farming Management
  • Smart Greenhouse Management
  • Soil Management
  • Intelligent Spraying
  • Automatic Weeding
  • Plantix app
  • Other Applications

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 2021, 2022, 2023, 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 Artificial Intelligence (AI) in Agriculture Market, By Offering

  • 5.1 Introduction
  • 5.2 Service
    • 5.2.1 Support & Maintenance
    • 5.2.2 Deployment & Integration
  • 5.3 Software
    • 5.3.1 AI Solution
    • 5.3.2 AI Platform
    • 5.3.3 Other Softwares
  • 5.4 Hardware
    • 5.4.1 Network
    • 5.4.2 Storage Device
    • 5.4.3 Processor
    • 5.4.4 Other Hardwares
  • 5.5 Other Offerings

6 Global Artificial Intelligence (AI) in Agriculture Market, By Technology

  • 6.1 Introduction
  • 6.2 Predictive Analytics
  • 6.3 Computer Vision
  • 6.4 Machine Learning
  • 6.5 Other Technologies

7 Global Artificial Intelligence (AI) in Agriculture Market, By Application

  • 7.1 Introduction
  • 7.2 Agriculture Robots
  • 7.3 Drone Analytics
  • 7.4 Labor Management
  • 7.5 Livestock Monitoring
  • 7.6 Precision Farming
    • 7.6.1 Irrigation Management
    • 7.6.2 Weather Tracking & Forecasting
    • 7.6.3 Crop Scouting
    • 7.6.4 Field Mapping
    • 7.6.5 Yield Monitoring
  • 7.7 Fish Farming Management
  • 7.8 Smart Greenhouse Management
  • 7.9 Soil Management
    • 7.9.1 Nutrient Monitoring
    • 7.9.2 Moisture Monitoring
  • 7.10 Intelligent Spraying
  • 7.11 Automatic Weeding
  • 7.12 Plantix app
  • 7.13 Other Applications

8 Global Artificial Intelligence (AI) in 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 aWhere Inc.
  • 10.2 Cainthus Corp
  • 10.3 Climate LLC (The Climate Corporation)
  • 10.4 Corteva
  • 10.5 Descartes Labs, Inc
  • 10.6 Gamaya
  • 10.7 Granular Inc.
  • 10.8 IBM Corporation
  • 10.9 Microsoft Corporation
  • 10.10 PrecisionHawk Inc
  • 10.11 Taranis
  • 10.12 Valmont Industries (Prospera Technologies)

List of Tables

  • Table 1 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Offering (2021-2030) ($MN)
  • Table 3 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Service (2021-2030) ($MN)
  • Table 4 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Support & Maintenance (2021-2030) ($MN)
  • Table 5 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Deployment & Integration (2021-2030) ($MN)
  • Table 6 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Software (2021-2030) ($MN)
  • Table 7 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By AI Solution (2021-2030) ($MN)
  • Table 8 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By AI Platform (2021-2030) ($MN)
  • Table 9 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Other Softwares (2021-2030) ($MN)
  • Table 10 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Hardware (2021-2030) ($MN)
  • Table 11 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Network (2021-2030) ($MN)
  • Table 12 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Storage Device (2021-2030) ($MN)
  • Table 13 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Processor (2021-2030) ($MN)
  • Table 14 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Other Hardwares (2021-2030) ($MN)
  • Table 15 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Other Offerings (2021-2030) ($MN)
  • Table 16 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Technology (2021-2030) ($MN)
  • Table 17 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Predictive Analytics (2021-2030) ($MN)
  • Table 18 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Computer Vision (2021-2030) ($MN)
  • Table 19 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 20 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Other Technologies (2021-2030) ($MN)
  • Table 21 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Application (2021-2030) ($MN)
  • Table 22 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Agriculture Robots (2021-2030) ($MN)
  • Table 23 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Drone Analytics (2021-2030) ($MN)
  • Table 24 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Labor Management (2021-2030) ($MN)
  • Table 25 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Livestock Monitoring (2021-2030) ($MN)
  • Table 26 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Precision Farming (2021-2030) ($MN)
  • Table 27 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Irrigation Management (2021-2030) ($MN)
  • Table 28 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Weather Tracking & Forecasting (2021-2030) ($MN)
  • Table 29 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Crop Scouting (2021-2030) ($MN)
  • Table 30 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Field Mapping (2021-2030) ($MN)
  • Table 31 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Yield Monitoring (2021-2030) ($MN)
  • Table 32 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Fish Farming Management (2021-2030) ($MN)
  • Table 33 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Smart Greenhouse Management (2021-2030) ($MN)
  • Table 34 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Soil Management (2021-2030) ($MN)
  • Table 35 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Nutrient Monitoring (2021-2030) ($MN)
  • Table 36 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Moisture Monitoring (2021-2030) ($MN)
  • Table 37 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Intelligent Spraying (2021-2030) ($MN)
  • Table 38 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Automatic Weeding (2021-2030) ($MN)
  • Table 39 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Plantix app (2021-2030) ($MN)
  • Table 40 Global Artificial Intelligence (AI) in Agriculture Market Outlook, By Other Applications (2021-2030) ($MN)

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