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2030 年農業市場人工智慧 (AI) 預測：依產品、技術、用途和地區分類的全球分析
市場調查報告書
商品編碼
1358974

2030 年農業市場人工智慧 (AI) 預測：依產品、技術、用途和地區分類的全球分析

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個工作天內

價格

根據 Stratistics MRC 的數據，2023 年全球農業人工智慧 (AI) 市場規模將達到 21 億美元，預計預測期內年複合成長率為 21.1%，到 2030 年將達到 79 億美元。

人工智慧是指創造智慧電腦系統，能夠模擬或顯示自然智慧（人類智慧）並在無需人為干預的情況下執行分析、判斷和決策等任務的科學與工程科學與工程，具有學術性。由於人工智慧 (AI)，農業發生了重大轉變，徹底改變了農業和相關任務的執行方式。機器學習、電腦視覺和資料分析等人工智慧技術正被用來配合措施這些問題並充分發揮農業的潛力。農業中的人工智慧超越了標準耕作方法，可以幫助農民和農業相關人員做出資料主導的洞察和智慧決策，以提高產量、最佳化資源利用並改善眾多農藝方面，幫助您解決問題。

不斷成長的糧食需求和人口

隨著世界人口的成長，對糧食生產的需求增加。借助人工智慧技術，農民可以提高農業產量並最大限度地利用資源，以永續地滿足不斷成長的糧食需求。例如，2022年11月中旬地球人口為80億。預計世界人口將從現在的80億人增加到2050年的97億人，世界人口將增加約20億人。隨著人口的成長，更快生產農作物的需求也在增加，但人工智慧可能會以多種方式減緩農業活動。

非熟練勞動力和高成本

高昂的初始實施成本是該領域發展的主要障礙。根據要求，低收入家庭，特別是農村地區的低收入家庭將智慧農業的成本視為難以逾越的障礙，阻礙了此類尖端設備的普及。但由於土地碎片化、初始成本較高，海量累積資料沒有標準化，導致資源配置效率低下，嚴重限制了分析期間的市場拓展。

政府推動人工智慧在小型農場管理中使用的配合措施

全球有超過5.7億個農場，其中95%是5公頃及以下的小型農場。 100公頃以上的農業用地大部分採用了人工智慧技術。開發人工智慧系統所需的大量初始投資就證明了這一點。一般來說，擁有 100 公頃或更多土地的農民可以投資以人工智慧為基礎的農場管理和其他用途解決方案。然而，隨著世界各國政府支持人工智慧在農業用途中的使用並幫助小農，解決方案提供者也有機會專注於小於 5 公頃的農場。

新興經濟體大規模技術的局限性

人工智慧和與第四次工業革命相關的其他技術將以日益互動和複雜的方式實現各種流程的自動化。這些發展預計將為低度開發國家的經濟和社會發展創造多種前景，例如透過提高糧食生產。它也可能加強和擴大發展中國家內部以及開發中國家地區與已開發地區之間業已存在的差距。

COVID-19 的影響：

COVID-19的迅速爆發促使許多國家採取了嚴格的封鎖法，並暫時停止了許多農業活動，對全球農業人工智慧市場產生了負面影響。這次疫情凸顯了農業自動化維持糧食供應和減少人為錯誤的必要性。全球供應鏈受到新冠肺炎 (COVID-19) 的影響，影響了化肥、農藥和機械等農業用品的供應。這項障礙重新優先考慮減少廢棄物和最佳化製造效率。

軟體部分預計將在預測期內成為最大的部分

由於易於整合到農業機械、節省勞動力成本和即時資料收集，軟體領域在預測期內佔據了最大的市場佔有率。此外，雲端中產生和儲存的大量資料以及分析工具的使用可以幫助農民識別和管理農業作業的各個方面。該計劃的使用將大大提高農民適應不斷變化的需求的能力。

預測分析領域預計在預測期內年複合成長率最高

據估計，預測分析領域在整個預測期內將呈現良好的成長。人工智慧的一個領域稱為預測分析，它使用歷史資料、機器學習演算法和統計方法來預測未來的事件和結果。此外，預測分析在農業中發揮越來越大的作用，幫助農民改善業務、做出資訊的決策並降低風險。預測分析模型檢查有關作物產量、天氣模式、土壤條件和其他重要變數的歷史資訊。

佔比最大的地區：

由於中國和印度等新興國家的需求不斷增加，亞太地區在預測期內佔最大佔有率。農業人工智慧市場預計將受到機械技術和物聯網設備在農業中擴大使用的推動。農業領域的各種尖端發展和產品正在推動市場擴張。此外，該地區的人工智慧農業是由人口成長、氣候變遷和水資源短缺要素的。該地區的市場成長將受到自動化程度提高、人工智慧和機器學習等技術進步以及土壤品質下降等要素的推動。

複合年複合成長率最高的地區：

由於北美農民和農業經營者採用人工智慧技術來提高生產力、改善資源配置和增強決策流程，預計北美在預測期內將出現良好的成長。此外，人工智慧在該地區的農業應用包括自動化農業系統、遙感、作物監測和精密農業。在現代科技的幫助下，農民可以提高產量、最大限度地減少開支、降低風險並做出資料主導的決策。

免費客製化服務：

訂閱此報告的客戶可以存取以下免費自訂選項之一：

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 家公司）
    • 主要企業SWOT分析（最多3家企業）
  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和年複合成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章 執行摘要

第2章 前言

  • 概述
  • 利害關係人
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 調查來源
    • 主要調查來源
    • 二次調查來源
    • 先決條件

第3章 市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 新興市場
  • 新型冠狀病毒感染疾病（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 全球農業市場人工智慧（AI）：依產品分類

  • 服務
    • 支援與維護
    • 部署與整合
  • 軟體
    • 人工智慧解決方案
    • 人工智慧平台
    • 其他軟體
  • 硬體
    • 通訊網路
    • 儲存設備
    • 處理器
    • 其他硬體
  • 其他產品

第6章 全球農業人工智慧 (AI) 市場：依技術分類

  • 預測分析
  • 電腦視覺
  • 機器學習
  • 其他技術

第7章 全球農業人工智慧 (AI) 市場：依用途

  • 農業機器人
  • 無人機分析
  • 勞動管理
  • 牲畜監控
  • 精密農業
    • 灌溉管理
    • 氣象追蹤與預報
    • 作物調查
    • 現場測繪
    • 產量監控
  • 水產養殖管理
  • 智慧溫室管理
  • 土壤管理
    • 養分監測
    • 濕度監測
  • 智慧噴霧
  • 自動除草
  • Plantix 應用程式
  • 其他用途

第8章 全球人工智慧（AI）農業市場：依地區

  • 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
  • 中東和非洲
    • 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 進展

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

第10章 公司簡介

  • 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.