市場調查報告書
商品編碼
1069236

農業中的人工智能 (AI):全球市場展望(2021-2028 年)

Artificial Intelligence in Agriculture - Global Market Outlook (2021 - 2028)

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
  • 全貌
  • 簡介
  • 目錄
簡介

2021 年全球人工智能 (AI) 農業市場將達到 10.8 億美元,在預測期內以 6.5% 的複合年增長率增長,到 2028 年將達到 16.7 億美元。

本報告研究和分析全球農業領域的人工智能 (AI) 市場,提供市場趨勢分析、按細分市場和地區劃分的市場信息以及企業概況。

目錄

第 1 章執行摘要

第2章前言

第三章市場趨勢分析

  • 促進因素
  • 抑制器
  • 市場機會
  • 威脅
  • 技術分析
  • 使用分析
  • 新興市場
  • COVID-19 的影響

第四章波特五力分析

第 5 章世界農業中的人工智能 (AI):技術

  • 計算機視覺
  • 機器學習
  • 預測分析

第6章世界農業中的人工智能(AI):通過提供

  • 人工智能即服務
  • 硬件
    • 通訊網絡
    • 處理器
    • 存儲設備
  • 服務
    • 整合
    • 支持與維護
  • 軟件
    • 人工智能平台
    • 人工智能解決方案

第 7 章世界農業中的人工智能 (AI):部署

  • 混合
  • 本地

第 8 章世界農業中的人工智能 (AI):按用途

  • 農業機器人
  • 無人機分析
  • 水產養殖管理
  • 勞動管理
  • 牲畜監測
    • 動物生長監測
    • 動物健康監測
  • 精準農業
    • 作物偵察
    • 字段映射
    • 灌溉管理
    • 天氣跟蹤和預報
    • 產量監控
    • 室內農業
  • 智能溫室管理
  • 土壤管理
    • 營養監測
    • 水分監測
  • 供應鏈效率
  • 農業機械自動化
  • 作物生長評價

第 9 章世界農業中的人工智能 (AI):按地區劃分

  • 北美
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 意大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳大利亞
    • 新西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東/非洲
    • 沙特阿拉伯
    • 阿拉伯聯合酋長國
    • 卡塔爾
    • 南非
    • 其他中東/非洲

第 10 章主要發展

  • 合同、合作夥伴關係、聯盟、合資企業
  • 收購/合併
  • 推出新產品
  • 擴展
  • 其他重要策略

第 11 章公司簡介

  • Cainthus Corporation
  • Connecterra B.V
  • CropX Inc
  • Descartes Labs, Inc
  • Farmers Edge
  • Granular, Inc
  • IBM
  • John Deere
  • Microsoft Corporation
  • Precision Hawk Inc
  • Prospera
  • Trimble
  • The Climate Corporation
  • Trace Genomics, Inc
  • Vision Robotics Corporation
目錄
Product Code: SMRC19114

According to Stratistics MRC, the Global Artificial Intelligence in Agriculture Market is accounted for $1.08 billion in 2021 and is expected to reach $1.67 billion by 2028 growing at a CAGR of 6.5% during the forecast period. Agriculture involves a number of processes and stages, the lion's share of which are manual. By complementing adopted technologies, AI can facilitate the most complex and routine tasks. It can gather and process big data on a digital platform, come up with the best course of action, and even initiate that action when combined with other technology. With the introduction of AI technologies, farmers can yield healthier crops, monitor their soil and growing conditions, and control pests. AI in agriculture helps the farmer by organizing data for farmers; it helps with the workload and enhances a wide range of the tasks which are related to agriculture and the entire food supply chain. Artificial Intelligence in agriculture is used for various applications such as driverless tractors, rural automation, computerized water system frameworks, facial acknowledgment, etc.

Market Dynamics:

Driver:

Rising need for real-time livestock monitoring

The rising need for the monitoring of livestock is another key factor driving the AI in agriculture market. With the application of advanced AI solutions, such as facial recognition for livestock and image classification incorporated with body condition score and feeding patterns, dairy farms are now able to individually monitor all behavioural aspects of a herd. In addition, for monitoring the health of the livestock, farmers are increasingly using machine vision that helps recognize hide patterns and facial features, monitor water and food intake of livestock, as well as record their body temperature and behaviour.

Restraint:

Lack of experience with emerging technologies

The agricultural sector in developing countries is different from the agricultural sector in Western Europe and the US. Some regions could benefit from artificial intelligence agriculture, but it may be hard to sell such technology in areas where agricultural technology is not common. Farmers will most likely need help adopting it. Farmers tend to perceive AI as something that applies only to the digital world. They might not see how it can help them work the physical land. This is not because they're conservative or wary of the unknown. Their resistance is caused by a lack of understanding of the practical application of AI tools. Although AI can be useful, there's still a lot of work to be done by technology providers to help farmers implement it the right way.

Opportunity:

Trend of decline in the agricultural workforce

A lack of skilled labor, aging farmers, and younger generations finding farming an unattractive profession contribute to the decline, thus encouraging trends for automated farming operations. The trend of decline in the agricultural workforce is encouraging governments and private organizations to focus on automating operations by adopting artificial intelligence technologies in the agricultural sector. The developed countries are not an exception in this declining trend. Asia-Pacific, where agriculture occupies a significant part of the economy, is witnessing a massive decline in the workforce. In Japan, the number of people working in farms witnessed a steep fall decline from the previous year. The European agricultural sector has also faced an enormous decline in the workforce, nearly accounting for 12.8% for the corresponding period. Owing to the above factors, the market for artificial intelligence in the agricultural sector is likely to boom in the years to come.

Threat:

Privacy and security issues

Since there are no clear policies and regulations around the use of AI not just in agriculture but in general, precision agriculture and smart farming raises various legal issues that often remain unanswered. Privacy and security threats like cyberattacks and data leaks may cause farmers serious problems. Unfortunately, many farms are vulnerable to these threats.

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

The services segment is estimated to have a lucrative growth and is expected to witness the faster growth in the AI in agriculture market during the forecast period. This can be attributed to the rising adoption of AI solutions in the agriculture industry, thereby creating a high requirement for proper installation, maintenance, and training services among farmers and other industry stakeholders. This category is further bifurcated into managed and professional. Of the two, the professional service bifurcation is expected to be the faster-growing over the forecast period. This can be attributed to the increasing demand for support, maintenance, and training services by farmers who are deploying the AI technology.

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

The precision farming segment is anticipated to witness the fastest CAGR growth during the forecast period due to the fact that the precision farming method is gaining popularity among farmers, owing to the increasing need for optimum yield production from the limited available resources, as well as for reducing the cost of crop production. It comprises a technology-driven analysis of data acquired from the fields for increasing crop productivity. Precision devices integrated with AI technologies help in collecting farm-related data, thereby helping the farmers make better decisions and increase the productivity of their lands. Moreover, farm managers and producers are leveraging the capabilities of IoT devices for field mapping and irrigation management, which is also resulting in the rapid growth.

Region with highest share:

North America is projected to hold the largest market share during the forecast period due to the early adoption of technologies such as machine learning (ML) and computer vision for agricultural applications, including precision farming, livestock management, greenhouse management, and soil management. Moreover, with the increasing adoption of technologies like IoT, in combination with computer vision, in the agriculture space, the market would exhibit positive growth over the forecast period. Additionally, certain players in the region are offering services to regional consumers by engaging in partnerships with other leading players. Companies such as IBM Corporation and Raven Industries Inc. are increasingly collaborating with other players, to enhance their offerings for the agriculture industry.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR over the forecast period owing to the high adoption rate of AI in the agriculture sector in major countries, such as China, India, Japan, and Australia. In the region, China is witnessing huge growth in the adoption of AI solutions in agriculture, owing to the entry of Alibaba Group in the agricultural solution business with its AI technology, to assist small farmers in the country. In addition, the Indian AI in agriculture market is witnessing significant growth, due to the increasing effort by the government, as well as various multinational companies (MNCs), for spreading awareness about farm analytics and data sciences among Indian farmers in the region.

Key players in the market

Some of the key players profiled in the Artificial Intelligence in Agriculture Market include Cainthus Corporation, Connecterra B.V, CropX Inc, Descartes Labs, Inc, Farmers Edge, Granular, Inc, IBM, John Deere, Microsoft Corporation, Precision Hawk Inc, Prospera, Trimble, The Climate Corporation, Trace Genomics, Inc, and Vision Robotics Corporation.

Key Developments:

In August 2021, Trimble introduced Trimble Ventures to set up $200 million funds and invest in early and growth-stage startups that lend a strong focus on technology-enabled innovation in industries including agriculture.

In July 2020, Prospera Technologies and Bayer partnered to help improve the output at greenhouses by using big data and machine learning. Using machine learning and big data, the company has monitored the production of $5 trillion worth of agricultural produce. Prospera uses AI and advanced data collecting methods to ensure each plant, every seed, is brought to its full potential in the field. This way, farming can be done in minute detail, ensuring that nothing is wasted and that the resources of our planet provide a bountiful harvest.

In March 2020, Farmers Edge and Nufarm Brasil, a leading crop protection company, announced an exclusive, three-year partnership to digitize at least three million acres of farmland in Brazil by 2023. Leveraging the strengths of both companies, Farmers Edge and Nufarm will provide improved crop protection, and the modern tools growers need for making better-informed agronomic decisions to maximize profitability.

In January 2020, Deere & Company announced the list for its startup collaborator program. The startup companies included are DataFarm (Brazil), FaunaPhotonics (Denmark), Fieldin (Israel), and EarthSense (US). This program will help the company leverage technologies offered by the startups and provide value to customers.

Technologies Covered:

  • Computer Vision
  • Machine Learning
  • Predictive Analytics

Offerings Covered:

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

Deployments Covered:

  • Cloud
  • Hybrid
  • On-Premise

Applications Covered:

  • Agriculture Robots
  • Drone Analytics
  • Fish Farming Management
  • Labor Management
  • Livestock Monitoring
  • Precision Farming
  • Smart Green House Management
  • Soil Management
  • Supply Chain Efficiency
  • Farm Machinery Automation
  • Crop Growth Assessment

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 2020, 2021, 2022, 2025, and 2028
  • 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 in Agriculture Market, By Technology

  • 5.1 Introduction
  • 5.2 Computer Vision
  • 5.3 Machine Learning
  • 5.4 Predictive Analytics

6 Global Artificial Intelligence in Agriculture Market, By Offering

  • 6.1 Introduction
  • 6.2 AI-as-a-Service
  • 6.3 Hardware
    • 6.3.1 Network
    • 6.3.2 Processor
    • 6.3.3 Storage Device
  • 6.4 Services
    • 6.4.1 Integration
    • 6.4.2 Support & Maintenance
  • 6.5 Software
    • 6.5.1 AI Platform
    • 6.5.2 AI Solution

7 Global Artificial Intelligence in Agriculture Market, By Deployment

  • 7.1 Introduction
  • 7.2 Cloud
  • 7.3 Hybrid
  • 7.4 On-Premise

8 Global Artificial Intelligence in Agriculture Market, By Application

  • 8.1 Introduction
  • 8.2 Agriculture Robots
  • 8.3 Drone Analytics
  • 8.4 Fish Farming Management
  • 8.5 Labor Management
  • 8.6 Livestock Monitoring
    • 8.6.1 Animal Growth Monitoring
    • 8.6.2 Animal Health Monitoring
  • 8.7 Precision Farming
    • 8.7.1 Crop Scouting
    • 8.7.2 Field Mapping
    • 8.7.3 Irrigation Management
    • 8.7.4 Weather Tracking & Forecasting
    • 8.7.5 Yield Monitoring
    • 8.7.6 Indoor Farming
  • 8.8 Smart Green House Management
  • 8.9 Soil Management
    • 8.9.1 Nutrient Monitoring
    • 8.9.2 Moisture Monitoring
  • 8.10 Supply Chain Efficiency
  • 8.11 Farm Machinery Automation
  • 8.12 Crop Growth Assessment

9 Global Artificial Intelligence in Agriculture Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Cainthus Corporation
  • 11.2 Connecterra B.V
  • 11.3 CropX Inc
  • 11.4 Descartes Labs, Inc
  • 11.5 Farmers Edge
  • 11.6 Granular, Inc
  • 11.7 IBM
  • 11.8 John Deere
  • 11.9 Microsoft Corporation
  • 11.10 Precision Hawk Inc
  • 11.11 Prospera
  • 11.12 Trimble
  • 11.13 The Climate Corporation
  • 11.14 Trace Genomics, Inc
  • 11.15 Vision Robotics Corporation

List of Tables

  • Table 1 Global Artificial Intelligence in Agriculture Market Outlook, By Region (2020-2028) ($MN)
  • Table 2 Global Artificial Intelligence in Agriculture Market Outlook, By Technology (2020-2028) ($MN)
  • Table 3 Global Artificial Intelligence in Agriculture Market Outlook, By Computer Vision (2020-2028) ($MN)
  • Table 4 Global Artificial Intelligence in Agriculture Market Outlook, By Machine Learning (2020-2028) ($MN)
  • Table 5 Global Artificial Intelligence in Agriculture Market Outlook, By Predictive Analytics (2020-2028) ($MN)
  • Table 6 Global Artificial Intelligence in Agriculture Market Outlook, By Offering (2020-2028) ($MN)
  • Table 7 Global Artificial Intelligence in Agriculture Market Outlook, By AI-as-a-Service (2020-2028) ($MN)
  • Table 8 Global Artificial Intelligence in Agriculture Market Outlook, By Hardware (2020-2028) ($MN)
  • Table 9 Global Artificial Intelligence in Agriculture Market Outlook, By Network (2020-2028) ($MN)
  • Table 10 Global Artificial Intelligence in Agriculture Market Outlook, By Processor (2020-2028) ($MN)
  • Table 11 Global Artificial Intelligence in Agriculture Market Outlook, By Storage Device (2020-2028) ($MN)
  • Table 12 Global Artificial Intelligence in Agriculture Market Outlook, By Services (2020-2028) ($MN)
  • Table 13 Global Artificial Intelligence in Agriculture Market Outlook, By Integration (2020-2028) ($MN)
  • Table 14 Global Artificial Intelligence in Agriculture Market Outlook, By Support & Maintenance (2020-2028) ($MN)
  • Table 15 Global Artificial Intelligence in Agriculture Market Outlook, By Software (2020-2028) ($MN)
  • Table 16 Global Artificial Intelligence in Agriculture Market Outlook, By AI Platform (2020-2028) ($MN)
  • Table 17 Global Artificial Intelligence in Agriculture Market Outlook, By AI Solution (2020-2028) ($MN)
  • Table 18 Global Artificial Intelligence in Agriculture Market Outlook, By Deployment (2020-2028) ($MN)
  • Table 19 Global Artificial Intelligence in Agriculture Market Outlook, By Cloud (2020-2028) ($MN)
  • Table 20 Global Artificial Intelligence in Agriculture Market Outlook, By Hybrid (2020-2028) ($MN)
  • Table 21 Global Artificial Intelligence in Agriculture Market Outlook, By On-Premise (2020-2028) ($MN)
  • Table 22 Global Artificial Intelligence in Agriculture Market Outlook, By Application (2020-2028) ($MN)
  • Table 23 Global Artificial Intelligence in Agriculture Market Outlook, By Agriculture Robots (2020-2028) ($MN)
  • Table 24 Global Artificial Intelligence in Agriculture Market Outlook, By Drone Analytics (2020-2028) ($MN)
  • Table 25 Global Artificial Intelligence in Agriculture Market Outlook, By Fish Farming Management (2020-2028) ($MN)
  • Table 26 Global Artificial Intelligence in Agriculture Market Outlook, By Labor Management (2020-2028) ($MN)
  • Table 27 Global Artificial Intelligence in Agriculture Market Outlook, By Livestock Monitoring (2020-2028) ($MN)
  • Table 28 Global Artificial Intelligence in Agriculture Market Outlook, By Animal Growth Monitoring (2020-2028) ($MN)
  • Table 29 Global Artificial Intelligence in Agriculture Market Outlook, By Animal Health Monitoring (2020-2028) ($MN)
  • Table 30 Global Artificial Intelligence in Agriculture Market Outlook, By Precision Farming (2020-2028) ($MN)
  • Table 31 Global Artificial Intelligence in Agriculture Market Outlook, By Crop Scouting (2020-2028) ($MN)
  • Table 32 Global Artificial Intelligence in Agriculture Market Outlook, By Field Mapping (2020-2028) ($MN)
  • Table 33 Global Artificial Intelligence in Agriculture Market Outlook, By Irrigation Management (2020-2028) ($MN)
  • Table 34 Global Artificial Intelligence in Agriculture Market Outlook, By Weather Tracking & Forecasting (2020-2028) ($MN)
  • Table 35 Global Artificial Intelligence in Agriculture Market Outlook, By Yield Monitoring (2020-2028) ($MN)
  • Table 36 Global Artificial Intelligence in Agriculture Market Outlook, By Indoor Farming (2020-2028) ($MN)
  • Table 37 Global Artificial Intelligence in Agriculture Market Outlook, By Smart Green House Management (2020-2028) ($MN)
  • Table 38 Global Artificial Intelligence in Agriculture Market Outlook, By Soil Management (2020-2028) ($MN)
  • Table 39 Global Artificial Intelligence in Agriculture Market Outlook, By Nutrient Monitoring (2020-2028) ($MN)
  • Table 40 Global Artificial Intelligence in Agriculture Market Outlook, By Moisture Monitoring (2020-2028) ($MN)
  • Table 41 Global Artificial Intelligence in Agriculture Market Outlook, By Supply Chain Efficiency (2020-2028) ($MN)
  • Table 42 Global Artificial Intelligence in Agriculture Market Outlook, By Farm Machinery Automation (2020-2028) ($MN)
  • Table 43 Global Artificial Intelligence in Agriculture Market Outlook, By Crop Growth Assessment (2020-2028) ($MN)

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