Dublin, May 06, 2020 (GLOBE NEWSWIRE) -- The "Artificial Intelligence in Agriculture Market by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, Hardware, AI-as-a-Service, and Services), Application, and Geography - Global Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.
The AI in the agriculture market is projected to grow at a CAGR of 25.5% from 2020 to 2026.
The AI in agriculture market growth is propelled by the increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep-learning technology, and government support for the adoption of modern agricultural techniques. However, the high cost of gathering precise field data restrains the market growth. Developing countries, such as China, Brazil, and India, are likely to provide an opportunity for the players in the AI in agriculture market due to the increasing use of unmanned aerial vehicles/drones by these countries in their agricultural farms.
By technology, the machine learning segment is estimated to account for the largest share of the AI in the agriculture market during the forecast period.
Machine learning-enabled solutions are being significantly adopted by agricultural organizations and farmers worldwide to enhance farm productivity and to gain a competitive edge in business operations. In the coming years, the application of machine learning in various agricultural practices is expected to rise exponentially.
By offering, the AI-as-a-Service segment is projected to register the highest CAGR from 2020 to 2026.
Increasing demand for machine learning tool kits and applications that are available in AI-based services, along with benefits, such as advanced infrastructure at minimal cost, transparency in business operations, and better scalability, is leading to the growth of the AI-as-a-Service segment.
By application, the precision farming segment held the largest market size in 2019.
Precision farming involves the usage of innovative artificial intelligence (AI) technologies, such as machine learning, computer vision, and predictive analytics tools, for increasing agriculture productivity. It comprises a technology-driven analysis of data acquired from the fields for increasing crop productivity. Precision farming helps in managing variations in the field accurately, thus enabling the growth of more crops using fewer resources and at reduced production costs. 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
Key Topics Covered:
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Attractive Opportunities for the AI in the Agriculture Market
4.2 AI in Agriculture Market, by Offering
4.3 AI in Agriculture Market, by Technology
4.4 AI in Agriculture Market for Apac, by Application & Country
4.5 AI in Agriculture Market, by Geography
5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Increasing Strain on Global Food Supply Owing to Rising Population
5.2.1.2 Increasing Implementation of Data Generation Through Sensors and Aerial Images for Crops
5.2.1.3 Increasing Crop Productivity Through Deep Learning Technology
5.2.1.4 Government Support to Adopt Modern Agricultural Techniques
5.2.2 Restraints
5.2.2.1 High Cost of Gathering Precise Field Data
5.2.3 Opportunities
5.2.3.1 Developing Countries to Offer Significant Growth Opportunities
5.2.3.2 Use of AI Solutions to Manage Small Farms (Less than 5 Hectares)
5.2.4 Challenges
5.2.4.1 Lack of Standardization
5.2.4.2 Lack of Awareness About AI Among Farmers
5.2.4.3 Limited Availability of Historical Data
5.3 Value Chain Analysis
5.4 Impact of Covid-19 on AI in Agriculture Market
6 Artificial Intelligence in Agriculture Market, by Technology
6.1 Introduction
6.2 Machine Learning
6.2.1 Machine Learning Technology to Hold the Largest Share of AI in Agriculture Market
6.3 Computer Vision
6.3.1 Computer Vision Technology is Expected to Grow at the Highest CAGR during the Forecast Period
6.4 Predictive Analytics
6.4.1 Increasing Predictive Analytics Applications is Expected to Drive the Growth of AI in Agriculture Market
7 Artificial Intelligence in Agriculture Market, by Offering
7.1 Introduction
7.2 Hardware
7.2.1 Technological Advancements in the Hardware Segment is Leading to the Widespread Adoption of AI in Agriculture
7.2.2 Processor
7.2.3 Storage Device
7.2.4 Network
7.3 Software
7.3.1 AI in Agriculture Market for Software Segment is Projected to Hold the Largest Market Share during the Forecast Period
7.3.2 AI Platform
7.3.3 AI Solution
7.4 Ai-As-A-Service
7.4.1 Ai-As-A-Service Segment is Expected to Grow at the Highest CAGR during the Forecast Period
7.5 Services
7.5.1 Increasing Requirement of Online and Offline Support Services is Leading to the Growth of This Segment
7.5.2 Deployment & Integration
7.5.3 Support & Maintenance
8 Artificial Intelligence in Agriculture Market, by Application
8.1 Introduction
8.2 Precision Farming
8.2.1 Precision Farming is Expected to Hold the Largest Market Share during the Forecast Period
8.2.2 Yield Monitoring
8.2.3 Field Mapping
8.2.4 Crop Scouting
8.2.5 Weather Tracking & Forecasting
8.2.6 Irrigation Management
8.3 Livestock Monitoring
8.3.1 Increasing Livestock Monitoring Applications is Driving the Growth of This Segment
8.4 Drone Analytics
8.4.1 Drone Analytics Application Expected to Grow at the Highest CAGR during the Forecast Period
8.5 Agriculture Robots
8.5.1 Increased Deep Learning Capabilities of Agriculture Robots is Driving the Growth of This Segment
8.6 Labor Management
8.6.1 Major Benefits Such As Reduced Production Costs Due to Labor Management Application is Leading to the Growth of This Segment
8.7 Others
8.7.1 Smart Greenhouse Management
8.7.2 Soil Management
8.7.2.1 Moisture Monitoring
8.7.2.2 Nutrient Monitoring
8.7.3 Fish Farming Management
9 Geographic Analysis
9.1 Introduction
9.2 Americas
9.2.1 North America
9.2.1.1 Us
9.2.1.1.1 Us Projected to Account for the Largest Size of the AI in Agriculture Market in North America
9.2.1.2 Canada
9.2.1.2.1 Increasing AI Technology Adoption is Leading to the Growth of Canadian AI in Agriculture Market
9.2.1.3 Mexico
9.2.1.3.1 AI in Agriculture Market in Mexico is Projected to Grow at the Highest CAGR during the Forecast Period
9.2.2 South America
9.2.2.1 Brazil
9.2.2.1.1 Brazil Expected to Hold the Largest Share in the South American AI in Agriculture Market
9.2.2.2 Argentina
9.2.2.2.1 Expanding Industrial Production in Argentina is Driving the Market
9.2.2.3 Rest of South America
9.3 Europe
9.3.1 Uk
9.3.1.1 Increasing Adoption of Ai-Based Solutions for Agriculture is Driving the Uk Market
9.3.2 Germany
9.3.2.1 Germany Held the Largest Share of European AI in Agriculture Market in 2019
9.3.3 France
9.3.3.1 Increasing Number of Start-Ups Developing AI Solutions for Agriculture is Driving the Market in Europe
9.3.4 Italy
9.3.4.1 AI in Agriculture Market in Italy is Growing Steadily to Overcome Drastic Climate Conditions
9.3.5 Spain
9.3.5.1 Favorable Government Policies are Driving the AI in Agriculture Market in Spain
9.3.6 Rest of Europe
9.4 Asia Pacific
9.4.1 Australia
9.4.1.1 Australia Expected to Hold the Largest Share of the AI in Agriculture Market in Apac
9.4.2 China
9.4.2.1 Increasing Precision Farming Applications in China is Expected to Drive the AI in Agriculture Market for Apac
9.4.3 Japan
9.4.3.1 in 2019, Japan Held the Second-Largest Share of AI in Agriculture Market in Apac
9.4.4 South Korea
9.4.4.1 Government Funding and Initiatives are Driving the Growth of AI in Agriculture Market in South Korea
9.4.5 India
9.4.5.1 India is Expected to be the Fastest-Growing AI in Agriculture Market in Apac
9.4.6 Rest of Apac
9.5 Rest of the World
9.5.1 Increasing Awareness Among Farmers Regarding the Benefits of AI-Assisted Agricultural Operations is Driving the Market in Row
10 Competitive Landscape
10.1 Overview
10.2 Ranking Analysis
10.3 Competitive Scenario
10.3.1 Product Launches and Developments
10.3.2 Partnerships, Agreements, and Collaborations
10.3.3 Mergers and Acquisitions
10.4 Competitive Leadership Mapping
10.4.1 Visionary Leaders
10.4.2 Dynamic Differentiators
10.4.3 Innovators
10.4.4 Emerging Companies
11 Company Profiles
11.1 Key Players
11.1.1 IBM
11.1.2 Deere & Company
11.1.3 Microsoft
11.1.4 the Climate Corporation
11.1.5 Farmers Edge
11.1.6 Granular
11.1.7 Ageagle
11.1.8 Descartes Labs
11.1.9 Prospera
11.1.10 Taranis
11.1.11 Awhere
11.2 Right-To-Win
11.3 Other Key Companies
11.3.1 Gamaya
11.3.2 Ec2Ce
11.3.3 Precision Hawk
11.3.4 Vineview
11.3.5 Cainthus
11.3.6 Tule Technologies
11.3.7 Resson
11.3.8 Connecterra
11.3.9 Vision Robotics
11.3.10 Farmbot
11.3.11 Harvest Croo
11.3.12 Peat
11.3.13 Autonomous Tractor Corporation
11.3.14 Trace Genomics
11.3.15 Cropx Technologies
For more information about this report visit https://www.researchandmarkets.com/r/sqhb4s
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