The market report of artificial intelligence (AI) in agriculture is a definitive study of various parts of the global market. It shows the constant evolution of the market regardless of the deviations and changing trends of the corporate sector. The ratio depends on some important limitations.
The whole world has been affected by the COVID-19 epidemic, which has significantly affected the global economy. Almost all industries, large and small, have not been spared the impacts of the coronavirus. The food and beverage industry is no different. Agribusiness companies face drastically reduced consumption and hampered supply chains. Although home consumption has increased, out-of-home consumption – responsible for generating the highest margin – has declined.
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The report explains the drivers shaping the long term of the artificial intelligence (AI) in agriculture market. It assesses the various forces that are expected to have a positive influence on the market in general. Analysts have studied investments in research and development of products and technologies that are expected to offer a particular boost to gamers. In addition, the researchers have also included an analysis of changing consumer behavior that is expected to impact the availability and demand cycles present in the global Artificial Intelligence (AI) in Agriculture market. Changes in per capita incomes, improving economic conditions and emerging trends have all been explored during this research report.
Key players in the artificial intelligence (AI) in agriculture market: IBM, John Deere, Microsoft, Agribotix, The Climate Corporation, ec2ce, Descartes Labs, Sky Squirrel Technologies, Mavrx, aWhere, Gamaya, Precision Hawk, Granular, Prospera, Cainthus, Spensa Technologies, Resson, FarmBot, Connecterra, Vision Robotics, Harvest Croo, Autonomous Tractor Corporation, Trace Genomics, Vine Rangers, CropX ..
Segmentation by product type: Machine Learning, Computer Vision, Predictive Analytics
Apart from this, the application market is segmented into: precision farming, drone analysis, agricultural robots, livestock monitoring, others
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Market segment by region, regional analysis covers
- North America (United States, Canada and Mexico)
- Europe (Germany, France, United Kingdom, Russia, Italy and rest of Europe)
- Asia-Pacific (China, Japan, Korea, India, Southeast Asia and Australia)
- South America (Brazil, Argentina, Colombia and the rest of South America)
- Middle East and Africa (Saudi Arabia, United Arab Emirates, Egypt, South Africa and Rest of Middle East and Africa)
|The report contains||specification|
|By the best players||IBM, John Deere, Microsoft, Agribotix, The Climate Corporation, ec2ce, Descartes Labs, Sky Squirrel Technologies, Mavrx, aWhere, Gamaya, Precision Hawk, Granular, Prospera, Cainthus, Spensa Technologies, Resson, FarmBot, Connecterra, Vision Robotics, Harvest Croo, Autonomous Tractor Corporation, Trace Genomics, Vine Rangers, CropX.|
|Historical data||2015 to 2019|
|Market segments||Types, applications, end users, etc.|
|By product types||Machine learning, computer vision, predictive analytics|
|By applications / end user||Precision agriculture, drone analysis, agricultural robots, livestock monitoring, others|
|Regional scope||North America, Europe, Asia-Pacific, Latin America, Middle East and Africa|
The objectives of the study are as follows:
- To identify, determine, and forecast the segments of the global artificial intelligence (AI) in agriculture market on the basis of its type, sub-type, technology used, applications, end-users, and regions.
- To examine micro markets based on growth trends, development patterns, future prospects, and contribution to the overall Artificial Intelligence (AI) in Agriculture market.
- Study the market opportunities for different stakeholders and investors by determining high-end growth segments and sub-segments.
- To determine the size of the overall market, in terms of value, and for different segments with respect to North America, Asia-Pacific, Latin America, Middle East and Africa.
- To accurately profile the major vendors and players operating in the Artificial Intelligence (AI) in Agriculture market, in terms of rank and core skills, as well as to determine the competitive landscape.
- To study competitive developments such as partnerships and collaborations, mergers and acquisitions (M&A), research and development (R&D) activities, product developments and expansions in the global artificial intelligence (AI) market in agriculture.
This report examines the key questions mentioned below:
- What are some of the most favorable and favorable growth prospects for the global Artificial Intelligence (AI) in Agriculture market?
- Which components of the product will grow at a faster rate throughout the forecast period and why?
- Which geography will expand faster and why?
- What are the major factors impacting the outlook of the market What are the driving factors, restraints, and challenges during this Artificial Intelligence (AI) in Agriculture market?
- What is the issue and the competitive threats in the market?
- What are the evolving trends during this Artificial Intelligence (AI) in Agriculture market and reasons for their emergence?
- What is the number of changing customer demands in the Artificial Intelligence (AI) market in the agricultural industry?
Chapter 1: Introduction, Market Driving Force Product Study Objective and Research Scope Artificial Intelligence (AI) in Agriculture Market
Chapter 2: Exclusive summary – the basic information of artificial intelligence (AI) in the agriculture market.
Chapter 3: Viewing Market Dynamics – Drivers, Trends and Challenges of Artificial Intelligence (AI) in Agriculture
Chapter 4: Presentation of artificial intelligence (AI) in the agricultural sector Market factor analysis Porters Five Forces, Supply / Value Chain, PESTEL analysis, Market Entropy, Patent / Trademark Analysis.
Chapter 5: View by type, end user and region 2013-2018
Chapter 6: Major Manufacturers Assessment of the Artificial Intelligence (AI) in Agriculture Market including its competitive landscape, peer group analysis, BCG matrix and company profile
Chapter 7: Evaluate the market by segments, by country and by manufacturer with a share of revenue and sales by key countries in these different regions.
Chapter 8 and 9: Display of appendix, methodology and data source
Conclusion: At the end of the Artificial Intelligence (AI) in Agriculture market report, all results and estimates are given. It also includes key drivers and opportunities as well as regional analysis. Segmental analysis also provides in terms of both type and application.
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