The Artificial Intelligence in Agriculture Market report also gives an insight into product portfolios, costs, sales, production capacities, and market players. Raw materials, demand analysis, product flow, and distribution channels have been studied and surveyed extensively in this research report. The Artificial Intelligence in Agriculture Market key growth trends and opportunities are offered through a thorough investigation and examination of the market. A detailed course of development is offered in the report along with insights into businesses connected with it, which include firms, industries, organizations, vendors, and local manufacturers.
The Artificial Intelligence (AI) in agriculture market size reached USD 1.70 Billion in 2021 and is expected to register a revenue CAGR of 27.0% during the forecast period to a latest analysis by Emergen Research. The increasing implementation of data generation through sensors is a key factor driving revenue growth of the market. Precision agriculture is one type of farm management strategy that can assist farmers in producing more crops with fewer resources. The next big thing in farming may be AI-powered precision agriculture. To assist farmers to maximize yields and cut costs, precision farming combines the best soil management techniques, variable rate technologies, and the most efficient data management processes. Farmers may identify fields that require irrigation, fertilizer, or pesticide application by using real-time insights from AI. Additionally, innovative farming techniques such as vertical agriculture may assist boost food production while using fewer resources. Herbicide use is reduced, harvest quality is improved, earnings are increased, and there are significant cost savings as a result.
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Some Key Highlights From the Report
- The software segment is expected to register significant market revenue growth. AI-based software boosts crop productivity and yield by utilizing prediction-based analytics and computer vision. The advantages of AI-enabled software for upcoming applications in agriculture, such as drone analytics and precision farming, are what is really driving the market's growth.
- The predictive analysis segment is expected to grow considerably. One of the most intriguing technologies now being used, significantly modified, and created is predictive analytics. Only a handful of the numerous statistical methods that make up predictive analytics as a whole include modeling, machine learning, and data mining.
- The drone analytics segment is expected to register steady growth. The majority of the labor-intensive task associated with growth can be eliminated by using drones to explore an area and unearth new information. Drone analytics help identify plant stress, assess the health and productivity of plants, and There are a variety of tasks that can be accomplished, including the detection of resistant weeds or invasive species, altering nitrogen fertilization for row crops, speedy storm damage assessment to settle claims, optimum water use by keeping track of drought stress at different growth stages, inventorying plant population, size, and health, offering guidance on the best time to harvest, and accurately estimating yield.
- The market in Europe is expected to register considerable growth. Agriculture, which is in charge of approximately half of Europe's economy, is the main industry there.
The report on the Global Artificial Intelligence in Agriculture Market is an investigative study on the key features of the business landscape along with an analysis of the growth opportunities, challenges, threats, drivers and restraints, and limitations of the market. The report also offers insights into the segments, sub-segments, and regions exhibiting promising growth.
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The report further sheds light on the competitive landscape of the Artificial Intelligence in Agriculture market to offer the readers an advantage over others. The competitive landscape section of the report talks about the recent advancements in the RD and technologies undertaken by the prominent players, along with their strategic business expansion plans, product launches, and brand promotions. The report pays special attention to the strategic alliances such as mergers and acquisitions, joint ventures, collaborations, agreements, corporate and government deals, and others adopted by the prominent players of the industry to expand their market presence and gain a substantial market position.
The prominent players profiled in the report are:
Microsoft Corporation, Descartes Labs, Inc., Gamaya Inc., Precision Hawk, Connecterra B.V, Autonomous Tractor Corporation, Taranis, IBM Corporation, Granular Inc., and VineView.
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Emergen Research has segmented the artificial intelligence in agriculture market on the basis of component, technology, application, and region:
- Component Outlook (Revenue, USD Billion; 2019–2030)
- Hardware
- Software
- Technology Outlook (Revenue, USD Billion; 2019–2030)
- Machine Learning Deep Learning
- Computer Vision
- Predictive Analysis
- Application Outlook (Revenue, USD Billion; 2019–2030)
- Precision Farming
- Drone Analytics
- Agriculture Robots
- Others
- Regional Outlook (Revenue, USD Billion; 2019–2030)
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- France
- U.K.
- Italy
- Spain
- Benelux
- Rest of Europe
- Asia Pacific
- China
- India
- Japan
- South Korea
- Rest of APAC
- Latin America
- Brazil
- Rest of LATAM
- Middle East Africa
- Saudi Arabia
- U.A.E.
- South Africa
- Turkey
- Rest of MEA
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The report covers the analysis of the factors anticipated to drive the Global Artificial Intelligence in Agriculture Market growth over the forecast period of 2020-2027. The report is an all-inclusive document covering the market landscape and a futuristic perspective on its growth and progress. The report also provides an analysis of the entry-level driving and restraining factors for the new entrants contributing to the market. The report considers 2019 as the base year and 2017-2018 as the historical years. It puts examines drivers and restraints of the Artificial Intelligence in Agriculture market and analyzes their impact on the industry throughout the forecast period.
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