Artificial Intelligence in Agriculture Market Is Expected To Grow At a CAGR Of 6.0% FROM 2018-2027.
According to Stratistics MRC, the “Global Artificial Intelligence in Agriculture Market” is accounted for $0.89 billion in 2018 and is expected to reach $1.50 billion by 2027 growing at a CAGR of 6.0% during the forecast period. Increasing crop productivity through deep learning technology, and government support to adopt modern agricultural techniques are the major factors propelling the market growth. However, factors such as high cost of gathering precise field data, and limited availability of historic data are hampering the market growth.
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The AI in agriculture has various applications ranging from facial acknowledgment, rural automatons, computerized water system frameworks, and driverless tractors. This artificial intelligence in agriculture applications is done in a relationship with an alternate sort of sensors, radars, GPS frameworks, other cutting-edge contraptions dependent on AI. Seeing these broad applications, artificial intelligence in agriculture is getting a colossal reaction from investors all around. The increasing utilization and rising necessity of better yield of products are evaluated to be one of the essential points that are fueling the demand for artificial intelligence in agriculture. Agriculture is seeing prompt implementation of AI and machine learning (ML) both in terms of agricultural products and in-field agriculture techniques. Intellectual computing in specific is all set to become the most disruptive technology in agriculture service sector as it can understand, learn, and respond to different circumstances to raise efficacy. Providing some of these solutions as a service such as chatbot or other conversational platform to all the farmers will help them keep pace with technological innovations as well as apply the same in their day-to-day farming to obtain the benefits of this service. Artificial Intelligence has various applications in agriculture ranging from rural automatons, facial acknowledgment, computerized water system frameworks, and driverless tractors. These applications are done in relationship with an alternate sort of sensors, GPS frameworks, radars, and other cutting edge contraptions dependent on AI.
Opportunity: Image-based insight generation would provide ample opportunities for the market growth.
Exactitude farming is one of the maximum discussed areas in farming now-a-days. Drone-based images can support in in-depth field analysis, crop observing and scanning of fields. Computer vision technology, IOT and drone data can be collective to assure rapid actions by farmers. Feeds from drone image data can create alerts in real time to increase the speed of precision farming. For, instance, the companies such as Aerialtronics have employed IBM Watson IoT platform and the visual recognition APIs in commercial drones for image analysis in real time. More or less areas under computer vision technology can be put to utilization in disease detection, crop readiness identification, field management, etc.
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Driver: Rise in usage of smart sensors is driving the market growth.
Increasing use of smart sensors in agriculture is a major trend observed in the AI in agriculture market. With rise in precision agriculture practices, there has been an increasing use of sensors in the agricultural fields. Through the use of sensor-based technology in agriculture, farmers are now able to map their crop fields accurately, and can also monitor and apply crop treatments only to areas that need it. The rise in development of various operation specific sensors, such as location sensors, optical sensors, electrochemical sensors, mechanical sensors, airflow sensors, soil moisture sensors, and weather sensors, is helping farmers in monitoring and optimizing yields of crops, as well as making them adaptable to changing environmental factors effectively.
Asia Pacific region is anticipated to hold considerable market share during the forecast period:
By geography, the Asia Pacific region is anticipated to hold considerable market share during the forecast period. The wide-scale adoption of AI technologies in agriculture farms is the key factor supporting the growth of the market in this region. AI is increasingly applied in the agriculture sector in developing countries, such as India and China. The increasing adoption of deep learning and computer vision algorithm for agriculture applications is also expected to fuel the growth of the AI in agriculture market in the Asia Pacific region. Asia Pacific is anticipated to meet high growth rate in the forecast period due to the rising demand from emerging nations, for instance, India and China. Also, rising adoption of the mechanical technology and IoT devices in agriculture is additionally evaluated to drive the Artificial Intelligence in Agriculture market.
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Some of the key players profiled in the Artificial Intelligence in Agriculture Market include IBM, Cainthus Corporation, Connecterra B.V, CropX Inc, Descartes Labs, Inc, Farmers Edge, Granular, Inc, John Deere,Microsoft Corporation, Precision Hawk Inc., The Climate Corporation, Trace Genomics, Inc, and Vision Robotics Corporation.
IBM: In January 2020, IBM partnered with Yara International (Norway), a global leader in crop nutrition and digital farming solutions, invited farmer associations, industry players, academia, and NGOs from the food and agriculture industry to join a movement to develop an open data exchange that facilitates collaboration around farm and field data, with the aim of improving the efficiency, transparency, and sustainability of global food production.
Farmers Edge: In March 2020, Farmers Edge partnered with Nufarm Brasil, a leading crop protection company, 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
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