PUNE, India, June 25, 2019 (GLOBE NEWSWIRE) — Global Artificial Intelligence in Agriculture Industry was valued at USD 479 Million in the year 2017. Global Artificial Intelligence in Agriculture Industry is further estimated to grow at a CAGR of 21.4 % from 2019 to reach USD 2240.89 Million by the year 2025. The Asia Pacific region holds the highest Industry share in 2017 and is considered the fastest growing Industry in the forecasted period. At the country level, China Australia, India, and Japan are the major industries in Asia Pacific region and holds a substantial Industry share in 2017 and it is projected to grow at a gradual pace in the coming years. The increasing adoption of deep learning and computer vision technologies for agricultural applications is the major driving factor for the Industry growth in the APAC region.

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The Industry is segmented by application, by offerings, and by region. By application, it is sub-segmented into Precision Farming, Agriculture Robots, and Others. In the year 2017, Precision Farming segment by application generated the highest revenue in the global Industry. Over the last two decades, precision farming has successfully made the transition from being an academic research topic to a highly beneficial practice in the field of agriculture.

Based on the basis of offerings, the Industry is segmented into Hardware, Software, and Service. Among these, the software segment held the largest Industry size in 2017. The Industry for the software segment is mainly driven by the integration of mobile technologies with farming techniques, growing use of artificial intelligence software to improve farm efficiency, and rising demand for real-time data management systems.

Major market players in Artificial Intelligence in Agriculture Industry are Agribotix, IBM, Deere & Company, aWhere Inc., FieldIn Tech, Pycno Agriculture, CropMetrics, Farmers Edge Inc., Granular AG, SST Software, and brief information of 10 companies will be provided in the report. Rising research and development expenses to cater changing demand of end users, similarly growth strategies such as acquisition, merger and expansion of the distribution network were few techniques adopted by most of Tier 1 and Tier 2 manufacturers in recent years.

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Source: “artificial intelligence” – Google News