The leading companies own the advantages on better performance, more abundant product’s types, better technical and impeccable after-sales service. Consequently, they take the majority of the market share of high-end market. Looking to the future years, the slow upward price trend in recent years will maintain. As competition intensifies, prices gap between different brands will go narrowing. Similarly, there will be fluctuation in gross margin.
The industry is expected to remain innovation-led, with frequent acquisitions and strategic alliances adopted as the key strategies by the players to increase their industry presence. Market stays in mature period with a clear concentration. Meanwhile, optimize product mix and further develop value-added capabilities to maximize margins.
The emergence of new age technologies like Artificial Intelligence (AI), Cloud Machine Learning, Satellite Imagery and advanced analytics are creating an ecosystem for smart farming. Fusion of all this technology is enabling farmers achieve higher average yield and better price control.
Microsoft is currently working with farmers from Andhra Pradesh to provide advisory services using Cortana Intelligence Suite including Machine Learning and Power BI. The pilot project uses an AI sowing app to recommend sowing date, land preparation, soil test-based fertilization, farm yard manure application, seed treatment, optimum sowing depth and more to farmers which has resulted in 30% increase in average crop yield per hectare.
Technology can also be used to identify optimal sowing period, historic climate data, real time Moisture Adequacy Data (MAI) from daily rainfall and soil moisture to build predictability and provide inputs to farmers on ideal sowing time.
To identify potential pest attacks, Microsoft in collaboration with United Phosphorus Limited is building a Pest Risk Prediction API that leverages AI and machine learning to indicate in advance, the risk of pest attack. Based on the weather condition and crop growth stage.
Global Artificial Intelligence in Agriculture Market: Forecast by Application
Artificial Intelligence (AI) in Agriculture is mainly used for three applications: Precision Farming, Livestock Monitoring, Drone Analytics, Agriculture Robots, Others. And Precision Farming was the most widely used area which took up about 34.60% of the global total in 2017. However, in the future, Agriculture Robots will occupy more share.
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