Using AI to Derive Insights to Enhance Crop Yield
Agriculture is one of the major industries that contribute to the economy of a country. The increasing consumption with the rapid growth in population is driving demand for agricultural production. But the productivity in the agricultural region is altering with the changing weather and water availability. To tackle these challenges growers around the globe are seeking innovative approaches that do not strain the resource the planet irreparably and protect and improve crop yield simultaneously. Researchers and scientist are using various tools of plant genetics, agronomics, chemistry, and machinery to sustainably intensify agriculture. And now they are using the new and emerging tool, Artificial intelligence (AI). The requirement for better yield of vegetation and increasing consumption has led to the introduction of AI into the agriculture industry resulting in automating farming operations.
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AI in agriculture can guide farmers through the process of growing, sowing, harvesting and sale of produce. Algorithmic models of Artificial intelligence (AI) that mimic human behavior are considered in the field. Using cognitive processing as the human mind AI can adapt itself to execute tasks in real time situations and does not require constant supervision. The major categories of AI application in agriculture are agricultural robots, crop and soil monitoring, and predictive analytics.
John Deere, Trimble, AGCO, Ag Leader Technology, Gamaya, Iteris, aWhere, Granular, and Raven Industries are the leading vendors in Artificial intelligence (AI) in the agriculture market. To handle the crucial tasks of agriculture such as harvesting crops at a higher volume with a faster pace, companies are developing autonomous robots. Drones are used to monitor crop and soil health. Companies are using computer vision and deep-learning algorithms to the fullest to process data captured by drones and software-based technology for monitoring soil and crop health. to track and predict various environmental impacts such as weather change on crop yield, machine learning models are being developed. According to a report by Krishi Jagran, by 2025 the global AI in the agriculture market will reach 1100 million dollars.
AI technology is assisting farmers in analyzing a large amount of data from multiple sources to extract actionable insights to enhance crop yield and product quality. Deployment of robots in fields is helping to discovering diseases with 98 percent accuracy. Artificial intelligence (AI) makes it very practical to assess demand and supply, market intelligence, crop competitiveness, and regional crop planning leading to precision in agriculture.