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AI in Agriculture: Will AI help farmers to make better decision for optimized crop production
AI in Agriculture: Will AI help farmers to make better decision for optimized crop production

July 4, 2021

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With the increasing world population and the increasing demand for food, efficient farming techniques for more productivity in the scarce amount of area is essential. In the field of agriculture, AI is emerging day by day and AI-based machines are taking today's farming system to another level. Agriculture depends on various factors like nutrients content of the soil, moisture, crop rotation, rainfall, temperature, etc. and these factors can be utilized by AI-based products to monitor the crop yield.

 

How has AI helped and where it helped

Agricultural farms produce countless data points daily and including the hardware and software AI-based techniques with proper data analytics would help enhance farm productivity. Farmers can analyze a variety of things from the data collected from their farms and help them make proper decisions regarding which crop to choose, pests' controls, the best hybrid seed choices, monitor soil, and help them with other workloads.

Large scale agriculture players in America uses AI technologies to significantly improve the speed and accuracy of planting and crop management techniques to yield healthier crops. Brazil’s leading sugar and ethanol producer, Raizen, will partnership with Space Time Analytics (Brazil) to use AI to forecast the size of sugarcane harvests. Many regions around the world have started using AI-based drones to monitor their crops.

 

The problem in adopting AI for agriculture

There is a big gap between advancement in technology, application area, and adoption of its modern products. The reason for this can range from being less technology conscious to the high cost of less precise Agri-Tech solutions available. Even though Al may be very helpful in agriculture but its adoption is a big task. Further advancement is needed to clearly explain the usefulness of the practical application of agricultural AI tools so as to make the most of it.

 

What needs to be done

More awareness in technology about the possibility of the physical and practical application of AI is much needed. Easy applications like apps that can be easily functional in mobile phones can also be a solution. A system that uses AI with other technology like computer vision, predictive analysis, and machine learning to predict the most profitable crop in the current soil conditions, weather, area availability, and region would work best. This can help increase the profit margins of farmers by improving crop yield productivity over the longer run. Thus with proper AI methodologies, AI can be very helpful to farmers for decision making in every stage of crop production from the preparation of soil and sowing to harvesting and storage.


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