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Using AI systems to improve harvest quality and accuracy is a management style known as precision agriculture. Predictive Analytics uses AI technology to aid in detecting diseases in plants, pests and poor plant nutrition on farms. AI sensors can detect and target weeds while deciding which herbicides to apply within the right buffer — preventing …

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Precision forecasting is the backbone of another agricultural AI tool: risk management. Risk management offerings and algorithms are used to determine economic trends, commodity prices, supply chain management, if a farmer should use government insurance and minimum yield requirements Benefits for the company Growing a sustainable crop in mass quantities requires a farmer to take …

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The aim of the current use case is to develop bunch of Artificial, machine and deep learning algorithms with highest smartness and can control a Robot for doing above tasks with accuracy of 95% or above. Agricultural AI bots are harvesting crops at a higher volume and faster pace than human laborers, more accurately identifying …

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Farmers want the company to take care of the exact mapping of farm boundaries and cost-effective. A farmer will provide the company typical land boundaries of farmland, challenges they are facing while using drowns e.g. 1) farm will give today in the middle of the form, 2) farm will have a semi-arid land in the …

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A farmer will provide a company sales representative with information about previous crop yields and his or her target yields and the company representatives will visit the farm to obtain soil samples, which are analyzed in the company labs. A report is generated, which indicates the soil requirements for nutrients, including nitrogen, phosphorus, potassium, boron, …

Continue reading “Determining Optimal Fertilizer Mixes”