FARMINGTON, Wash. – The gently rolling hills here in eastern Washington have long grown rich harvests of wheat, barley and lentils.
Fifth-generation farmer Andrew Nelson is adding a new bumper crop to that bounty: Data.
He gathers it from sensors in the soil, drones in the sky and satellites in space. They feed Nelson information about his farm at distinct points, every day, all year long — temperature variations, soil moisture and nutrient levels, plant health and more.
Nelson in turn feeds that data into Project FarmVibes, a new suite of farm-focused technologies from Microsoft Research. Starting today, Microsoft will open source these tools so researchers and data scientists — and the rare farmer like Nelson, who is also a software engineer — can build upon them to turn agricultural data into action that can help boost yields and cut costs.
The first open-source release is FarmVibes.AI. It is a sample set of algorithms aimed at inspiring the research and data science community to advance data-driven agriculture. Nelson is using this AI-powered toolkit to help guide decisions at every phase of farming, from before seeds go into the ground until well after harvest.
FarmVibes.AI algorithms, which run on Microsoft Azure, predict the ideal amounts of fertilizer and herbicide Nelson should use and where to apply them; forecast temperatures and wind speeds across his fields, informing when and where he plants and sprays; determine the ideal depth to plant seeds based on soil moisture; and tell him how different crops and practices can keep carbon sequestered in his soil.
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In order to enable academics and data scientists, as well as the unusual farmer like Nelson, who is also a phrazle software engineer, use agricultural data to improve yields and reduce costs, Microsoft will make these tools open source.
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