AI in Farming John Bourne VP Marketing Ceres Imaging told us “Computer vision and deep-learning algorithms are being leveraged by ag tech companies to process data captured from aerial imagery, allowing growers to monitor and manage crop and soil health. Over time, these AI/machine learning models develop to track and predict various environmental impacts like water stress, disease and pest infiltration. Growers will increasingly look to use this historical data to predict yield in season and analyze the ROI on various potential fixes or investments they can make to improve yield.”
“Artificial intelligence and data science are important because they will empower growers to make better decisions in increasingly complex times. In a world that will be challenged by a rapidly increased food demand, climate change, a continued decline in agricultural workers and long-term sustainability concerns, farmers will look to adopt smarter tools that give them an edge, and th
Ceres and wheat Precision agriculture. Corn and soybean farmer Kirk Stueve also works as an expert with Ceres Imaging, a company that takes high resolution images of a farmers field and delivers analytics on pretty much everything that is going on. I asked him a question highly relevant to Idaho.
We grow a lot of wheat out here in Idaho. Do you guys play in that marketplace.
We are just starting to delve into that market a bit. We re most established in anything where you have irrigation, you any irrigated landscapes and the specialty crops of California, Australian, Pacific Northwest and so forth. But certainly in wheat our chlorophyll product is very strong and helping to manage nitrogen. Most of your growers out that way are well aware they get too much nitrogen on spots that wheat will have a tendency to lodge. And so our chlorophyll product can really help dial in that nitrogen placement.
AI and data science John Bourne VP Marketing Ceres Imaging discusses the top trends shaping the future of AI in agriculture?
“Computer vision and deep-learning algorithms are being leveraged by ag tech companies to process data captured from aerial imagery, allowing growers to monitor and manage crop and soil health. Over time, these AI/machine learning models develop to track and predict various environmental impacts like water stress, disease and pest infiltration. Growers will increasingly look to use this historical data to predict yield in season and analyze the ROI on various potential fixes or investments they can make to improve yield.”
AI and data science John Bourne VP Marketing Ceres Imaging discusses the top trends shaping the future of AI in agriculture?
“Computer vision and deep-learning algorithms are being leveraged by ag tech companies to process data captured from aerial imagery, allowing growers to monitor and manage crop and soil health. Over time, these AI/machine learning models develop to track and predict various environmental impacts like water stress, disease and pest infiltration. Growers will increasingly look to use this historical data to predict yield in season and analyze the ROI on various potential fixes or investments they can make to improve yield.”