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Ag-Analytics and LSU AgCenter Partnership Brings AI and Machine Learning to Yield Predictions

The Ag-Analytics cloud platform makes big data and machine learning applications in agriculture a reality for universities by securely connecting farmers with researchers and extension.


News provided by

Ag-Analytics

Jun 20, 2019, 17:07 ET

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ITHACA, N.Y., June 20, 2019 /PRNewswire/ -- Ag-Analytics is partnering with the LSU AgCenter to help farmers maintain and improve yields through the use of machine learning and big data.

Ag-Analytics, a cloud-based secure farm management platform, works with farmers, industry and universities with the goal of helping farmers make better management decisions and mitigate risk. The data partnership with the LSU AgCenter is a first of its kind with any university.

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The ProfitLayers tool is an example of what can be achieved with data by Ag-Analytics. This tool utilizes farmers' operational data to produce profit maps and summaries.
The ProfitLayers tool is an example of what can be achieved with data by Ag-Analytics. This tool utilizes farmers' operational data to produce profit maps and summaries.

"The Ag-Analytics/LSU AgCenter partnership will allow farmers to opt-in to confidentially and securely share data with their land-grant university researchers in a seamless manner with protocols in place to protect privacy," says Josh Woodard, CEO of Ag-Analytics and an associate professor of agribusiness at Cornell University. "This research and development will directly result in new tools and models that will allow us to better serve our farmers by leveraging Ag-Analytics and the university extension system."

The system allows growers with John Deere Operations Center to sign up for free and easily link their agricultural equipment to the Ag-Analytics platform. 

Thanos Gentimis, LSU AgCenter mathematician, plans to take the massive volume of data Ag-Analytics collects, apply machine learning techniques to it — teaching a computer program to recognize patterns in the data — and develop models that can predict yield.

"We can turn a tangled set of data into a valuable asset, but we can't do this with data from just one field," Gentimis said. "If we have a million acres, then we can train the model to make more accurate predictions and then apply it to a farmer's field."

Improving yield-predictor models also would allow farmers to account for volatile weather, fluctuations in temperatures or precipitation and other events that affect yields.

Farmers can sign up with Ag-Analytics for free and opt-in to share data confidentially with the LSU AgCenter at https://ag-analytics.org/LSUAgCenter. The information gathered on individual farms will remain confidential, and personally identifiable information will be stripped. Farmers who sign up can also get access to resources, such as a real-time feed with information about their fields, weather and insurance forecasts.

Press Contact

Irene Bradley
Executive Assistant, Ag-Analytics

Email: [email protected]
Phone: (607) 321-1389

Related Images

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SOURCE Ag-Analytics

Related Links

https://ag-analytics.org

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