USDA, Microsoft announce winners of Ag app contest
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WASHINGTON, Jan. 27, 2016 - The Agriculture Department will dole out $63,000 in cash and prizes to the six winners of the USDA-Microsoft Innovation Challenge. The winners, announced Wednesday, developed tools using USDA agricultural production data that can help farmers cope with climate change.
“The winners of the USDA-Microsoft Innovation Challenge have used open government data to create an impressive array of innovative tools to help food producers and our communities prepare for the impacts of climate change and ensure our nation's ability to provide plentiful, affordable food,” Agriculture Secretary Tom Vilsack said in a release. “For more than 100 years, USDA has compiled data on the farm economy, production, and the health of crops around the country, and it is exciting to see such modern, useful tools spring from these information sources.”
The contest is part of the Obama administration's Climate Data Initiative, which is focused on using data in ways that will help the American food system become more resilient in the face of climate change. It also supports USDA's 10 Building Blocks for Climate Smart Agriculture, which Vilsack announced in April last year. The Building Blocks are expected to reduce net greenhouse gas emissions and enhance carbon sequestration by more than 120 million metric tons of CO2 equivalent - about 2 percent of economy-wide emissions - by 2025.
USDA provided contestants with more than 100 years of crop and climate data through Microsoft Azure, Microsoft's cloud computing platform. Daron Green, deputy managing director of Microsoft Research, said “Microsoft's partnership with the USDA evidences how public-private partnership can stimulate new applications, explore novel scenarios and, in this case, work towards a more resilient and sustainable food production.”
The contest winners were selected from more than 346 registrants and 33 submissions from around the world. They are:
- Grand Prize, Open Source Application Award, and Best Visualization in Time or Space Award recipient: Farm Plenty application, submitted by George Lee of San Francisco, Calif., will allow farmers to analyze USDA data about crops grown within 5 kilometers of their farms to make informed decisions about their own crop choices.
- Second Prize and Open Source Application Award recipient: Green Pastures dashboard interface, submitted by Khyati Majmudar of Mumbai, India, allows a farmer to visualize production, economic, livestock, and commodity data from NASS, ERS, ARMS, and other sources at scales from national to local, including information on farmers markets.
- Third Prize recipient: What's Local tool, submitted by Benjamin Wellington of Landscape Metrics LLC in Brooklyn, N.Y., analyzes the resources that are required to produce agricultural outputs by using data from the Census of Agriculture in a way that allows urban population centers to connect with farmers in their area.
- Honorable Mention: Open Source Application Award, and Best Student-Made Award recipient: Farm Profit Calculator mobile phone application, submitted by Fernando Napier and Matt Pedersen of Lincoln, Neb., allows farmers to compare their input costs (fertilizer, seed, fuel, etc.) to regional averages, and find financial efficiencies where their costs are above the norm.
- Honorable Mention recipient: Croptrends tool, submitted by Chaiyawut Lertvichaivoravit and Ta Chiraphadhanakul of Thousand Eyes in San Francisco, Calif., can be used to view spatial and temporal trends in crop production and yield by county for the entire United States by using NASS data.
- Popular Choice Award recipient: VAIS tool, submitted by Ken Moini of Thallo Tech in Nashville, Tenn., uses NASS data for the entire United States to provide a unique approach to visualizing crowd-sourced pricing data.
- Large Organization Recognition Award recipient: Farmed tool, submitted by Bryan Tower of Applied Technical Systems in Silverdale, Wash., allows farmers to view crop conditions in their area by using VegScape data from NASS combined with local weather data.
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