2014 Awards Of Excellence Winners: Champions Of Precision Ag
The 2014 Class of PrecisionAg Awards of Excellence recipients have spent their careers working to improve precision practices, increase adoption and put best practices in place on the ground. Here’s an up close look at this year’s five winners.
Dr. Matthew Darr | Iowa State University
Dr. Matthew Darr, associate professor within the Agricultural and Biosystems Engineering Department at Iowa State University, is considered a “young star” in the precision ag arena. Darr pioneered advanced equipment systems now being used across the world, and he is bringing precision ag to all levels of users in the industry.
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In his writing and presentations to growers, integrators and industry, Darr has a knack for drilling down to what the value proposition is for the practitioner.
With equipment, Darr is helping to develop the next generation of yield monitoring technology to improve yield estimates that accommodate increasingly large field equipment. Darr’s research focuses on developing systems that gather improved and more consistent yield data over the course of the entire season. His work also covers merging existing yield data with high resolution imagery and topographic data to achieve a spatially more precise yield map.
Teaching Multiple Generations, Players
Darr’s influence in precision ag education over the past six years has been immense, on a number of levels. His precision ag course draws up to 150 students a year. He has developed innovative lessons and laboratory exercises to help student understand the variety of precision ag topics, and his classes have received substantial industry support from leading equipment and precision technology manufacturers.
“Many of these students are being employed by precision ag companies, service providers and dealers, and machinery manufacturers,” Fulton says. “Matt’s impact on students and, ultimately, their role within companies, has been remarkable. He is a true teacher and mentor.”
Data’s Time Has Arrived
Darr’s educational efforts reach further beyond the classroom. He is helping a few of the larger U.S. ag companies and their employees understand the value of precision ag technologies, data and services. He also speaks to farmer groups at field days and workshops, especially helping them figure out the data space and privacy issues.
In fact, Darr says his team at Iowa State has continually transitioned course content to focus more on data management, data quality and data decisions. “By training the next generation of leaders we can shape their philosophy on data usage and help stimulate adoption and long-term solutions around data services,” Darr says.
He adds that it is extremely rewarding to work with these young people who have a thirst for precision ag and a belief in its future. “Today is very different than even five years ago,” Darr says. “Today’s student grew up in the smart phone era. They are naturally cloud connected at all times and have a much greater sense of data through social media sharing and other platforms. They more clearly see the real potential with these systems and can more easily see how the IT infrastructure ties into future ag plans.”
Darr sees the future of precision ag hinging on data. “Data analytics is the future of precision ag,” he says. “We’ve tried for 20 years to get here and are now in a position where IT infrastructure, machine intelligence and market demands are all converging to make this the right time for this to be a reality. Ten years from now we’ll wonder how we ever farmed without nitrogen fuel gauges, on farm weather stations, high resolution yield data and real-time soil sensors.”
But Darr also says data standards, data mobility and access to high quality data are the biggest challenges facing the field today. “It is going to be a bumpy three years in terms of navigating data licensing and data analytics maturity. And the drive towards data analytics will continue to press the issue around quality data to make good informed decisions. As analytic tools grow, so should the quality of data.”