Professor Bullock, in conjunction with members of the team behind the recent NSF INFEWS application, submitted the following abstract for consideration in the upcoming INLRS Annual Workshop’s Research Showcase:
We propose to create an integrated FEW model and with user-friendly software to 1) enable individual farmers to examine the predicted economic and environmental impacts of their fertilizer management strategies, and 2) provide policy makers with a user-friendly tool in order to design policies that will lead to efficient reduction of N-nitrate contamination in the Mississippi River Basin. The model will be based on the ideal CyberGIS computation platform, and expand to the scale of the Mississippi River Basin the DSSAT crop growth model and the SWAT water drainage model. The model will also integrate the BioScope model of biomass supply, and a partial equilibrium economic model of crop, energy, and biomass markets in the U.S. Midwest and beyond. We argue that the principal shortcoming of current agricultural “Big Data” is that there is little record of variance in managed input use. Of course, managing inputs efficiently is the whole point of farm management, whether the goal is to increase monetary returns or environmental sustainability. Therefore, we propose to parameterize our integrated model with data we generate from large-scale, on-farm agronomic field trials over an entire small watershed. Those trials will randomize N application rates and cover-crop management strategies to measure both yield and water quality results of varying these managed input variables. We will use the generated data with existing agricultural “Big Data” to create “decision tool” software to improve private and public crop fertilization strategies. The proposed research will rely heavily on the proven abilities and infrastructure of the CyberGIS Center for Advanced Digital and Spatial Studies, and on the software, administrative capacity, and scientist-farmer relationships developed in an on-going USDA-NIFA Food Security project on data-intensive fertilizer management. In addition, we will provide opportunities for underrepresented undergraduates to gain research experience through an extension of the WE CAN program.
Professor and PI David Bullock has submitted and co-submitted a pair of abstracts for the ISPA Conference in 2019. With P. Paccioretti, M. Cordoba, C. Bruno, and Monica Balzarini, Professor Bullock submitted “Statistical modeling for on-farm experimentation with precision agricultural technology.” Professor Bullock submitted an additional abstract regarding the value of on-farm experimentation.
Joshua Babes is an undergraduate at UIUC studying Agricultural and Consumer Economics who is volunteering to work with the Data-Intensive Farm Management project. Joshua comes from the north side of Chicago and is working towards a career in consulting doing data analytics. He hopes to begin to learn more about the analytics while contributing to DIFM.
Rodrigo Goncalves Trevisan is a new graduate student in crop sciences under Professor Nicolas Martin who is focused on harnessing the power of new analytical methods to improve the decision-making process in agricultural systems. Trevisan received a baccalaureate degree in agronomy from the Federal University of Mato Grosso, and his master’s degree in agricultural systems engineering from the Luis de Queiroz College of Agriculture at the University of Sao Pãulo. He is the precision agriculture coordinator in one of the largest agriculture companies in Brazil, and is co-founder and the head of research and development of technological solutions for agribusiness at Smart Agri. Trevisan has participated in events as speaker and organizer and is a founding member of the Brazilian Association of Precision Agriculture. He is experienced in agricultural planning, precision agriculture, on-farm experimentation, remote sensing, geographic information systems, data analysis, and artificial intelligence.
Laila Puntel, of Iowa State University, and Brittani Edge and Aolin Gong, of the University of Illinois, presented at the 14th International Conference on Precision Agriculture in Montreal. Puntel stated, “It was great to see such a big community from all over the world…people from Australia, Germany, Belgium, South America, Canada, and US.”
In order to collaborate internationally, scientists from Curtin University in Australia organized a consortium for on-farm experimentation, to which Puntel was invited. This partnership will allow the DIFM project to be connected with OFE in different countries.
Montana State University- and University of Montana-based researchers affiliated with DIFM also shared their research: Amy Peerlinck, John Sheppard, and Bruce Maxwell gave a presentation titled “Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision Agriculture,” and Bruce Maxwell, Paul Hegedus, Anton Bekkerman, Robert Payn, John Sheppard, Nicholas Silverman, and Clemente Izurieta gave a presentation titled, “Can Optimization Associated with On-Farm Experimentation Using On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?”
Luciano Shiratsuchi and Lisa Fultz approved an internal budget of $70,000 from the Louisiana State University (LSU) to build a Digital Agriculture Laboratory to support DIFM in cloud data processing and storage. The initial plan is to invest in equipment (electrical conductivity machines, on-the-go sensors, drones and workstations) to promote multi-disciplinary work, provide teaching materials, and to start up a Precision Agriculture Program at LSU.
Bob Dunker, a member of our research team, spent an afternoon in the sun testing out our new Veris U3 on the Morrow Plots, the oldest continually used experimental agricultural fields in the United States. The Veris U3 uses an electrical array to map deep into the soil rooting profile of a field. These maps will help us to characterize fields by providing us with information about the electroconductivity of the fields in our experiments. Check out the Veris website for more information about their technology!