B013
Agriculture in the 21st Century: Leveraging Technological Advances to Provide Insights and Promote Sustainability
Session ID#: 83261
Session Description:
The practice of farming has changed dramatically in recent years. Fueled by remotely sensed data, sensors, new data streams from equipment and decreasing costs, big data is transforming the modern farm. Huge volumes of data are being processed to provide real-time insights to farmers and help improve decision making, both for farmers and machinery. As these technological advances are combined with modern analyses and algorithms, the modern farm is becoming more data-driven and increasingly automated. Additional insights into the environmental impact, sustainability and waste of agriculture operations can help farmers manage their operations, increase revenue and conserve their lands for succeeding generations. This session focuses on the emerging tools, techniques and advancements being applied globally to ensure agriculture remains sustainable and profitable while growing to meet the demands of an increasing human population.
Index Terms:
0402 Agricultural systems [BIOGEOSCIENCES]
0480 Remote sensing [BIOGEOSCIENCES]
1926 Geospatial [INFORMATICS]
1942 Machine learning [INFORMATICS]
Primary Convener: Matthew Hayes, Granular, Data Science, Des Moines, IA, United States
Conveners: Dane Kane, Yale, Yale School of Forestry & Environmental Studies, New Have, United States, Kaiyu Guan, University of Illinois at Urbana Champaign, National Center for Supercomputing Applications, Urbana, IL, United States; Stanford University, Stanford, CA, United States and Anuradha Swatantran, Corteva, Des Moines, United States
Primary Liaison: Matthew Hayes, Granular, Data Science, Des Moines, IA, United States
Aligning research, policy, and practice for the Sustainable Development Goals in European agriculture (491810)
Kimberly A Nicholas1, Murray Scown2 and Klara J Winkler2, (1)Lund University, Lund University Centre for Sustainability Studies, Lund, Sweden, (2)Lund University Centre for Sustainability Studies, Lund, Sweden
Implication of lowering fertilizer usage on energy, agriculture, and land systems (502731)
Eva Sinha1, Katherine V Calvin1, Page Kyle1, Mohamad Issa Hejazi2, Stephanie Waldhoff3 and Maoyi Huang4, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Joint Global Change Research Institute, College Park, MD, United States, (3)Pacific Northwest National Laboratory, College Park, MD, United States, (4)Pacific NW Nat'l Lab-Atmos Sci, Richland, WA, United States
Precision agriculture using Planet satellites: capturing daily water use and crop behavior over a growing season (577952)
Matthew F McCabe1, Rasmus Houborg2, Bruno Aragon1, Joshua Fisher3 and Trenton Franz4, (1)King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, (2)Planet Labs, San Francisco, United States, (3)Jet Propulsion Laboratory, Pasadena, CA, United States, (4)University of Nebraska Lincoln, Lincoln, NE, United States
Using Spectral, Photosynthetic, Gas Exchange and Visually-Scored Data to Identify Ozone Stress in Soybean Crops (583524)
Nichole Gosselin1, Vasit Sagan2, Matthew Maimaitiyiming3, Jack Fishman3, Kelley Belina4, Ann Podleski5, Jayashree Balakrishna5 and Anbreen Bashir6, (1)Saint Louis University, Saint Charles, MO, United States, (2)Saint Louis University, Earth and Atmospheric Sciences, St. Louis, MO, United States, (3)Saint Louis Univ-O'Neil Hall, St Louis, MO, United States, (4)Saint Louis University, Saint Louis, United States, (5)Harris-Stowe State University, St. Louis, MO, United States, (6)Harris-Stowe State University, Saint Louis, United States
Ensuring Co-Sustainability of Food Production and Environmental Quality in the U.S. Midwest Agroecosystems (Invited) (588231)
Kaiyu Guan1, Bin Peng1, Ming Pan2, Zhenong Jin3, Jinyun Tang4 and Chongya Jiang5, (1)University of Illinois at Urbana Champaign, National Center for Supercomputing Applications, Urbana, IL, United States, (2)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (3)University of Minnesota-Twin Cities, Department of Bioproducts and Biosystems Engineering, Saint Paul, MN, United States, (4)Lawrence Berkeley Natl Lab, Berkeley, CA, United States, (5)State Key laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China
Initial results and perspectives from the AR1K Project Consortium: machine learning for sustainable agriculture (603242)
Karl Bernard Schaettle1, Nicola Falco2, Craig Ulrich3, Baptiste Dafflon2, Haruko Murakami Wainwright2 and James Bentley Brown4, (1)University of California Berkeley, Departments of Chemistry, Bioengineering, Chemical and Biomolecular Engineering, Berkeley, CA, United States, (2)Lawrence Berkeley National Laboratory, Earth and Environmental Sciences, Berkeley, CA, United States, (3)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (4)Lawrence Berkeley National Laboratory, Environmental Genomics and Systems Biology, Berkeley, CA, United States
Quick Carbon: A Rapid, Landscape-Scale Soil Carbon Assessment Tool (626476)
Daniel Kane, Yale University, School of Forestry & Environmental Studies, New Haven, CT, United States, Emily Oldfield, Yale, New Haven, United States and Mark Bradford, Yale University, New Haven, CT, United States
