Scaling Up Agricultural Research With Artificial Intelligence
| Autor: | Sarah E. McCord, Glenn E. Moglen, Lisa G. Neven, Debra P. C. Peters, Clement D.D. Sohoulande, Brandon T. Bestelmeyer, Tewodros Wakie, Steven B. Mirsky, Guillermo S. Marcillo |
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| Rok vydání: | 2020 |
| Předmět: |
Warning system
business.industry Big data 02 engineering and technology Computer Science Applications Data modeling Hardware and Architecture Agriculture 020204 information systems 0202 electrical engineering electronic engineering information engineering Leverage (statistics) Artificial intelligence business Software Management practices |
| Zdroj: | IT Professional. 22:33-38 |
| ISSN: | 1941-045X 1520-9202 |
| Popis: | Agricultural systems are enormously variable in space and time. New and developing artificial intelligence (AI)-based tools can leverage site-based science and big data to help farmers and land managers make site-specific decisions. These tools are improving information about soils and vegetation that forms the basis for investments in management actions, provides early warning of pest and disease outbreaks, and facilitates the selection of sustainable cropland management practices. Continued progress with AI will require more observational data across a wide range of agricultural settings, over long time periods. |
| Databáze: | OpenAIRE |
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