{"id":27603,"date":"2023-06-21T21:24:43","date_gmt":"2023-06-21T21:24:43","guid":{"rendered":"https:\/\/aes.colostate.edu\/divi-wcrc\/?page_id=27603"},"modified":"2024-05-08T18:43:23","modified_gmt":"2024-05-08T18:43:23","slug":"ai-sustainable-management","status":"publish","type":"page","link":"https:\/\/aes.colostate.edu\/wcrc\/grand-valley\/irrigation-and-water-resources\/ai-sustainable-management\/","title":{"rendered":"Equipment to Support Artificial Intelligence for Sustainable Water, Nutrient, Salinity, and Pest Management in the Western US"},"content":{"rendered":"

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Equipment to Support Artificial Intelligence for Sustainable Water, Nutrient, Salinity, and Pest Management in the Western US<\/h1>\n

Project Overview<\/h2>\n

US agriculture faces rapidly increasing pressure from changing climate, competition for resources, and uncertain global markets that threaten rural prosperity due to reduced profits, harsher growing conditions, and environmental degradation. The guiding principle of this project is that leveraging advances in AI, DA, big geodata analytics and other supercomputing technology, can contribute to a redesign of US agriculture into systems that place resource optimization and sustainability as top priority goals.\u00a0 The larger project into which this effort is embedded can be reviewed at the NIFA USDA projects website.<\/a><\/p>\n

Read an article from Progressive Crop Consultant website about AI\u00a0<\/a><\/p>\n

[\/et_pb_text][et_pb_button button_url=”https:\/\/coloradosun.com\/2023\/08\/21\/colorado-researcher-tool-farmers-artificial-intelligence\/” url_new_window=”on” button_text=”Learn more from the Colorado Sun” _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_button][et_pb_button button_url=”https:\/\/progressivecrop.com\/2021\/07\/08\/can-artificial-intelligence-enhance-the-profit-and-environmental-sustainability-of-agriculture\/” url_new_window=”on” button_text=”Learn more from Progressive Crop Consultant about AI ” _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.20.0″ _module_preset=”default” header_font_size=”36px” header_line_height=”1.4em” header_2_font_size=”26.1px” global_colors_info=”{}”]<\/p>\n

Scope and Rationale<\/h3>\n

Within Colorado, the interface of agriculture and water resources is a critical area in which to apply this same principle. Foundational knowledge on remote sensing data to model and monitor agricultural processes is at the stage where local to regional scale applied research is needed to translate basic science into actionable strategies and tools. Previous research has often emphasized single or a few agricultural system components: water management, soil mapping, crop phenotyping, crop water requirement estimation, nutrient management, pest detection and monitoring.<\/p>\n

Despite significant advances, focused projects often:<\/p>\n

    \n
  • have narrow scope (e.g., estimate idealized crop water requirements for non-stressed crops)<\/li>\n
  • do not integrate stress indicators<\/li>\n
  • fail to take full advantage of integrated big geodata, AI, and data assimilation<\/li>\n
  • do not connect with industry partners to ensure full translation of academic research into actionable tools for growers.<\/li>\n<\/ul>\n

    The project’s rationale and its anticipated significance derive from an interdisciplinary integration of available knowledge and tools under a single AI framework for system-wide sustainable agricultural and natural resource management. The objectives of the larger research project described here do require the installation of new irrigation infrastructure at the WCRC-GV. Typical project milestones for a construction project at a CSU facility would included an immediate initiation of a competitive bid process, selection of the awarded contractor and beginning of construction. Construction of the sprinkler system is not expected to be unique, such that the progress of installation will proceed under a typical timeline, which would begin with basic earthwork, bringing 3-phase power, filtration\/control system installation and span\/tower assembly.<\/p>\n

    \n

    From the Colorado Water Plan: \u201cBenefits of agricultural conservation and efficiency can include increased crop\/production, reduced vulnerability to drought, enhanced flows for the environment and\/recreation, and improved water quality. In many cases, better irrigation efficiency results\/in water application that is more in sync with plant demands (both in timing and amount),\/which results in fully utilizing and consuming the available supply.\u201d<\/p>\n

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    Project Location<\/h2>\n

    Western Colorado Research Center at Grand Valley<\/h3>\n

     <\/p>\n

    Collaborators<\/h2>\n
      \n
    • Raj Khosla, Professor, Department of Agronomy, Kansas State University<\/li>\n
    • Eugene Kelly, Professor of Pedology, Deputy Director CSU Agricultural Experiment Station<\/li>\n
    • Perry E. Cabot, Extension Professor, Colorado Water Center, CSU Extension, CSU AES<\/li>\n
    • Khaled M. Bali, Irrigation Water Management Specialist, University of California<\/li>\n
    • Elia Scudiero, Associate Researcher, Environmental Sciences, UC-Riverside<\/li>\n
    • Michael Cahn, Irrigation and Water Resources Advisor, UC-Davis<\/li>\n
    • Charles Anthony Sanchez, Professor, University of Arizona<\/li>\n
    • Karletta Chief, Professor, University of Arizona<\/li>\n
    • Dipankar Mandal, Postdoctoral Fellow, Department of Agronomy, Kansas State University<\/li>\n<\/ul>\n

      [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.20.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n

      Funding<\/h2>\n

      $240,923<\/h3>\n

      This project is supported with funding from the Colorado River District and the USDA Agriculture and Food Research Initiative.<\/p>\n

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      \n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/div>\n\t\tEquipment to Support Artificial Intelligence for Sustainable Water, Nutrient, Salinity, and Pest Management in the Western US Project Overview US agriculture faces rapidly increasing pressure from changing climate, competition for resources, and uncertain global markets that threaten rural prosperity due to reduced profits, harsher growing conditions, and environmental degradation. The guiding principle of this project […]<\/p>\n","protected":false},"author":260,"featured_media":0,"parent":25229,"menu_order":8,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":"","_members_access_role":[],"_members_access_error":""},"class_list":["post-27603","page","type-page","status-publish","hentry"],"yoast_head":"\nArtificial Intelligence for Sustainable Agriculture - Grand Valley<\/title>\n<meta name=\"description\" content=\"Advances in AI are contributing to a redesign in US agriculture to create resource optimization and sustainability through a series of systems.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/aes.colostate.edu\/wcrc\/grand-valley\/irrigation-and-water-resources\/ai-sustainable-management\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Artificial Intelligence for Sustainable Agriculture - 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