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Full-Text Articles in Life Sciences
Robust Spatial Frameworks For Leveraging Research On Sustainable Crop Intensification, Patricio Grassini, Cameron M. Pittelkow, Kenneth Cassman, Haishun S. Yang, Sotirios Archontoulis, Mark Licht, Kendall R. Lamkey, Ignacio A. Ciampitti, Jeffrey A. Coulter, Sylvie M. Brouder, Jeffrey J. Volenec, Noemi Guindin-Garcia
Robust Spatial Frameworks For Leveraging Research On Sustainable Crop Intensification, Patricio Grassini, Cameron M. Pittelkow, Kenneth Cassman, Haishun S. Yang, Sotirios Archontoulis, Mark Licht, Kendall R. Lamkey, Ignacio A. Ciampitti, Jeffrey A. Coulter, Sylvie M. Brouder, Jeffrey J. Volenec, Noemi Guindin-Garcia
Department of Agronomy and Horticulture: Faculty Publications
Meeting demand for food, fiber, feed, and fuel in a world with 9.7 billion people by 2050 without negative environmental impact is the greatest scientific challenge facing humanity. We hypothesize that this challenge can only be met with current and emerging technologies if guided by proactive use of a broad array of relevant data and geospatial scaling approaches to ensure local to global relevance for setting research priorities and implementing agricultural systems responsive to real-time status of weather, soils, crops, and markets. Despite increasing availability of field-scale agricultural data, robust spatial frameworks are lacking to convert these data into actionable …
Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong
Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong
Research outputs 2014 to 2021
The capacity of farmers and agricultural scientists to be able to make in-season decisions is dependent on accurate climate, soil and plant data. This paper will provide a review of the types of environmental and crop data that can be collected by sensors which can used for decision support systems (DSS) or be further interrogated for real time data mining and analysis. This paper also presents a review of the data requirements for agricultural decision making by firstly reviewing decision support frameworks and agricultural DSSs, data acquisition, sensors for data acquisition and examples of data incorporation for agricultural DSSs.