Improving data management and decision support systems in agriculture
Leisa Armstrong (Hrsg.)
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Naturwissenschaften, Medizin, Informatik, Technik / Technik
This collection reviews and summarises the wealth of research on key challenges in developing better data management and decision support systems (DSS) for farmers and examples of how those systems are being deployed to optimise efficiency in crop and livestock production.
Part 1 reviews general issues underpinning effective decision support systems (DSS) such as data access, standards, tagging and security. Part 2 contains case studies of the practical application of data management and DSS in areas such as crop planting, nutrition and use of rotations, livestock feed and pasture management as well as optimising supply chains for fresh produce.
With its distinguished editor and international team of authors, Improving data management and decision support systems in agriculture will be a standard reference for researchers in agriculture and computer science interested in improving data management, modelling and decision support systems in farming, as well as government and other agencies supporting the use of precision farming techniques, and companies supplying decision support services to the farming sector.
precision agriculture, artificial intelligence (AI), cybersecurity, decision support systems (DSS)