Improving data management and decision support systems in agriculture

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. It also reviews developments in artificial intelligence (AI) such as the use of data mining and artificial neural networks. Part 2 contains case studies of the practical application of data management and DSS in areas such as crop nutrition, use of rotations, pest monitoring and management, 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. Dr Leisa Armstrong is Senior Lecturer in Computer Science and Leader of the eAgriculture Research Group at Edith Cowan University, Australia. Dr Armstrong is President of the Australian Society of ICT in Agriculture as well as past President of the Asian Federation of Information Technologies in Agriculture (AFITA). She has an international reputation for her research on the use of ICT in agriculture in such areas as agricultural information and decision support systems.