About the Book
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.
Table of Contents:
Part 1 General issues
1.Improving data access for more effective decision making in agriculture: Ben Schaap, Wageningen University and Research, The Netherlands and Global Open Data for Agriculture and Nutrition (GODAN), UK; and Suchith Anand and André Laperrière, Global Open Data for Agriculture and Nutrition (GODAN), UK
2.Improving data standards and integration for more effective decision-making in agriculture: Sjaak Wolfert, Wageningen University and Research, The Netherlands
3.Improving data identification and tagging for more effective decision making in agriculture: Pascal Neveu and Romain David, MISTEA, INRAE, Montpellier SupAgro, University of Montpellier, France; and Clement Jonquet, LIRMM, CNRS and University of Montpellier, France
4.Advances in data security for more effective decision-making in agriculture: Jason West, University of New England, Australia; 5.Advances in artificial intelligence (AI) for more effective decision making in agriculture: L. J. Armstrong, Edith Cowan University, Australia; N. Gandhi, University of Mumbai, India; P. Taechatanasat, Edith Cowan University, Australia; and D. A. Diepeveen, Department of Primary Industries and Regional Development, Australia
6.Improving data management and decision-making in precision agriculture: Soumyashree Kar, Rohit Nandan, Rahul Raj, Saurabh Suradhaniwar and J. Adinarayana, Indian Institute of Technology Bombay (IIT Bombay), India
Part 2 Case studies
7.Decision support systems (DSS) for better fertiliser management: Dhahi Al-Shammari, Patrick Filippi, James P. Moloney, Niranjan S. Wimalathunge, Brett M. Whelan and Thomas F. A. Bishop, The University of Sydney, Australia
8.Developing decision-support systems for crop rotations: Zia Mehrabi, University of British Columbia, Canada
9.Decision-support systems for pest monitoring and management: B. Sailaja, Ch. Padmavathi, D. Krishnaveni, G. Katti, D. Subrahmanyam, M. S. Prasad, S. Gayatri and S. R. Voleti, ICAR-Indian Institute of Rice Research, India
10.Developing decision support systems for improving data management in agricultural supply chains: Gerhard Schiefer, University of Bonn, Germany
11.Developing decision support systems for optimizing livestock diets in farms: Marina Segura, Concepción Maroto, Baldomero Segura and Concepción Ginestar, Universitat Politècnica de València, Spain
12.Developing decision-support systems for pasture and rangeland management: Callum Eastwood and Brian Dela Rue, DairyNZ, New Zealand
About the Author :
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.
