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.
- Reviews key steps in improving data management, from improving data access and establishing standards for reliable data to effective tagging for discoverability as well as data security
- Covers a wide range of practical applications of decision support systems (DSS) in crop production, such as crop planting, nutrition and use of rotations
- Includes the use of DSS in key areas of livestock production such as feed optimization and pasture management
Table of contents
Part 1 General issues
1.Improving data access for more effective decision making in agriculture: André Lapperrière, 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, The Netherlands;
3.Improving data identification/tagging for more effective decision making in agriculture: Pascal Neveu, Montpellier SupAgro/INRA, France;
4.Advances in data security for more effective decision making in agriculture: Jason West, University of Queensland, Australia; 5.Advances in Artificial Intelligence (AI) for more effective decision making in agriculture: Leisa Armstrong, Edith Cowan University, Australia;
6.Improvements in precision agriculture/geospatial technologies/autonomous vehicles/real-time data for more effective decision making in agriculture: J. Adinarayana, IIT Bombay, India;
Part 2 Case studies
7.Developing decision support systems for applying crop fertiliser: Thomas Bishop, University of Sydney, Australia;
8.Developing decision support systems for crop rotations/cover cropping: Zia Mehrabi, University of British Columbia, Canada;
9.Decision support systems for pest monitoring and management: B. Sailaja, ICAR-IIR, India;
10.Developing decision support systems for agricultural supply chains: Gerhard Schiefer, University of Bonn, Germany;
11.Developing decision support systems for livestock management: Concepción Maroto, Universitat Politècnica de València, Spain;
12.Developing decision support systems for pasture and rangeland management: Callum Eastwood, DairyNZ, New Zealand;