Instant Insights: Artificial Intelligence Applications in Agriculture

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.

Chapter 1 - 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; 1 Introduction2 Agricultural DSS using AI technologies: an overview3 Data and image acquisition4 Core AI technologies5 Case study 1: AgData DSS tool for Western Australian broad acrecropping6 Case study 2: GeoSense7 Case study 3: Rice-based DSS8 Summary and future trends9 Where to look for further information10 References
Chapter 2 - The use of intelligent/autonomous systems in crop irrigation: Stefano Carpin, University of California-Merced, USA; Ken Goldberg, University of California- Berkeley, USA; Stavros Vougioukas, University of California-Davis, USA; Ron Berenstein, University of California-Berkeley, USA; and Josh Viers, University of California-Merced, USA; 1 Introduction2 Related work3 Overview of RAPID4 Preliminary results5 Future trends and conclusion6 Acknowledgements7 Where to look for further information8 References
Chapter 3 - Advances in automated in-field grading of harvested crops: Jose Blasco, María Gyomar González González, Patricia Chueca and Sergio Cubero, Instituto Valenciano de Investigaciones Agrarias (IVIA), Spain; and Nuria Aleixos, Universitat Politècnica de València, Spain; 1 Introduction2 Advantages of in-field sorting3 Harvest-assist platforms4 Case study: in-field pre-sorting of citrus5 Summary6 Future trends in research7 Where to look for further information8 References
Chapter 4 - Automated assessment of plant diseases and traits by sensors: how can digital technologies support smart farming and plant breeding?: Anne-Katrin Mahlein, Institute of Sugar Beet Research, Germany; Jan Behmann, Bayer Crop Science, Germany; David Bohnenkamp, BASF Digital Farming GmbH, Germany; René H. J. Heim, UAV Research Centre (URC), Ghent University, Belgium; and Sebastian Streit and Stefan Paulus, Institute of Sugar Beet Research, Germany; 1 Introduction2 Digital plant disease detection3 Complexity of host–pathogen interactions4 Complexity in a crop stand5 Case study: application of deep learning to foliar plant diseases6 Summary7 Future trends in research8 Where to look for further information9 Acknowledgement10 References