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Instant Insights: Decision support systems in agriculture

Code: 9781801462112
Publication Date: 14/09/2021

Contributions by: Matt Aitkenhead, The James Hutton Institute, UK; 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; Oliver Körner, Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Germany; Nicolas Tremblay, Agriculture and Agri-Food Canada, Canada; Clyde W. Fraisse, University of Florida-Gainesville, USA; Norman E. Breuer, Catholic University Nuestra Señora de la Asunción, Paraguay; and Victor Cabrera, University of Wisconsin-Madison, USA

Description

This collection features five peer-reviewed literature reviews on decision support systems (DSS) in agriculture.

The first chapter provides a review of DSS in agriculture, whilst addressing the key questions surrounding their use for farm soil and crop management. The different aspects of agricultural DSS design, implementation and operation are also discussed.

The second chapter assesses the role of DSS for pest monitoring and management through information technology such as, remote sensing, GIS, spectral indices, image-based diagnostics, and phenology-based degree day models.

The third chapter discusses the potential of implementing DSS within the growing mechanisation in greenhouses. It examines differences in development and application of deterministic explanatory and data-based models for real-time control and DSS.

The fourth chapter explores the key issues associated with deploying DSS in precision agriculture, whilst also considering their human and social aspects. The chapter also considers how future research on DSS can be moulded to improve productivity in a precision agriculture setting.

The final chapter outlines the importance of a participatory approach in DSS development, whilst also offering examples of climate-based DSS for crop and land management, pest and disease management, and livestock (dairy) management.

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Table of Contents

Chapter 1 - Developing decision support systems (DSS) for farm soil and crop management: Matt Aitkenhead, The James Hutton Institute, UK; 1 Introduction 2 Spatial data and sensor requirements for DSS 3 Models and software for DSS 4 DSS user interface design, actuators and systems 5 Decision support or decision-making? 6 What reasons are there for low uptake of DSS? 7 What will DSSs of the future look like? 8 Summary 9 Where to look for further information 10 References
Chapter 2 - 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; 1 Introduction 2 Pest identification 3 Pest monitoring 4 Pest forecasting 5 Integrated pest management (IPM) 6 Case studies 7 Summary and future trends 8 Where to look for further information 9 References
Chapter 3 - Models, sensors and decision support systems in greenhouse cultivation: Oliver Körner, Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Germany; 1 Introduction 2 Greenhouses as controllable units for decision making 3 The decision-making process 4 Growers’ decision tools 5 Models for decision support 6 Case studies 7 Future trends and conclusion 8 Where to look for further information 9 References
Chapter 4 - Modelling and decision support systems in precision agriculture: Nicolas Tremblay, Agriculture and Agri-Food Canada, Canada; 1 Introduction 2 Key issues 3 Human and social aspects 4 Case studies with an emphasis on nitrogen management 5 Research options for decision support systems to improve productivity in a precision agriculture framework 6 Conclusion 7 Future trends 8 Where to look for further information 9 References
Chapter 5 - Developing climate-based decision support systems from agricultural systems models: Clyde W. Fraisse, University of Florida-Gainesville, USA; Norman E. Breuer, Catholic University Nuestra Señora de la Asunción, Paraguay; and Victor Cabrera, University of Wisconsin-Madison, USA; 1 Introduction 2 Importance of a participatory approach in DSS development 3 Examples of climate-based DSSs for crop and land management 4 Examples of climate-based DSSs for pest and disease management 5 Examples of climate-based DSSs for livestock (dairy) management 6 Lessons learned on the development of climate-based DSSs 7 Future trends and conclusion 8 Where to look for further information 9 References

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