Improving data management and decision support systems in agriculture / edited by Leisa Armstrong.

Format:

Book

Contributor:

Armstrong, Leisa, editor.

Series:

Burleigh Dodds series in agricultural science ; Number 85.

Burleigh Dodds series in agricultural science ; Number 85

Language:

English

Subjects (All):

Agriculture--Decision making.

Agriculture.

Physical Description:

1 online resource (341 pages).

Edition:

1st ed.

Place of Publication:

Cambridge, England ; Philadelphia, Pennsylvania : Burleigh Dodds Science Publishing, [2020]

Summary:

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 DSS in areas such as crop planting and nutrition, livestock feed and pasture management as well as supply chains.

Contents:

Intro

Improving data management and decision support systems in agriculture

Contents

Series list

Introduction

Part 1 General issues

Chapter 1 Improving data access for more effective decision making in agriculture

1 Introduction

2 Key issues in current availability of data

3 Use of data for decision making: case studies

4 Current trends

5 Conclusions

6 Where to look for further information

7 References

Chapter 2 Improving data standards and integration for more effective decision-making in agriculture

2 Business process modelling to identify data requirements

3 Data flows for a particular process: the example of variable rate fertilization

4 Linking platforms and software

5 Creating a reference architecture for interoperability, replicability and reuse

6 Key elements in data management

7 Conclusions

8 Where to look for further information

9 References

Chapter 3 Improving data identification and tagging for more effective decision making in agriculture

2 Structuring the data

3 Case study: plant phenotyping

4 Conclusion and future trends

5 Where to look for further information

6 Acknowledgements

Chapter 4 Advances in data security for more effective decision-making in agriculture

2 Security challenges in PA systems

3 System architecture and legal recourse

4 Security framework considerations for PA systems

5 Modern cyberattack methods

6 Classifying cyberattack source psychology

7 Cybersecurity frameworks for PA

8 Case study: PA system assessment

9 Future trends

10 Conclusion

11 Where to look for further information

12 References

13 Appendix

Chapter 5 Advances in artificial intelligence (AI) for more effective decision making in agriculture.

1 Introduction

2 Agricultural DSS using AI technologies: an overview

3 Data and image acquisition

4 Core AI technologies

5 Case study 1: AgData DSS tool for western Australian broad acre cropping

6 Case study 2: GeoSense

7 Case study 3: Rice-based DSS

8 Summary and future trends

9 Where to look for information

10 References

Chapter 6 Improving data management and decision-making in precision agriculture

2 Remote sensing technologies

3 Geographic information system (GIS) technologies

4 Sensors and sensor networks

5 Statistical and crop simulation models

6 Identifying variability in crop production systems

7 Summary and future trends

Part 2 Case studies

Chapter 7 Decision support systems (DSS) for better fertiliser management

2 Direct methods for determining crop nitrogen requirements for decision support

3 Indirect methods for determining crop nitrogen requirements for decision support: simulation models

4 Indirect methods for determining crop nitrogen requirements for decision support: yield forecasts using data-driven approaches

5 Indirect methods for determining crop nitrogen requirements for decision support: yield forecasts based on water supply

6 Decision support in action: case studies

7 Case study 1: nitrogen fertiliser applications using a data-driven approach

8 Case study 2: nitrogen fertiliser decision-making based on soil moisture predictions

9 Comparing the two approaches

10 Conclusion and future trends

11 References

Chapter 8 Developing decision-support systems for crop rotations

2 Key information challenges

3 Ecological theory

4 Agronomic models

5 Encoding farmer decisions

6 Design principles

7 Outlook.

8 Where to look for further information

Chapter 9 Decision-support systems for pest monitoring and management

2 Pest identification

3 Pest monitoring

4 Pest forecasting

5 Integrated pest management (IPM)

6 Case studies

Chapter 10 Developing decision support systems for improving data management in agricultural supply chains

2 Decisions in supporting data management

3 Decision tools

4 Principal case studies

5 Conclusion and future trends

6 References

Chapter 11 Developing decision support systems for optimizing livestock diets in farms

2 Mathematical programming models for livestock production: a review

3 Linear programming (LP) models to minimize feed costs: solutions and sensitivity analysis

4 Goal programming (GP) models: balancing costs and environmental impact

5 Decision support systems and data management for sustainable diets

6 Case study 1: sustainable rations for intensive broiler production

7 Case study 2: reducing emissions in pig production

8 Summary and future trends in research

9 Acknowledgements

10 Where to look for further information

Chapter 12 Developing decision-support systems for pasture and rangeland management

2 Decision-support systems (DSSs) in pasture and rangeland management

3 Decision-making processes of pasture and rangeland farmers

4 Development of effective decision-support tools

5 Case studies of decision-support system (DSS) development in pasture and rangeland management

6 Conclusion and future trends

7 Where to look for further information

8 References

Index.

Notes:

Includes bibliographical references and index.

Description based on print version record.

Description based on publisher supplied metadata and other sources.

ISBN:

1-78676-342-7

OCLC:

1153694236