Advances in plant phenotyping for more sustainable crop production

Half Title Page
Series Page
Title Page
Contents
Series list
Introduction
Acknowledgement
Part 1 The development of phenotypingas a research field
Chapter 1 Origins and drivers of crop phenotyping
1 Introduction
2 Technological progress in plant phenotyping
3 Community integration in plant phenotyping
4 Plant phenotyping as a tool for enhanced and sustainable crop production
5 Future trends
6 Where to look for further information
7 Acknowledgements
8 References
Chapter 2 The evolution of trait selection in breeding: from seeing to remote sensing
1 Introduction
2 Selection of progeny and large-scale genetic resources
3 Characterization of parents and gene discovery panels: increasing throughput with sensors
4 Traits related to spike fertility and partitioning to yield
5 Traits to improve lodging resistance in cereals
6 Selecting for disease resistance
7 How might trait selection look in the future
8 Where to look for further information
9 References
Part 2 Sensor types
Chapter 3 Advances in optical analysis for crop phenotyping
1 Introduction
2 Popular optical sensors
3 Major challenges in optical sensing
4 Case studies
5 Summary and future trends
6 Where to look for further information
7 References
Chapter 4 Advances in the use of thermography in crop phenotyping
1 Introduction
2 Foundational theory of thermography
3 Principles of thermography measurement
4 Technologies available and thermography methods
5 Traits measured
6 Case studies
7 Main challenges
8 Summary and future trends
9 Where to look for further information
10 References
Chapter 5 Advances in the use of X-ray computed tomography in crop phenotyping
1 Introduction
2 X-ray sources
3 Interaction of X-rays with material
4 Detector
5 Computed tomography systems for crop phenotyping
6 From sensor to data
7 Case studies: Phenotyping using computed tomography
8 Summary and future trends
9 Where to look for further information
10 References
Part 3 Carrier/delivery systems
Chapter 6 Field robots for plant phenotyping
1 Introduction
2 Specific challenges associated with field robots
3 Currently available field robots for phenotyping
4 Sensors and technologies for phenotyping field robots
5 Robotic arms for fruit phenotyping and harvesting
6 Conclusion and future trends
7 Where to look for further information
8 References
Chapter 7 Advances in high-throughput crop phenotyping using unmanned aerial vehicles (UAVs)
1 Introduction
2 Remote sensing tools: unmanned aerial vehicles and flight protocols
3 Major plant traits that can be extracted using unmanned aerial vehicle remote sensing
4 Conclusion and future trends
5 Authors’ contributions
6 Acknowledgements
7 References
Part 4 Data analysis
Chapter 8 Meeting computer vision and machine learning challenges in crop phenotyping
1 Introduction
2 Key dimensions to consider in computer vision applications in plant phenotyping
3 Creating synergies between research communities: the Computer Vision Problems in Plant Phenotyping (CVPPP) Workshop
4 Data challenges to accelerate progress in computer vision techniques: leaf counting and segmentation
5 Recent agriculture-related computer vision challenges
6 Summary
7 Where to look for further information
8 References
Chapter 9 Digital phenotyping and genotype-to-phenotype (G2P) models to predict complex traits in cereal crops
1 Introduction
2 Digital phenotyping as a tool to support breeding programs
3 Genotype-to-phenotyping (G2P) models: integrating data from phenomics and envirotyping in predictive breeding
4 Conclusion
5 Acknowledgements
6 Where to look for further information
7 Abbreviations
8 References
Chapter 10 The role of crop growth models in crop improvement: integrating phenomics, envirotyping and genomic prediction
1 Introduction
2 Crop growth models to understand gene × environment × management interactions
3 The role of crop simulation modelling in envirotyping
4 The role of crop models in defining phenotyping methods and targets
5 Crop models of the future: how can they gain from the current developments in phenotyping?
6 Integrating statistical genetic models and crop growth models (SGM–CGM)
7 Where to look for further information
8 References
Part 5 Case studies
Chapter 11 Using phenotyping techniques to analyse crop functionality and photosynthesis
1 Introduction
2 Understanding photosynthesis and its relationship to crop growth and stress response
3 Phenotyping photosynthesis in varying environmental conditions
4 Using gas exchange to analyse photosynthesis
5 Using porometry and thermal imaging of gs and hyperspectral techniques
6 Using chlorophyll fluorescence
7 Photosynthesis and climate change: accounting for heat stress, drought stress and elevated CO2
8 Case studies
9 Conclusions
10 Where to look for further information
11 References
Chapter 12 Using phenotyping techniques to predict and model grain yield: translating phenotyping into genetic gain
1 Introduction
2 Boosting genetic gain in grain yield by focusing on phenomics
3 Stomatal conductance
4 Functional stay green
5 Case study
6 Conclusion and future trends
7 Where to look for further information
8 References
Chapter 13 Automated assessment of plant diseases and traits by sensors: how can digital technologies support smart farming and plant breeding?
1 Introduction
2 Digital plant disease detection
3 Complexity of host–pathogen interactions
4 Complexity in a crop stand
5 Case study: application of deep learning to foliar plant diseases
6 Summary
7 Future trends in research
8 Where to look for further information
9 Acknowledgements
10 References
Index
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