Instant Insights: Advances in Detecting and Forecasting Crop Pests and Diseases

Chapter 1 - Using machine learning to identify and diagnose crop diseases: Megan Long, John Innes Centre, UK; 1 Introduction 2 A quick introduction to deep learning 3 Preparation of data for deep learning experiments 4 Crop disease classification 5 Different visualisation techniques 6 Hyperspectral imaging for early disease detection 7 Case study: Identification and classification of diseases on wheat 8 Conclusion and future trends 9 Where to look for more information 10 References
Chapter 2 - Advances in crop disease forecasting models: Nathaniel Newlands, Summerland Research and Development Centre, Science and Technology Branch, Agriculture and Agri-Food Canada, Canada; 1 Introduction 2 Modeling complex, crop-disease-environment dynamics 3 Big data assimilation to improve forecast quality 4 Novel artificial intelligence (AI)-based methodologies 5 Case study: operational, crop disease early-warning systems 6 Conclusion and future trends 7 Where to look for further information 8 References
Chapter 3 - Advances in remote/aerial sensing technologies to assess crop health: Michael Schirmann, Leibniz Institute of Agricultural Engineering, Germany; 1 Introduction 2 Remote sensing of crop health 3 Remote sensing of crop diseases 4 Case study: detecting stripe rust using very high-resolution imaging 5 Conclusion and future trends 6 Where to look for further information 7 References
Chapter 4 - Precision crop protection systems: E. C. Oerke, University of Bonn, Germany; 1 Introduction 2 Variability of pest incidence and pest management strategies 3 Sensor use for disease management 4 Sensor use for the management of invertebrate pests 5 Perspectives 6 References
Chapter 5 - 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 6 - Advances in insect pest and disease monitoring and forecasting in horticulture: Irene Vänninen, Natural Resources Institute Finland (LUKE), Finland; 1 Introduction 2 Addressing key issues and challenges of pest monitoring and forecasting 3 Case study: whitefly sampling, monitoring and forecasting
4 Conclusion 5 Future trends in research 6 Where to look for further information 7 References