Precision Agriculture: Modelling

Davide Cammarano is a Professor of Environmental Crop Science at Aarhus University, Denmark. His main aim is translating digital information into agronomic practices by maximizing the tradeoffs between economic and environmental impacts. One focus of his research is how to optimize the use of crop-soil-atmosphere models with observed data to support and improve the farmers’ decision-making. His other scientific interests are precision agriculture, crop modelling, agronomy, climate change, crop and soil sciences, remote sensing, and climate forecasts in agriculture.Frits van Evert is a senior researcher in precision agriculture at Wageningen University & Research. His main research interest is increasing crop yield, crop quality, and the profitability of farming while reducing the use of inputs and the impact of agriculture on the environment. He believes this can be achieved by supporting farmers with information that is based on crop and soil models combined with observational data from satellites, drones, and sensors on the ground. Additional research interests include agricultural robotics, data management, and measuring the sustainability of agricultural systems.Corné Kempenaar is senior researcher in precision agriculture at Wageningen University & Research, and associate professor Precision Agriculture at Aeres University of Applied Sciences . He has a background in crop protection and weed management science. He coordinates public–private research projects on precision agriculture applications, and is also involved with an adoption stimulation project for precision agriculture in The Netherlands. A general theme in his studies is the linking of data to decision support systems for the implementation and development of precision agriculture, with specialization in arable farming.

• Chapter 1 Introduction.- PART 1: MODELLING.- Chapter 2 Statistical Modelling.- Chapter 3 Geostatistics.- Chapter 4 Crop and Soil Modelling.- Chapter 5 Pest and Disease Modelling.- Chapter 6 Adoption of Model-Based Practices in Precision Agriculture.- PART 2: ACADEMIC/STATE-OF-THE-ART.- Chapter 7 Water.- Chapter 8 Nitrogen.- Chapter 9 Pest Diseases.- Chapter 10 Data Assimilation/Fusion.- PART 3: CASE STUDIES.- Chapter 11 Potato Company McCain.-Chapter 12 Soil Essentials.- Chapter 13 Adapt-N.- Chapter 14 Granular.- Chapter 15 BASF /XARVIO.- Chapter 16 Watch It Grow Belgium.- Chapter 17 Akkerweb.- Chapter 18 Kubota.- Chapter 19 India TATA Consultancy.- Chapter 20 DACOM.- PART 4: SUMMARY AND OUTLOOK.- Chapter 21 Summary.- Chapter 22 Outlook.