Advances in crop modelling for a sustainable agriculture

This collection provides a comprehensive review of key advances in crop modelling, with a focus on developing the next generation of whole-farm models to improve decision making and support for farmers. Chapters review advances in modelling individual components of agricultural systems such as plant responses to environmental conditions, crop growth stages, nutrient and water cycles as well as pest/disease dynamics. The book also addresses the challenges of combining modular sub-systems into whole farm system models, including integration of rotations, intercropping and livestock. Chapters also review the performance of specific models such as APSIM and DSSAT and the challenges of developing decision support systems (DSS) from such models. The book also considers landscape models such as agroecological zone (AEZ) models and Coordinated Global and Regional Assessments (CGRA). The final part of the book reviews wider issues in improving model reliability such as data sharing and the supply of real-time data as well as crop model inter-comparison.

This collection provides a comprehensive review of key advances in crop modelling, with a focus on developing the next generation of whole-farm models to improve decision making and support for farmers. Chapters review advances in modelling individual components of agricultural systems such as plant responses to environmental conditions, crop growth stages, nutrient and water cycles as well as pest/disease dynamics. The book also addresses the challenges of combining modular sub-systems into whole farm system models, including integration of rotations, intercropping and livestock. Chapters also review the performance of specific models such as APSIM and DSSAT and the challenges of developing decision support systems (DSS) from such models. The book also considers landscape models such as agroecological zone (AEZ) models and Coordinated Global and Regional Assessments (CGRA). The final part of the book reviews wider issues in improving model reliability such as data sharing and the supply of real-time data as well as crop model inter-comparison.