Gebundenes Buch

Plant Model Greenlab for Botany and Agronomy

Beschreibung

This book provides a general presentation of knowledge and methods in mathematical modelling and simulation of individual plants. The chapters mainly describe the algorithms of mathematical modelling, simulation and computer visualization and prospective aspects related to future developments of plant models. The book highlights the concepts coming from different disciplines and their mathematical integration to build robust, calibrated, and realistic integrative modeling solutions. Its original and groundbreaking focus is on the integration of structural and functional modeling for a living system such as a whole plant (or a crop field, a forest): most of the time, it has been believed among modeling practitioners that choices have to be made between the two, this belief no more prevails in the era of integrative (well-conceptually grounded) simulations. The content of this book is sufficient for a non-specialist to understand the fundamentals of mathematical modelling of plant architecture. Readers or even software developers can supplement their knowledge by consulting the book.

Autor

Prof. Philippe de Reffye, Senior Professor, he has always focused on the scientific researches of plant growth modelling for the past 40 years, and published more than two hundred research articles. He has rich research experiences in interdisciplinary subject, including Botany, Ecology, Agronomy, Applied Mathematics and Computer Sciences. In the field of Computer Graphics, he is one of the pioneering researchers in plant morphologic modeling and published a paper in Siggraph 1988. He created the research team of AMAP in 1995. In the field of plant modelling, he developed a new method of plant modeling named "GreenLab (Functional-Structural Plant Model)" in cooperation with CASIA and CAU, based on the theory of AMAP modeling. He got the  gold medal of French Agriculture Academy in 2016 for his research work on plant modelling. Dr. Mengzhen Kang is an Associate Professor with State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences (CASIA), a former student of Philippe de Reffye. Her current research interests include parallel agriculture and computational plant sciences. She has published over 100 scientific papers in her research field. She received the Ph.D. degree in pattern recognition and intelligent systems from CASIA in 2003. From 2005-2006, she was a Postdoctoral Fellow with DigiPlante, INRIA in France and Plant Sciences, Wageningen University in Netherland. She organized the international conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Application (PMA'12 and FSPMA2016) as the General Co-Chair from China. Dr. Marc Jaeger, from AMAP joint research unit(CIRAD) is a computer scientist research director (IEEE member) interested in natural phenomena and imaging. He specializes on plant growth simulation, visualisation from organ to landscape scale (PhD 1988 under P. de Reffye supervision). He is involved the GreenLab project, and joined LIAMA in China from 2001 to 2006 and also developed later Greenlab online teaching resources. He is currently deputy director Amap unit, after being in charge of its Digital Plant research line. Prof. Zhang Bao Gui obtained his bachelor degree in agronomy in 1985 and study ecophysiology in university of Paris XI, France where he got Ph. D of life science in plant ecology. Since 1993, he worked as associate professor, professor in China Agricultural University, College of Resources and Environmental Science, and since 2019, College of Land Science and Technology. His research works covered plant-soil system modelling, soil biological processes and sustainable agriculture.

Produktdetails

• Verlag: Editions QUAE / Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-97-7540-8
• Seitenzahl: 800
• Erscheinungstermin: 15. Mai 2025
• Englisch
• Abmessung: 241mm x 160mm x 46mm
• Gewicht: 1438g
• ISBN-13: 9789819775408
• ISBN-10: 981977540X
• Artikelnr.: 71294830