The concept of using mathematical models to investigate crop growth and productivity has attracted much attention in recent years. A major reason is that modelling can allow an expert in one area to assess the impact of his ideas in the light of other advances in our understanding of crop performance. Whether or not many of the claims made for or the demands made of models can ever be satisfied, this role as a focus for quantitative definition of crop growth is an important one. One consequence is that the development and appraisal of such models requires the efforts of scientists from a wide range of disciplines. This NATO Advanced Research workshop was designed to bring together such a range of scientists to consider the wheat crop, and assess our understanding of the crop and our ability to model its growth and yield. The ideas and organization behind the workshop involved many people. The U. K. interest in a computer model of wheat growth was instigated by Dr. Joe Landsberg (then of Long Ashton Research Station, but now Director of CSIRO Division of Forest Research), who in 1979 started a modelling exercise as part of a collaborative study of the causes of yield variation in winter wheat, involving four research institutes supported by the Agricultural and Food Research Council. Dr.

The concept of using mathematical models to investigate crop growth and productivity has attracted much attention in recent years. A major reason is that modelling can allow an expert in one area to assess the impact of his ideas in the light of other advances in our understanding of crop performance. Whether or not many of the claims made for or the demands made of models can ever be satisfied, this role as a focus for quantitative definition of crop growth is an important one. One consequence is that the development and appraisal of such models requires the efforts of scientists from a wide range of disciplines. This NATO Advanced Research workshop was designed to bring together such a range of scientists to consider the wheat crop, and assess our understanding of the crop and our ability to model its growth and yield. The ideas and organization behind the workshop involved many people. The U. K. interest in a computer model of wheat growth was instigated by Dr. Joe Landsberg (then of Long Ashton Research Station, but now Director of CSIRO Division of Forest Research), who in 1979 started a modelling exercise as part of a collaborative study of the causes of yield variation in winter wheat, involving four research institutes supported by the Agricultural and Food Research Council. Dr.

"Crop Modeling and Decision Support" presents 36 papers selected from the International Symposium on Crop Modeling and Decision Support (ISCMDS-2008), held at Nanjing of China from 19th to 22nd in April, 2008. Many of these papers show the recent advances in modeling crop and soil processes, crop productivity, plant architecture and climate change; the rests describe the developments in model-based decision support systems (DSS), model applications, and integration of crop models with other information technologies. The book is intended for researchers, teachers, engineers, and graduate students on crop modeling and decision support. Dr. Weixing Cao is a professor at Nanjing Agricultural University, China.

Proceedings of the 5th International Wheat Conference, 10-14 June 1996, Ankara, Turkey

The first premise of this book is that farmers need access to options for improving their situation. In agricultural terms, these options might be manage ment alternatives or different crops to grow, that can stabilize or increase household income, that reduce soil degradation and dependence on off-farm inputs, or that exploit local market opportunities. Farmers need a facilitating environment, in which affordable credit is available if needed, in which policies are conducive to judicious management of natural resources, and in which costs and prices of production are stable. Another key ingredient of this facilitating environment is information: an understanding of which options are viable, how these operate at the farm level, and what their impact may be on the things that farmers perceive as being important. The second premise is that systems analysis and simulation have an impor tant role to play in fostering this understanding of options, traditional field experimentation being time-consuming and costly. This book summarizes the activities of the International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT) project, an international initiative funded by the United States Agency for International Development (USAID). IBSNAT was an attempt to demonstrate the effectiveness of understanding options through systems analysis and simulation for the ultimate benefit of farm households in the tropics and subtropics. The idea for the book was first suggested at one of the last IBSNAT group meetings held at the University of Hawaii in 1993.

Model studies focus experimental investigations to improve our understanding and performance of systems. Concentrating on crop modelling, this book provides an introduction to the concepts of crop development, growth, and yield, with step-by-step outlines to each topic, suggested exercises and simple equations. A valuable text for students and researchers of crop development alike, this book is written in five parts that allow the reader to develop a solid foundation and coverage of production models including water- and nitrogen-limited systems.

Uncertainty in the predictions of science when applied to the environment is an issue of great current relevance in relation to the impacts of climate change, protecting against natural and man-made disasters, pollutant transport and sustainable resource management. However, it is often ignored both by scientists and decision makers, or interpreted as a conflict or disagreement between scientists. This is not necessarily the case, the scientists might well agree, but their predictions would still be uncertain and knowledge of that uncertainty might be important in decision making. Environmental Modelling: An Uncertain Future? introduces students, scientists and decision makers to: the different concepts and techniques of uncertainty estimation in environmental prediction the philosophical background to different concepts of uncertainty the constraint of uncertainties by the collection of observations and data assimilation in real-time forecasting techniques for decision making under uncertainty. This book will be relevant to environmental modellers, practitioners and decision makers in hydrology, hydraulics, ecology, meteorology and oceanography, geomorphology, geochemistry, soil science, pollutant transport and climate change. A companion website for the book can be found at www.uncertain-future.org.uk