Advances In Modeling Agricultural Systems

Agriculture has experienced a dramatic change during the past decades. The change has been structural and technological. Structural changes can be seen in the size of current farms; not long ago, agricultural production was organized around small farms, whereas nowadays the agricultural landscape is dominated by large farms. Large farms have better means of applying new technologies, and therefore technological advances have been a driving force in changing the farming structure. New technologies continue to emerge, and their mastery and use in requires that farmers gather more information and make more complex technological choices. In particular, the advent of the Internet has opened vast opportunities for communication and business opportunities within the agricultural com- nity. But at the same time, it has created another class of complex issues that need to be addressed sooner rather than later. Farmers and agricultural researchers are faced with an overwhelming amount of information they need to analyze and synthesize to successfully manage all the facets of agricultural production. This daunting challenge requires new and complex approaches to farm management. A new type of agricultural management system requires active cooperation among multidisciplinary and multi-institutional teams and ref- ing of existing and creation of new analytical theories with potential use in agriculture. Therefore, new management agricultural systems must combine the newest achievements in many scientific domains such as agronomy, economics, mathematics, and computer science, to name a few.

Why model? Agricultural system models enhance and extend field research...to synthesize and examine experiment data and advance our knowledge faster, to extend current research in time to predict best management systems, and to prepare for climate-change effects on agriculture. The relevance of such models depends on their implementation. Methods of Introducing System Models into Agricultural Research is the ultimate handbook for field scientists and other model users in the proper methods of model use. Readers will learn parameter estimation, calibration, validation, and extension of experimental results to other weather conditions, soils, and climates. The proper methods are the key to realizing the great potential benefits of modeling an agricultural system. Experts cover the major models, with the synthesis of knowledge that is the hallmark of the Advances in Agricultural Systems Modeling series.

Crop modelling has huge potential to improve decision making in farming. This collection reviews advances in next-generation models focused on user needs at the whole farm system and landscape scale.

Modeling Processes and Their Interactions in Cropping Systems A complete discussion of soil-plant-climate-management processes In Modeling Processes and Their Interactions in Cropping Systems: Challenges for the 21st Century, a team of distinguished researchers delivers a comprehensive and up-to-date scientific textbook devoted to teaching the modeling of soil-plant-climate-management processes at the upper undergraduate and graduate levels. The book emphasizes the new opportunities and paradigms available to modern lab and field researchers and aims to improve their understanding and quantification of individual processes and their interactions. The book helps readers quantify field research results in terms of the fundamental theory and concepts broadly generalizable beyond specific sites, as well as predict experimental results from knowledge of the fundamental factors that determine the environment and plant growth in different climates. Readers will also discover: An introduction to water and chemical transport in the soil matrix and macropores Explorations of heat transport, water balance, snowpack, and soil freezing Discussions of merging machine learning with APSIM models to improve the evaluation of the impact of climate extremes on wheat yields in Australia Examinations of the quantification and modeling of management effects on soil properties, including discussions of tillage, reconsolidation, crop residues, and crop management The book will be essential reading for anyone interested in the 2030 breakthroughs in agriculture identified by the National Academies of Sciences, Engineering, and Medicine.

Crop model intercomparison and improvement are required to advance understanding of the impact of future climate change on crop growth and yield. The initial efforts undertaken in the Agriculture Model Intercomparison and Improvement Project (AgMIP) led to several observations where crop models were not adequately simulating growth and development. These studies revealed where enhanced efforts should be undertaken in experimental data to quantify the carbon dioxide × temperature × water interactions in plant growth and yield. International leaders in this area held a symposium at the 2013 ASA, CSSA, and SSSA Annual Meeting to discuss this topic. This volume in the Advances in Agricultural Systems Modeling series presents experimental observations across crops and simulation modeling outcomes and addresses future challenges in improving crop simulation models. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.

Completely devoted to applicati on of models to opti mize the use of limited water and nutrients in various climates, this collecti on will inspire confi dence in the capacity of modeling to tackle the biggest threats to secure agriculture. To obtain the most producti on from available water while maintaining natural resources, we need whole system–based quanti tati ve knowledge and tools to help select appropriate crops and manage water and associated inputs on a site-specifi c basis under changing climate. Site-specifi c experimental results are available for limited locati ons, limited periods of ti me, and limited management opti ons. Well-tested process models of cropping systems can extend fi eld research results to long-term weather conditi ons, as well as other climates and soils, allowing us to explore new management opti ons. The case studies in this volume are promising examples of these kinds of soluti ons.

Most books covering the use of computer models in agricultural management systems target only one or two types of models. There are few texts available that cover the subject of systems modeling comprehensively and that deal with various approaches, applications, evaluations, and uses for technology transfer. Agricultural System Models in Field Research and Technology Transfer fills this need. It presents the latest advances in the use of various computer models in agricultural management systems. This authoritative reference provides guidance on the use of models in field research, decision support, precision farming, and technology transfer to farmers and ranchers. Derived from an international symposium co-sponsored by the American Society of Agronomy, the Soil Science Society of America, and the USDA's Agricultural Research Service, it analyzes current system model applications for the modeling of natural resources, crop production, grazing lands, and animal production systems. Leading international agricultural system scientists present their experiences and provide guidance on how models can be used to enhance the quality of field research, transfer of research information and technology to farmers and ranchers, and decision support for agricultural management. They provide an expert review of the existing problems and possible solutions to improve future applications. In addition, Agricultural System Models in Field Research and Technology Transfer explores the possible use of an international modular computer framework to improve current modeling procedures in an effort to develop problem-specific models in the future.