Enhancing Agricultural Research and Precision Management for Subsistence Farming Insightful applications of crop system models to developing countries to explore climate change mitigation and management decision tools Enhancing Agricultural Research and Precision Management for Subsistence Farming by Integrating System Models with Experiments delivers an authoritative collection of applications of crop system models to Asian and African environments and evaluates current agricultural systems in developing nations. The book provides models to assist in the precision management of soil, water, fertilizers and manures, soil organic matter, alternative crops, and cultivars in both rainfed and irrigated systems. Contributions cover recent and ongoing research in knowledge gap areas such as modeling the long-term effect of management soil health, the effect of extreme temperatures and drought on evapotranspiration and crop growth, root growth and the uptake of water and nutrients. The book also includes An introduction to system models integrated with experiments as tools to develop improved management practices for subsistence farming Explorations of models of soil erosion impacts and trade-offs for sustainable land management practices in Kenya Discussions of the crop simulation model as a tool to quantify the effects of crop management practices in northern Ethiopia In-depth examinations of models of water dynamics for assessing and managing ecosystem services in India Perfect for field research scientists and graduate students studying cropping and range systems, and essential reading for agricultural consultants, progressive farmers, plant breeders, and policymakers. Advances in Agricultural Systems Modeling Transdisciplinary Research, Synthesis, and Applications Lajpat R. Ahuja, Series Editor Agricultural system modeling has made substantial progress, but there are still many critical gaps in our knowledge. The American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America are taking a leadership role with the initiation of this new series. Future breakthroughs in science and technology lie at the boundaries of disciplines. The new series will Advance critical transdisciplinary research, and its synthesis and quantification Encourage collaboration among top researchers in building and improving models Promote the application of system models to solve practical problems Achieve better instruction in these models and their applications

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.

This book describes the contributing aspects of contemporary developments related to sustainable agricultural resources and assessment of sustainable agriculture in developing nations. The issues like food crisis and declining agro-productivity, post-pandemic food security, zonation and mapping technique viewing food crisis, biotechnology and sustainable agricultural, scaling hunger indices, health hazard and food crisis, changing climate and food availability, consumer load and fertilizer usage, growing demand and increasing usage of harmful chemical in agro-fields are regarded as serious concerns. Thereafter, the scope of sustainable agricultural potentiality (SAP) modeling, amidst the arena of deforestation and encroachment of new cultivable land, impact of pandemic on sustainable agriculture, using wastewater as non-sustainable agricultural practice, applying geospatial techniques on extreme weather susceptibility and agro-production, soil erosion and poor agricultural production, questioning shifting cultivation on the issue of sustainability, meteorological drought and irrigational gaps, occupational mobility and loss of agricultural heritage, farm-excreta burning and air quality index (AQI), GI-Science and sustainable agro-management, community preparedness in food crisis management, multi-criteria hunger index (MCHI), climate change declining sustainable agro-production are worth some. Almost the entire world has recently suffered from several natural and human-induced problems, among which food crisis and unsustainable agriculture throw significant challenges to human society. Contrastingly, if modern technology and means, with advanced monitoring and calibration methodology and policy guidance, can help, it will undoubtedly reduce half of the world's problems and ensure the future survival of human society. In addition, this approach also can minimize the other partially linked problems, like climate change and food shortage, livelihood crisis, environmental refugees, international trade balance, global food supply chain interruption, the ever-expanding gap between rich and poor, and so on. Therefore, properly nurturing the knowledge on the application of GI-Science for an agriculturally sustainable society and their monitoring and management can curtail the gap between science, policy, and the ground-level scenario concerned.

A fast-growing interest in the concepts and application of systems research has spawned a wide and general literature over the past decade. Most disciplinary areas have been touched, but commerce, engineering and military studies have, perhaps, been best served with outstanding texts. No provision has so far been made for a general book at introductory level of direct relevance to agricultural science, technology and management. General reviews are, of course, valuable to the agricultural-systems researcher but agricultural systems, with important biological components interacting with equally vital social and economic elements, embody particular characteristics which influence the approach to their study. This book is written in the belief that the concepts as well as the technology of the systems approach have a basic role in the rational advancement of the agricultural discipline and in the improvement of efficiency in agricultural research and practice. A basic and introductory text is an essential pre requisite to this role being realised. A reiteration of basic concepts is expressed in the introductory chapter while in the final chapter particular attention is given to the general problems of integrating systems concepts in research, extension and practice. The dialogue of these chapters is necessarily brief and in some respects speculative but it is supported by appropriate bibliography. The main body of the text is concerned with the methodology of systems research; the conception, construction, implementation, validation and exploitation of computer-based simulation models of agricultural systems.

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.

This book investigates new agricultural systems such as organic and green manuring, as well as integrated pest management practices, and looks at how they can improve farm productivity against the enhancements for the environment. Much of the information presented focuses on microinvestigation of the soil, and on the effects of soil variability within fields on yields and nutrient flows.

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 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.

Modern agriculture faces some of the most pressing problems in the 21st century: farm profitability, food security, and environmental sustainability. To address these problems, it is essential to raise productivity in a sustainable manner, an overarching goal known as sustainable intensification. In efforts to increase productivity through improved management of agricultural systems, a fundamental challenge is enormous complexity arising from both biological and social aspects of agricultural systems. However, despite the apparent need for research in modeling such socio-ecological systems without trivializing their complexity, most of the existing agricultural research only focuses on basic component sub-processes, making itself largely irrelevant for practical decision making for sustainable intensification. My contribution to the research community is twofold: exemplify practical models for management of agricultural systems and lay the foundation for some specific problems. In particular, two distinct models are constructed to support decision making at different levels of agricultural systems. Both models are predominantly characterized by their computational approaches, which capitalize on the ever increasing data and computational capacity. At an individual level, adaptive experimental designs based on Bayesian optimization techniques help individual farmers to efficiently learn complex management practices through on-farm experiments. In contrast, agent-based models help policy makers to gain insights into complex socio-ecological systems and design effective mitigation policies for insect resistance management at an aggregate landscape level. Although these models are necessarily ad hoc solutions to the specific problems, their modeling techniques (Bayesian optimization and agent-based modeling) are very general and applicable to many other practical problems.