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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.
Plant phenotyping is an emerging technology that involves the quantitative analysis of structural and functional plant traits. However, it is widely recognised that phenotyping needs to match similar advances in genetics if it is to not create a bottleneck in plant breeding. Advances in plant phenotyping for more sustainable crop production reviews the wealth of research on advances in plant phenotyping to meet this challenge, such as the development of new technologies including hyperspectral sensors such as LIDAR, NIR/SWIR, as well as alternative delivery/carrier systems, such as ground-based proximal distance systems and UAVs. The book details the development of plant phenotyping as a technique to analyse crop roots and functionality, as well as its use in understanding and improving crop response to biotic and abiotic stresses.
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.
Can we unlock resilience to climate stress by better understanding linkages between the environment and biological systems? Agroclimatology allows us to explore how different processes determine plant response to climate and how climate drives the distribution of crops and their productivity. Editors Jerry L. Hatfield, Mannava V.K. Sivakumar, and John H. Prueger have taken a comprehensive view of agroclimatology to assist and challenge researchers in this important area of study. Major themes include: principles of energy exchange and climatology, understanding climate change and agriculture, linkages of specific biological systems to climatology, the context of pests and diseases, methods of agroclimatology, and the application of agroclimatic principles to problem-solving in agriculture.
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.
Continued population growth, rapidly changing consumption patterns and the impacts of climate change and environmental degradation are driving limited resources of food, energy, water and materials towards critical thresholds worldwide. These pressures are likely to be substantial across Africa, where countries will have to find innovative ways to boost crop and livestock production to avoid becoming more reliant on imports and food aid. Sustainable agricultural intensification - producing more output from the same area of land while reducing the negative environmental impacts - represents a solution for millions of African farmers. This volume presents the lessons learned from 40 sustainable agricultural intensification programmes in 20 countries across Africa, commissioned as part of the UK Government's Foresight project. Through detailed case studies, the authors of each chapter examine how to develop productive and sustainable agricultural systems and how to scale up these systems to reach many more millions of people in the future. Themes covered include crop improvements, agroforestry and soil conservation, conservation agriculture, integrated pest management, horticulture, livestock and fodder crops, aquaculture, and novel policies and partnerships.
As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is a necessity for understanding these technological developments. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture provides emerging research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. Featuring coverage on a broad range of topics such as crop monitoring, precision livestock farming, and agronomic data processing, this book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.
For nearly a century, scientific advances have fueled progress in U.S. agriculture to enable American producers to deliver safe and abundant food domestically and provide a trade surplus in bulk and high-value agricultural commodities and foods. Today, the U.S. food and agricultural enterprise faces formidable challenges that will test its long-term sustainability, competitiveness, and resilience. On its current path, future productivity in the U.S. agricultural system is likely to come with trade-offs. The success of agriculture is tied to natural systems, and these systems are showing signs of stress, even more so with the change in climate. More than a third of the food produced is unconsumed, an unacceptable loss of food and nutrients at a time of heightened global food demand. Increased food animal production to meet greater demand will generate more greenhouse gas emissions and excess animal waste. The U.S. food supply is generally secure, but is not immune to the costly and deadly shocks of continuing outbreaks of food-borne illness or to the constant threat of pests and pathogens to crops, livestock, and poultry. U.S. farmers and producers are at the front lines and will need more tools to manage the pressures they face. Science Breakthroughs to Advance Food and Agricultural Research by 2030 identifies innovative, emerging scientific advances for making the U.S. food and agricultural system more efficient, resilient, and sustainable. This report explores the availability of relatively new scientific developments across all disciplines that could accelerate progress toward these goals. It identifies the most promising scientific breakthroughs that could have the greatest positive impact on food and agriculture, and that are possible to achieve in the next decade (by 2030).
Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.