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Crop Modeling and Decision Support by Weixing Cao,Jeffrey W. White,Enli Wang Pdf
"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.
Advances in Crop Modelling for a Sustainable Agriculture by Kenneth Boote Pdf
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.
Crop Growth Simulation Modelling And Climate Change by M. Mohanty,Nishant K. Sinha,K.M. Hati,R.S. Chaudhary,A.K. Patra Pdf
This book on “Crop Growth Simulation Modelling and Climate Change”. A group of authors have dealt with different aspects of crop modelling viz., Crop growth simulation models in agricultural crop production, Applications of Crop Growth Simulation Models in Climate Change Assessments, Biophysical impacts and priorities for adaptation of agricultural crops in a changing climate, Climate change projections – India’s Perspective, Impact of Rising Atmospheric CO2 concentration on Plant and Soil processes, Modelling the impact of climate change on soil erosion in stabilization and destabilization of soil organic carbon, Simulating Crop Yield, Soil Processes, Greenhouse Gas Emission and Climate Change Impacts with APSIM, InfoCrop Model, CropSyst model and its application in natural resource management, Climate change and crop production system: assessing the consequences for food security, A biophysical model to analyze climate change impacts on rainfed rice productivity in the mid-hills of Northeast India, AquaCrop Modelling: A Water Driven Simulation Model, Conservation Agriculture: A strategy to cope with Climate Change, Effect of climate change on productivity of wheat and possible mitigation strategies using DSSAT model in foot hill of Western Himalayas, Integrating Remote Sensing Data in Crop Process Models, Climate change impact assessment using DSSAT model, Decision Support System for Managing Soil Fertility and Productivity in Agriculture, De-Nitrification De-Composition Model - An Introduction for SOC Simulations, Crop Simulation Modeling for Climate Risk assessment: Adaptation and Mitigation Measures and Rules of Simulations, Rothamsted Carbon (RothC) Model and its Application in Agriculture etc.
Understanding Options for Agricultural Production by G.Y. Tsuji,G. Hoogenboom,P.K. Thornton Pdf
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.
Crop-soil Simulation Models by William Stephens Pdf
The use of crop-soil modelling has so far been mainly confined to the research community. Practical applications have occurred in the areas of decision tools for irrigation studies and pest management. However, there is potential to increase its applied use.This book reviews progress in crop-soil simulation modelling and assesses its application to agriculture in developing countries. It is based on work sponsored by the Natural Resources Systems Programme of the UK Department for International Development.
Systems Analysis and Modeling in Food and Agriculture by K.C.Ting,David H. Fleisher,Luis F. Rodriguez Pdf
Systems Analysis and Modeling in Food and Agriculture is a component of Encyclopedia of Food and Agricultural Sciences, Engineering and Technology Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Systems analysis and modeling is being used increasingly in understanding and solving problems in food and agriculture. The purpose of systems analysis is to support decisions by emphasizing the interactions of processes and components within a system. Frequently investigated systems level questions in agriculture and food are relevant to the 6 E's: Environment, Energy, Ecology, Economics, Education, and Efficiency. The theme on Systems Analysis and Modeling in Food and Agriculture with contributions from distinguished experts in the field provides information on key topics related to food and agricultural system. The coverage include an overview of food system; system level aspects related to energy, environment, and social/policy issues; knowledge bases and decision support; computer models for crops, food processing, water resources, and agricultural meteorology; collection and analysis methods for data from field experiments; use of models and information systems. This volume is aimed at the following a wide spectrum of audiences from the merely curious to those seeking in-depth knowledge: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.
Remote Sensing Applications for Agriculture and Crop Modelling by Piero Toscano Pdf
Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling, provide insight into the diversity and the complexity of developments of RS applications in agriculture. Five thematic focuses have emerged from the published papers: yield estimation, land cover mapping, soil nutrient balance, time-specific management zone delineation and the use of UAV as agricultural aerial sprayers. All contributions exploited the use of remote sensing data from different platforms (UAV, Sentinel, Landsat, QuickBird, CBERS, MODIS, WorldView), their assimilation into crop models (DSSAT, AQUACROP, EPIC, DELPHI) or on the synergy of Remote Sensing and modeling, applied to cardamom, wheat, tomato, sorghum, rice, sugarcane and olive. The intended audience is researchers and postgraduate students, as well as those outside academia in policy and practice.
Agricultural System Models in Field Research and Technology Transfer by Lajpat R. Ahuja,Liwang Ma,Terry A Howell Pdf
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 Res
Data Science and Data Analytics by Amit Kumar Tyagi Pdf
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy. FEATURES Gives the concept of data science, tools, and algorithms that exist for many useful applications Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems Identifies many areas and uses of data science in the smart era Applies data science to agriculture, healthcare, graph mining, education, security, etc. Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm’s productivity.
Improving Soil Fertility Recommendations in Africa using the Decision Support System for Agrotechnology Transfer (DSSAT) by Job Kihara,Dougbedji Fatondji,James W Jones,Gerrit Hoogenboom,Ramadjita Tabo,Andre Bationo Pdf
The book gives a detailed description of the application of DSSAT in simulating crop and soil processes within various Agro-ecological zones in Africa. The book, an output of a series of 3 workshops, provides examples of the application of DSSAT models to simulate nitrogen applications, soil and water conservation practices including effects of zai technology, phosphorus and maize productivity, generation of genetic coefficients, long-term soil fertility management technologies in the drylands, microdosing, optimization of nitrogen x germplasms x water, spatial analysis of water and nutrient use efficiencies and, tradeoff analysis. The minimum dataset requirements for DSSAT is discussed. This book arises from attempts to address the limited use of models in decision support by African agricultural (both soil scientist and agronomists) scientists.
Decision Support Systems for Weed Management by Guillermo R. Chantre,José L. González-Andújar Pdf
Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate `concepts and practice’ providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas.
Wheat Growth and Modelling by W. Day,R.K. Atkin Pdf
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.
Landscape Modelling and Decision Support by Wilfried Mirschel,Vitaly V. Terleev,Karl-Otto Wenkel Pdf
This book contributes to a deeper understanding of landscape and regional modelling in general, and its broad range of facets with respect to various landscape parameters. It presents model approaches for a number of ecological and socio-economic landscape indicators, and also describes spatial decision support systems (DSS), frameworks, and model-based tools, which are prerequisites for deriving sustainable decision and solution strategies for the protection of comprehensively functioning landscapes. While it mainly focuses on the latest research findings in regional modelling and DSS in Europe, it also highlights the work of scientists from Russia. The book is intended for landscape modellers, scientists from various fields of landscape research, university teaching staff, and experts in landscape planning and management, landscape conservation and landscape policy.
