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"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.
Book Synopsis Crop Modeling and Decision Support by : Weixing Cao
Download or read book Crop Modeling and Decision Support written by Weixing Cao and published by Springer Science & Business Media. This book was released on 2010-07-10 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
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.
Book Synopsis Advances in Crop Modelling for a Sustainable Agriculture by : Kenneth Boote
Download or read book Advances in Crop Modelling for a Sustainable Agriculture written by Kenneth Boote and published by Burleigh Dodds Series in Agric. This book was released on 2019-10-22 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Crop Modeling and Decision Support by : Jeffrey W. White
Download or read book Crop Modeling and Decision Support written by Jeffrey W. White and published by . This book was released on 2009 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Book Synopsis Understanding Options for Agricultural Production by : G.Y. Tsuji
Download or read book Understanding Options for Agricultural Production written by G.Y. Tsuji and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Book Synopsis Data Science and Data Analytics by : Amit Kumar Tyagi
Download or read book Data Science and Data Analytics written by Amit Kumar Tyagi and published by CRC Press. This book was released on 2021-09-22 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Book Synopsis Remote Sensing Applications for Agriculture and Crop Modelling by : Piero Toscano
Download or read book Remote Sensing Applications for Agriculture and Crop Modelling written by Piero Toscano and published by MDPI. This book was released on 2020-02-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Book Synopsis Decision Support Systems for Weed Management by : Guillermo R. Chantre
Download or read book Decision Support Systems for Weed Management written by Guillermo R. Chantre and published by Springer Nature. This book was released on 2020-07-31 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Book Synopsis Crop Growth Simulation Modelling And Climate Change by : M. Mohanty
Download or read book Crop Growth Simulation Modelling And Climate Change written by M. Mohanty and published by Scientific Publishers. This book was released on 2015-06-01 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines. New to this edition: 50% new content – 100% reviewed and updated Clearly explains practical application of the methods presented, including R language examples Presents real-life examples of core crop modeling methods, and ones that are translatable to dynamic system models in other fields
Book Synopsis Working with Dynamic Crop Models by : Daniel Wallach
Download or read book Working with Dynamic Crop Models written by Daniel Wallach and published by Academic Press. This book was released on 2013-11-25 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines. New to this edition: 50% new content – 100% reviewed and updated Clearly explains practical application of the methods presented, including R language examples Presents real-life examples of core crop modeling methods, and ones that are translatable to dynamic system models in other fields
While a good grasp of the many separate aspects of agriculture is important, it is equally essential for all those involved in agriculture to understand the functioning of the farming system as a whole and how it can be best managed. It is necessary to re-assess and understand rain-fed farming systems around the world and to find ways to improve the selection, design and operation of such systems for long term productivity, profitability and sustainability. The components of the system must operate together efficiently; yet many of the relationships and interactions are not clearly understood. Appreciation of these matters and how they are affected by external influences or inputs are important for decision making and for achieving desirable outcomes for the farm as a whole. This book analyses common rain-fed farming systems and defines the principles and practices important to their effective functioning and management.
Book Synopsis Rainfed Farming Systems by : Philip Tow
Download or read book Rainfed Farming Systems written by Philip Tow and published by Springer Science & Business Media. This book was released on 2011-09-16 with total page 1324 pages. Available in PDF, EPUB and Kindle. Book excerpt: While a good grasp of the many separate aspects of agriculture is important, it is equally essential for all those involved in agriculture to understand the functioning of the farming system as a whole and how it can be best managed. It is necessary to re-assess and understand rain-fed farming systems around the world and to find ways to improve the selection, design and operation of such systems for long term productivity, profitability and sustainability. The components of the system must operate together efficiently; yet many of the relationships and interactions are not clearly understood. Appreciation of these matters and how they are affected by external influences or inputs are important for decision making and for achieving desirable outcomes for the farm as a whole. This book analyses common rain-fed farming systems and defines the principles and practices important to their effective functioning and management.
