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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
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 2018-11-13 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
Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment, 3e, is a complete guide to working with dynamic system models, with emphasis on models in agronomy and environmental science. The introductory section presents the foundational information for the book including the basics of system models, simulation, the R programming language, and the statistical notions necessary for working with system models. The most important methods of working with dynamic system models, namely uncertainty and sensitivity analysis, model calibration (frequentist and Bayesian), model evaluation, and data assimilation are all treated in detail, in individual chapters. New chapters cover the use of multi-model ensembles, the creation of metamodels that emulate the more complex dynamic system models, the combination of genetic and environmental information in gene-based crop models, and the use of dynamic system models to aid in sampling. The book emphasizes both understanding and practical implementation of the methods that are covered. Each chapter simply and clearly explains the underlying principles and assumptions of each method that is presented, with numerous examples and illustrations. R code for applying the methods is given throughout. This code is designed so that it can be adapted relatively easily to new problems. An expanded introductory section presents the basics of dynamic system modeling, with numerous examples from multiple fields, plus chapters on numerical simulation, statistics for modelers, and the R language. Covers in detail the basic methods: uncertainty and sensitivity analysis, model calibration (both frequentist and Bayesian), model evaluation, and data assimilation. Every method chapter has numerous examples of applications based on real problems, as well as detailed instructions for applying the methods to new problems using R. Each chapter has multiple exercises for self-testing or for classroom use. An R package with much of the code from the book can be freely downloaded from the CRAN package repository.
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 2018-09-25 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment, 3e, is a complete guide to working with dynamic system models, with emphasis on models in agronomy and environmental science. The introductory section presents the foundational information for the book including the basics of system models, simulation, the R programming language, and the statistical notions necessary for working with system models. The most important methods of working with dynamic system models, namely uncertainty and sensitivity analysis, model calibration (frequentist and Bayesian), model evaluation, and data assimilation are all treated in detail, in individual chapters. New chapters cover the use of multi-model ensembles, the creation of metamodels that emulate the more complex dynamic system models, the combination of genetic and environmental information in gene-based crop models, and the use of dynamic system models to aid in sampling. The book emphasizes both understanding and practical implementation of the methods that are covered. Each chapter simply and clearly explains the underlying principles and assumptions of each method that is presented, with numerous examples and illustrations. R code for applying the methods is given throughout. This code is designed so that it can be adapted relatively easily to new problems. An expanded introductory section presents the basics of dynamic system modeling, with numerous examples from multiple fields, plus chapters on numerical simulation, statistics for modelers, and the R language. Covers in detail the basic methods: uncertainty and sensitivity analysis, model calibration (both frequentist and Bayesian), model evaluation, and data assimilation. Every method chapter has numerous examples of applications based on real problems, as well as detailed instructions for applying the methods to new problems using R. Each chapter has multiple exercises for self-testing or for classroom use. An R package with much of the code from the book can be freely downloaded from the CRAN package repository.
Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including the specific subject of this book, crop-soil systems). The models are important aids in understanding, predicting and managing these systems. Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations. The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap. * State-of-the-art methods explained simply and illustrated specifically for crop models * Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods * Includes model evaluation, understanding and estimating prediction error * Offers a unique data assimilation by using the Kalman filter and beyond
Book Synopsis Working with Dynamic Crop Models by : Francois Brun
Download or read book Working with Dynamic Crop Models written by Francois Brun and published by Elsevier. This book was released on 2006-05-10 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including the specific subject of this book, crop-soil systems). The models are important aids in understanding, predicting and managing these systems. Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations. The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap. * State-of-the-art methods explained simply and illustrated specifically for crop models * Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods * Includes model evaluation, understanding and estimating prediction error * Offers a unique data assimilation by using the Kalman filter and beyond
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.
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.
Book Synopsis Agroclimatology by : Jerry L. Hatfield
Download or read book Agroclimatology written by Jerry L. Hatfield and published by John Wiley & Sons. This book was released on 2020-01-22 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
This easy-to-follow book presents the fundamentals of how to measure vision and visual function. It offers a solid understanding of the neural basis of vision where it is known or can be deduced. Each chapter features an overview summarizing the chapter, declarative headings throughout for instant review, study guide questions, and a glossary. Explanations of the neural mechanisms underlying visual function help readers understand how vision is measured. It details the scientific basis of how visual function is measured and applies laboratory measurement to clinical procedures.
Book Synopsis The Psychophysical Measurement of Visual Function by : Thomas T. Norton
Download or read book The Psychophysical Measurement of Visual Function written by Thomas T. Norton and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-follow book presents the fundamentals of how to measure vision and visual function. It offers a solid understanding of the neural basis of vision where it is known or can be deduced. Each chapter features an overview summarizing the chapter, declarative headings throughout for instant review, study guide questions, and a glossary. Explanations of the neural mechanisms underlying visual function help readers understand how vision is measured. It details the scientific basis of how visual function is measured and applies laboratory measurement to clinical procedures.
A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in successful greenhouse control using different techniques and show how the models obtained can be exploited for simulation or control design; they suggest ideas for the development of physical and/or black-box models for this purpose. Strategies for the control of climate- and irrigation-related variables are brought forward. The uses of PID control and feedforward compensators, both widely used in commercial tools, are summarized. The benefits of advanced control techniques—event-based, robust, and predictive control, for example—are used to improve on the performance of those basic methods. A hierarchical control architecture is developed governed by a high-level multiobjective optimization approach rather than traditional constrained optimization and artificial intelligence techniques. Reference trajectories are found for diurnal and nocturnal temperatures (climate-related setpoints) and electrical conductivity (fertirrigation-related setpoints). The objectives are to maximize profit, fruit quality, and water-use efficiency, these being encouraged by current international rules. Illustrative practical results selected from those obtained in an industrial greenhouse during the last eight years are shown and described. The text of the book is complemented by the use of illustrations, tables and real examples which are helpful in understanding the material. Modeling and Control of Greenhouse Crop Growth will be of interest to industrial engineers, academic researchers and graduates from agricultural, chemical, and process-control backgrounds.
Book Synopsis Modeling and Control of Greenhouse Crop Growth by : Francisco Rodríguez
Download or read book Modeling and Control of Greenhouse Crop Growth written by Francisco Rodríguez and published by Springer. This book was released on 2014-11-01 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in successful greenhouse control using different techniques and show how the models obtained can be exploited for simulation or control design; they suggest ideas for the development of physical and/or black-box models for this purpose. Strategies for the control of climate- and irrigation-related variables are brought forward. The uses of PID control and feedforward compensators, both widely used in commercial tools, are summarized. The benefits of advanced control techniques—event-based, robust, and predictive control, for example—are used to improve on the performance of those basic methods. A hierarchical control architecture is developed governed by a high-level multiobjective optimization approach rather than traditional constrained optimization and artificial intelligence techniques. Reference trajectories are found for diurnal and nocturnal temperatures (climate-related setpoints) and electrical conductivity (fertirrigation-related setpoints). The objectives are to maximize profit, fruit quality, and water-use efficiency, these being encouraged by current international rules. Illustrative practical results selected from those obtained in an industrial greenhouse during the last eight years are shown and described. The text of the book is complemented by the use of illustrations, tables and real examples which are helpful in understanding the material. Modeling and Control of Greenhouse Crop Growth will be of interest to industrial engineers, academic researchers and graduates from agricultural, chemical, and process-control backgrounds.
This book is a textbook (it includes, for example, exercises and outline solutions). The plant scientist is shown how to express physiological ideas mathematically and how to deduce quantitative conclusions, which can then be compared with experiment. There is little new biology in the book, but it is presented in a way that will be new to many biologists. The matching of models to experiments means using mathematics for formulating biological concepts and second, using algebra, calculus, or, now more frequently, computers to solve or simulate the resulting model; and finally, comparing, qualitatively or quantitatively, prediction to measurement. Computers are the important enabling technology that makes it all possible: solving equations, assembling models of increasing sophistication and complexity, and comparing theory with experiment. The book is divided into three parts. Part I. Covers subjects of wide relevance to modelling and plant biology. Part II. The reader may choose to select topics of particular interest from part II. However, the whole-plant modeller will need to study all chapters, and the plant ecosystem modeller may need to add other material also. Part III. Plant morphology is at an introductory level. It is included because morphological characters may prove to be of equal importance to some physiological traits in determining plant function and performance. "This textbook presents, in an interesting and clearly written fashion, a mathematical approach to a wide range of topics in plant and crop physiology, including light interception, leaf and canopy photosynthesis, respiration, partitioning, transpiration and water relations, branching and phyllotaxis. The biochemistry of plant growth and maintenanace is also presented in some detail. I was very pleased with the text, especially with the philosophy presented by the authors that biological models are necessarily simplifications of complex detail. I would strongly recommend it for reading and consultation by graduates and research workers." J. Exp. Botany "The authors' approach succeeds admirably, giving a thorough account of the mathematical toolbox available to researchers and the areas in which those tools have been used." Plant, Cell and Environment "Combining considerable technical cleverness with creativity and the refreshing notion that science is a "common-sense, unpredictable, fascinating and thoroughly human activity." Times Higher Educational Supplement "Exceptionally scholarly volume. Logical and systematic. Authors have assembled a mass of mathematical material in an elegant layout." Agricultural Systems
Book Synopsis Plant and Crop Modelling by : J. H. M. Thornley
Download or read book Plant and Crop Modelling written by J. H. M. Thornley and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a textbook (it includes, for example, exercises and outline solutions). The plant scientist is shown how to express physiological ideas mathematically and how to deduce quantitative conclusions, which can then be compared with experiment. There is little new biology in the book, but it is presented in a way that will be new to many biologists. The matching of models to experiments means using mathematics for formulating biological concepts and second, using algebra, calculus, or, now more frequently, computers to solve or simulate the resulting model; and finally, comparing, qualitatively or quantitatively, prediction to measurement. Computers are the important enabling technology that makes it all possible: solving equations, assembling models of increasing sophistication and complexity, and comparing theory with experiment. The book is divided into three parts. Part I. Covers subjects of wide relevance to modelling and plant biology. Part II. The reader may choose to select topics of particular interest from part II. However, the whole-plant modeller will need to study all chapters, and the plant ecosystem modeller may need to add other material also. Part III. Plant morphology is at an introductory level. It is included because morphological characters may prove to be of equal importance to some physiological traits in determining plant function and performance. "This textbook presents, in an interesting and clearly written fashion, a mathematical approach to a wide range of topics in plant and crop physiology, including light interception, leaf and canopy photosynthesis, respiration, partitioning, transpiration and water relations, branching and phyllotaxis. The biochemistry of plant growth and maintenanace is also presented in some detail. I was very pleased with the text, especially with the philosophy presented by the authors that biological models are necessarily simplifications of complex detail. I would strongly recommend it for reading and consultation by graduates and research workers." J. Exp. Botany "The authors' approach succeeds admirably, giving a thorough account of the mathematical toolbox available to researchers and the areas in which those tools have been used." Plant, Cell and Environment "Combining considerable technical cleverness with creativity and the refreshing notion that science is a "common-sense, unpredictable, fascinating and thoroughly human activity." Times Higher Educational Supplement "Exceptionally scholarly volume. Logical and systematic. Authors have assembled a mass of mathematical material in an elegant layout." Agricultural Systems
