working with dynamic crop models

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Working with Dynamic Crop Models
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Publisher : Academic Press
Release Date :
ISBN 10 : 0128117575
Pages : 613 pages
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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.

Working with Dynamic Crop Models

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,

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Working with Dynamic Crop Models

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.

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Working with Dynamic Crop Models

This textbook covers 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

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Crop Modeling and Decision Support

"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

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Understanding Options for Agricultural Production

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

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Advances in Crop Modelling for a Sustainable 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.

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Applications of Systems Approaches at the Field Level

Systems approaches for agricultural development are needed to determine rational strategies for the role of agriculture in national development. Mathematical models and computer simulation provide objective tools for applying science to determine and evaluate options for resource management at field, farm and regional scales. However, these tools would not be

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From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students

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A tool for climate smart crop insurance  Combining farmers    pictures with dynamic crop modelling for accurate yield estimation prior to harvest

The study found that dynamic crop models have the accuracy to predict normal to high yields, but there are limits to their ability to capture low yields. On the other hand, the machine learning (CNN) model has better ability to capture lower yields. It is worth noting that the crop

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Crop Systems Dynamics

This book presents a generic process-based crop growth model, GECROS (Genotype-by-Environment interaction on CROp growth Simulator), recently developed in Wageningen. The model uses robust yet simple algorithms to summarize the current knowledge of individual physiological processes and their interactions and feedback mechanisms. It was structured from the basics of whole-crop

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Modelling Crop weed Interactions

General introduction; Empirical models for crop-weed competition; Eco-physiological models for crop-weed competition; Mechanisms of competition for light; Mechanisms of competition for water; Mechanisms of competition for nitrogen; Eco-physiological characterization of the species; Understanding crop-weed interaction in field situation; The impact of environmental and genetic factors; Practical applications.

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Landscape Modelling and Decision Support

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

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Viticulture and Winemaking under Climate Change

The importance of viticulture and the winemaking socio-economic sector is acknowledged worldwide. The most renowned winemaking regions show very specific environmental characteristics, where climate usually plays a central role. Considering the strong influence of weather and climatic factors on grapevine yields and berry quality attributes, climate change may indeed significantly

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Predicting Crop Phenology

Predicting Crop Phenology focuses on an analysis of the issues faced in predicting the phenology of crop plants and weeds. It discusses how these issues have been handled by active crop growth simulation model developers and emphasizes areas such as the role of modeling in agricultural research and the roles

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Environmental Software Systems  Infrastructures  Services and Applications

This book constitutes the refereed proceedings of the 11th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2015, held in Melbourne, Australia, in March 2015. The 62 revised full papers presented were carefully reviewed and selected from 104 submissions. The papers are organized in the following topical sections: information systems, information modeling and

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