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Advances in Modeling Agricultural Systems

  • Book
  • © 2009

Overview

Editors:
  1. Panos M. Pardalos
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    You can also search for this editor in PubMed   Google Scholar

  2. Petraq J. Papajorgji
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  • Presents an up-to-date review of advances in the mathematical modeling of agricultural systems
  • Covers a broad spectrum of problems and applications based on internet and communications technology
  • Uses methodological approaches based on the integration of different simulation and data management tools
  • Provides detailed solutions of real-world problems

Part of the book series: Springer Optimization and Its Applications (SOIA, volume 25)

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Table of contents (22 chapters)

  1. Front Matter

    Pages i-xviii
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  2. The Model Driven Architecture Approach: A Framework for Developing Complex Agricultural Systems

    • Petraq Papajorgji, Ryan Clark, Eric Jallas
    Pages 1-18

  3. A New Methodology to Automate the Transformation of GIS Models in an Iterative Development Process

    • André Miralles, Thérèse Libourel
    Pages 19-36

  4. Application of a Model Transformation Paradigm in Agriculture: A Simple Environmental System Case Study

    • André Miralles, Thérèse Libourel
    Pages 37-54

  5. Constraints Modeling in Agricultural Databases

    • François Pinet, Magali Duboisset, Birgit Demuth, Michel Schneider, Vincent Soulignac, François Barnabé
    Pages 55-65

  6. Design of a Model -Driven Web Decision Support System in Agriculture : From Scientific Models to the Final Software

    • Loudovic Tambour, Vianney Houlès, Laurence Cohen-Jonathan, Valerie Auffray, Pierre Escande, Eric Jallas
    Pages 67-102

  7. How2QnD: Design and Construction of a Game-Style, Environmental Simulation Engine and Interface Using UML, XML, and Java

    • Gregory A. Kiker, Rohit Thummalapalli
    Pages 103-129

  8. The Use of UML as a Tool for the Formalisation of Standards and the Design of Ontologies in Agriculture

    • François Pinet, Catherine Roussey, Thomas Brun, Frédéric Vigier
    Pages 131-147

  9. Modeling External Information Needs of Food Business Networks

    • Melanie Fritz
    Pages 149-166

  10. Enterprise Business Modelling Languages Applied to Farm Enterprise: A Case Study for IDEF0, GRAI Grid, and AMS Languages

    • Vincent Abt, Frédéric Vigier, Michel Schneider
    Pages 167-191

  11. A UML-Based Plug&Play Version of RothC

    • Petraq Papajorgji, Osvaldo Gargiulo, James W. Jones, Sibiri Traore
    Pages 193-208

  12. Ontology-Based Simulation Applied to Soil, Water, and Nutrient Management

    • Howard Beck, Kelly Morgan, Yunchul Jung, Jin Wu, Sabine Grunwald, Ho-young Kwon
    Pages 209-242

  13. Precision Farming, Myth or Reality: Selected Case Studies from Mississippi Cotton Fields

    • Jeffrey L. Willers, Eric Jallas, James M. McKinion, Michael R. Seal, Sam Turner
    Pages 243-272

  14. Rural Development Through Input–Output Modeling

    • Konstadinos Mattas, Efstratios Loizou, Vangelis Tzouvelekas
    Pages 273-295

  15. Modeling in Nutrient Sensing for Agricultural and Environmental Applications

    • Won Suk Lee, Ismail Bogrekci, Min Min
    Pages 297-315

  16. Estimation of Land Surface Parameters Through Modeling Inversion of Earth Observation Optical Data

    • Guido D’Urso, Susana Gomez, Francesco Vuolo, Luigi Dini
    Pages 317-338

  17. A Stochastic Dynamic Programming Model for Valuing a Eucalyptus Investment

    • M. Ricardo Cunha, Dalila B. M. M. Fontes
    Pages 339-359

  18. Modelling Water Flow and Solute Transport in Heterogeneous Unsaturated Porous Media

    • Gerardo Severino, Alessandro Santini, Valeria Marina Monetti
    Pages 361-383

  19. Genome Analysis of Species of Agricultural Interest

    • Maria Luisa Chiusano, Nunzio D’Agostino, Amalia Barone, Domenico Carputo, Luigi Frusciante
    Pages 385-402

  20. Modeling and Solving Real-Life Global Optimization Problems with Meta-heuristic Methods

    • Antonio Mucherino, Onur Seref
    Pages 403-419
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Keywords

About this book

Agriculture has experienced a dramatic change during the past decades. The change has been structural and technological. Structural changes can be seen in the size of current farms; not long ago, agricultural production was organized around small farms, whereas nowadays the agricultural landscape is dominated by large farms. Large farms have better means of applying new technologies, and therefore technological advances have been a driving force in changing the farming structure. New technologies continue to emerge, and their mastery and use in requires that farmers gather more information and make more complex technological choices. In particular, the advent of the Internet has opened vast opportunities for communication and business opportunities within the agricultural com- nity. But at the same time, it has created another class of complex issues that need to be addressed sooner rather than later. Farmers and agricultural researchers are faced with an overwhelming amount of information they need to analyze and synthesize to successfully manage all the facets of agricultural production. This daunting challenge requires new and complex approaches to farm management. A new type of agricultural management system requires active cooperation among multidisciplinary and multi-institutional teams and ref- ing of existing and creation of new analytical theories with potential use in agriculture. Therefore, new management agricultural systems must combine the newest achievements in many scientific domains such as agronomy, economics, mathematics, and computer science, to name a few.

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