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Next generation agricultural system data, models and knowledge products: Introduction

Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research in...

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Detalles Bibliográficos
Autores principales: Antle, John M., Jones, James W., Rosenzweig, Cynthia E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Applied Science [etc.] 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485643/
https://www.ncbi.nlm.nih.gov/pubmed/28701811
http://dx.doi.org/10.1016/j.agsy.2016.09.003
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author Antle, John M.
Jones, James W.
Rosenzweig, Cynthia E.
author_facet Antle, John M.
Jones, James W.
Rosenzweig, Cynthia E.
author_sort Antle, John M.
collection PubMed
description Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30–40 years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. The Special Issue is based on a “NextGen” study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP) with support from the Bill and Melinda Gates Foundation.
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spelling pubmed-54856432017-07-10 Next generation agricultural system data, models and knowledge products: Introduction Antle, John M. Jones, James W. Rosenzweig, Cynthia E. Agric Syst Article Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30–40 years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. The Special Issue is based on a “NextGen” study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP) with support from the Bill and Melinda Gates Foundation. Elsevier Applied Science [etc.] 2017-07 /pmc/articles/PMC5485643/ /pubmed/28701811 http://dx.doi.org/10.1016/j.agsy.2016.09.003 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Antle, John M.
Jones, James W.
Rosenzweig, Cynthia E.
Next generation agricultural system data, models and knowledge products: Introduction
title Next generation agricultural system data, models and knowledge products: Introduction
title_full Next generation agricultural system data, models and knowledge products: Introduction
title_fullStr Next generation agricultural system data, models and knowledge products: Introduction
title_full_unstemmed Next generation agricultural system data, models and knowledge products: Introduction
title_short Next generation agricultural system data, models and knowledge products: Introduction
title_sort next generation agricultural system data, models and knowledge products: introduction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485643/
https://www.ncbi.nlm.nih.gov/pubmed/28701811
http://dx.doi.org/10.1016/j.agsy.2016.09.003
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