Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science
James W. Jones,John M. Antle,Bruno Basso,Kenneth J. Boote,Richard T. Conant,Ian Foster,H. Charles J. Godfray,Mario Herrero,Richard E. Howitt,Sander Janssen,Brian Keating,Rafael Muñoz-Carpena,Cheryl H. Porter,Cynthia Rosenzweig,Tim Wheeler +14 more
TLDR
It is concluded that multiple platforms and multiple models are needed for model applications for different purposes, and the Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.About:
This article is published in Agricultural Systems.The article was published on 2017-07-01 and is currently open access. It has received 251 citations till now. The article focuses on the topics: Systems science & Information system.read more
Citations
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Journal ArticleDOI
Brief History of Agricultural Systems Modeling
James W. Jones,John M. Antle,Bruno Basso,Kenneth J. Boote,Richard T. Conant,Ian Foster,H. Charles J. Godfray,Mario Herrero,Richard E. Howitt,Sander Janssen,Brian Keating,Rafael Muñoz-Carpena,Cheryl H. Porter,Cynthia Rosenzweig,Tim Wheeler +14 more
TL;DR: The history of agricultural systems modeling is summarized and lessons learned are identified that can help guide the design and development of next generation of agricultural system tools and methods.
Book ChapterDOI
Principles of Systems
TL;DR: The feedback mechanism involved in all principles for artificial learning refers back to the notion of the control-circuit, which serves as a basis for the analysis and the design of feedback-control systems.
Journal ArticleDOI
A comparison of global agricultural monitoring systems and current gaps
Steffen Fritz,Linda See,Juan Carlos Laso Bayas,François Waldner,François Waldner,Damien Christophe Jacques,Inbal Becker-Reshef,A. K. Whitcraft,Bettina Baruth,Rogerio Bonifacio,Jim Crutchfield,Felix Rembold,Oscar Rojas,Anne Schucknecht,Marijn van der Velde,James P. Verdin,Bingfang Wu,Nana Yan,Liangzhi You,Sven Gilliams,Sander Mücher,Robert Tetrault,Inian Moorthy,Ian McCallum +23 more
TL;DR: This paper provides an overview of the eight main global and regional scale agricultural monitoring systems currently in operation and compares them based on the input data and models used, the outputs produced and other characteristics such as the role of the analyst, their interaction with other systems and the geographical scale at which they operate.
Journal ArticleDOI
Introducing digital twins to agriculture
TL;DR: The extent of digital twin adoption in agriculture is examined, light is shed on the concept and the benefits it brings, and an application-based roadmap for a more extended adoption is proposed.
References
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Journal ArticleDOI
IMPACT: Generic household-level databases and diagnostics tools for integrated crop-livestock systems analysis
Mario Herrero,Mario Herrero,E. González-Estrada,Philip K. Thornton,Philip K. Thornton,Carlos Quiros,Michael Waithaka,Roberto Ruiz,Gerrit Hoogenboom +8 more
TL;DR: The need for generic crop-livestock systems databases and data standards for comprehensive systems analysis in developing countries are outlined and IMPACT, a database and analysis tool that goes some way to meeting the demands that may be made of such systems data is described.
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Reduced state–variable tomato growth model
TL;DR: In this paper, the authors developed a dynamic tomato growth model with a minimum number of state variables to determine its applicability across different growing conditions, and the model could be easily adapted for simulating other greenhouse crops.
Journal ArticleDOI
Farm household models to analyse food security in a changing climate: a review
M.T. van Wijk,Mariana C. Rufino,Mariana C. Rufino,Dolapo K. Enahoro,David Parsons,Silvia Silvestri,Roberto O. Valdivia,Mario Herrero,Mario Herrero +8 more
TL;DR: In this article, the authors systematically reviewed the literature on farm household models, with emphasis on those focused on smallholder systems, and evaluated the models on their predictive ability to describe short-term food security of smallholder farm households under climate variability and under different scenarios of climate change.
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Improving Physiological Assumptions Of Simulation Models By Using Gene-Based Approaches
TL;DR: It can be concluded that understanding the genetic control of quantitative traits can guide improvements to simulation models in GeneGro to incorporate the effect of the Tip gene.
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New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.
TL;DR: Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data and make use of a new scenario design concept called representative agricultural pathways.
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