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
The HADES Yield Prediction System - A Case Study on the Turkish Hazelnut Sector.
Simone Bregaglio,Kim Fischer,Fabrizio Ginaldi,Taynara Tuany Borges Valeriano,Laura Giustarini +4 more
TL;DR: In this article, the authors presented HADES (HAzelnut yielD forEcaSt), a hazelnut yield prediction system, in which process-based modelling and machine learning techniques are hybridized and applied in Turkey.
Book ChapterDOI
Geo-ICDTs: Principles and Applications in Agriculture
TL;DR: This chapter closely discusses the MMA (monitoring, management and adaptation) framework, its components and their implementation in precision agriculture.
Journal ArticleDOI
Clisagri: An R package for agro-climate services
TL;DR: A new climate service tool Clisagri has been developed for the agricultural sector that models the risk of unfavourable climate events during crop growth and enables targeting sensitive growth stages.
Journal ArticleDOI
Data requirements for crop modelling - applying the learning curve approach to the simulation of winter wheat flowering time under climate change.
M. Montesino-San Martin,Daniel Wallach,Jes Olesen,Andrew J. Challinor,M.P Hoffman,Ann-Kristin Koehler,Reimund P. Rötter,John R. Porter,John R. Porter +8 more
TL;DR: In this paper, the learning curve of two winter wheat phenology models is analyzed under different assumptions about the size of the calibration dataset, the measurement error and the accuracy of the model structure.
Journal ArticleDOI
Use of identifiability analysis in designing phenotyping experiments for modelling forage production and quality.
TL;DR: It is demonstrated that identifiability analysis improves experimental design to ensure independent parameter estimation for yield and quality outputs of a complex grassland model.
References
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Book
Spatial Econometrics: Methods and Models
TL;DR: In this article, a typology of Spatial Econometric Models is presented, and the maximum likelihood approach to estimate and test Spatial Process Models is proposed, as well as alternative approaches to Inference in Spatial process models.
Journal ArticleDOI
Estimación lineal de los requerimientos nutricionales del NRC para ganado de leche
TL;DR: Linear regression equations have been obtained to directly calculate the nutrient requirements of dairy cattle (TDN, DE, ME, NEL,CP, Ca, P, Vitamin A and Vitamin D) on different physiological stages: maintenance, pregnancy and milk production based on NRC nutrient requirements tables.
Journal ArticleDOI
Climate change : the IPCC scientific assessment
TL;DR: A review of the intergovernmental panel on climate change report on global warming and the greenhouse effect can be found in this paper, where the authors present chemistry of greenhouse gases and mathematical modelling of the climate system.
Journal ArticleDOI
The DSSAT cropping system model
James W. Jones,Gerrit Hoogenboom,Cheryl H. Porter,Kenneth J. Boote,William D. Batchelor,L. A. Hunt,Paul W. Wilkens,Upendra Singh,Arjan J. Gijsman,Joe T. Ritchie +9 more
TL;DR: The benefits of the new, re-designed DSSAT-CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.
Journal ArticleDOI
Climate Trends and Global Crop Production Since 1980
TL;DR: It was found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability.
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