（一）作物模型不确定性

第一个专辑是European Journal of Agronomy在2017年8月出版的Uncertainty in crop model preductions。

本次专辑由Daniel Wallach, Peter J. Thorburn主编。主要有关作物模型不确定性方面的研究。具体的论文如下：

Daniel Wallach, Peter J. Thorburn,

Estimating uncertainty in crop model predictions: Current situation and future prospects,

European Journal of Agronomy,

Volume 88,

2017,

Pages A1-A7,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2017.06.001.

(http://www.sciencedirect.com/science/article/pii/S116103011730076X)

Keywords: uncertainty; crop model; structural uncertainty; parameter uncertainty; input uncertainty; model bias

Phillip D. Alderman, Bryan Stanfill,

Quantifying model-structure- and parameter-driven uncertainties in spring wheat phenology prediction with Bayesian analysis,

European Journal of Agronomy,

Volume 88,

2017,

Pages 1-9,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.09.016.

(http://www.sciencedirect.com/science/article/pii/S1161030116301800)

Keywords: Bayesian parameter estimation; Prediction uncertainty; Crop modeling; Agricultural systems modeling; Wheat phenology

Vera Porwollik, Christoph Müller, Joshua Elliott, James Chryssanthacopoulos, Toshichika Iizumi, Deepak K. Ray, Alex C. Ruane, Almut Arneth, Juraj Balkovič, Philippe Ciais, Delphine Deryng, Christian Folberth, Roberto C. Izaurralde, Curtis D. Jones, Nikolay Khabarov, Peter J. Lawrence, Wenfeng Liu, Thomas A.M. Pugh, Ashwan Reddy, Gen Sakurai, Erwin Schmid, Xuhui Wang, Allard de Wit, Xiuchen Wu,

Spatial and temporal uncertainty of crop yield aggregations,

European Journal of Agronomy,

Volume 88,

2017,

Pages 10-21,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.08.006.

(http://www.sciencedirect.com/science/article/pii/S1161030116301472)

Keywords: Aggregation uncertainty; Global crop model; Crop yields; Gridded data; Harvested area

R. Sándor, Z. Barcza, M. Acutis, L. Doro, D. Hidy, M. Köchy, J. Minet, E. Lellei-Kovács, S. Ma, A. Perego, S. Rolinski, F. Ruget, M. Sanna, G. Seddaiu, L. Wu, G. Bellocchi,

Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance,

European Journal of Agronomy,

Volume 88,

2017,

Pages 22-40,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.06.006.

(http://www.sciencedirect.com/science/article/pii/S1161030116301204)

Keywords: Biomass; Grasslands; Modelling; Multi-model ensemble; Soil processes

Matthias Kuhnert, Jagadeesh Yeluripati, Pete Smith, Holger Hoffmann, Marcel van Oijen, Julie Constantin, Elsa Coucheney, Rene Dechow, Henrik Eckersten, Thomas Gaiser, Balász Grosz, Edwin Haas, Kurt-Christian Kersebaum, Ralf Kiese, Steffen Klatt, Elisabet Lewan, Claas Nendel, Helene Raynal, Carmen Sosa, Xenia Specka, Edmar Teixeira, Enli Wang, Lutz Weihermüller, Gang Zhao, Zhigan Zhao, Stephen Ogle, Frank Ewert,

Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands,

European Journal of Agronomy,

Volume 88,

2017,

Pages 41-52,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.06.005.

(http://www.sciencedirect.com/science/article/pii/S1161030116301186)

Keywords: Net primary production; NPP; Scaling; Extreme events; Crop modelling; Climate; Data aggregation

Daniel Wallach, Sarath P. Nissanka, Asha S. Karunaratne, W.M.W. Weerakoon, Peter J. Thorburn, Kenneth J. Boote, James W. Jones,

Accounting for both parameter and model structure uncertainty in crop model predictions of phenology: A case study on rice,

European Journal of Agronomy,

Volume 88,

2017,

Pages 53-62,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.05.013.

(http://www.sciencedirect.com/science/article/pii/S1161030116301022)

Keywords: Uncertainty; Phenology; Parameter uncertainty; Multi-model ensemble; Generalized least squares; Rice; Crop model; APSIM; DSSAT

D. Cammarano, M. Rivington, K.B. Matthews, D.G. Miller, G. Bellocchi,

Implications of climate model biases and downscaling on crop model simulated climate change impacts,

European Journal of Agronomy,

Volume 88,

2017,

Pages 63-75,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.05.012.

(http://www.sciencedirect.com/science/article/pii/S1161030116301010)

Keywords: Climate model; Bias; Uncertainty; Downscaling; Bias correction; Crop simulation models; Barley

David Makowski,

A simple Bayesian method for adjusting ensemble of crop model outputs to yield observations,

European Journal of Agronomy,

Volume 88,

2017,

Pages 76-83,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2015.12.012.

(http://www.sciencedirect.com/science/article/pii/S1161030115300873)

Keywords: Bayesian method; Climate change; Ensemble modelling; Uncertainty; Yield

Julian Ramirez-Villegas, Ann-Kristin Koehler, Andrew J. Challinor,

Assessing uncertainty and complexity in regional-scale crop model simulations,

European Journal of Agronomy,

Volume 88,

2017,

Pages 84-95,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2015.11.021.

(http://www.sciencedirect.com/science/article/pii/S1161030115300666)

Keywords: GLAM; Parametric uncertainty; Groundnut; India; Model structure; Predictability

Edmar I. Teixeira, Gang Zhao, John de Ruiter, Hamish Brown, Anne-Gaelle Ausseil, Esther Meenken, Frank Ewert,

The interactions between genotype, management and environment in regional crop modelling,

European Journal of Agronomy,

Volume 88,

2017,

Pages 106-115,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2016.05.005.

(http://www.sciencedirect.com/science/article/pii/S1161030116300922)

Keywords: Apsim; Corn; Clustering; Spatial modelling; Uncertainty; Sensitivity

J. Sexton, Y.L. Everingham, G. Inman-Bamber,

A global sensitivity analysis of cultivar trait parameters in a sugarcane growth model for contrasting production environments in Queensland, Australia,

European Journal of Agronomy,

Volume 88,

2017,

Pages 96-105,

ISSN 1161-0301,

https://doi.org/10.1016/j.eja.2015.11.009.

(http://www.sciencedirect.com/science/article/pii/S1161030115300563)

Keywords: APSIM; Sugarcane; Sensitivity; Cultivar; Bayesian; Trait

（二）下一代作物模型

第二个专辑2017年Agricultural System上关于下一代作物模型的，由James W.Jones等领衔主编。主要的论文如下：

John M. Antle, James W. Jones, Cynthia Rosenzweig,

Next generation agricultural system models and knowledge products: Synthesis and strategy,

Agricultural Systems,

Volume 155,

2017,

Pages 179-185,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2017.05.006.

(http://www.sciencedirect.com/science/article/pii/S0308521X17304511)

John M. Antle, James W. Jones, Cynthia E. Rosenzweig,

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

Agricultural Systems,

Volume 155,

2017,

Pages 186-190,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.09.003.

(http://www.sciencedirect.com/science/article/pii/S0308521X16304887)

Keywords: Agricultural systems; Data; Models; Knowledge products; Next generation

Susan M. Capalbo, John M. Antle, Clark Seavert,

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making,

Agricultural Systems,

Volume 155,

2017,

Pages 191-199,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.10.009.

(http://www.sciencedirect.com/science/article/pii/S0308521X16306898)

Keywords: Data systems; Knowledge products; AgBizLogic; TOA-MD; Next generation

Sander J.C. Janssen, Cheryl H. Porter, Andrew D. Moore, Ioannis N. Athanasiadis, Ian Foster, James W. Jones, John M. Antle,

Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology,

Agricultural Systems,

Volume 155,

2017,

Pages 200-212,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.09.017.

(http://www.sciencedirect.com/science/article/pii/S0308521X16305637)

Keywords: Agricultural models; ICT; Linked data; Big data; Open science; Sensing; Visualization

M. Donatelli, R.D. Magarey, S. Bregaglio, L. Willocquet, J.P.M. Whish, S. Savary,

Modelling the impacts of pests and diseases on agricultural systems,

Agricultural Systems,

Volume 155,

2017,

Pages 213-224,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2017.01.019.

(http://www.sciencedirect.com/science/article/pii/S0308521X1730104X)

Keywords: Model coupling; Model integration; Process-based models; Yield loss; Modelling frameworks

C. Hwang, M.J. Correll, S.A. Gezan, L. Zhang, M.S. Bhakta, C.E. Vallejos, K.J. Boote, J.A. Clavijo-Michelangeli, J.W. Jones,

Next generation crop models: A modular approach to model early vegetative and reproductive development of the common bean (Phaseolus vulgaris L),

Agricultural Systems,

Volume 155,

2017,

Pages 225-239,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.10.010.

(http://www.sciencedirect.com/science/article/pii/S0308521X16306886)

Keywords: Gene-based crop model; G by E effects; Modular; Dynamic QTL effect model; Node addition rate; Time to first anthesis

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 A. Keating, Rafael Munoz-Carpena, Cheryl H. Porter, Cynthia Rosenzweig, Tim R. Wheeler,

Brief history of agricultural systems modeling,

Agricultural Systems,

Volume 155,

2017,

Pages 240-254,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.05.014.

(http://www.sciencedirect.com/science/article/pii/S0308521X16301585)

Keywords: Agricultural systems; Models; Next generation; Data; History

John M Antle, Bruno Basso, Richard T Conant, H Charles J Godfray, James W Jones, Mario Herrero, Richard E Howitt, Brian A Keating, Rafael Munoz-Carpena, Cynthia Rosenzweig, Pablo Tittonell, Tim R Wheeler,

Towards a new generation of agricultural system data, models and knowledge products: Design and improvement,

Agricultural Systems,

Volume 155,

2017,

Pages 255-268,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.10.002.

(http://www.sciencedirect.com/science/article/pii/S0308521X16306096)

Keywords: Agriculture; Systems; Models; Data; Knowledge products; Next generation

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 A. Keating, Rafael Munoz-Carpena, Cheryl H. Porter, Cynthia Rosenzweig, Tim R. Wheeler,

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science,

Agricultural Systems,

Volume 155,

2017,

Pages 269-288,

ISSN 0308-521X,

https://doi.org/10.1016/j.agsy.2016.09.021.

(http://www.sciencedirect.com/science/article/pii/S0308521X1630590X)

Keywords: Integrated agricultural systems models; Crop models; Economic models; Livestock models; Use cases; Agricultural data