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Huang, X., G. Huang, C. Yu, S. Ni, and L. Yu. (2017). A multiple crop model ensemble for improving broad-scale yield prediction using Bayesian model averaging. Field Crops Research, 211, 114–124.
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Winter, J. M., C.A. Young, V.K. Mehta, A.C. Ruane, M. Azarderakhsh, A. Davitt, K. McDonald, V.R. Haden, and C. Rosenzweig. (2017). Integrating water supply constraints into irrigated agricultural simulations of California. Environmental Modelling and Software, 96, 335–346.
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Wang, E., P. Matre, Z. Zhao, F. Ewert, A. Maiorano, R.P. Rötter, B.A. Kimball, M.J. Ottman, G.W. Wall, J.W. White, M.P. Reynolds, P.D. Alderman, P.K. Aggarwal, J. Anothai, B. Basso, C. Biernath, D. Cammarano, A.J. Challinor, G. De Sanctis, J. Doltra, E. Fereres, M. Garcia-Vila, S. Gayler, G. Hoogenboom, L.A. Hunt, R.C. Izaurralde, M. Jabloun, C.D. Jones, K.C. Kersebaum, A.-K. Koehler, L. Liu, C. Müller, S. Naresh Kumar, C. Nendel, G. O’Leary, Jø.E. Olesen, T. Palosuo, E. Priesack, E. Eyshi Rezaei, D. Ripoche, A.C. Ruane, M.A. Semenov, I. Shcherbak, C. Stöckle, P. Stratonovitch, T. Streck, I. Supit, F. Tao, P. Thorburn, K. Waha, D. Wallach, Z. Wang, J. Wolf, Y. Zhu, and S. Asseng. (2017). The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat Plants, 3.
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Houtkamp, J., I. La Rivière, H. de Groot, S. Janssen, and A. de Jong. (2016). From Research Data to Web-Based Policy Tools: User-Centered Design Techniques in the Development of the AgMIP Impacts Explorer. In and A.R.Pérez M. Sánchez J. Sabine Sauvage (Ed.), Proceedings of the 8th International Congress on Environmental Modelling and Software.
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Marin, F., J.W. Jones, and K. J. Boote. (2017). A Stochastic Method for Crop Models: Including Uncertainty in a Sugarcane Model. Agron. J., 109(2), 483–495.
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