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A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation SCI/SSCI论文
2016
Authors:  Confalonieri R.;  Bregaglio, S.;  Adam, M.;  Ruget, F.;  Li, T.;  Hasegawa, T.;  Yin, X. Y.;  Zhu, Y.;  Boote, K.;  Buis, S.;  Fumoto, T.;  Gaydon, D.;  Lafarge, T.;  Marcaida, M.;  Nakagawa, H.;  Ruane, A. C.;  Singh, B.;  Singh, U.;  Tang, L.;  Tao, F. L.;  Fugice, J.;  Yoshida, H.;  Zhang, Z.;  Wilson, L. T.;  Baker, J.;  Yang, Y. B.;  Masutomi, Y.;  Wallach, D.;  Acutis, M.;  Bouman, B.
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Model classification  Model parameterisation  Model ensemble  Model  structure  Rice  Uncertainty  crop models  sensitivity-analysis  climate-change  calibration  yield  wheat  uncertainty  water  plasticity  evolution  
Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions SCI/SSCI论文
2015
Authors:  Li T.;  Hasegawa, T.;  Yin, X. Y.;  Zhu, Y.;  Boote, K.;  Adam, M.;  Bregaglio, S.;  Buis, S.;  Confalonieri, R.;  Fumoto, T.;  Gaydon, D.;  Marcaida, M.;  Nakagawa, H.;  Oriol, P.;  Ruane, A. C.;  Ruget, F.;  Singh, B.;  Singh, U.;  Tang, L.;  Tao, F. L.;  Wilkens, P.;  Yoshida, H.;  Zhang, Z.;  Bouman, B.
Adobe PDF(680Kb)  |  Favorite  |  View/Download:217/72  |  Submit date:2015/12/09
Agmip  Climate Change  Crop-model Ensembles  Oryza Sativa  Yield  Prediction Uncertainty  Air Co2 Enrichment  High-temperature Stress  Elevated Co2  Spikelet  Fertility  Night Temperature  Carbon-dioxide  Growth  Sterility  Face  Productivity