Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions.

@article{Li2015UncertaintiesIP,
  title={Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions.},
  author={Tao Li and Toshihiro Hasegawa and Xinyou Yin and Yan Zhu and Kenneth J. Boote and Myriam Adam and Simone Bregaglio and Samuel Buis and Roberto Confalonieri and Tamon Fumoto and Donald S. Gaydon and Manuel Marcaida and Hiroshi Nakagawa and Philippe Oriol and Alex C. Ruane and Françoise Ruget and Balwinder- Singh and Upendra Singh and Liang Tang and Fulu Tao and Paul Wilkens and Hiroe Yoshida and Zhao Zhang and Bas Bouman},
  journal={Global change biology},
  year={2015},
  volume={21 3},
  pages={
          1328-41
        }
}
Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes… CONTINUE READING
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