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Validating CERES-wheat under North-German environmental conditions

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  • Langensiepen, M.
  • Hanus, H.
  • Schoop, P.
  • Gräsle, W.

Abstract

The predictive quality of CERES-wheat was tested under contrasting nitrogen management and temperate-maritime climate conditions of North-Germany. Field data from 9 years of observations were used in this study. The magnitudes of the genetic parameters of the local wheat cultivar "Orestis" were strongly influenced by seasonal weather fluctuations. For predicted yield and harvest biomass, the root mean square error was 2.2 t/ha and 3.2 t/ha, respectively. These errors were too large to permit a practical application of the CERES-wheat model for optimizing fertilizer management under the production conditions of North-Germany. The results of this study suggest that the model needs to be considerably improved with respect to the simulation of soil and plant water-relations, as well as the interaction between water and nitrogen uptake which were found to be inconsistent.

Suggested Citation

  • Langensiepen, M. & Hanus, H. & Schoop, P. & Gräsle, W., 2008. "Validating CERES-wheat under North-German environmental conditions," Agricultural Systems, Elsevier, vol. 97(1-2), pages 34-47, April.
    • Handle: RePEc:eee:agisys:v:97:y:2008:i:1-2:p:34-47
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    References listed on IDEAS

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    1. Timsina, J. & Humphreys, E., 2006. "Performance of CERES-Rice and CERES-Wheat models in rice-wheat systems: A review," Agricultural Systems, Elsevier, vol. 90(1-3), pages 5-31, October.
    2. Sadler, E. J. & Gerwig, B. K. & Evans, D. E. & Busscher, W. J. & Bauer, P. J., 2000. "Site-specific modeling of corn yield in the SE coastal plain," Agricultural Systems, Elsevier, vol. 64(3), pages 189-207, June.
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    1. Braune, Henning & Müller, Johannes & Diepenbrock, Wulf, 2009. "Integrating effects of leaf nitrogen, age, rank, and growth temperature into the photosynthesis-stomatal conductance model LEAFC3-N parameterised for barley (Hordeum vulgare L.)," Ecological Modelling, Elsevier, vol. 220(13), pages 1599-1612.
    2. Zhang, Yuxi & Walker, Jeffrey P. & Pauwels, Valentijn R.N., 2022. "Assimilation of wheat and soil states for improved yield prediction: The APSIM-EnKF framework," Agricultural Systems, Elsevier, vol. 201(C).
    3. Yao, Ning & Li, Yi & Xu, Fang & Liu, Jian & Chen, Shang & Ma, Haijiao & Wai Chau, Henry & Liu, De Li & Li, Meng & Feng, Hao & Yu, Qiang & He, Jianqiang, 2020. "Permanent wilting point plays an important role in simulating winter wheat growth under water deficit conditions," Agricultural Water Management, Elsevier, vol. 229(C).

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