Arne M. Ratjen
University of Kiel
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Featured researches published by Arne M. Ratjen.
Computers and Electronics in Agriculture | 2015
Arne M. Ratjen; Henning Kage
We present a method of in-season model assessments using reference calculations.The method can be seen as an alternative for site-specific model parameterizations.Useful relative statements, about the expected yield are generated from BBCH39 on.The method is particularly beneficial for sites highly variable in yield. The site-specific average yield is a well-known value to most producers, thus the inter-annual yield variability is the actual target value of any yield forecast. Using mechanistic models for in-season yield forecasts may help to optimize crop management decisions such as absolute fertilizer rates. However, a biased simulated yield can limit the potential benefits and is often a consequence of yield limiting factors like preceding crop, not considered by the model. This paper outlines a methodology which uses site-specific, historical weather records for a relative yield prognosis (Yrel) via yield projections and reference calculations. In order to obtain the yield forecast in absolute terms, Yrel is then multiplied with average observed yield. The key benefit of this design is that the bias is mostly cancelled out, thereby improving the model accuracy. The used crop-soil model HumeWheat was developed and parameterized on a broad experimental database including several modern wheat cultivars. We assume that the broad parameterization of key-processes allows the detection of inter-annual yield variability, even without genotype- or site-specific model calibrations. Our first aim was to evaluate the general applicability of this new approach of yield forecasting empirically at different phenological stages. The second aim was to evaluate the impact of different soil and weather conditions on forecast accuracy. Yield observations from several modern bread wheat cultivars (Triticum aestivum L.) were used to evaluate the method. For forecasts at the start of anthesis, the overall mean absolute error for yield (MAE, tha-1 dry matter) was reduced by 0.24 (or in relative terms 27%) compared to the assumption of treatment-specific (site?preceding crop) average yield. A subsequent simulation study with three different climate and varying water holding capacities water holding capacities reveals that a greater benefit can be expected for sites less stable in yield because of drought limitations.
Journal of Plant Nutrition and Soil Science | 2009
Arne M. Ratjen; Jóska Gerendás
Field Crops Research | 2013
Arne M. Ratjen; Henning Kage
Field Crops Research | 2012
Arne M. Ratjen; Ulf Böttcher; Henning Kage
The Journal of Agricultural Science | 2016
Arne M. Ratjen; Henning Kage
Journal of Agronomy and Crop Science | 2016
Arne M. Ratjen; D. Neukam; Henning Kage
Nutrient Cycling in Agroecosystems | 2014
Sabine Heumann; Arne M. Ratjen; Henning Kage; Jürgen Böttcher
Field Crops Research | 2018
Heidi Webber; Jeffrey W. White; Bruce A. Kimball; Frank Ewert; Senthold Asseng; Ehsan Eyshi Rezaei; Paul J. Pinter; Jerry L. Hatfield; Matthew P. Reynolds; Behnam Ababaei; Marco Bindi; Jordi Doltra; Roberto Ferrise; Henning Kage; Belay T. Kassie; Kurt Christian Kersebaum; Adam Luig; Jørgen E. Olesen; Mikhail A. Semenov; Pierre Stratonovitch; Arne M. Ratjen; Robert L. LaMorte; Steven W. Leavitt; Douglas J. Hunsaker; Gerard W. Wall; Pierre Martre
Journal of Agronomy and Crop Science | 2016
Arne M. Ratjen; Henning Kage
Nutrient Cycling in Agroecosystems | 2018
Arne M. Ratjen; Henning Kage