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Agronomy 2019, 9(3), 120; https://doi.org/10.3390/agronomy9030120

Development and Evaluation of a Leaf Disease Damage Extension in Cropsim-CERES Wheat

1
Department of Agronomy, Institute of Crop Science, University of Hohenheim, 70599 Stuttgart, Germany
2
Biosystems Engineering Department, Auburn University, Auburn, AL 36849, USA
3
Cerealicultura, Facultad de Ciencias Agrarias y Forestales, Universidad Nacional de La Plata, Av. 60 y 119, La Plata 1900, Argentina
4
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Centro Científico Tecnológico (CCT), La Plata 1900, Argentina
5
Comisión de Investigaciones Científicas, Pcia. de Buenos Aires, 526, 10 y 11, La Plata 1900, Argentina
*
Author to whom correspondence should be addressed.
Received: 10 January 2019 / Revised: 26 February 2019 / Accepted: 1 March 2019 / Published: 2 March 2019
(This article belongs to the Special Issue Remote Sensing Applications for Agriculture and Crop Modelling)
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Abstract

Developing disease models to simulate and analyse yield losses for various pathogens is a challenge for the crop modelling community. In this study, we developed and tested a simple method to simulate septoria tritici blotch (STB) in the Cropsim-CERES Wheat model studying the impacts of damage on wheat (Triticum aestivum L.) yield. A model extension was developed by adding a pest damage module to the existing wheat model. The module simulates the impact of daily damage on photosynthesis and leaf area index. The approach was tested on a two-year dataset from Argentina with different wheat cultivars. The accuracy of the simulated yield and leaf area index (LAI) was improved to a great extent. The Root mean squared error (RMSE) values for yield (1144 kg ha−1) and LAI (1.19 m2 m−2) were reduced by half (499 kg ha−1) for yield and LAI (0.69 m2 m−2). In addition, a sensitivity analysis of different disease progress curves on leaf area index and yield was performed using a dataset from Germany. The sensitivity analysis demonstrated the ability of the model to reduce yield accurately in an exponential relationship with increasing infection levels (0–70%). The extended model is suitable for site specific simulations, coupled with for example, available remote sensing data on STB infection. View Full-Text
Keywords: wheat; disease; yield; septoria tritici blotch; leaf area index; crop modelling; decision support system for agrotechnology transfer (DSSAT); Cropsim-CERES Wheat wheat; disease; yield; septoria tritici blotch; leaf area index; crop modelling; decision support system for agrotechnology transfer (DSSAT); Cropsim-CERES Wheat
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Röll, G.; Batchelor, W.D.; Castro, A.C.; Simón, M.R.; Graeff-Hönninger, S. Development and Evaluation of a Leaf Disease Damage Extension in Cropsim-CERES Wheat. Agronomy 2019, 9, 120.

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