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Acknowledgement to Reviewers of Agronomy in 2015
Open AccessArticle

Integrating Wheat Canopy Temperatures in Crop System Models

1
Agronomy and Crop Science, Institute of Crop Science and Plant Breeding, Christian-Albrechts-University of Kiel, Hermann-Rodewald-Str. 9, 24118 Kiel, Germany
2
Thünen Institute of Biodiversity, Federal Research Institute for Rural Areas, Forestry and Fisheries, Bundesallee 50, 38116 Braunschweig, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Philippe Debaeke
Agronomy 2016, 6(1), 7; https://doi.org/10.3390/agronomy6010007
Received: 21 November 2015 / Revised: 8 January 2016 / Accepted: 18 January 2016 / Published: 22 January 2016
(This article belongs to the Special Issue Practical Use of Crop Models in Agronomy)
Crop system models are generally parametrized with daily air temperatures recorded at 1.5 or 2 m height. These data are not able to represent temperatures at the canopy level, which control crop growth, and the impact of heat stress on crop yield, which are modified by canopy characteristics and plant physiological processes Since such data are often not available and current simulation approaches are complex and/or based on unrealistic assumptions, new methods for integrating canopy temperatures in the framework of crop system models are needed. Based on a forward stepwise-based model selection procedure and quantile regression analyses, we developed empirical regression models to predict winter wheat canopy temperatures obtained from thermal infrared observations performed during four growing seasons for three irrigation levels. We used daily meteorological variables and the daily output data of a crop system model as covariates. The standard cross validation revealed a root mean square error (RMSE) of ~0.8 °C, 1.5–2 °C and 0.8–1.2 °C for estimating mean, maximum and minimum canopy temperature, respectively. Canopy temperature of both water-deficit and fully irrigated wheat plots significantly differed from air temperature. We suggest using locally calibrated empirical regression models of canopy temperature as a simple approach for including potentially amplifying or mitigating microclimatic effects on plant response to temperature stress in crop system models. View Full-Text
Keywords: wheat; crop model; canopy temperature; drought stress; heat stress wheat; crop model; canopy temperature; drought stress; heat stress
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MDPI and ACS Style

Neukam, D.; Ahrends, H.; Luig, A.; Manderscheid, R.; Kage, H. Integrating Wheat Canopy Temperatures in Crop System Models. Agronomy 2016, 6, 7.

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