Article Dans Une Revue Journal of Experimental Botany Année : 2022

Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment

1 LEPSE - Écophysiologie des Plantes sous Stress environnementaux
2 Plant & Food Research - The New Zealand Institute for Plant & Food Research Limited [Auckland]
3 TUM - Technische Universität Munchen = Technical University Munich = Université Technique de Munich
4 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
5 INRES - Institut für Nutzpflanzenwissenschaften und Ressourcenschutz
6 BTU - Brandenburg University of Technology [Cottbus – Senftenberg]
7 FAR - Foundation for Arable Research
8 UF - University of Florida [Gainesville]
9 Earth Institute at Columbia University
10 CIMMYT - International Maize and Wheat Improvement Center
11 SLU - Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet
12 AAUR - Pir Mehr Ali Shah Arid Agriculture University = PMAS-Arid Agriculture University Rawalpindi
13 OSU - Oklahoma State University [Stillwater]
14 Michigan State University [East Lansing]
15 INIA - Instituto Nacional de Investigación Agropecuaria
16 Georg-August-University of Goettingen = Georg-August-Universität Göttingen
17 Aarhus University [Aarhus]
18 IGSNRR - Institute of geographical sciences and natural resources research [CAS]
19 [FUSAGx] - Gembloux Agro-Bio Tech [Faculté universitaire des sciences agronomiques de Gembloux]
20 IAS CSIC - Instituto de Agricultura Sostenible - Institute for Sustainable Agriculture
21 Universidad de Córdoba = University of Córdoba [Córdoba]
22 DAGRI - Department of Agriculture, Food, Environment and Forestry
23 INRES - Institute of Crop Science and Resource Conservation [Bonn]
24 Universität Hohenheim = University of Hohenheim
25 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Australia]
26 CzechGlobe - Global Change Research Centre
27 University of Potsdam = Universität Potsdam
28 LUKE - Natural Resources Institute Finland
29 HMGU - Helmholtz Zentrum München = German Research Center for Environmental Health
30 BIOP - Institute of Biochemical Plant Pathology
31 CEIGRAM - Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales
32 UCLM - Universidad de Castilla-La Mancha = University of Castilla-La Mancha
33 CBL - Centre for Biodiversity and Sustainable Land-use [University of Göttingen]
34 Rothamsted Research
35 WSU - Washington State University
36 WUR - Wageningen University and Research [Wageningen]
37 Zhejiang University [Hangzhou, China]
38 NAU - Nanjing Agricultural University
39 CAU - China Agricultural University
Davide Cammarano
Johannes W M Pullens
Mikhail A Semenov
Nimai Senapati

Résumé

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures.

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DOI

Cite 10.7910/DVN/XA4VA2 Jeu de données Dueri, S., Brown, H., Asseng, S., Ewert, F., Webber, H., George, M., Craigie, R., Guarin, J. R., Pequeno, D., Stella, T., Ahmed, M., Alderman, P. D., Basso, B., Berger, A. G., Bracho Mujica, G., Cammarano, D., Chen, Y., Dumont, B., Eyshi Rezaei, E., … Martre, P. (2022). Data from the winter wheat potential yield experiment in New Zealand and response to variable sowing dates and densities: field experiments and AgMIP-Wheat multi-model simulations (Version 2.0) [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/XA4VA2

Dates et versions

hal-03746248 , version 1 (05-08-2022)

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Sibylle Dueri, Hamish Brown, Senthold Asseng, Frank Ewert, Heidi Webber, et al.. Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment. Journal of Experimental Botany, 2022, 73 (16), pp.5715-5729. ⟨10.1093/jxb/erac221⟩. ⟨hal-03746248⟩
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