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

A - Papers appearing in refereed journals

Dueri, S., Brown, H., Asseng, S., Ewert, F., Webber, H., George, M., Craigie, R., Guarin, J. R., Pequeno, D. N. L., Stella, T., Ahmed, M., Alderman, P. D., Basso, B., Berger, A. G., Mujica, G. B., Cammarano, D., Chen, Y., Dumont, B., Rezaei, E. E., Fereres, E., Ferrise, R., Gaiser, T., Gao, Y., Garcia-Vila, M., Gayler, S., Hochman, Z., Hoogenboom, G., Kersebaum, K. C., Nendel, C., Olesen, J. E., Padovan, G., Palosuo, T., Priesack, E., Pullens, J. W. M., Rodríguez, A., Rotter, R. P., Ramos, M. R., Semenov, M. A., Senapati, N., Siebert, S., Srivastava, A. K., Stockle, C., Supit, I., Tao, F., Thorburn, P., Wang, E., Weber, T. K. D., Xiao, L., Zhao, C., Zhao, J., Zhao, Z., Zhu, Y. and Martre, P. 2022. Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment. Journal of Experimental Botany. 73 (16), pp. 5715-5729. https://doi.org/10.1093/jxb/erac221

AuthorsDueri, S., Brown, H., Asseng, S., Ewert, F., Webber, H., George, M., Craigie, R., Guarin, J. R., Pequeno, D. N. L., Stella, T., Ahmed, M., Alderman, P. D., Basso, B., Berger, A. G., Mujica, G. B., Cammarano, D., Chen, Y., Dumont, B., Rezaei, E. E., Fereres, E., Ferrise, R., Gaiser, T., Gao, Y., Garcia-Vila, M., Gayler, S., Hochman, Z., Hoogenboom, G., Kersebaum, K. C., Nendel, C., Olesen, J. E., Padovan, G., Palosuo, T., Priesack, E., Pullens, J. W. M., Rodríguez, A., Rotter, R. P., Ramos, M. R., Semenov, M. A., Senapati, N., Siebert, S., Srivastava, A. K., Stockle, C., Supit, I., Tao, F., Thorburn, P., Wang, E., Weber, T. K. D., Xiao, L., Zhao, C., Zhao, J., Zhao, Z., Zhu, Y. and Martre, P.
Abstract

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.

KeywordsMulti-model ensemble ; Sowing date; Sowing density; Tillering; Tiller mortality; Wheat; Yield potential
Year of Publication2022
JournalJournal of Experimental Botany
Journal citation73 (16), pp. 5715-5729
Digital Object Identifier (DOI)https://doi.org/10.1093/jxb/erac221
Web address (URL)https://academic.oup.com/jxb/advance-article/doi/10.1093/jxb/erac221/6612782
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Natural Environment Research Council
Funder project or codeDesigning Future Wheat (DFW) [ISPG]
ASSIST - Achieving Sustainable Agricultural Systems
Publisher's version
Output statusPublished
Publication dates
Online21 Jun 2022
Publication process dates
Accepted21 Jun 2022
PublisherOxford University Press (OUP)
ISSN0022-0957

Permalink - https://repository.rothamsted.ac.uk/item/98955/simulation-of-winter-wheat-response-to-variable-sowing-dates-and-densities-in-a-high-yielding-environment

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