Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment. (21st June 2022)
- Record Type:
- Journal Article
- Title:
- Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment. (21st June 2022)
- Main Title:
- Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment
- Authors:
- Dueri, Sibylle
Brown, Hamish
Asseng, Senthold
Ewert, Frank
Webber, Heidi
George, Mike
Craigie, Rob
Guarin, Jose Rafael
Pequeno, Diego N L
Stella, Tommaso
Ahmed, Mukhtar
Alderman, Phillip D
Basso, Bruno
Berger, Andres G
Mujica, Gennady Bracho
Cammarano, Davide
Chen, Yi
Dumont, Benjamin
Rezaei, Ehsan Eyshi
Fereres, Elias
Ferrise, Roberto
Gaiser, Thomas
Gao, Yujing
Garcia-Vila, Margarita
Gayler, Sebastian
Hochman, Zvi
Hoogenboom, Gerrit
Kersebaum, Kurt C
Nendel, Claas
Olesen, Jørgen E
Padovan, Gloria
Palosuo, Taru
Priesack, Eckart
Pullens, Johannes W M
Rodríguez, Alfredo
Rötter, Reimund P
Ramos, Margarita Ruiz
Semenov, Mikhail A
Senapati, Nimai
Siebert, Stefan
Srivastava, Amit Kumar
Stöckle, Claudio
Supit, Iwan
Tao, Fulu
Thorburn, Peter
Wang, Enli
Weber, Tobias Karl David
Xiao, Liujun
Zhao, Chuang
Zhao, Jin
Zhao, Zhigan
Zhu, Yan
Martre, Pierre
… (more) - Editors:
- Rebetzke, Greg
- Abstract:
- Abstract : An ensemble of 29 wheat crop models simulates seasonal wheat growth well under locally recommended sowing conditions, but needs improvements to capture the yield response to early sowing, especially under high sowing density. 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 tillerAbstract : An ensemble of 29 wheat crop models simulates seasonal wheat growth well under locally recommended sowing conditions, but needs improvements to capture the yield response to early sowing, especially under high sowing density. 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. … (more)
- Is Part Of:
- Journal of experimental botany. Volume 73:Number 16(2022)
- Journal:
- Journal of experimental botany
- Issue:
- Volume 73:Number 16(2022)
- Issue Display:
- Volume 73, Issue 16 (2022)
- Year:
- 2022
- Volume:
- 73
- Issue:
- 16
- Issue Sort Value:
- 2022-0073-0016-0000
- Page Start:
- 5715
- Page End:
- 5729
- Publication Date:
- 2022-06-21
- Subjects:
- Multi-model ensemble -- sowing date -- sowing density -- tillering -- tiller mortality -- wheat -- yield potential
Botany -- Periodicals
Botany, Experimental -- Periodicals
Plant physiology -- Periodicals
580 - Journal URLs:
- http://ukcatalogue.oup.com/ ↗
http://jxb.oxfordjournals.org/ ↗ - DOI:
- 10.1093/jxb/erac221 ↗
- Languages:
- English
- ISSNs:
- 0022-0957
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4981.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23290.xml