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1000 Titel
  • The potential of crop models in simulation of barley quality traits under changing climates: A review
1000 Autor/in
  1. Rezaei, Ehsan Eyshi |
  2. Rojas, Luis Vargas |
  3. Zhu, Wanxue |
  4. Cammarano, Davide |
1000 Erscheinungsjahr 2022
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2022-07-08
1000 Erschienen in
1000 Quellenangabe
  • 286:108624
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2022
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.fcr.2022.108624 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Most of the experimental and modeling studies that evaluate the impacts of climate change and variability on barley have been focused on grain yield. However, little is known on the effects of combined change in temperature, CO2 concentration, and extreme events on barley grain quality and how capable are the current process-based crop models capture the signal of climate change on quality traits. Here in this review, we initially explored the response of quality traits of barley to heat, drought, and CO2 concentration from experiential studies. Next, we reviewed the state of the art of some of the current modeling approaches to capture grain quality. Lastly, we suggested possible opportunities to improve current models for tracking the detailed quality traits of barley. Heat and drought stress increase the protein concentration which has a negative effect on malting quality. The rise of CO2 concentration significantly reduces the grain protein, again resulting in a decline of the malting and brewing quality since the nitrogen concentration of grains needs to be kept at a specific level. The current crop models that simulate barley grain quality are limited to simulation of grain nitrogen concentration, size, and number in response to climate extremes and CO2. Nevertheless, crop models fail to account for the complex interactions between the conflicting effects of rising temperatures and droughts as well as increasing CO2 concentrations on grain protein. They have mainly adapted wheat models that cannot capture barley’s protein composition and whole grain malting quality. Implementation of experiments from gene to canopy scales which are explicitly designed to detect the interactions among environmental variables on detailed quality traits and couple the remote sensing plus data-driven approaches to crop models are possible opportunities to improve modeling of barley grain quality. The development of modeling routines can capture the detailed grain quality provide valuable tools for forming climate adaptive strategies. Equally important, they can guide breeding programs to develop climate-resilient but high-quality barley genotypes.
1000 Sacherschließung
lokal Process-bases modeling
lokal Climate warming
lokal Barley
lokal Quality traits
lokal Extreme events
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/UmV6YWVpLCBFaHNhbiBFeXNoaQ==|https://frl.publisso.de/adhoc/uri/Um9qYXMsIEx1aXMgVmFyZ2Fz|https://frl.publisso.de/adhoc/uri/Wmh1LCBXYW54dWU=|https://frl.publisso.de/adhoc/uri/Q2FtbWFyYW5vLCBEYXZpZGU=
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1000 Erstellt am 2022-10-17T12:51:52.454+0200
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1000 Zuletzt bearbeitet 2023-01-03T10:53:12.541+0100
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