Wheat crop traits conferring high yield potential may also improve yield stability under climate change

IF 2.6 Q1 AGRONOMY in silico Plants Pub Date : 2023-07-01 DOI:10.1093/insilicoplants/diad013
Tommaso Stella, Heidi Webber, Ehsan Eyshi Rezaei, Senthold Asseng, Pierre Martre, Sibylle Dueri, Jose Rafael Guarin, Diego N L Pequeno, Daniel F Calderini, Matthew Reynolds, Gemma Molero, Daniel Miralles, Guillermo Garcia, Gustavo Slafer, Francesco Giunta, Yean-Uk Kim, Chenzhi Wang, Alex C Ruane, Frank Ewert
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Abstract

Abstract Increasing genetic wheat yield potential is considered by many as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulation model solution in the SIMPLACE framework to explore yield sensitivity to select trait characteristics (radiation use efficiency [RUE], fruiting efficiency and light extinction coefficient) across 34 locations representing the world’s wheat-producing environments, determining their relationship to increasing yields, yield variability and cultivar performance. The magnitude of the yield increase was trait-dependent and differed between irrigated and rainfed environments. RUE had the most prominent marginal effect on yield, which increased by about 45 % and 33 % in irrigated and rainfed sites, respectively, between the minimum and maximum value of the trait. Altered values of light extinction coefficient had the least effect on yield levels. Higher yields from improved traits were generally associated with increased inter-annual yield variability (measured by standard deviation), but the relative yield variability (as coefficient of variation) remained largely unchanged between base and improved genotypes. This was true under both current and future climate scenarios. In this context, our study suggests higher wheat yields from these traits would not increase climate risk for farmers and the adoption of cultivars with these traits would not be associated with increased yield variability.
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具有高产潜力的小麦作物性状也可能提高气候变化条件下的产量稳定性
提高小麦的遗传产量潜力被许多人认为是提高全球小麦产量和产量的关键,而消费模式将发生重大变化。气候变化使目标环境变得不可预测,改变了区域生产力,并可能增加产量的变异性,从而给育种带来挑战。在这里,我们使用SIMPLACE框架中的作物模拟模型解决方案来探索产量敏感性,以选择代表世界小麦生产环境的34个地点的性状特征(辐射利用效率[RUE],结果效率和光消系数),确定它们与增产,产量变异性和品种性能的关系。产量增加的幅度是性状依赖的,在灌溉和雨养环境中有所不同。RUE对产量的边际效应最为显著,在灌溉区和雨养区,该性状在最小值和最大值之间的边际效应分别约为45%和33%。消光系数的变化对产量水平的影响最小。改良性状的高产量通常与年际产量变异性(以标准差衡量)增加相关,但相对产量变异性(作为变异系数)在基本基因型和改良基因型之间基本保持不变。这在当前和未来的气候情景下都是正确的。在这种情况下,我们的研究表明,这些性状的小麦产量增加不会增加农民的气候风险,采用具有这些性状的品种不会增加产量变异性。
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来源期刊
in silico Plants
in silico Plants Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
4.70
自引率
9.70%
发文量
21
审稿时长
10 weeks
期刊最新文献
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