Engineering Research Center of Ecology and Agricultural Use of Wetland, College of Agriculture, Yangtze University, Jingzhou 434025, Hubei, China.
Tasmanian Institute of Agriculture, University of Tasmania, Burnie 7250, Tasmania, Australia.
Sci Total Environ. 2022 Feb 20;808:152170. doi: 10.1016/j.scitotenv.2021.152170. Epub 2021 Dec 5.
Climate change (CC) in central China will change seasonal patterns of agricultural production through increasingly frequent extreme climatic events (ECEs). Breeding climate-resilient wheat (Triticum aestivum L.) genotypes may mitigate adverse effects of ECEs on crop productivity. To reveal crop traits conducive to long-term yield improvement in the target population of environments, we created 8,192 virtual genotypes with contrasting but realistic ranges of phenology, productivity and waterlogging tolerance. Using these virtual genotypes, we conducted a genotype (G) by environment (E) by management (M) factorial analysis (G×E×M) using locations distributed across the entire cereal cropping zone in mid-China. The G×E×M invoked locally-specific sowing dates under future climates that were premised on shared socioeconomic pathways SSP5-8.5, with a time horizon centred on 2080. Across the simulated adaptation landscape, productivity was primarily driven by yield components and phenology (average grain yield increase of 6-69% across sites with optimal combinations of these traits). When incident solar radiation was not limiting carbon assimilation, ideotypes with higher grain yields were characterised by earlier flowering, higher radiation-use efficiency and larger maximum kernel size. At sites with limited solar radiation, crops required longer growing periods to realise genetic yield potential, although higher radiation-use efficiency and larger maximum kernel size were again prospective traits enabling higher rates of yield gains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1,010 kg ha. Ideotypes with optimal G×M could mitigate yield penalty caused by waterlogging by up to 15% under future climates. These results help distil promising crop trait by best management practice combinations that enable higher yields and robust adaptation to future climates and more frequent extreme climatic events, including flash flooding and soil waterlogging.
气候变化(CC)将通过日益频繁的极端气候事件(ECEs)改变华中地区农业生产的季节性模式。培育具有气候抗逆性的小麦(Triticum aestivum L.)基因型可能会减轻 ECEs 对作物生产力的不利影响。为了揭示有利于目标环境群体长期产量提高的作物特性,我们创建了 8192 个具有不同但现实范围的物候、生产力和耐淹水特性的虚拟基因型。使用这些虚拟基因型,我们使用分布在中国中部整个谷物种植区的地点进行了基因型(G)与环境(E)与管理(M)的析因分析(G×E×M)。G×E×M 根据共享社会经济途径 SSP5-8.5 调用未来气候下的局部特定播种日期,时间范围以 2080 年为中心。在模拟的适应景观中,生产力主要由产量构成和物候决定(在这些性状具有最佳组合的各个地点,平均谷物产量增加 6-69%)。当入射太阳辐射不限制碳同化时,具有较高粒产量的理想型特征是开花较早、辐射利用效率较高和最大籽粒尺寸较大。在太阳辐射有限的地点,作物需要更长的生长时间才能实现遗传产量潜力,尽管较高的辐射利用效率和较大的最大籽粒尺寸再次成为实现更高产量增长速度的有前景的性状。到 2080 年,中国中部一些地区的极端渍水胁迫将对生产力产生重大影响,产量损失高达 1010 公斤/公顷。在未来气候下,具有最佳 G×M 的理想型可以将渍水引起的产量损失降低 15%。这些结果有助于提取具有更高产量和对未来气候以及更频繁的极端气候事件(包括洪水和土壤渍水)具有稳健适应能力的最佳管理实践组合的有希望的作物特性。