TY - JOUR
T1 - Crop traits enabling yield gains under more freq.uent extreme climatic events
AU - Yan, Haoliang
AU - Harrison, Matthew Tom
AU - Liu, Ke
AU - Wang, Bin
AU - Feng, Puyu
AU - Fahad, Shah
AU - Meinke, Holger
AU - Yang, Rui
AU - Liu, De Li
AU - Archontoulis, Sotirios
AU - Huber, Isaiah
AU - Tian, Xiaohai
AU - Man, Jianguo
AU - Zhang, Yunbo
AU - Zhou, Meixue
N1 - Publisher Copyright:
© 2021 The Authors
PY - 2022/2/20
Y1 - 2022/2/20
N2 - 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 environment, we created 8192 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 grains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1010 kg ha−1. 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 extreme climatic events, such as flash flooding and soil waterlogging.
AB - 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 environment, we created 8192 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 grains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1010 kg ha−1. 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 extreme climatic events, such as flash flooding and soil waterlogging.
KW - Climate change
KW - Crop model
KW - Model parameters
KW - Waterlogging stress
KW - Wheat ideotypes
UR - http://www.scopus.com/inward/record.url?scp=85120784743&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2021.152170
DO - 10.1016/j.scitotenv.2021.152170
M3 - Article
C2 - 34875326
AN - SCOPUS:85120784743
SN - 0048-9697
VL - 808
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 152170
ER -