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Improving the predictions of leaf photosynthesis during and after short-term heat stress with current rice models.

Ting SunXiaohu ZhangSuyu LvXuanhao LinJifeng MaJiaming LiuQizhao FangLiang TangLeilei LiuWeixing CaoBing LiuYan Zhu
Published in: Plant, cell & environment (2023)
In response to increasing global warming, extreme heat stress significantly alters photosynthetic production. While numerous studies have investigated the temperature effects on photosynthesis, factors like vapour pressure deficit (VPD), leaf nitrogen, and feedback of sink limitation during and after extreme heat stress remain underexplored. This study assessed photosynthesis calculations in seven rice growth models using observed maximum photosynthetic rate (P max ) during and after short-term extreme heat stress in multi-year environment-controlled experiments. Biochemical models (FvCB-type) outperformed light response curve-based models (LRC-type) when incorporating observed leaf nitrogen, photosynthetically active radiation, temperatures, and intercellular CO 2 concentration (C i ) as inputs. Prediction uncertainty during heat stress treatment primarily resulted from variation in temperatures and C i . Improving FVPD (the slope for the linear effect of VPD on C i /C a ) to be temperature-dependent, rather than constant as in original models, significantly improved C i prediction accuracy under heat stress. Leaf nitrogen response functions led to model variation in leaf photosynthesis predictions after heat stress, which was mitigated by calibrated nitrogen response functions based on active photosynthetic nitrogen. Additionally, accounting for observed differences in carbohydrate accumulation between panicles and stems during grain filling improved the feedback of sink limitation, reducing C i overestimation under heat stress treatments.
Keyphrases
  • heat stress
  • heat shock
  • climate change
  • radiation therapy
  • atomic force microscopy