Niu Zhengwen, Ye Zi-Wu-Yin, Huang Qi, Peng Chunju, Kang Huajing
Wenzhou Key Laboratory of Agricultural & Forestry Carbon Sequestration and Tea Resource Development, Wenzhou Academy of Agricultural Sciences, Wenzhou, Zhejiang, China.
College of International Studies, Guangdong Baiyun University, Guangzhou, Guangdong, China.
Front Plant Sci. 2025 Aug 26;16:1455533. doi: 10.3389/fpls.2025.1455533. eCollection 2025.
Atmospheric CO elevation significantly impacts plant carbon metabolism, yet accurate quantification of respiratory parameters-photorespiration rate (R) and mitochondrial respiration rate in the light (R)-under varying CO remains challenging. Current CO-response models exhibit limitations in estimating these parameters, hindering predictions of crop responses under future climate scenarios.
Low-oxygen treatments and gas exchange measurements, calculating CO recovery/inhibition ratio in of wheat () and bean () were employed to elucidate the biological significance and interrelationships of R and R. Model-derived estimates of R and R were compared with measured values to assess the accuracy of three CO-response models (biochemical, rectangular hyperbola, modified rectangular hyperbola). Furthermore, the effects of ambient CO concentration (0~1200 μmol·mol) on the measured R and R were quantified through polynomial regression.
The A/C model achieved superior fitting performance over the A/Ci model. However, significant disparities persisted between A/Ca-derived R/R estimates and measurements ( < 0.05). CO concentration exhibited dose-dependent regulation of respiratory fluxes: R ranged from 4.923 ± 0.171 to 12.307 ± 1.033 μmol (CO) m s (wheat) and 4.686 ± 0.274 to 11.673 ± 2.054 μmol (CO) m s (bean), while R varied from 0.618 ± 0.131 to 3.021 ± 0.063 μmol (CO) m s (wheat) and 0.492 ± 0.069 to 2.323 ± 0.312 μmol (CO) m s (bean). Polynomial regression revealed strong non-linear correlations between CO concentrations and respiratory parameters (R > 0.891, < 0.05; except bean RC: R = 0.797). Species-specific CO thresholds governed peak R (600 μmol·mol for wheat vs. 1,000 μmol·mol for bean) and R (400 μmol·mol for wheat vs. 200 μmol·mol for bean).
These findings expose critical limitations in current respiratory parameter quantification methods and challenge linear assumptions of CO-respiration relationships. They establish a critical framework for refining photosynthetic models by incorporating CO-responsive respiratory mechanisms. The identified non-linear regulatory patterns and model limitations provide actionable insights for advancing carbon metabolism theory and optimizing crop carbon assimilation strategies under rising atmospheric CO, with implications for climate-resilient agricultural practices.
大气中二氧化碳浓度升高对植物碳代谢有显著影响，但在不同二氧化碳浓度下准确量化呼吸参数——光呼吸速率（R）和光下线粒体呼吸速率（R）仍然具有挑战性。目前的二氧化碳响应模型在估计这些参数方面存在局限性，阻碍了对未来气候情景下作物响应的预测。
采用低氧处理和气体交换测量，计算小麦（）和豆类（）的二氧化碳恢复/抑制率，以阐明R和R的生物学意义及相互关系。将模型推导的R和R估计值与测量值进行比较，以评估三种二氧化碳响应模型（生化模型、矩形双曲线模型、修正矩形双曲线模型）的准确性。此外，通过多项式回归量化环境二氧化碳浓度（0~1200 μmol·mol）对测量的R和R的影响。
A/C模型比A/Ci模型具有更好的拟合性能。然而，基于A/Ca推导的R/R估计值与测量值之间仍存在显著差异（<0.05）。二氧化碳浓度对呼吸通量表现出剂量依赖性调节：R范围为4.923±0.171至12.307±1.033 μmol（CO）m s（小麦）和4.686±0.274至11.673±2.054 μmol（CO）m s（豆类），而R在小麦中从0.618±0.131变化到3.021±0.063 μmol（CO）m s，在豆类中从0.492±0.069变化到2.323±0.312 μmol（CO）m s。多项式回归揭示了二氧化碳浓度与呼吸参数之间存在很强的非线性相关性（R>0.891，<0.05；豆类的Rc除外：R = 0.797）。特定物种的二氧化碳阈值决定了R的峰值（小麦为600 μmol·mol，豆类为1000 μmol·mol）和R的峰值（小麦为400 μmol·mol，豆类为200 μmol·mol）。
这些发现揭示了当前呼吸参数量化方法的关键局限性，并对二氧化碳与呼吸关系的线性假设提出了挑战。它们为通过纳入二氧化碳响应呼吸机制来完善光合模型建立了关键框架。所确定的非线性调节模式和模型局限性为推进碳代谢理论以及在大气二氧化碳浓度上升的情况下优化作物碳同化策略提供了可操作的见解，对适应气候变化的农业实践具有重要意义。
