Accuracy of photorespiration and mitochondrial respiration in the light fitted by CO response model for photosynthesis.

INTRODUCTION

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.

METHODS

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.

RESULTS

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).

DISCUSSION

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.