Abstract
INTRODUCTION: Atmospheric CO(2) elevation significantly impacts plant carbon metabolism, yet accurate quantification of respiratory parameters-photorespiration rate (R(p)) and mitochondrial respiration rate in the light (R(d))-under varying CO(2) remains challenging. Current CO(2)-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(2) recovery/inhibition ratio in of wheat (Triticum aestivum L.) and bean (Glycine max L.) were employed to elucidate the biological significance and interrelationships of R(p) and R(d). Model-derived estimates of R(p) and R(d) were compared with measured values to assess the accuracy of three CO(2)-response models (biochemical, rectangular hyperbola, modified rectangular hyperbola). Furthermore, the effects of ambient CO(2) concentration (0~1200 μmol·mol(-1)) on the measured R(p) and R(d) were quantified through polynomial regression. RESULTS: The A/C(a) model achieved superior fitting performance over the A/Ci model. However, significant disparities persisted between A/Ca-derived R(p)/R(d) estimates and measurements (p < 0.05). CO(2) concentration exhibited dose-dependent regulation of respiratory fluxes: R(p-measured) ranged from 4.923 ± 0.171 to 12.307 ± 1.033 μmol (CO(2)) m(-2) s(-1) (wheat) and 4.686 ± 0.274 to 11.673 ± 2.054 μmol (CO(2)) m(-2) s(⁻ ¹) (bean), while R(d-measured) varied from 0.618 ± 0.131 to 3.021 ± 0.063 μmol (CO(2)) m(-2) s(-1) (wheat) and 0.492 ± 0.069 to 2.323 ± 0.312 μmol (CO(2)) m(-2) s(-1) (bean). Polynomial regression revealed strong non-linear correlations between CO(2) concentrations and respiratory parameters (R(²) > 0.891, p < 0.05; except bean R(p-)C(a): R(²) = 0.797). Species-specific CO(2) thresholds governed peak R(p) (600 μmol·mol(-1) for wheat vs. 1,000 μmol·mol(-1) for bean) and R(d) (400 μmol·mol(-1) for wheat vs. 200 μmol·mol(-1) for bean). DISCUSSION: These findings expose critical limitations in current respiratory parameter quantification methods and challenge linear assumptions of CO(2)-respiration relationships. They establish a critical framework for refining photosynthetic models by incorporating CO(2)-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(2), with implications for climate-resilient agricultural practices.