There is a growing interest in accurate and comparable measurements of the CO2 photocompensation point (Γ*), a vital parameter to model leaf photosynthesis. The Γ* is measured as the common intersection of several CO2 response curves, but this method may incorrectly estimate Γ* by using linear fits to extrapolate curvilinear responses and single conductances to convert intercellular photocompensation points (Ci*) to chloroplastic Γ*. To determine the magnitude and minimize the impact of these artefacts on Γ* determinations, we used a combination of meta-analysis, modelling and original measurements to develop a framework to accurately determine Ci*. Our modelling indicated that the impact of using linear fits could be minimized based on the measurement CO2 range. We also propose a novel method of analysing common intersection measurements using slope-intercept regression. Our modelling indicated that slope-intercept regression is a robust analytical tool that can help determine if a measurement is biased because of multiple internal conductances to CO2. Application of slope-intercept regression to Nicotiana tabacum and Glycine max revealed that multiple conductances likely have little impact to Ci* measurements in these species. These findings present a robust and easy to apply protocol to help resolve key questions concerning CO2 conductance through leaves.
ASJC Scopus subject areas
- Plant Science