Berkley J. Walker and Donald R. Ort

There is 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 intercept 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 artifacts on Γ* determinations we used a combination of meta-analysis, modeling, and original measurements to develop a framework to accurately determine Ci*. Our modeling indicated that the impact of using linear fits could be minimized based on the measurement CO₂ range. We also propose a novel method of analyzing common intercept measurements using slope-intercept regression. Our modeling indicated that slope-intercept regression is a robust analytical tool that can help determine if a measurement is biased due to 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.