Edward B. Lochocki, Coralie E. Salesse-Smith, Justin M. McGrath

Fitting mechanistic models, such as the Farquhar-von-Caemmerer-Berry model, to experimentally measured photosynthetic CO₂ response curves (A-C_i curves) is a widely used technique for estimating the values of key leaf biochemical parameters and determining limitations to photosynthesis in vivo. Here, we present PhotoGEA, an R package with tools for C₃ A-C_i, C₃ Variable J and C₄ A-C_i curve fitting. In contrast to existing software, these automated tools use derivative-free optimizers to ensure close fits and they calculate non-Gaussian confidence intervals to indicate which parameter values are most reliable. Results from PhotoGEA's C₃ A-C_i curve fitting tool are compared against other available tools, where it is found to achieve the closest fits and most reasonable parameter estimates across a range of curves with different characteristics. PhotoGEA's C₃ Variable J and C₄ A-C_i fitting tools are also presented, demonstrating how they can provide insights into mesophyll conductance and the processes limiting C₄ photosynthesis at high CO₂ concentrations. PhotoGEA enables users to develop data analysis pipelines for efficiently reading, processing, fitting and analysing photosynthetic gas exchange measurements. It includes extensive documentation and example scripts to help new users become proficient as quickly as possible.