The importance of species-specific and temperature-sensitive parameterisation of A/C i models: A case study using cotton (Gossypium hirsutum L.) and the automated 'OptiFitACi' R-package.

Leaf gas exchange measurements are an important tool for inferring a plant's photosynthetic biochemistry. In most cases, the responses of photosynthetic CO 2 assimilation to variable intercellular CO 2 concentrations (A/C i response curves) are used to model the maximum (potential) rate of carboxylation by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco, V cmax ) and the rate of photosynthetic electron transport at a given incident photosynthetically active radiation flux density (PAR; J PAR ). The standard Farquhar-von Caemmerer-Berry model is often used with default parameters of Rubisco kinetic values and mesophyll conductance to CO 2 (g m ) derived from tobacco that may be inapplicable across species. To study the significance of using such parameters for other species, here we measured the temperature responses of key in vitro Rubisco catalytic properties and g m in cotton (Gossypium hirsutum cv. Sicot 71) and derived V cmax and J 2000 (J PAR at 2000 µmol m -2  s -1 PAR) from cotton A/C i curves incrementally measured at 15°C-40°C using cotton and other species-specific sets of input parameters with our new automated fitting R package 'OptiFitACi'. Notably, parameterisation by a set of tobacco parameters produced unrealistic J 2000 :V cmax ratio of <1 at 25°C, two- to three-fold higher estimates of V cmax above 15°C, up to 2.3-fold higher estimates of J 2000 and more variable estimates of V cmax and J 2000 , for our cotton data compared to model parameterisation with cotton-derived values. We determined that errors arise when using a g m,25 of 2.3 mol m -2  s -1  MPa -1 or less and Rubisco CO 2 -affinities in 21% O 2 (K C 21%O2 ) at 25°C outside the range of 46-63 Pa to model A/C i responses in cotton. We show how the A/C i modelling capabilities of 'OptiFitACi' serves as a robust, user-friendly, and flexible extension of 'plantecophys' by providing simplified temperature-sensitivity and species-specificity parameterisation capabilities to reduce variability when modelling V cmax and J 2000 .