Software for Fitting Photosynthetic CO₂ or Light Response Curves

A frequent question from LI-6800 and LI-6400XT users is a request for software resources for fitting the Farquhar, von Caemmerer and Berry (FvCB) model of photosynthesis (Farquhar, von Caemmerer & Berry 1980). There is a wealth of literature on this topic and a variety of methods developed to fit the model. There are currently no commercial software packages available for this purpose. Several software packages are, however, freely available for fitting the FvCB model of photosynthesis. Some approaches use only gas exchange data, while others combine gas exchange with chlorophyll fluorescence. LI-COR does not endorse or validate any of these approaches, but leaves it up to the user to choose the best model fit for their data.

C3 A/Ci curve fitting

Peer-reviewed

1

Duursma RA (2015) Plantecophys - An R Package for Analysing and Modelling Leaf Gas Exchange Data. PLOS ONE 10(11): e0143346. https://doi.org/10.1371/journal.pone.0143346. R package: https://bitbucket.org/remkoduursma/plantecophys/src/master/

2

Lei, T., Rizzo, K.T. & Bailey, B.N. PhoTorch: a robust and generalized biochemical photosynthesis model fitting package based on PyTorch. Photosynth Res 163, 21 (2025). https://doi.org/10.1007/s11120-025-01136-7. Python package: https://github.com/GEMINI-Breeding/photorch

Other

3

Fitting A/Ci curves with simple R scripts and a shiny interface: https://github.com/poales/msuRACiFit

Fitting the FvCB model to CO₂ Response Curves

Peer-reviewed

4

Sharkey, T. D. (2016) What gas exchange data can tell us about photosynthesis. Plant, Cell & Environment, 39: 1161–1163. https://doi.org/10.1111/pce.12641.

5

Dubois, J.-J.B., Fiscus, E.L., Booker, F.L., Flowers, M.D. and Reid, C.D. (2007), Optimizing the statistical estimation of the parameters of the Farquhar–von Caemmerer–Berry model of photosynthesis. New Phytologist, 176: 402-414. https://doi.org/10.1111/j.1469-8137.2007.02182.x

6

Web-based Exhaustive Dual Optimization (EDO) approach from Gu et al., 2010 at https://leafweb.org

Other

7

Excel spreadsheet: https://www.life.illinois.edu/bernacchi/links.html

8

Excel spreadsheet: https://landflux.org/tools

9

R code: https://www.fridleylab.org/protocols

10

R code 'photosynthesis' with modeling tools for C3 photosynthesis with analytic tools for curve-fitting plant ecophysiology responses: https://github.com/cdmuir/photosynthesis

Combined Gas Exchange and Chlorophyll Fluorescence Data

11

Lochocki, E.B., Salesse-Smith, C.E. and McGrath, J.M. (2025), PhotoGEA: An R Package for Closer Fitting of Photosynthetic Gas Exchange Data With Non-Gaussian Confidence Interval Estimation. Plant, Cell & Environment. https://doi.org/10.1111/pce.15501. https://eloch216.github.io/PhotoGEA/

12

Bellasio, C., Beerling, D. J., and Griffiths, H. (2016) An Excel tool for deriving key photosynthetic parameters from combined gas exchange and chlorophyll fluorescence: theory and practice. Plant, Cell & Environment, 39: 1180–1197. https://doi.org/10.1111/pce.12560.

13

Moualeu-Ngangue, D.P., Chen, T.-W. and Stützel, H. (2017), A new method to estimate photosynthetic parameters through net assimilation rate−intercellular space CO2 concentration (A−Ci) curve and chlorophyll fluorescence measurements. New Phytol, 213: 1543-1554. https://doi.org/10.1111/nph.14260

Fitting Models to Light Response Curves

Peer-reviewed

14

Danny Tholen, GasanalyzeR: advancing reproducible research using a new R package for photosynthesis data workflows. (2024), AoB PLANTS 16, 4. https://doi.org/10.1093/aobpla/plae035.

15

de Lobo, F.A., de Barros, M.P., Dalmagro, H.J., Dalmolin, Â.C., Pereira, W.E., de Souza, É.C., Vourlitis, G.L., & Rodríguez Ortíz, C.E. (2013). Fitting net photosynthetic light-response curves with Microsoft Excel - a critical look at the models. Photosynthetica, 51(3), 445-456. https://doi.org/10.1007/s11099-013-0045-y.

References

16

Farquhar, G.D., von Caemmerer, S. and Berry, J.A. (1980). A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 149(1), pp.78–90. https://doi.org/10.1007/bf00386231.