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The automatic measurement of developmental and physiological responses ofsunflowers to water stress represents an applied challenge for a betterknowledge of the varieties available to growers, but also a fundamental one foridentifying the biological, genetic and molecular bases of plant response totheir environment.On INRAE Toulouse's Heliaphen high-throughput phenotypingplatform, we set up two experiments, each with 8 varieties (2*96 plants), andacquired images of plants subjected or not to water stress, using a lightbarrier on a daily basis. At the same time, we manually measured the leafsurfaces of these plants every other day for the duration of the stress, whichlasted around ten days. The images were analyzed to extract morphologicalcharacteristics of the segmented plants and different models were evaluated toestimate total plant leaf areas using these data.A linear model with aposteriori smoothing was used to estimate total leaf area with a relativesquared error of 11% and an efficiency of 93%. Leaf areas estimatedconventionally or with the developed model were used to calculate the leafexpansion and transpiration responses (LER and TR) used in the SUNFLO cropmodel for 8 sunflower varieties studied. Correlation coefficients of 0.61 and0.81 for LER and TR respectively validate the use of image-based leaf areaestimation. However, the estimated values for LER are lower than for the manualmethod on Heliaphen, but closer overall to the manual method ongreenhouse-grown plants, potentially suggesting an overestimation of stresssensitivity.It can be concluded that the LE and TR parameter estimates can beused for simulations. The low cost of this method (compared with manualmeasurements), the possibility of parallelizing and repeating measurements onthe Heliaphen platform, and of benefiting from the Heliaphen platform's datamanagement, are major improvements for valorizing the SUNFLO model andcharacterizing the drought sensitivity of cultivated varieties.

Prediction of sunflower leaf area at vegetative stage by image analysis  and application to the estimation of water stress response parameters in  post-registration varieties