Integrating chlorophyll fluorescence parameters into a crop model improves growth prediction under severe drought

Abstract

Predicting biomass production is important for assessing yield losses caused by drought. Photosynthesis-driven crop growth models, such as SUCROS97, tend to overestimate crop production under severe drought, as they ignore slow post-drought recovery kinetics of leaf photosynthesis. In this study, Lilium plants (L. auratum × speciosum ‘Sorbonne’) were subjected to mild, intermediate and severe drought with different durations (3, 5, 7 and 9 days) at two developmental stages (leaf unfolding and flower bud break stage). Leaf photosynthesis and chlorophyll fluorescence (CF) were measured during and after drought. We found that at both developmental stages, drought significantly reduced light-saturated gross photosynthesis rate (Pg,max), which progressively recovered after re-watering. Under mild drought, Pg,max recovered fully to non-stress levels by re-watering, whereas under intermediate and severe drought, Pg,max did not recover fully. Drought occurring during leaf unfolding had a larger impact on biomass production than drought during bud break. Further, we identified a sigmoidal relationship (r2 = 0.81) between Pg,max and photosystem II operating efficiency (Φ2) during drought, and highly linear relationships (r2 = 0.88) between Pg,max and the quantum yield of non-regulated energy dissipation (ΦNO) during post-drought recovery. We integrated the aforementioned relationships into SUCROS97, and the extended SUCROS-CF model explicitly accounted for slow and incomplete Pg,max recovery in the post-drought phase. Compared to SUCROS97, SUCROS-CF improved biomass prediction by 7%, due to a 19% improvement in Pg,max predictions under severe drought. We conclude that to accurately predict productivity during and after severe drought, leaf photosynthetic capacity kinetics need to be considered. Furthermore, CF measurements can be applied to predict leaf photosynthetic capacity during and after drought, enabling rapid drought phenotyping in breeding programs and yield loss assessment in the field.