Rapid Chlorophyll a Fluorescence Light Response Curves Mechanistically Inform Photosynthesis Modeling

Crop improvement is crucial to ensuring global food security under climate change, and hence there is a pressing need for phenotypic observations that are both high throughput and improve mechanistic understanding of plant responses to environmental cues and limitations. In this study, chlorophyll a fluorescence light response curves and gas-exchange observations are combined to test the photosynthetic response to moderate drought in four genotypes of Brassica rapa The quantum yield of PSII (ϕ ) is here analyzed as an exponential decline under changing light intensity and soil moisture. Both the maximum ϕ and the rate of ϕ decline across a large range of light intensities (0-1,000 μmol photons m^-2 s^-1; β ) are negatively affected by drought. We introduce an alternative photosynthesis model (β model) incorporating parameters from rapid fluorescence response curves. Specifically, the model uses β as an input for estimating the photosynthetic electron transport rate, which agrees well with two existing photosynthesis models (Farquhar-von Caemmerer-Berry and Yin). The β model represents a major improvement in photosynthesis modeling through the integration of high-throughput fluorescence phenotyping data, resulting in gained parameters of high mechanistic value.