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 (ΦPSII) is here analyzed as an exponential decline under changing light intensity and soil moisture. Both the maximum ΦPSII and the rate of ΦPSII decline across a large range of light intensities (0-1, 000 mmol photons m-2 s-1; βPSII) are negatively affected by drought. We introduce an alternative photosynthesis model (βPSII model) incorporating parameters from rapid fluorescence response curves. Specifically, the model uses βPSII 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 βPSII model represents a major improvement in photosynthesis modeling through the integration of highthroughput fluorescence phenotyping data, resulting in gained parameters of high mechanistic value.