Rapid Chlorophyll a Fluorescence Light Response Curves Mechanistically Inform Photosynthesis Modeling.

Abstract

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 PSII ) is here analyzed as an exponential decline under changing light intensity and soil moisture. Both the maximum ϕ PSII and the rate of ϕ PSII decline across a large range of light intensities (0-1,000 μmol photons m -2 s -1 ; β PSII ) are negatively affected by drought. We introduce an alternative photosynthesis model ( β PSII model) incorporating parameters from rapid fluorescence response curves. Specifically, the model uses β PSII 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 PSII 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.

Code and data availability

The paper's phenotyping measurements are publicly available via two PhotosynQ projects (chlorophyll fluorescence and ECS protocols/data for the B. rapa drought experiment), and the authors' analysis code for the βPSII decline model and three photosynthesis models is publicly hosted on the first author's GitHub.