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.

Plant phenotyping relevance

高速クロロフィル蛍光フェノタイピングデータを用いた光合成モデルを新規に構築し、既存モデルと比較検証しており、表現型取得・解析手法が研究の中心である。

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.