Global assessment of plant photosynthesis optimization for climate change versus enhanced plant productivity

Project Information

PHOTOFLUX

Grant agreement ID: 101041768

DOI

10.3030/101041768

EC signature date 5 May 2022

Start date 1 October 2022

End date 31 January 2028

Funded under

• European Research Council (ERC)

Total cost

€ 1 499 981,00

EU contribution

€ 1 499 981,00

Coordinated by

UNIVERSITAT DE VALENCIA
Spain

Periodic Reporting for period 1 - PHOTOFLUX (Global assessment of plant photosynthesis optimization for climate change versus enhanced plant productivity)

Reporting period: 2022-10-01 to 2025-07-31

Summary of the context and overall objectives of the project

The optimised balance between the photochemical and non-photochemical energy pathways of absorbed radiation in plant species is poorly understood. To enhance our knowledge of this concept, the EU-funded PHOTOFLUX project aims to understand and quantify the dynamic plant adaptation process through non-invasive proximal and remote sensing techniques, which will allow a quantitative assessment of photosynthesis optimisation in a changing global context. To do this, the project will employ an interdisciplinary experimental approach to quantify carbon uptake from the quantitative description of the energy absorbance processes in the photosynthetic light reactions of plants. The project’s work is in line with the ongoing developments of the Fluorescence Explorer (FLEX) satellite mission of the European Space Agency.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

To reach the main goal of the project, an important methodological component planned in PHOTOFLUX received major attention in the project so far. The development of an unmixing strategy to spectrally decouple photosynthetic and non-photosynthetic fluxes of absorbed light for leaf, canopy and complex scenes was proposed as one of the sub-objectives of PHOTOFLUX.

To achieve this objective, we developed a core algorithm based on a non-negative least square (NNLS) spectral unmixing algorithm for reflectance (500–780 nm) data. The version implemented can retrieve the effective absorbance of individual pigments, i.e. Chlorophyll (Chl) a and b, beta-Carotene and (overall) xanthophylls. The NNLS fitting was successfully applied to fit the total effective absorbance at leaf level, linearly composed of pigment and background absorption coefficient spectra. The novel aspect of this spectral unmixing strategy is the implementation of a spectral endmember characterizing the absorption behaviour of xanthophylls, affecting the leaf absorbance only by a few percent. This subtle absorbance feature, linked to the xanthophyll-based energy dissipation mechanism, could be meaningfully retrieved from the spectral data at leaf scale. We applied the leaf-based algorithm to simulated images of the Fluorescence Explorer, the foreseen satellite mission of the European Space Agency devoted to the estimation of vegetation fluorescence and actual photosynthesis.

Further it was tested if the proposed absorption unmixing protocol could (1) detect the activation of the fast regulated heat dissipation, and (2) tackle the ambiguity in the fluorescence-photosynthesis relationship, currently an issue in remote sensing applications. To accomplish this, we achieved to test our algorithm using an inter-disciplinary experiment based on in vivo spectroscopy (absorption and fluorescence), combined with common plant physiology measurements, i.e. active fluorescence and gas exchange measurements. Our results so far underscore the potential of complementary in vivo quantitative spectroscopy-based products in the early and non-destructive stress diagnosis of plants, marking the path for further applications across various monitoring scales.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The methodology developed in the project has reached an initial phase where the proof-of-concept is being demonstrated and applied in real cases of early plant stress detection. However, further refinement of the methodology is required to make a significant achievement beyond the state-of-the-art. The upscaling of our methodology from proximal to remote detection will also require suitable datasets, and global monitoring will only be possible when the forthcoming Fluorescence Explorer Mission is launched.

Bottom-up stress monitoring stragegy of vegetation