Agrivoltaics intermittent shading: Defining ecophysiological responses and impact on rice yield
Lescroart L., Perez R., Boudon F., Fabre D., Dingkuhn M.. 2024. In : Macknick Jordan (ed.), Barron-Gafford Greg (ed.), Pascaris Alexis (ed.). Proceedings of Agrivoltaics 2024. Hanovre : TIB Open Publishing, 2 p.. AgriVoltaics World Conference 2024, 2024-06-11/2024-06-13, Denver (Etats-Unis).
DOI: 10.52825/agripv.v3i
Our research is part of the ADELI project, a collaborative effort involving EDF Renewables, ADEME, Rem Tec, INRAe, and CIRAD, which explores agrivoltaics on irrigated rice-based systems (rice-legume rotation) in the Camargue, a delta region in South France. In a previous work [1], we presented our aim to focus on characterizing shade heterogeneity under panels and studying its impact on rice physiology, development, and production. Our current reflection stems from two observations. Firstly, simulations data of the radiative environment under the ADELI Agrivoltaic demonstrator reveal three levels of heterogeneity depending on the studied zone of 0,25m²: distinct patterns of daily shade (intra-day heterogeneity), different levels of shading over the cycle (seasonal heterogeneity), and varied dynamics depending on the location under the panels (spatial heterogeneity). Secondly, while a few studies have considered horizontal heterogeneity [2], [3] or vertical heterogeneity [4], in microclimatic studies or crop response, we note a scarcity of works addressing these aspects in the context of agrivoltaics. The presented work focuses on the study of intra-day heterogeneity, addressing several key questions: (i) Does useful genetic diversity exist among locally adapted cultivars regarding tolerance to the type of shading encountered under solar panels? (ii) How does the diurnal distribution of a given quantity of PAR (intermittent vs. Constant shade) impact photosynthetic acclimation to shade, and consequently, growth and yield? Lastly, based on these considerations, (iii) how should microclimate, photosynthesis, and growth models be adapted to accurately predict crops in agrivoltaics?
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Agents Cirad, auteurs de cette publication :
- Boudon Frédéric — Bios / UMR AGAP
- Fabre Denis — Bios / UMR AGAP
- Lescroart Laura — Bios / UMR AGAP
- Perez Raphaël — Bios / UMR AGAP
