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Combining field experiments under an agrivoltaic system and a kinetic fruit model to understand the impact of shading on apple carbohydrate metabolism and quality

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Abstract

Shading with dynamic agrivoltaic (AV) could be a solution to mitigate the effects of climate change but their impact on the fruit quality has not been reported. Apple metabolism and quality were evaluated in a dynamic AV system in a mature ‘Golden Delicious’ orchard in the south of France (2019–2021). Trees were exposed to three different light treatments: maximal shading all day ‘AV max’, morning shading ‘AV morning’, and afternoon shading ‘AV afternoon’. Results were compared with control trees ‘C’. Shading did not modify fruit maturity and therefore harvest date. AV max reduced dry matter content (24%), soluble carbohydrate concentrations (23%) but maintained malic acid concentrations for 2 years out of 3. Sugar:acid ratio was significantly reduced under AV max. The kinetic model simulated the concentrations of soluble sugars, starch, and other compounds (organic acids, cell walls, proteins) and their interactions with reaction rates driven by multiple parameters. The calibration of these parameters with the experimental data made it possible to simulate carbohydrate dynamics of the different experimental years and treatments with a common set of parameters. This common set of parameters indicated that shading did not mostly alter apple metabolism. The model indicated that shading reduced incoming carbon flows and increased water entering the fruit, being the main reason of internal quality modifications. Shading with AV systems seems a useful tool to modify fruit quality for future higher temperatures. Dynamic AV offers the opportunity to tilt the solar panels for optimising carbon acquisition in critical periods for quality determination.

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Acknowledgements

This work was part of the R&D project “Sun’Agri 3”, supported by the PIA 2 (Programme d’Investissement d’Avenir), under the ADEME [Grant Agreement N°1782C0103]. This study was partly funded by the French ANRT National Research Agency in the frame of a CIFRE contract between Sun’Agri and INRAE. We thank the employees of the experimental station of La Pugère for helping with the experiment and managing the maintenance of the plot. Our gratitude goes to V. Serra, H. Hadjadj, E. Nicolaidis, O. Potard, Q. Barra, C. Gueze, and M. Gales, for their precious help during the experimental campaigns. Finally, we also want to thank the people who carried out the biochemical analysis of the fruit: S. Serino, P. Laugier, D. Dumont, L. Halgand and M. Brun. A special thanks to P. Valsesia and M. Memmah for their help in calibrating the model parameters.

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Authors and Affiliations

  1. INRAE-UR1115 (PSH), Site Agroparc, Avignon, France

    Perrine Juillion, Michel Génard & Gilles Vercambre

  2. Sun’Agri, 60 All. Yves Stourdze, 34830, Clapiers, France

    Perrine Juillion, Gerardo Lopez & Damien Fumey

  3. La Pugère, Chemin de La Barque de Malespine, Mallemort, France

    Vincent Lesniak

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  1. Perrine Juillion
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  2. Gerardo Lopez
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  4. Vincent Lesniak
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  6. Gilles Vercambre
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Contributions

All authors wrote the protocols. PJ and VL carried out the experiments. PJ and GV carried out the analyses and modelling. PJ wrote the manuscript. All authors reviewed the manuscript.

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Correspondence to Perrine Juillion.

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Appendix

Appendix

See Figs. Figs. 8, 9.

Fig. 8
figure 8

Interpolation of fruit dry mass [g] using Gompertz function according to fruit age [g] for the different treatments and years of experimentation based on our experimental data.The points represent the experimental data. The lines represent the modelisation for maximal (dark grey), mean (grey) and minimum fruit growth (light grey) based on our experimental data

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Fig. 9
figure 9

Interpolation of fruit water [g] using Gompertz function according to fruit age [day] for the different treatments and years of experimentation based on our experimental data.The points represent the experimental data. The lines represent the modelisation for maximal (dark grey), mean (grey) and minimum fruit growth (light grey) based on our experimental data

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Juillion, P., Lopez, G., Fumey, D. et al. Combining field experiments under an agrivoltaic system and a kinetic fruit model to understand the impact of shading on apple carbohydrate metabolism and quality. Agroforest Syst (2024). https://doi.org/10.1007/s10457-024-00965-0

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