Agrivoltaics based on light spectrum optimization

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Researchers at the University of California, Davis, have purportedly found that the red part of the light spectrum is more efficient for growing plants, while the blue part is better used for electricity production from solar technology. In  “Not All Light Spectra Were Created Equal: Can We Harvest Light for Optimum Food-Energy Co-Generation?,” recently published in Earth’s Future, they claim that their discovery could lead to efficiency improvements for agrivoltaic systems.

“Today’s solar panels take all the light and try to make the best of it,” said Matteo Camporese, one of the paper’s authors. “But what if a new generation of photovoltaics could take the blue light for clean energy and pass the red light onto the crops, where it is most efficient for photosynthesis?”

The scientists developed a photosynthesis and transpiration model to account for different light spectra. The model reproduced the response of various plants, including lettuce, basil, and strawberries, to different light spectra in controlled lab conditions.

The results suggest that the blue part of the light spectrum carries more potential energy, while also being “the less efficient in terms of carbon assimilation and water use and could be effectively filtered out to produce solar energy,” the academics said. On the other hand, the red spectrum could efficiently produce biomass and increase crop yield.

The academics believe their model could be used to inform future development of wavelength-selective semi-transparent solar modules.

“Organic PV … provide unique opportunities to ‘harvest' some parts of the incoming light spectrum to generate energy and letting through mostly the parts of the spectrum that are more useful for the plants,” the researchers said. “To fully reach this potential, accurate plant models are needed that explicitly consider light … spectra to compute the crop productivity.”

The study suggests that wavelength-selective agrivoltaic systems might be sensitive to environmental factors and crop type. The authors recommended using such systems in water-limited areas, rather than in areas with limited solar irradiation. They also noted that certain crops, like strawberries, are less sensitive to light treatments using different light spectra.

“Therefore, this model could be used to preliminarily assess the suitability of different plant species for use in agrivoltaics,” they concluded.

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