On the Impact of Light Spectrum on Lettuce Biophysics: A Dynamic Growth Model for Vertical Farming

46/2025

On the Impact of Light Spectrum on Lettuce Biophysics: A Dynamic Growth Model for Vertical Farming

Monday 11th August 2025

Mirabella, S.; David, E.; Antona, A.; Stanghellini, C.; Ferro, N.; Matteucci, M.; Heuvelink, E.; Perotto, S.

Current crop growth models, whether process-based or data-driven, rarely incorporate spectral light composition, limiting their applicability in highly controlled environments such as vertical farming. This work addresses this gap by adjusting a well-established process-based model for lettuce growth with an explicit, data-driven representation of light spectrum effects. Using explainable machine learning techniques, we identify the most relevant spectral features, specifically the Blue:Red and FarRed:Red ratios, and integrate them into a new model parameter, which captures their physiological impact on plant development. The resulting adjusted model (aVHopt) is then validated on an independent literature dataset, showing a substantial reduction in prediction error compared to the reference state-of-the-art model, with a more than 60% decrease in RMSE. The application of the aVHopt model to a commercial dataset confirms its capability to capture key spectral effects, but also reveals its sensitivity to environmental and biological variability not fully accounted for in the current formulation.