Developing Grow Light Spectrum Optimization Algorithm for Plant Models: Case Study of Spinacia oleracea

Abstract

Evolution uniquely modulates plants’ efficacy in absorbing photons of different frequencies-high altitude crops have evolved to more effectively absorb bluer, higher-frequency radiation, while low lying marsh crops are more sensitized to redder, lower-frequency spectral regions. Research has shown that plants’ phenotype(s) and biochemistry are indeed affected by the distribution and intensity of light. For the model organism S. oleracea (spinach), we were able to empirically identify a unique spectral distribution to achieve a minimum viable level of output that reduces energy consumption by 21%, compared to standard LED spectrum distributions. Additionally, by applying the customized spectrum to P. vulgaris (common beans), we showed that the spectrum produced was indeed customized to S. oleracea and not generalizable to all plants. We empirically customized a spectral distribution to optimize Spinacia oleracea (S. oleracea) plants for desirable phenotypes, including height, stem width, and leaf growth. When applied with horticultural grow lights, our spectrum dramatically reduces energy costs but maintains crop yield and quality as compared to standard LED lights. We propose standardized morphological and biochemical optimization methods for whole plant and/or plant cultures using high-throughput manners.