Red, blue or mix: choice of optimal light qualities for enhanced plant growth through in silico analysis.

DOI: 10.31220/agriRxiv.2023.00197
Statement: This article is a preprint and has not been peer-reviewed. It reports new research that has yet to be evaluated and so should not be used to guide clinical practice.
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    Abstract: Abstract In smart greenhouse farming, artificially adjustable light qualities (colours) play an important role to promote plant growth. While it is known that these light qualities have significant impacts on plant development, the suitable combinations enabling the plant to grow at its best are yet to be systematically identified. This study fills this gap by studying the effect of different properties of light qualities (i.e., photoperiod, light intensity, light ratio, light-dark order) on plant growth using a mathematical model of the model plant Arabidopsis thaliana , where days-to-flower (DTF) and hypocotyl (seedling stem) length are used as proxies for measuring plant growth. A comprehensive literature search is first conducted to establish a suitable range of each light property before they are systematically varied within that prescribed range to study their effect on plant growth. In comparison to a previous study using white light, monochromatic blue light with minimum intensity of 900 μmol/m 2 s - 1, at 16-hour light and 8-hour dark shows a reduction in DTF and hypocotyl length by 12% and 3%, respectively. Interestingly, similar results can be achieved using a shorter photoperiod of 14-hour light (composed of 8 hours of a mixture of red and blue lights followed by 6 hours of monochromatic red light) and 10-hour dark, with red and blue light intensities of 66.7 μmol/m 2 s -1 and 800 μmol/m 2 s -1 , respectively (i.e., blue: red ratio of 12:1). These discoveries have tremendous potential in smart greenhouse farming sectors in developing the optimal growth light recipe that promotes productivity while reducing the energy usage.

    Key words: light; light qualities; hour; mol; dark; plant growth

    Submit time: 1 January 2023

    Copyright: The copyright holder for this preprint is the author/funder, who has granted agriXiv a license to display the preprint in perpetuity.
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Aye Nyein Chan, Miao Lin Pay, Jesper Christensen, Fei He, Laura C. Roden, Hafiz Ahmed, Mathias Fo. Red, blue or mix: choice of optimal light qualities for enhanced plant growth through in silico analysis.. 2023. agriXiv.2023.00197

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