Chan, A.M.H., Pay, M.L., Christensen, J. et al. (4 more authors) (2024) Red, blue or mix: choice of optimal light qualities for enhanced plant growth and development through in silico analysis. in silico Plants, 6 (1). diae008. ISSN 2517-5025
Abstract
In smart greenhouse farming, the impact of light qualities on plant growth and development is crucial but lacks systematic identification of optimal combinations. This study addresses this gap by analysing various light properties’ effects (photoperiod, intensity, ratio, light–dark order) on Arabidopsis thaliana growth using days-to-flower (DTF) and hypocotyl length as proxies to measure plant growth and development. After establishing suitable ranges through a comprehensive literature review, these properties varied within those ranges. Compared to white light, a 16-h cycle of blue light reduces DTF and hypocotyl length by 12 % and 3 %, respectively. Interestingly, similar results can be achieved using a shorter photoperiod of 14-h light (composed of 8 h of a mixture of 66.7 μmol m−2s−1 red and 800 μmol m−2s−1 blue lights (i.e. blue:red ratio of 12:1) followed by 6 h of monochromatic red light and 10-h dark. These findings offer potential for efficient growth light recipes in smart greenhouse farming, optimizing productivity while minimizing energy consumption.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2024. Published by Oxford University Press on behalf of the Annals of Botany Company. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Jul 2024 15:18 |
Last Modified: | 04 Jul 2024 15:18 |
Published Version: | http://dx.doi.org/10.1093/insilicoplants/diae008 |
Status: | Published |
Publisher: | Oxford University Press (OUP) |
Refereed: | Yes |
Identification Number: | 10.1093/insilicoplants/diae008 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:214288 |