Incorporating the effect of the photon spectrum on biomass accumulation of lettuce using a dynamic growth model
| dc.contributor.author | Abedi, Mahyar | en |
| dc.contributor.author | Tan, Xu | en |
| dc.contributor.author | Stallknecht, Eric J. | en |
| dc.contributor.author | Runkle, Erik S. | en |
| dc.contributor.author | Klausner, James F. | en |
| dc.contributor.author | Murillo, Michael S. | en |
| dc.contributor.author | Benard, Andre | en |
| dc.date.accessioned | 2026-01-28T14:28:44Z | en |
| dc.date.available | 2026-01-28T14:28:44Z | en |
| dc.date.issued | 2023-05-23 | en |
| dc.description.abstract | Cultivation studies in specialty crop optimization utilize models to estimate the fresh and dry mass yield. However, the spectral distribution and photon flux density (μmol m-2 s-1) affect plant photosynthetic rate and morphology, which is usually not incorporated in plant growth models. In this study, using data for indoor-grown lettuce (<i>Lactuca sativa</i>) cultivated under different light spectra, a mathematical model that incorporates these effects is presented. Different experimental cases are used to obtain a modified quantum use efficiency coefficient that varies with the spectral distribution. Several models for this coefficient are fitted using experimental data. Comparing the accuracy of these models, a simple first- or second-order linear model for light-use efficiency coefficient has about 6 to 8 percent uncertainty, while a fourth-order model has a 2 percent average error in prediction. In addition, normalizing overall spectral distribution leads to a more accurate prediction of the investigated parameter. A novel mathematical model based on normalized spectral irradiance integrated over wavelength for photosynthetically active radiation (PAR) wavebands and the far-red waveband is presented in this study. It accurately predicts lettuce dry mass grown indoors under different light spectra. | en |
| dc.description.version | Published version | en |
| dc.format.extent | 18 page(s) | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier | ARTN 1106576 (Article number) | en |
| dc.identifier.doi | https://doi.org/10.3389/fpls.2023.1106576 | en |
| dc.identifier.eissn | 1664-462X | en |
| dc.identifier.issn | 1664-462X | en |
| dc.identifier.orcid | Stallknecht, Eric [0000-0002-6815-6592] | en |
| dc.identifier.other | PMC10286798 | en |
| dc.identifier.pmid | 37360721 | en |
| dc.identifier.uri | https://hdl.handle.net/10919/141022 | en |
| dc.identifier.volume | 14 | en |
| dc.language.iso | en | en |
| dc.publisher | Frontiers | en |
| dc.relation.uri | https://www.ncbi.nlm.nih.gov/pubmed/37360721 | en |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject | plant growth | en |
| dc.subject | dynamic modeling | en |
| dc.subject | spectral distribution | en |
| dc.subject | Lactuca sativa | en |
| dc.subject | indoor crop production | en |
| dc.subject | regression-based modeling | en |
| dc.subject | controlled environment agriculture | en |
| dc.title | Incorporating the effect of the photon spectrum on biomass accumulation of lettuce using a dynamic growth model | en |
| dc.title.serial | Frontiers in Plant Science | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |
| dc.type.other | Article | en |
| dc.type.other | Journal | en |
| dcterms.dateAccepted | 2023-04-14 | en |
| pubs.organisational-group | Virginia Tech | en |
| pubs.organisational-group | Virginia Tech/Agriculture & Life Sciences | en |
| pubs.organisational-group | Virginia Tech/Agriculture & Life Sciences/Hampton Roads AREC | en |
| pubs.organisational-group | Virginia Tech/All T&R Faculty | en |
| pubs.organisational-group | Virginia Tech/Agriculture & Life Sciences/CALS T&R Faculty | en |