Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)

Mathematic Modelling of Bok Choy Plant Canopy Area on Different Artificial Light at Plant Factory

Authors
DA Setiawati1, 2, L Sutiarso1, *, Ngadisih1, Murtiningrum1, AP Nugroho1, GMD Putra1, 2, MSI Chaer1
1Department of Agricultural and Biosystem Engineering, Faculty of Agricutural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia
2Department of Agriculture Engineering, Faculty of Food technology and Agro-industry, Mataram University, Mataram, Indonesia
*Corresponding author. Email: lilik-soetiarso@ugm.ac.id
Corresponding Author
L Sutiarso
Available Online 28 December 2022.
DOI
10.2991/978-94-6463-086-2_2How to use a DOI?
Keywords
LED; leaf canopy area; plant factory; plant growth
Abstract

In the plant factory, plants carry out the process of photosynthesis using artificial light sources in the form of growth lights instead of sunlight. Each type of lamp will emit light with a different wavelength, so the effect on the photosynthesis process is also different. This study examines the pattern of canopy area expansion on plants in response to the light quality of artificial light in the plant factory. Canopy area of Bok choy (Brassica rapa subsp. Chinensis) plant samples for white LED dan red-blue LED treatments were measured non-destructively every two and three days using the Easy Leaf Area application. The growth data is then modeled using linear and polynomial regression. The results showed that the canopy area of the plant in the plant factory increased with the growth period. The plants exposed to red-blue LED lights grew better than plants exposed to white LED, indicating that red-blue lights supported the photosynthesis process better than white light. The regression results also show that the growth of plants in plant factories with a combination of red-blue LED lights is better in terms of MAPE (Mean Absolute Percentage Error) values. The model validation and prediction are also better using red-blue LED than white LED. Based on prediction using the best regression model, the result shows that red-blue LED as artificial light sources better support plant growth in plant factories than white LED lamps.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
Series
Advances in Biological Sciences Research
Publication Date
28 December 2022
ISBN
10.2991/978-94-6463-086-2_2
ISSN
2468-5747
DOI
10.2991/978-94-6463-086-2_2How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - DA Setiawati
AU  - L Sutiarso
AU  - Ngadisih
AU  - Murtiningrum
AU  - AP Nugroho
AU  - GMD Putra
AU  - MSI Chaer
PY  - 2022
DA  - 2022/12/28
TI  - Mathematic Modelling of Bok Choy Plant Canopy Area on Different Artificial Light at Plant Factory
BT  - Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
PB  - Atlantis Press
SP  - 3
EP  - 11
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-086-2_2
DO  - 10.2991/978-94-6463-086-2_2
ID  - Setiawati2022
ER  -