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Evaluating plant growth performance in a greenhouse hydroponic salad system using the internet of things

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 16 No. 1 (2026)

DOI
10.11591/ijece.v16i1.pp505-517
ISSN
2722-2578, 2088-8708
Published
2026-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Hydroponic salad cultivation is becoming increasingly popular. However, a common challenge is the lack of time to maintain hydroponic vegetables due to other responsibilities. This study presents a hydroponic system based on the internet of things (IoT) technique, designed to save time by enabling remote control through a mobile application connected to a NodeMCU microcontroller. Various sensors are integrated with the NodeMCU for real-time monitoring and automation. The study also explores the use of RGB LEDs, which significantly accelerated plant growth and reduced cultivation time. A comparative experimental design was employed to evaluate the growth rate of green oak salad vegetables under two different greenhouse systems. The primary factor compared was the greenhouse system type, with plant growth rate as the outcome variable. Each treatment was replicated 10 times. F-tests were used to statistically determine significant differences in growth rates between the two systems across measured intervals. Results showed that the automated greenhouse system produced the highest leaf width and plant weight values. The use of RGB LEDs reduced the cultivation period from 45 days to 30 days, enabling more planting cycles and ultimately increasing overall yield.

Collaboration network of the authors

4 authors · 6 co-authorship links · 3 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Princess of Naradhiwas University
  • King Mongkut's Institute of Technology Ladkrabang
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Evaluating plant growth performance in a greenhouse hydroponic salad system using the internet of things</dc:title><dc:creator>Rattanachu, Chonthisa</dc:creator><dc:creator>Phetjirachotkul, Wiyuda</dc:creator><dc:creator>Chaopisit, Isara</dc:creator><dc:creator>Rothjanawan, Kronsirinut</dc:creator><dc:description>&lt;jats:p&gt;Hydroponic salad cultivation is becoming increasingly popular. However, a common challenge is the lack of time to maintain hydroponic vegetables due to other responsibilities. This study presents a hydroponic system based on the internet of things (IoT) technique, designed to save time by enabling remote control through a mobile application connected to a NodeMCU microcontroller. Various sensors are integrated with the NodeMCU for real-time monitoring and automation. The study also explores the use of RGB LEDs, which significantly accelerated plant growth and reduced cultivation time. A comparative experimental design was employed to evaluate the growth rate of green oak salad vegetables under two different greenhouse systems. The primary factor compared was the greenhouse system type, with plant growth rate as the outcome variable. Each treatment was replicated 10 times. F-tests were used to statistically determine significant differences in growth rates between the two systems across measured intervals. Results showed that the automated greenhouse system produced the highest leaf width and plant weight values. The use of RGB LEDs reduced the cultivation period from 45 days to 30 days, enabling more planting cycles and ultimately increasing overall yield.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2026-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v16i1.pp505-517</dc:identifier><dc:identifier>10.11591/ijece.v16i1.pp505-517</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 16 No 1 (2026); 505</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/40672/18645</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>