Quantitative evaluation of supplemental LED lighting for Axonopus compressus recovery using ANOVA and growth analysis

Urban turfgrass management, particularly for species like Axonopus compressus (Cow Grass), faces significant challenges due to light limitation in high-density built environments such as semi-enclosed stadia. This study investigates the integration of mechatronic principles and supplemental LED lighting to accelerate the recovery of chlorotic turfgrass, comparing natural sunlight exposure against a supplemental red-blue LED grow light system. A red-blue LED grow light system (5000 ± 1000 lumens) was applied nocturnally for three hours to one of two experimental patches over 15 days, with five marked sampling areas per patch; leaf colour, leaf length, leaf width, root/stem length, stem width, and leaf count were recorded on Days 1, 4, 9, and 15 and compared using ANOVA and the Mann–Whitney U test. The LED-treated patch showed a higher colour-recovery rate (0.352 versus 0.274 units day−1; 28.7% improvement) and a lower vertical-growth rate (1.438 versus 1.915 mm day−1; 24.9% lower) than the control; ANOVA identified a statistically significant between-group difference only for leaf length (p = 0.0395), with the remaining parameters not significant at α = 0.05. Canopy colour and vertical elongation emerge as candidate feedback variables for future closed-loop, energy-aware lighting control, although the present findings should be regarded as preliminary given the small sample size and limited replication.

Authors

Publication Details

Journal
Mekatronika
Published
2026-11-06
DOI
https://doi.org/10.15282/mekatronika.v8i2.14788
Primary Topic
Turfgrass Adaptation and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Quantitative evaluation of supplemental LED lighting for Axonopus compressus recovery using ANOVA and growth analysis

Muhammad Nur Aiman Shapiee, Amir FakarulIsroq Abdul Razak, Nur Aliya Syahirah Badrol Hisam, Ismail Mohd Khairuddin et al.
Mekatronika
Turfgrass Adaptation and Management
article

Quantitative evaluation of supplemental LED lighting for Axonopus compressus recovery using ANOVA and growth analysis

Muhammad Nur Aiman Shapiee, Amir FakarulIsroq Abdul Razak, Nur Aliya Syahirah Badrol Hisam, Ismail Mohd Khairuddin, Muhammad Haris Zulkifly, Muhammad Ahraz Mohd Nor Mimbar, Ahmad Nur Iman Ahmad Fauzi
article en

Abstract

Urban turfgrass management, particularly for species like Axonopus compressus (Cow Grass), faces significant challenges due to light limitation in high-density built environments such as semi-enclosed stadia. This study investigates the integration of mechatronic principles and supplemental LED lighting to accelerate the recovery of chlorotic turfgrass, comparing natural sunlight exposure against a supplemental red-blue LED grow light system. A red-blue LED grow light system (5000 ± 1000 lumens) was applied nocturnally for three hours to one of two experimental patches over 15 days, with five marked sampling areas per patch; leaf colour, leaf length, leaf width, root/stem length, stem width, and leaf count were recorded on Days 1, 4, 9, and 15 and compared using ANOVA and the Mann–Whitney U test. The LED-treated patch showed a higher colour-recovery rate (0.352 versus 0.274 units day−1; 28.7% improvement) and a lower vertical-growth rate (1.438 versus 1.915 mm day−1; 24.9% lower) than the control; ANOVA identified a statistically significant between-group difference only for leaf length (p = 0.0395), with the remaining parameters not significant at α = 0.05. Canopy colour and vertical elongation emerge as candidate feedback variables for future closed-loop, energy-aware lighting control, although the present findings should be regarded as preliminary given the small sample size and limited replication.

Mekatronika
Openalex Percentile: Top 18%
Turfgrass Adaptation and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon