Abstract Seedlings of Andrographis paniculata (Burm.f.) Wall. ex Nees cv. Phichit were cultivated in 8-inch pots containing a growing medium composed of coconut coir and peat moss at a ratio of 70:30 (v/v). The pots were placed on cultivation shelves in a plant factory system equipped with five light-emitting diode (LED) lighting treatments: (i) red and blue light in an 8:2 ratio (RB), (ii) RB supplemented with additional red light (RBR), (iii) RB supplemented with additional blue light (RBB), (iv) RB supplemented with warm white light (RBW) and (v) RB supplemented with daylight LEDs (RBD). Five pots were assigned to each lighting treatment and exposed to a 16-h photoperiod for 7 weeks. The results indicated that plant height, leaf dimensions, canopy width, stem diameter, number of leaves and flowering showed no significant differences among the lighting treatments. However, the spectral quality of light significantly influenced the accumulation of secondary metabolites. The RBR treatment produced the highest total phenolic content (TPC) (7.00 ± 0.23 mg GAE g − ¹ extract), whereas the RB treatment resulted in the highest total flavonoid content (TFC) (13.83 ± 1.10 mg CE g − ¹ extract). Total lactone content was also enhanced under the RBR and RBB treatments, reaching (17.48 and 17.40 mg AE g − ¹ extract), respectively. In addition, antioxidant activity was strongly affected by light quality. The RBW treatment exhibited high radical scavenging activity, with values of 84.41% for DPPH and 88.99% for 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays. Meanwhile, the RBB treatment demonstrated the greatest antioxidant potency, as indicated by the lowest IC₅₀ values (2.58 mg ml − ¹ for DPPH and 2.46 mg ml − ¹ for ABTS). Lower phenolic contents were observed under the RBW and RBD treatments. Overall, these findings suggest that LED spectra enriched with red and blue wavelengths can enhance phytochemical accumulation in A. paniculata without negatively affecting plant growth. Significance of the Study What is already known on this subject: Light quality, especially red and blue wavelengths, strongly affects plant growth and the production of important bioactive compounds. Light-emitting diode (LED) lighting is widely used in horticulture for its efficiency and ability to customize light spectra. While many studies show benefits in various medicinal plants, how different light spectra affect specific cultivars like Andrographis paniculata cv. Phichit is still not well understood. What are the new findings: This study provides new evidence that different LED spectra can be used as an effective production strategy to improve the medicinal quality of A. paniculata cv. Phichit in plant factory systems. Red–blue lighting, particularly when enriched with additional red or blue wavelengths, enhanced flavonoid and lactone accumulation without compromising plant growth. Notably, supplemental blue light (RBB) maximized antioxidant activity, highlighting its potential application for controlled-environment medicinal plant production of high-value medicinal herbs. What are the expected impacts on horticulture: This study offers a practical approach for improving the quality of medicinal crops produced in plant factories and vertical farming systems. The use of optimized LED light spectra allows growers to enhance bioactive compound accumulation without additional cultivation time, energy or inputs. These findings support the adoption of controlled LED lighting strategies tailored to specific cultivars and reinforce the role of smart LED technologies in sustainable, high-value horticultural production.
Building similarity graph...
Analyzing shared references across papers
Loading...
Panchai et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69fd7eb0bfa21ec5bbf06e4a — DOI: https://doi.org/10.1079/ejhs.2026.0010
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:
W. Panchai
P. Khodchanop
D. Naphrom
European Journal of Horticultural Science
Chiang Mai University
Building similarity graph...
Analyzing shared references across papers
Loading...