Metabolic Variations in Grass <italic>C. dactylon</italic> and Selection of Optimal LEDs for the Horticulture Luminaire Using LM Algorithm

Abstract

Healing of various ailments using herbal medicines is gaining much interest. Plants classified as grasses, specifically Cynodon dactylon, are an appreciated group of monocots used in many herbal remedies. In this work, C. dactylon, is grown naturally and also under market available LED Luminaires with different lighting conditions. Until 2010, most of the plants are grown under conventional lamps that are not spectrally tunable. Cynodon dactylon, the grass is grown under two different light spectrum, two light levels and three photoperiods (9hours, 12 hours, 15 hours) to extend our experiential knowledge. The biomass accumulation was the highest when grown under a lower RB ratio-12-hour- $163\mu $ mol/s, and phenolic content was the highest at 92.8 mg/g wt Gallic Acid Equivalents under combined light source at 15-hour photoperiod. A spectrally tunable LED light source with an optimal quantity of LEDs saves cost, space and energy. Considering the light parameters from the light sources used for growing C. dactylon, Levenberg–Marquardt (LM) algorithm is implemented to select an optimal LED quantity that composes the light source. The algorithm simulates the given target spectrum with minimum fitness error. The method applied to model LEDs, its validation against the practical LED spectrum, spectrum matching and computation of Luminous flux, Photosynthetic Photon Flux and efficacy are also presented. Many spectrums are simulated to validate the performance of the algorithm. A solution of optimal LEDs for three Photosynthetic Photon Flux (PPF) levels with LEDs is derived, and it is observed that the number of LEDs increased with PPF.

Keywords

• LED lamps
• photosynthetic active radiation
• photosynthetic photon efficiency
• spectral power density
• applied optimization
• LM algorithm