The correlation of leaf parameters with flower yield and cannabinoid accumulation in medical cannabis under different LED light spectra

Light is a critical factor in cannabis cultivation, influencing photosynthesis, secondary metabolite production, and photomorphogenesis. Despite its significance, the metabolic interactions between leaves and flowers under varying light spectra remain inadequately understood. Here, we are aiming to evaluate the correlation between metabolism in leaves and flowers of cannabis plants upon the responses of different light spectra. Cannabinol (CBD)-rich cannabis plants growing in 16-hour of light for 5 weeks enhanced the growth of cannabis plants after switching to 12-hour light for another 7 weeks without any differences among spectra. However, total CBD content and flower yield were more enriched in blue/red ratio 5:5 and 2:8. Gene expression analysis revealed that cannabinoid biosynthesis and glycolysis pathways in flowers were closely aligned with growth and CBD accumulation, except in blue/red ratio 8:2 which produce higher CBD/CBDA ratio than the other treatments. In leaves of blue/red ratio 5:5 and 2:8, genes associated with the photosynthetic system and the Krebs cycle were upregulated. Flower dry weight and total CBD had positive correlation with photosynthetic rate (r = 0.89), PSAG (r = 0.68), and LHCA4 expression (r = 0.63), respectively. The observed metabolic link between leaves and flowers may provide valuable insights for predicting the effects of environmental factors on cannabinoid yield in flower from the leaf perspectives. • LED conditions with Blue/Red ratio 5:5 and 2:8 induced maximum flower dry weight and CBD content. • High intensity of full spectrum of light promoted vegetative growth but not cannabinoid biosynthesis. • One-to-one ratio of blue and red light induced the same level of photosynthesis and biochemical limitation with the 400 µmol m −2 s −1 higher intensity of full spectrum. • Flower dry weight can be predicted by photosynthetic rate, V c,max , J, TPU, GBSS1 , ISA2 and PSAG expression. • Total CBD content can be predicted by LHCA 4, LHC2 , PSAO and PSAF expression.