Modeling growth and development of cannabidiol-rich hemp (Cannabis sativa L.) cultivars under greenhouse and controlled environment conditions

Hemp is a strain of Cannabis sativa L. that is grown for industrial use as fiber, fuel, and phytochemicals. Florida hemp growers are currently facing numerous agronomic challenges in an uncertain market, policy and climatic environment, ultimately limiting the potential of hemp as a sustainable source for fiber and other bioproducts. It would, therefore, be useful to develop a dynamic model-based decision support system to address some of the challenges faced by hemp growers and other stakeholders. This study collected both destructive and non-destructive measurements from three cannabidiol-rich hemp cultivars, i.e., ‘Cherry’, ‘Wife’ and ‘ACDC’ grown under greenhouse and growth chamber conditions, to analyze the development of morphology and biomass accumulation during the growing season. Flower material was sampled at weekly intervals to determine the development of the cannabinoid profile and quality-quantity dynamics throughout the flowering period. The experimental data were then analyzed for patterns, correlations, and statistical models. Simple growth curves based on second degree polynomial functions were able to predict the various growth parameters well (R² 0.77-0.97). Correlations between growth patterns were identified and related to observed morphology and phenology. This research presents an initial data set and a systems approach toward simulating growth and development of industrial hemp for different environmental conditions. Future work will include flower quality data, and refinement toward process-based mechanistic modeling of physiological processes and evaluation with data sets for different cultivars and other environments.