Articles
Process-based modeling of growth and development of cannabidiol-rich hemp (Cannabis sativa L.) cultivars grown in controlled environments
Article number
1425_44
Pages
341 – 348
Language
English
Abstract
Hemp (Cannabis sativa L.) is a versatile crop that can be used for food, fiber, fuel, and medicine.
Despite considerable economic potential, hemp currently only makes up a small portion of the agricultural sector.
Achieving yield quantity and quality in line with regulations and consumer demand, market uncertainty, and managing cultivar-specific flowering response particularly in open field production, remain barriers for a wider adoption by growers.
A dynamic model-based decision support system could greatly assist producers and improve the viability and sustainability of the hemp industry.
However, this requires a robust understanding of the growth and development of hemp as a function of environmental conditions, genetic factors, and crop management.
To narrow this knowledge gap, we collected foundational growth data at weekly intervals for three cannabidiol (CBD-rich hemp cultivars grown in different environments, assessing the development of plant architecture and accumulation of biomass using destructive and non-destructive methods.
The results were evaluated to determine key physiological processes, growth patterns and correlations.
Initial growth simulations based on second-order polynomial functions predicted the architecture and morphological parameters very well (R2 0.77-0.97). These statistical correlations were further refined to parameterize the SIMPLE process-based model for three hemp cultivars, considering growing degree days and mechanistic processes for hemp growth and development.
This research presents an analysis of the growth patterns and a first approach toward process-based modeling of hemp growth and development.
Future work will include the development of a more comprehensive process-based model, considering the impact of photoperiod on phenology, adapting it to a wider range of growing environments, and evaluation with independent data sets.
Despite considerable economic potential, hemp currently only makes up a small portion of the agricultural sector.
Achieving yield quantity and quality in line with regulations and consumer demand, market uncertainty, and managing cultivar-specific flowering response particularly in open field production, remain barriers for a wider adoption by growers.
A dynamic model-based decision support system could greatly assist producers and improve the viability and sustainability of the hemp industry.
However, this requires a robust understanding of the growth and development of hemp as a function of environmental conditions, genetic factors, and crop management.
To narrow this knowledge gap, we collected foundational growth data at weekly intervals for three cannabidiol (CBD-rich hemp cultivars grown in different environments, assessing the development of plant architecture and accumulation of biomass using destructive and non-destructive methods.
The results were evaluated to determine key physiological processes, growth patterns and correlations.
Initial growth simulations based on second-order polynomial functions predicted the architecture and morphological parameters very well (R2 0.77-0.97). These statistical correlations were further refined to parameterize the SIMPLE process-based model for three hemp cultivars, considering growing degree days and mechanistic processes for hemp growth and development.
This research presents an analysis of the growth patterns and a first approach toward process-based modeling of hemp growth and development.
Future work will include the development of a more comprehensive process-based model, considering the impact of photoperiod on phenology, adapting it to a wider range of growing environments, and evaluation with independent data sets.
Authors
P. Daiber, A. Hopf, E. Luedeling, G. Hoogenboom
Keywords
crop simulation, SIMPLE model, cannabinoids, growth, development
Groups involved
- Division Plant-Environment Interactions in Field Systems
- Division Precision Horticulture and Engineering
- Working Group Modelling in Fruit Research and Orchard Management
- Working Group Modelling Plant Growth, Environmental Control, Greenhouse Environment
- Division Greenhouse and Indoor Production Horticulture
Online Articles (61)