Browsing by Person "Schober, Torsten"

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The effects of plant density and duration of vegetative growth phase on agronomic traits of medicinal cannabis (Cannabis sativa L.): a regression analysis
(2024) Schober, Torsten; Präger, Achim; Hartung, Jens; Graeff-Hönninger, Simone
Empirical data on the effect of plant density (PD) and length of the vegetative phase (DVP) on plant growth, yield, and cannabinoid concentration of medicinal cannabis (Cannabis sativa L.) are still scarce, leading to a lack of specific cultivation recommendations. We conducted two greenhouse experiments to investigate the effect of PD in the range of 12–36 plants m-2 (D-trial) and DVP in the range of 1–4 weeks (V-trial) on plant morphology, biomass growth of individual plant organs, and CBD concentration of individual inflorescence fractions. Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (p = 0.02), whereas a positive linear relationship was found for inflorescence yield (p = 0.0001) and CBD yield (p = 0.0002) per m2. Total area yields in the D-trial ranged from 119 to 247 g m-2 from lowest to highest PD. DVP showed a positive linear relationship with inflorescence yield on an individual plant (p = 0.0001) and area basis (p < 0.0001) along with most other relevant agronomic traits such as CBD production, plant size and lateral shoot length. Total area yields in the V-trial ranged from 295 to 571 g m-2 from lowest to highest DVP. The yield increase could be linked to the increased inflorescence number per plant rather than inflorescence size. In contrast to expectations, neither PD nor DVP had significant effects on the cannabinoid concentration gradient from upper to lower canopy layers. CBD concentrations in inflorescences from lower canopy layers were reduced by 23% in the V-trial and 46% in the D-trial. However, with increasing PD, the proportion of higher-concentrated inflorescence fractions from upper canopy layers increased from 46% to 68%, while an extension of DVP shifted this proportion only marginally from 45% to 50%. In the context of standardized production, we therefore advocate high-density production systems that increase the proportion of desired inflorescence fractions from upper canopy layers.
Non-destructive near-infrared technology for efficient cannabinoid analysis in cannabis inflorescences
(2024) Rafiq, Hamza; Hartung, Jens; Schober, Torsten; Vogt, Maximilian M.; Carrera, Dániel Árpád; Ruckle, Michael; Graeff-Hönninger, Simone
In the evolving field of cannabis research, scholars are exploring innovative methods to quantify cannabinoids rapidly and non-destructively. This study evaluates the effectiveness of a hand-held near-infrared (NIR) device for quantifying total cannabidiol (total CBD), total delta-9-tetrahydrocannabinol (total THC), and total cannabigerol (total CBG) in whole cannabis inflorescences. Employing pre-processing techniques, including standard normal variate (SNV) and Savitzky–Golay (SG) smoothing, we aim to optimize the portable NIR technology for rapid and non-destructive cannabinoid analysis. A partial least-squares regression (PLSR) model was utilized to predict cannabinoid concentration based on NIR spectra. The results indicated that SNV pre-processing exhibited superior performance in predicting total CBD concentration, yielding the lowest root mean square error of prediction (RMSEP) of 2.228 and the highest coefficient of determination for prediction (R2P) of 0.792. The ratio of performance to deviation (RPD) for total CBD was highest (2.195) with SNV. In contrast, raw data exhibited the least accurate predictions for total THC, with an R2P of 0.812, an RPD of 2.306, and an RMSEP of 1.651. Notably, total CBG prediction showed unique characteristics, with raw data yielding the highest R2P of 0.806. SNV pre-processing emerges as a robust method for precise total CBD quantification, offering valuable insights into the optimization of a hand-held NIR device for the rapid and non-destructive analysis of cannabinoid in whole inflorescence samples. These findings contribute to ongoing efforts in developing portable and efficient technologies for cannabinoid analysis, addressing the increasing demand for quick and accurate assessment methods in cannabis cultivation, pharmaceuticals, and regulatory compliance.
Towards standardized medicinal cannabis production systems: development of agronomic strategies and automated tools for plant growth monitoring and prediction in controlled environments
(2025) Schober, Torsten; Graeff-Hönninger, Simone
Medicinal cannabis producers are once again in a highly competitive market, which, despite good prospects, has had to contend with price erosion due to overproduction and rising production costs in recent years. Meanwhile, there is a growing awareness of the need for standardized cultivation systems and methods that enable a consistent and homogeneous quality of the flower material regarding cannabinoid and terpene profiles. Cultivation in indoor systems is therefore coming into focus, as these systems allow the plant life cycle, relevant environmental parameters (e.g., light, temperature, humidity, CO2 content of the air), and nutrient and water supply to be freely controlled. However, these systems often require a high input of energy and resources. Therefore, indoor growers face a multivariate optimization problem because the optimal interplay of genotype, environment, and plant management must be found regarding the target triangle of yield optimization, cost efficiency, and sustainability. Although agronomic research on cannabis has been on the rise in recent years, many practices and strategies in the industry are still based on anecdotal evidence and personal belief systems. Even basic agronomic principles vary widely across the industry and in research papers. At the same time, the influences of individual environmental parameters are often only considered separately without being able to integrate them into the complex overall picture. The development of standardized, controlled cultivation systems requires implementing “decision support systems” to incorporate the existing complexity of influencing factors. This involves monitoring systems that enable conclusions about the actual condition of the plant in real-time, as well as dynamic models that will allow the prediction of future growth behavior of the plant in response to changing environmental parameters. The main focus of this work was to investigate the influence of fundamental agronomic management decisions on the temporal course of plant growth and yield formation. The factors studied were to be evaluated regarding their effect on biomass production and cannabinoid homogeneity. The focus was on investigating different growing media, plant densities, and vegetation lengths. The data collected was used to create a basic concept for a real-time monitoring system and to calibrate a process-oriented growth model. Publication I describes two experiments comparing the most common growing media in the cannabis industry, namely rockwool, peat, and coco-coir mixtures. One experiment simulated the entire cultivation cycle, while the parallel experiment was designed to simulate an extended vegetative growth phase. A fertigation system was set up that allowed for an integrative, i.e., medium-specific, root zone management. Weekly destructive and non-destructive measurements were taken to generate a data set that was as detailed as possible to record plant growth. Likewise, environmental parameters such as light, temperature, and humidity were recorded in close temporal and spatial intervals. The comparison of the growing media was based on the estimated functional parameters of adjusted growth functions. The results showed that the effect of the growing medium on biomass production was primarily due to the ratio of transpiration area to available water. Furthermore, differences in nutrient uptake and assimilate distribution were observed, which had no significant effect on plant growth. The growing media only plays a minor role in the production and homogeneity of the secondary metabolites. In publication II, two further elementary management parameters were varied: planting density and the length of the vegetative phase. The aim was to develop empirical models for the effects of both factors on relevant growth parameters and, if possible, to derive recommendations for optimal canopy management. A strong linear correlation between yield per unit area and CBD production was demonstrated in both cases. Surprisingly, there was no yield saturation per unit area at high planting densities. However, the results illustrated how systems with high planting densities significantly increase the proportion of biomass in the upper half of the crop and, thus, the proportion of the desired inflorescence fractions. For standardized cultivation systems, it is, therefore, essential to optimize the planting density for the growth behavior of the genotypes used, whereby the possible planting densities can be significantly higher than the industry standards currently in place. The experiments served as the primary data basis for establishing an HSI system for quantifying plant nutrient status, which is presented in publication III. With the help of a self-built mobile camera frame, images were taken on a single-leaf and whole-plant basis using a hyperspectral camera. A chemometric model correlated the extracted spectra with the observed foliar concentrations of N, P, and K. This study was designed as a proof of concept. It showed that the system could accurately predict N and P concentrations under non-standardized light conditions in the greenhouse. The results of publications I - III were used in the subsequent discussion to outline a baseline for a standardized cultivation system for medicinal cannabis. The vertical gradient of the secondary metabolite concentration in inflorescences from the different canopy layers proves particularly problematic for standardized flower material. Maximizing plant density while considering microclimatic aspects is a key means of minimizing these gradients. At the same time, the duration of the vegetative phase, associated with height and side shoot growth, can be minimized. This allows the position of the inflorescences to be controlled as well as possible while minimizing the need for human intervention. The smaller plant size also simplifies fertigation management. It is a prerequisite for introducing vertical cultivation systems, significantly increasing indoor productivity and resource efficiency. Plant-based monitoring systems, such as the HSI system presented, can be expanded to capture further plant parameters in real-time. These can provide essential input data, especially in automated control systems for fertigation control. Due to the high acquisition rate, they also allow monitoring of the cultivation area with high spatial resolution. Thus, they can be used for the early detection of disease outbreaks and to reduce horizontal variability. In addition, the generated data sets were used to calibrate the CROPGRO model for the potential biomass production of medicinal cannabis in semi-controlled conditions. The model provided good predictions for the temporal course of height growth, leaf formation rate, biomass gain, and N mobilization. CROPGRO has the necessary interfaces to integrate further growth-limiting processes. The future of indoor cannabis cultivation is closely linked to developing smart greenhouses with intelligent, model-based control systems. This work provided important insights into agronomic conditions while creating the basic tools for future decision support systems.