Browsing by Person "Rafiq, Hamza"

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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.
Potential of impedance flow cytometry to assess the viability and quantity of Cannabis sativa L. pollen
(2021) Rafiq, Hamza; Hartung, Jens; Burgel, Lisa; Röll, Georg; Graeff-Hönninger, Simone
Over the last decade, efforts to breed new Cannabis sativa L. cultivars with high Cannabidiol (CBD) and other non-psychoactive cannabinoids with low tetrahydrocannabinol (THC) levels have increased. In this context, the identification of the viability and quantity of pollen, which represents the fitness of male gametophytes, to accomplish successful pollination is of high importance. The present study aims to evaluate the potential of impedance flow cytometry (IFC) for the assessment of pollen viability (PV) and total number of pollen cells (TPC) in two phytocannabinoid-rich cannabis genotypes, KANADA (KAN) and A4 treated with two different chemical solutions, silver thiosulfate solution (STS) and gibberellic acid (GA3). Pollen was collected over a period of 8 to 24 days after flowering (DAF) in a greenhouse experiment. Impedance flow cytometry (IFC) technology was used with Cannabis sativa to assess the viability and quantity of pollen. The results showed that the number of flowers per plant was highest at 24 DAF for both genotypes, A4 (317.78) and KAN (189.74). TPC induced by STS was significantly higher compared to GA3 over the collection period of 8 to 24 DAF with the highest mean TPC of 1.54 × 105 at 14 DAF. STS showed significantly higher viability of pollen compared to GA3 in genotype KAN, with the highest PV of 78.18% 11 DAF. Genotype A4 also showed significantly higher PV with STS at 8 (45.66%), 14 (77.88%), 18 (79.37%), and 24 (51.92%) DAF compared to GA3. Furthermore, counting the numbers of flowers did not provide insights into the quality and quantity of pollen; the results showed that PV was highest at 18 DAF with A4; however, the number of flowers per plant was 150.33 at 18 DAF and was thus not the maximum of produced flowers within the experiment. IFC technology successfully estimated the TPC and differentiated between viable and non-viable cells over a period of 8 to 24 DAF in tested genotypes of Cannabis sativa. IFC seems to be an efficient and reliable method to estimate PV, opening new chances for plant breeding and plant production processes in cannabis.