<p>Understanding the stability and degradation pathways of cannabinoids during storage is crucial for both medicinal and forensic applications of <i>Cannabis sativa</i> L. This study investigated the long-term storage effects on cannabinoid profiles in <i>Cannabis sativa</i> L. (<i>C. sativa</i>) resin. 150 resin samples, seized by the Royal Gendarmerie of Morocco and stored for long periods of up to 8&#xa0;years, were analyzed. Cannabinoid percentages were quantified using gas chromatography with a flame ionization detector (GC/FID). Fresh, unstored cannabis samples initially exhibited the greatest overall extraction yield (37.9 ± 1.45%) and were characterized by high Δ<sup>9</sup>-tetrahydrocannabinol (THC) concentrations (35.16 ± 3.87%), alongside lower levels of cannabidiol (CBD) (3.92 ± 0.40%) and cannabinol (CBN) (0.87 ± 0.35%). Interestingly, after 2&#xa0;years of storage, a significant decrease in THC content was observed 2.74 ± 0,33%, accompanied by a corresponding increase in CBD (6.71 ± 0.77%) and CBN (6.94 ± 0.83%) concentrations. Principal component analysis (PCA) revealed strong correlations between storage time, yield of extraction, and cannabinoid profiles, and enabled the classification of samples based on storage duration and cannabinoids content. Polynomial and multiple regression were developed to predict the relationship between cannabinoid content and storage time. The prediction results indicate that the cubic model exhibit superior predictive performance compared to linear and quadratic alternatives in prediction cannabinoids in terms of storage time. Further, a multiple linear regression model with a hight R<sup>2</sup> = 0.99 was developed to predict the storage time based on cannabinoid levels. These findings provide valuable insights into the long-term stability of cannabinoids in <i>C. sativa</i> resin and hold potential implications for forensic applications, particularly in cases involving the analysis of aged cannabis samples.</p>

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Chemometric and predictive modeling of long term cannabinoid transformation in stored Cannabis sativa resin

  • Nezha Fettoukh,
  • Mouhcine Fadil,
  • Hamid Stambouli,
  • Aziz EL Bouri,
  • Taoufik Bouyoun,
  • Saoussan Annemer,
  • Abdelfattah Boukhaled,
  • Abdellah Farah

摘要

Understanding the stability and degradation pathways of cannabinoids during storage is crucial for both medicinal and forensic applications of Cannabis sativa L. This study investigated the long-term storage effects on cannabinoid profiles in Cannabis sativa L. (C. sativa) resin. 150 resin samples, seized by the Royal Gendarmerie of Morocco and stored for long periods of up to 8 years, were analyzed. Cannabinoid percentages were quantified using gas chromatography with a flame ionization detector (GC/FID). Fresh, unstored cannabis samples initially exhibited the greatest overall extraction yield (37.9 ± 1.45%) and were characterized by high Δ9-tetrahydrocannabinol (THC) concentrations (35.16 ± 3.87%), alongside lower levels of cannabidiol (CBD) (3.92 ± 0.40%) and cannabinol (CBN) (0.87 ± 0.35%). Interestingly, after 2 years of storage, a significant decrease in THC content was observed 2.74 ± 0,33%, accompanied by a corresponding increase in CBD (6.71 ± 0.77%) and CBN (6.94 ± 0.83%) concentrations. Principal component analysis (PCA) revealed strong correlations between storage time, yield of extraction, and cannabinoid profiles, and enabled the classification of samples based on storage duration and cannabinoids content. Polynomial and multiple regression were developed to predict the relationship between cannabinoid content and storage time. The prediction results indicate that the cubic model exhibit superior predictive performance compared to linear and quadratic alternatives in prediction cannabinoids in terms of storage time. Further, a multiple linear regression model with a hight R2 = 0.99 was developed to predict the storage time based on cannabinoid levels. These findings provide valuable insights into the long-term stability of cannabinoids in C. sativa resin and hold potential implications for forensic applications, particularly in cases involving the analysis of aged cannabis samples.