Profiling of Various Dry Cannabis Sativa From Aceh, Indonesia Based on Cannabinoids Compound Characteristics DOI
Supiyani Supiyani,

Sarah Salsabil,

Alya Mumtazah

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Abstract Background Cannabis, which is a narcotic plant, refers to the leaves, flowers, stems, and seeds. Cannabis used globally for its psychoactive properties with 2.5% of world's population consuming it for. In Indonesia, plant classified as Class 1 prevalence use reaching 41.4%. Aceh one largest cannabis producing regions in due favorable geographical climatic conditions. Despite illegal status, contains valuable phytocannabinoid compounds potentially important medical applications. Previous studies have shown correlation between compound profile origin. This study aims develop classification method based on cannabinoids profiles dried samples taken from five (Aceh Besar, Tengah, Bireuen, Lhokseumawe, Pidie Jaya), by microscopy, raman spectrophotometry, GC-MS, parametric statistical analysis assist authorities tracing source law enforcement forensic purposes. Results In this study, sativa Aceh, was tested Raman spectroscopy GC-MS produce informative cannabinoid profiling. The results obtained 10 quantified (Δ9-THC, CBD, THCV, CBL, CBTC, Methoxy-THC, CBC, CBG, Δ9-THCH, CBN). showed Δ9-THC had highest overall content indicated most clustering profile. Among various regions, Besar content. Statistical data found (1) revealed responsible cultivars clusters, (2) variation among chemical result growing environment, (3) facilitated prediction helping categorize unknown origin profiles. Conclusion Raman proven reliable efficient methods classifying Indonesia. findings help reveal location specimens. All contained major constituent. comes AB influence environmental factors. Parametric test concluded that there no significant effect geog raphical related relatively close distance range samples. Additionally, comparing these other analytical techniques will support defined models improve their application science, particularly drug quality assessment.

Language: Английский

Profiling of Various Dry Cannabis Sativa From Aceh, Indonesia Based on Cannabinoids Compound Characteristics DOI
Supiyani Supiyani,

Sarah Salsabil,

Alya Mumtazah

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Abstract Background Cannabis, which is a narcotic plant, refers to the leaves, flowers, stems, and seeds. Cannabis used globally for its psychoactive properties with 2.5% of world's population consuming it for. In Indonesia, plant classified as Class 1 prevalence use reaching 41.4%. Aceh one largest cannabis producing regions in due favorable geographical climatic conditions. Despite illegal status, contains valuable phytocannabinoid compounds potentially important medical applications. Previous studies have shown correlation between compound profile origin. This study aims develop classification method based on cannabinoids profiles dried samples taken from five (Aceh Besar, Tengah, Bireuen, Lhokseumawe, Pidie Jaya), by microscopy, raman spectrophotometry, GC-MS, parametric statistical analysis assist authorities tracing source law enforcement forensic purposes. Results In this study, sativa Aceh, was tested Raman spectroscopy GC-MS produce informative cannabinoid profiling. The results obtained 10 quantified (Δ9-THC, CBD, THCV, CBL, CBTC, Methoxy-THC, CBC, CBG, Δ9-THCH, CBN). showed Δ9-THC had highest overall content indicated most clustering profile. Among various regions, Besar content. Statistical data found (1) revealed responsible cultivars clusters, (2) variation among chemical result growing environment, (3) facilitated prediction helping categorize unknown origin profiles. Conclusion Raman proven reliable efficient methods classifying Indonesia. findings help reveal location specimens. All contained major constituent. comes AB influence environmental factors. Parametric test concluded that there no significant effect geog raphical related relatively close distance range samples. Additionally, comparing these other analytical techniques will support defined models improve their application science, particularly drug quality assessment.

Language: Английский

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