Research record19 September 2025Journal article
Profiling of various dry Cannabis sativa from Aceh, Indonesia, based on cannabinoids spectroscopy characteristics
Supiyani Supiyani, Sarah Salsabil, Alya Mumtazah, Alya Syakira
Egyptian Journal of Forensic Sciences · 2025
Abstract
Cannabis, which is a psychoactive plant, refers to the leaves, flowers, stems, and seeds. Cannabis is used globally for its psychoactive properties, with 2.5% of the world's population consuming it for recreational purposes. But in Indonesia, the plant is classified as a Class 1 narcotic, with a prevalence of use reaching 41.4%. Aceh is one of the largest cannabis-producing regions in Indonesia due to its favorable geographical and climatic conditions. Despite its illegal status, cannabis contains valuable phytocannabinoid compounds and is potentially important in medical applications. Previous studies have shown a correlation between the compound profile of cannabis and its geographical origin. This study aims to develop a classification method based on the cannabinoids compound profiles of dried cannabis samples taken from five regions in Aceh (Aceh Besar, Aceh Tengah, Bireuen, Lhokseumawe, and Pidie Jaya) by microscopy, Raman spectrophotometry, GC–MS, and parametric statistical analysis to assist authorities in tracing the source of cannabis for law enforcement and forensic purposes. In this study, dried Cannabis sativa from five regions of Aceh, Indonesia, was tested with Raman spectroscopy and GC–MS to produce informative cannabinoid compound profiles as plant profiling. The results obtained 10 cannabinoids quantified in plant samples (Δ9-THC, CBD, THCV, CBL, CBTC, Methoxy-THC, CBC, CBG, Δ9-THCH, and CBN). The cannabinoids compound profile showed Δ9-THC had the highest overall content and was indicated as the most important compound in the cannabis plant clustering profile. Among the various regions, Aceh Besar had the highest cannabis content. Statistical analysis of Raman spectroscopy and GC–MS data found (1) revealed compounds responsible for clustering cultivars between clusters, (2) variation among cannabis chemical profiles as a result of growing environment, and (3) facilitated prediction of cannabis profiles in helping to categorise regions of unknown cannabis origin based on chemical profiles. Raman spectroscopy and GC–MS have proven reliable and efficient methods for classifying Cannabis sativa based on its cannabinoid profile in Aceh, Indonesia. The findings help reveal the geographical origin of the growing location of cannabis plant specimens. All five cannabis samples contained a major Δ9-THC psychoactive constituent. The highest Δ9-THC content comes from AB due to the influence of environmental factors. Parametric test analysis concluded that there was no significant effect of geographical origin related to the relatively close distance range of samples. Additionally, comparing these methods with other analytical techniques will support defined classification models and improve their application in forensic science, particularly in drug enforcement and quality assessment.
The paper's abstract, reproduced as published.
Record created 8 August 2026 · maintained by landrace.wiki editors ·
page history
Published19 Sep 2025
TypeJournal article
VenueEgyptian Journal of Forensic Sciences
Year2025
Growing regionAceh
2025-09-19
2026-08-08
Profiling of various dry Cannabis sativa from Aceh, Indonesia, based on cannabinoids spectroscopy characteristics
Journal article
Chemistry
Supiyani Supiyani, Sarah Salsabil, Alya Mumtazah, Alya Syakira
Egyptian Journal of Forensic Sciences
2025
10.1186/s41935-025-00480-y
https://link.springer.com/article/10.1186/s41935-025-00480-y
Forensic profiling of five dried Cannabis sativa samples seized in Aceh province, one each from Aceh Besar, Aceh Tengah, Bireuen, Lhokseumawe and Pidie Jaya, using microscopy, Raman spectroscopy and GC-MS. The authors identified ten cannabinoids, with delta-9-THC dominant in every sample; reported THC values range from 28.90% (Aceh Tengah) to 57.48% (Aceh Besar), a spread the authors attribute to environmental factors. The accessible text does not state whether the percentages are by dry weight or relative abundance among detected cannabinoids. Sampling is confined to Aceh; no North Sumatra material was analysed.
Cannabis, which is a psychoactive plant, refers to the leaves, flowers, stems, and seeds. Cannabis is used globally for its psychoactive properties, with 2.5% of the world's population consuming it for recreational purposes. But in Indonesia, the plant is classified as a Class 1 narcotic, with a prevalence of use reaching 41.4%. Aceh is one of the largest cannabis-producing regions in Indonesia due to its favorable geographical and climatic conditions. Despite its illegal status, cannabis contains valuable phytocannabinoid compounds and is potentially important in medical applications. Previous studies have shown a correlation between the compound profile of cannabis and its geographical origin. This study aims to develop a classification method based on the cannabinoids compound profiles of dried cannabis samples taken from five regions in Aceh (Aceh Besar, Aceh Tengah, Bireuen, Lhokseumawe, and Pidie Jaya) by microscopy, Raman spectrophotometry, GC–MS, and parametric statistical analysis to assist authorities in tracing the source of cannabis for law enforcement and forensic purposes. In this study, dried Cannabis sativa from five regions of Aceh, Indonesia, was tested with Raman spectroscopy and GC–MS to produce informative cannabinoid compound profiles as plant profiling. The results obtained 10 cannabinoids quantified in plant samples (Δ9-THC, CBD, THCV, CBL, CBTC, Methoxy-THC, CBC, CBG, Δ9-THCH, and CBN). The cannabinoids compound profile showed Δ9-THC had the highest overall content and was indicated as the most important compound in the cannabis plant clustering profile. Among the various regions, Aceh Besar had the highest cannabis content. Statistical analysis of Raman spectroscopy and GC–MS data found (1) revealed compounds responsible for clustering cultivars between clusters, (2) variation among cannabis chemical profiles as a result of growing environment, and (3) facilitated prediction of cannabis profiles in helping to categorise regions of unknown cannabis origin based on chemical profiles. Raman spectroscopy and GC–MS have proven reliable and efficient methods for classifying Cannabis sativa based on its cannabinoid profile in Aceh, Indonesia. The findings help reveal the geographical origin of the growing location of cannabis plant specimens. All five cannabis samples contained a major Δ9-THC psychoactive constituent. The highest Δ9-THC content comes from AB due to the influence of environmental factors. Parametric test analysis concluded that there was no significant effect of geographical origin related to the relatively close distance range of samples. Additionally, comparing these methods with other analytical techniques will support defined classification models and improve their application in forensic science, particularly in drug enforcement and quality assessment.
Indonesia
Aceh
