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• W2896779089 abstract "It is known that Cannabis in Brazil could either originate from Paraguay or be cultivated in Brazil. While consumer markets in the North and Northeast regions are maintained by national production, the rest of the country is supplied with Cannabis from Paraguay. However, the Brazilian Federal Police (BFP) has exponentially increased the seizure number of Cannabis seeds sent by mail. For this reason, the aim of the study was to assess the 13-loci short tandem repeat (STR) multiplex system proposed by Houston et al. (2015) to evaluate the power of such markers in individualization and origin differentiation of Cannabis sativa samples seized in Brazil by the BFP. To do so, 72 Cannabis samples seized in Brazil by BFP were analyzed. The principal coordinate analysis (PCoA) and probability identity (PI) analysis were computed. Additionally, the Cannabis samples’ genotypes were subjected to comparison by Kruskal-Wallis H, followed by a multiple discriminant analysis (MDA). All samples analyzed revealed a distinct genetic profile. PCoA clearly discriminated the seizure sets based on their geographic origin. A combination of seven loci was enough to differentiate samples’ genotypes, and the PI for a random sample is approximately one in 50 billion. The Cannabis samples were 100% correct as classified by Kruskal-Wallis H, followed by an MDA. The results of this study demonstrate that the 13-loci STR multiplex system successfully achieved the aim of sample individualization and origin differentiation and suggest that it could be a useful tool to help BFP intelligence in tracing back-trade routes." @default.
• W2896779089 created "2018-10-26" @default.
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• W2896779089 date "2018-10-15" @default.
• W2896779089 modified "2023-10-15" @default.
• W2896779089 title "13-loci STR multiplex system for Brazilian seized samples of marijuana: individualization and origin differentiation" @default.
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• W2896779089 doi "https://doi.org/10.1007/s00414-018-1940-3" @default.
• W2896779089 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30324327" @default.
• W2896779089 hasPublicationYear "2018" @default.
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