Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties

FEDERICO ZAMBERLAN; ENZO TAGLIAZUCCHI; ANDRÉS SÁNCHEZ FERRÁN; CARLA PALLAVICINI ; ALETHIA DE LA FUENTE; FACUNDO CARRILLO

Journal of Cannabis Research

biomedcentral

Año: 2020

2522-5782

BackgroundWidespread commercialization of cannabis has led to the introduction of brand names based on users? subjective experience of psychological effects and flavors, but this process has occurred in the absence of agreed standards. The objective of this work was to leverage information extracted from large databases to evaluate the consistency and validity of these subjective reports, and to determine their correlation with the reported cultivars and with estimates of their chemical composition (delta-9-THC, CBD, terpenes).MethodsWe analyzed a large publicly available dataset extracted from Leafly.com where users freely reported their experiences with cannabis cultivars, including different subjective effects and flavour associations. This analysis was complemented with information on the chemical composition of a subset of the cultivars extracted from Psilabs.org. The structure of this dataset was investigated using network analysis applied to the pairwise similarities between reported subjective effects and/or chemical compositions. Random forest classifiers were used to evaluate whether reports of flavours and subjective effects could identify the labelled species cultivar. We applied Natural Language Processing (NLP) tools to free narratives written by the users to validate the subjective effect and flavour tags. Finally, we explored the relationship between terpenoid content, cannabinoid composition and subjective reports in a subset of the cultivars.ResultsMachine learning classifiers distinguished between species tags given by ?Cannabis sativa? and ?Cannabis indica? based on the reported flavours:  = 0.828 ± 0.002 (p