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

Autores
de la Fuente de la Torre, Laura Alethia; Zamberlan, Federico; Sánchez Ferrán, Andrés; Carrillo, Facundo; Tagliazucchi, Enzo Rodolfo; Pallavicini, Carla
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: Widespread commercialization of cannabis has led to the introduction of brand names based onusers? subjective experience of psychological effects and flavors, but this process has occurred in the absence ofagreed standards. The objective of this work was to leverage information extracted from large databases toevaluate the consistency and validity of these subjective reports, and to determine their correlation with thereported cultivars and with estimates of their chemical composition (delta-9-THC, CBD, terpenes).Methods: We analyzed a large publicly available dataset extracted from Leafly.com where users freely reportedtheir experiences with cannabis cultivars, including different subjective effects and flavour associations. This analysiswas complemented with information on the chemical composition of a subset of the cultivars extracted fromPsilabs.org. The structure of this dataset was investigated using network analysis applied to the pairwise similaritiesbetween reported subjective effects and/or chemical compositions. Random forest classifiers were used to evaluatewhether reports of flavours and subjective effects could identify the labelled species cultivar. We applied NaturalLanguage Processing (NLP) tools to free narratives written by the users to validate the subjective effect and flavourtags. Finally, we explored the relationship between terpenoid content, cannabinoid composition and subjectivereports in a subset of the cultivars.Results: Machine learning classifiers distinguished between species tags given by ?Cannabis sativa? and ?Cannabisindica? based on the reported flavours: = 0.828 ± 0.002 (p < 0.001); and effects: = 0.9965 ± 0.0002 (p <0.001). A significant relationship between terpene and cannabinoid content was suggested by positive correlationsbetween subjective effect and flavour tags (p < 0.05, False-Discovery-rate (FDR)-corrected); these correlationsclustered the reported effects into three groups that represented unpleasant, stimulant and soothing effects. Theuse of predefined tags was validated by applying latent semantic analysis tools to unstructured written reviews, alsoproviding breed-specific topics consistent with their purported subjective effects. Terpene profiles matched theperceptual characterizations made by the users, particularly for the terpene-flavours graph (Q = 0.324).
Fil: de la Fuente de la Torre, Laura Alethia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina
Fil: Zamberlan, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Sánchez Ferrán, Andrés. Universidad Nacional de Tucumán; Argentina
Fil: Carrillo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Pallavicini, Carla. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Materia
CANNABIS
CANNABINOIDS
TERPENES
FLAVOUR
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/140909
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/140909
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varietiesde la Fuente de la Torre, Laura AlethiaZamberlan, FedericoSánchez Ferrán, AndrésCarrillo, FacundoTagliazucchi, Enzo RodolfoPallavicini, CarlaCANNABISCANNABINOIDSTERPENESFLAVOURhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Background: Widespread commercialization of cannabis has led to the introduction of brand names based onusers? subjective experience of psychological effects and flavors, but this process has occurred in the absence ofagreed standards. The objective of this work was to leverage information extracted from large databases toevaluate the consistency and validity of these subjective reports, and to determine their correlation with thereported cultivars and with estimates of their chemical composition (delta-9-THC, CBD, terpenes).Methods: We analyzed a large publicly available dataset extracted from Leafly.com where users freely reportedtheir experiences with cannabis cultivars, including different subjective effects and flavour associations. This analysiswas complemented with information on the chemical composition of a subset of the cultivars extracted fromPsilabs.org. The structure of this dataset was investigated using network analysis applied to the pairwise similaritiesbetween reported subjective effects and/or chemical compositions. Random forest classifiers were used to evaluatewhether reports of flavours and subjective effects could identify the labelled species cultivar. We applied NaturalLanguage Processing (NLP) tools to free narratives written by the users to validate the subjective effect and flavourtags. Finally, we explored the relationship between terpenoid content, cannabinoid composition and subjectivereports in a subset of the cultivars.Results: Machine learning classifiers distinguished between species tags given by ?Cannabis sativa? and ?Cannabisindica? based on the reported flavours: <AUC> = 0.828 ± 0.002 (p < 0.001); and effects: <AUC> = 0.9965 ± 0.0002 (p <0.001). A significant relationship between terpene and cannabinoid content was suggested by positive correlationsbetween subjective effect and flavour tags (p < 0.05, False-Discovery-rate (FDR)-corrected); these correlationsclustered the reported effects into three groups that represented unpleasant, stimulant and soothing effects. Theuse of predefined tags was validated by applying latent semantic analysis tools to unstructured written reviews, alsoproviding breed-specific topics consistent with their purported subjective effects. Terpene profiles matched theperceptual characterizations made by the users, particularly for the terpene-flavours graph (Q = 0.324).Fil: de la Fuente de la Torre, Laura Alethia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; ArgentinaFil: Zamberlan, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Sánchez Ferrán, Andrés. Universidad Nacional de Tucumán; ArgentinaFil: Carrillo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Pallavicini, Carla. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaBioMed Central2020-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/140909de la Fuente de la Torre, Laura Alethia; Zamberlan, Federico; Sánchez Ferrán, Andrés; Carrillo, Facundo; Tagliazucchi, Enzo Rodolfo; et al.; Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties; BioMed Central; Journal of Cannabis Research; 2; 1; 7-2020; 1-182522-5782CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://jcannabisresearch.biomedcentral.com/articles/10.1186/s42238-020-00028-yinfo:eu-repo/semantics/altIdentifier/doi/10.1186/s42238-020-00028-yinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:46Zoai:ri.conicet.gov.ar:11336/140909instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:48:47.124CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
title Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
spellingShingle Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
de la Fuente de la Torre, Laura Alethia
CANNABIS
CANNABINOIDS
TERPENES
FLAVOUR
title_short Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
title_full Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
title_fullStr Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
title_full_unstemmed Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
title_sort Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties
dc.creator.none.fl_str_mv de la Fuente de la Torre, Laura Alethia
Zamberlan, Federico
Sánchez Ferrán, Andrés
Carrillo, Facundo
Tagliazucchi, Enzo Rodolfo
Pallavicini, Carla
author de la Fuente de la Torre, Laura Alethia
author_facet de la Fuente de la Torre, Laura Alethia
Zamberlan, Federico
Sánchez Ferrán, Andrés
Carrillo, Facundo
Tagliazucchi, Enzo Rodolfo
Pallavicini, Carla
author_role author
author2 Zamberlan, Federico
Sánchez Ferrán, Andrés
Carrillo, Facundo
Tagliazucchi, Enzo Rodolfo
Pallavicini, Carla
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv CANNABIS
CANNABINOIDS
TERPENES
FLAVOUR
topic CANNABIS
CANNABINOIDS
TERPENES
FLAVOUR
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Background: Widespread commercialization of cannabis has led to the introduction of brand names based onusers? subjective experience of psychological effects and flavors, but this process has occurred in the absence ofagreed standards. The objective of this work was to leverage information extracted from large databases toevaluate the consistency and validity of these subjective reports, and to determine their correlation with thereported cultivars and with estimates of their chemical composition (delta-9-THC, CBD, terpenes).Methods: We analyzed a large publicly available dataset extracted from Leafly.com where users freely reportedtheir experiences with cannabis cultivars, including different subjective effects and flavour associations. This analysiswas complemented with information on the chemical composition of a subset of the cultivars extracted fromPsilabs.org. The structure of this dataset was investigated using network analysis applied to the pairwise similaritiesbetween reported subjective effects and/or chemical compositions. Random forest classifiers were used to evaluatewhether reports of flavours and subjective effects could identify the labelled species cultivar. We applied NaturalLanguage Processing (NLP) tools to free narratives written by the users to validate the subjective effect and flavourtags. Finally, we explored the relationship between terpenoid content, cannabinoid composition and subjectivereports in a subset of the cultivars.Results: Machine learning classifiers distinguished between species tags given by ?Cannabis sativa? and ?Cannabisindica? based on the reported flavours: <AUC> = 0.828 ± 0.002 (p < 0.001); and effects: <AUC> = 0.9965 ± 0.0002 (p <0.001). A significant relationship between terpene and cannabinoid content was suggested by positive correlationsbetween subjective effect and flavour tags (p < 0.05, False-Discovery-rate (FDR)-corrected); these correlationsclustered the reported effects into three groups that represented unpleasant, stimulant and soothing effects. Theuse of predefined tags was validated by applying latent semantic analysis tools to unstructured written reviews, alsoproviding breed-specific topics consistent with their purported subjective effects. Terpene profiles matched theperceptual characterizations made by the users, particularly for the terpene-flavours graph (Q = 0.324).
Fil: de la Fuente de la Torre, Laura Alethia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina
Fil: Zamberlan, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Sánchez Ferrán, Andrés. Universidad Nacional de Tucumán; Argentina
Fil: Carrillo, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Pallavicini, Carla. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
description Background: Widespread commercialization of cannabis has led to the introduction of brand names based onusers? subjective experience of psychological effects and flavors, but this process has occurred in the absence ofagreed standards. The objective of this work was to leverage information extracted from large databases toevaluate the consistency and validity of these subjective reports, and to determine their correlation with thereported cultivars and with estimates of their chemical composition (delta-9-THC, CBD, terpenes).Methods: We analyzed a large publicly available dataset extracted from Leafly.com where users freely reportedtheir experiences with cannabis cultivars, including different subjective effects and flavour associations. This analysiswas complemented with information on the chemical composition of a subset of the cultivars extracted fromPsilabs.org. The structure of this dataset was investigated using network analysis applied to the pairwise similaritiesbetween reported subjective effects and/or chemical compositions. Random forest classifiers were used to evaluatewhether reports of flavours and subjective effects could identify the labelled species cultivar. We applied NaturalLanguage Processing (NLP) tools to free narratives written by the users to validate the subjective effect and flavourtags. Finally, we explored the relationship between terpenoid content, cannabinoid composition and subjectivereports in a subset of the cultivars.Results: Machine learning classifiers distinguished between species tags given by ?Cannabis sativa? and ?Cannabisindica? based on the reported flavours: <AUC> = 0.828 ± 0.002 (p < 0.001); and effects: <AUC> = 0.9965 ± 0.0002 (p <0.001). A significant relationship between terpene and cannabinoid content was suggested by positive correlationsbetween subjective effect and flavour tags (p < 0.05, False-Discovery-rate (FDR)-corrected); these correlationsclustered the reported effects into three groups that represented unpleasant, stimulant and soothing effects. Theuse of predefined tags was validated by applying latent semantic analysis tools to unstructured written reviews, alsoproviding breed-specific topics consistent with their purported subjective effects. Terpene profiles matched theperceptual characterizations made by the users, particularly for the terpene-flavours graph (Q = 0.324).
publishDate 2020
dc.date.none.fl_str_mv 2020-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/140909
de la Fuente de la Torre, Laura Alethia; Zamberlan, Federico; Sánchez Ferrán, Andrés; Carrillo, Facundo; Tagliazucchi, Enzo Rodolfo; et al.; Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties; BioMed Central; Journal of Cannabis Research; 2; 1; 7-2020; 1-18
2522-5782
CONICET Digital
CONICET
url http://hdl.handle.net/11336/140909
identifier_str_mv de la Fuente de la Torre, Laura Alethia; Zamberlan, Federico; Sánchez Ferrán, Andrés; Carrillo, Facundo; Tagliazucchi, Enzo Rodolfo; et al.; Relationship among subjective responses, flavor, and chemical composition across more than 800 commercial cannabis varieties; BioMed Central; Journal of Cannabis Research; 2; 1; 7-2020; 1-18
2522-5782
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://jcannabisresearch.biomedcentral.com/articles/10.1186/s42238-020-00028-y
info:eu-repo/semantics/altIdentifier/doi/10.1186/s42238-020-00028-y
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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