AIMC Topic: Cannabis
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Machine Learning-Aided Optimization of In Vitro Tetraploid Induction in Cannabis.
International journal of molecular sciences
Feb 18, 2025
Polyploidy, characterized by an increase in the number of whole sets of chromosomes in an organism, offers a promising avenue for cannabis improvement. Polyploid cannabis plants often exhibit altered morphological, physiological, and biochemical char...
Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis.
The Plant journal : for cell and molecular biology
Nov 27, 2024
Cannabis sativa L., known for its medicinal and psychoactive properties, has recently experienced rapid market expansion but remains understudied in terms of its fundamental biology due to historical prohibitions. This pioneering study implements GS ...
An initial exploration of machine learning for establishing associations between genetic markers and THC levels in Cannabis sativa samples.
Forensic science international. Genetics
Aug 9, 2024
Cannabis sativa, a globally commercialized plant used for medicinal, food, fiber production, and recreation, necessitates effective identification to distinguish legal and illegal varieties in forensic contexts. This research utilizes multivariate st...
Rapid In Situ Near-Infrared Assessment of Tetrahydrocannabinolic Acid in Cannabis Inflorescences before Harvest Using Machine Learning.
Sensors (Basel, Switzerland)
Aug 6, 2024
Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-ef...
Applying machine learning to international drug monitoring: classifying cannabis resin collected in Europe using cannabinoid concentrations.
European archives of psychiatry and clinical neuroscience
May 21, 2024
In Europe, concentrations of ∆-tetrahydrocannabinol (THC) in cannabis resin (also known as hash) have risen markedly in the past decade, potentially increasing risks of mental health disorders. Current approaches to international drug monitoring cann...
Deep learning-based quantification and transcriptomic profiling reveal a methyl jasmonate-mediated glandular trichome formation pathway in Cannabis sativa.
The Plant journal : for cell and molecular biology
Feb 8, 2024
Cannabis glandular trichomes (GTs) are economically and biotechnologically important structures that have a remarkable morphology and capacity to produce, store, and secrete diverse classes of secondary metabolites. However, our understanding of the ...
A broader view on deriving a reference dose for THC traces in foods.
Critical reviews in toxicology
Feb 17, 2022
An Acute Reference Dose (ARfD) of 1 µg of -9-tetrahydrocannabinol (THC) per kilogram (kg) of body weight (bw) per day was recommended by the European Food Safety Authority (EFSA) for its assessment of possible acute health risks from the intake of in...
Predicting suicidal thoughts and behavior among adolescents using the risk and protective factor framework: A large-scale machine learning approach.
PloS one
Nov 3, 2021
INTRODUCTION: Addressing the problem of suicidal thoughts and behavior (STB) in adolescents requires understanding the associated risk factors. While previous research has identified individual risk and protective factors associated with many adolesc...
Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.
Applied microbiology and biotechnology
Jun 4, 2021
Plant callus is generally considered to be a mass of undifferentiated cells and can be used for secondary metabolite production, physiological studies, and plant transformation/regeneration. However, there are several types of callus with different m...
An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.
Cannabis and cannabinoid research
Jun 19, 2020
Relatively little is known about the molecular pathways influenced by cannabis use in humans. We used a multi-omics approach to examine protein, metabolomic, and lipid markers in plasma differentiating between cannabis users and nonusers to understa...
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