Dataset Information

Microbial hazards during harvesting and processing at an outdoor United States cannabis farm.

ABSTRACT: Cannabis cultivation is an emerging industry within the United States. Organic dust derived in part from naturally occurring microorganisms is known to cause byssinosis in the hemp industry. In this pilot study, bacteria and fungi encountered by workers at an outdoor cannabis farm that utilized organic practices were elucidated by 16 S ribosomal RNA (rRNA) and Internal Transcribed Spacer (ITS) region sequencing, respectively. Area (n = 14) and personal air samples (n = 12) were collected during harvesting and processing activities. 16 S rRNA and ITS regions of extracted bacterial and fungal genomic DNA were amplified and sequenced using Sanger sequencing. Bacterial sequencing resolved 1,077 sequences that were clustered into 639 operational taxonomic units (OTUs) and predominantly placed in the phylum, Actinobacteria (46%). Personal air samples revealed higher bacterial and Actinobacteria diversity compared to outdoor area samples collected within the facility (p < 0.05). A high degree of dissimilarity between bacteria was identified within and between samples. Fungal sequences (n = 985) were identified and predominantly clustered in the phylum Ascomycota (53%). Of the 216 fungal OTUs elucidated, the cannabis plant pathogenic species, Botrytis cinerea, was the most prevalent and accounted for 34% of all fungal sequences. The relative abundance of B. cinerea was highest in personal air samples (59%) compared to area samples collected in the drying room (19%), greenhouse (18%), and outdoor environment (6%). There was 49% sample similarity between fungi identified within personal air samples, but higher dissimilarity coefficients were observed within and between greenhouse, drying room, and outdoor area air samples. The results of this pilot study suggest that the cannabis farm workers are potentially exposed to Actinobacteria as well as the cannabis plant pathogen, B. cinerea during harvesting, bud-stripping, and hand-trimming processes.

SUBMITTER: Green BJ

PROVIDER: S-EPMC6314012 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microbial hazards during harvesting and processing at an outdoor United States cannabis farm.

Green Brett J BJ Couch James R JR Lemons Angela R AR Burton Nancy C NC Victory Kerton R KR Nayak Ajay P AP Beezhold Donald H DH

Journal of occupational and environmental hygiene 20180501 5

Cannabis cultivation is an emerging industry within the United States. Organic dust derived in part from naturally occurring microorganisms is known to cause byssinosis in the hemp industry. In this pilot study, bacteria and fungi encountered by workers at an outdoor cannabis farm that utilized organic practices were elucidated by 16 S ribosomal RNA (rRNA) and Internal Transcribed Spacer (ITS) region sequencing, respectively. Area (n = 14) and personal air samples (n = 12) were collected during ...[more]

PMID: 29370578

Similar Datasets

Project description:BackgroundThis study used surveillance data from 2018 and 2020 to test the stability of work-related strain symptoms (high stress, sleep deprivation, exhaustion) with demographic factors, work characteristics, and musculoskeletal symptoms among farm and ranch operators in seven midwestern states of the United States.MethodsCross-sectional surveys were conducted among farm and ranch operators in 2018 (n = 4423) and 2020 (n = 3492). Operators were asked whether, in the past 12 months, they experienced extended work periods that resulted in high stress levels, sleep deprivation, exhaustion/fatigue, or other work-related strain symptoms. Covariates included personal and demographic factors, work characteristics, number of injuries, work-related health conditions, and exposures on the operation. Summary statistics were tabulated for explanatory and outcome variables. The classification (decision) tree approach was used to assess what variables would best separate operators with and without reported strain symptoms, based on a set of explanatory variables. Regularized regression was used to generate effect estimates between the work strain variables and explanatory variables.ResultsHigh stress level, sleep deprivation, and exhaustion were reported more frequently in 2018 than 2020. The classification tree reproduced the 2018 model using 2020 data with approximately 80% accuracy. The mean number of reported MSD symptoms increased slightly from 1.23 in 2018 to 1.41 in 2020. Older age, more time spent in farm work, higher gross farm income (GFI), and MSD symptoms in six body regions (ankles/feet, knees, lower back, neck, shoulders, wrists/hands) were associated with all three work strain symptoms.ConclusionsMusculoskeletal pain and discomfort was a strong predictor for stress, sleep deprivation, and exhaustion among farmers and ranchers. This finding indicates that reducing MSD pain and discomfort is beneficial for both physical and mental health.

Dataset Information

Microbial hazards during harvesting and processing at an outdoor United States cannabis farm.

Publications

Microbial hazards during harvesting and processing at an outdoor United States cannabis farm.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets