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Photoperiodic Response of in vitro <em>Cannabis sativa </em>Plants

2020· preprint· en· W3124029807 on OpenAlexafffund
Melissa Moher, Max Jones, Youbin Zheng

Bibliographic record

VenuePreprints.org · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of Guelph
FundersOntario Centres of Excellence
KeywordsExplant cultureCannabis sativaphotoperiodismBiologyHorticultureCultivarCannabisGenotypeIn vitroBotanyGeneMedicineGenetics

Abstract

fetched live from OpenAlex

Most commercial Cannabis sativa L. (cannabis) genotypes are short-day plants and cultivators typically use a 12.0 h uninterrupted dark period to induce flowering; however, scientific information is lacking to prove this is the optimal dark period for all genotypes, and cultivar specific photoperiods may increase productivity. Tissue culture can be used for research requiring multiple treatments, proper replication, and in a controlled environment on a smaller scale compared to greenhouse and indoor facilities. To determine whether cannabis explants can flower under varied photoperiods in vitro, explants were grown under one of six photoperiod treatments: 12.0, 13.2, 13.8, 14.4, 15.0, and 16.0 h for four weeks. The percentage of flowering explants was highest under 12.0 and 13.2 h treatments. There were no treatment effects on the fresh weight, final height, or growth index of the explants. The results suggest an uninterrupted dark period of at least 10.8 h (i.e. 13.2 h photoperiod) is needed to induce the flowering of this genotype. In vitro flowering could provide a unique and high throughput approach to study floral/seed development and secondary metabolism in cannabis under highly controlled conditions. Further research should determine if this response is the same on a whole plant level.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.294
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2020
Admission routes2
Has abstractyes

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