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Record W3200564635 · doi:10.3389/fmicb.2021.715758

Interactions Between Bacillus Spp., Pseudomonas Spp. and Cannabis sativa Promote Plant Growth

2021· article· en· W3200564635 on OpenAlexafffund
Dominique Comeau, Carole Balthazar, Amy Novinscak, Nadia Bouhamdani, David L. Joly, Martin Filion

Bibliographic record

VenueFrontiers in Microbiology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsAgriculture and Agri-Food CanadaUniversité de Moncton
FundersNew Brunswick Innovation FoundationGenome Canada
KeywordsRhizosphereRhizobacteriaPseudomonasBiologyMicrobiomeCannabis sativaBotanyBacillus (shape)BiotechnologyBacteriaMicrobiologyBioinformatics

Abstract

fetched live from OpenAlex

Plant growth-promoting rhizobacteria (PGPR) deploy several mechanisms to improve plant health, growth and yield. The aim of this study was to evaluate the efficacy of two Pseudomonas spp. strains and three Bacillus spp. strains used as single treatments and in consortia to improve the yield of Cannabis sativa and characterize the impact of these treatments on the diversity, structure and functions of the rhizosphere microbiome. Herein, we demonstrate a significant C. sativa yield increase up to 70% when inoculated with three different Pseudomonas spp./ Bacillus spp. consortia but not with single inoculation treatments. This growth-promoting effect was observed in two different commercial soil substrates commonly used to grow cannabis: Promix and Canna coco. Marker-based genomic analysis highlighted Bacillus spp. as the main modulator of the rhizosphere microbiome diversity and Pseudomonas spp. as being strongly associated with plant growth promotion. We describe an increase abundance of predicted PGPR metabolic pathways linked with growth-promoting interactions in C. sativa .

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations69
Published2021
Admission routes2
Has abstractyes

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