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Record W2789623097 · doi:10.1111/jam.13749

Enhancing total lipid and stearidonic acid yields in<i>Buglossoides arvensis</i>through PGPR inoculation

2018· article· en· W2789623097 on OpenAlexafffund
Amy Novinscak, Martin Filion

Bibliographic record

VenueJournal of Applied Microbiology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversité de Moncton
FundersAtlantic Canada Opportunities Agency
KeywordsPseudomonas fluorescensInoculationShootBiologyHorticulturePseudomonasFood scienceRhizobacteriaBotanyMicrobiologyBacteriaRhizosphere

Abstract

fetched live from OpenAlex

AIM: This study was performed to identify bacterial isolates capable of enhancing total lipid and stearidonic acid (SDA) yields in Buglossoides arvensis. METHODS AND RESULTS: Pot experiments were conducted to screen the effects of 40 bacterial isolates on different B. arvensis growth parameters. Five isolates increased total lipid and SDA yields by at least 20%. These isolates were tested in a second pot experiment and in field trials. The second pot experiment confirmed that all isolates significantly increased total lipid and SDA yields over controls. Plants inoculated with four bacterial strains experienced significantly higher shoot weights, however, the increase in shoot weight decreased over time. Three isolates led to higher total seed numbers. In field trials, the inoculations had no significant effect on seed or lipid yields. However, isolate Pseudomonas fluorescens LBUM677 significantly increased SDA yield by 33% as compared to control plants. This strain was also the most efficient biofilm producer. CONCLUSIONS: Pseudomonas fluorescens LBUM677 can significantly increase SDA yield in B. arvensis under controlled and field conditions. SIGNIFICANCE AND IMPACT OF THE STUDY: Using bacterial strains to increase plant yield is of great interest under commercial settings. Pseudomonas fluorescens LBUM677 shows promise to promote SDA accumulation in B. arvensis under production conditions.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.206

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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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