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Synergistic effect of phytohormone-producing ectomycorrhizal fungus <i>Suillus luteus</i> and fertilizer GGR6 on <i>Pinus massoniana</i> growth

2022· article· en· W6958944134 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSalicylic acidInoculationFungusFertilizerChlorophyllPlant growth

Abstract

fetched live from OpenAlex

<i>Suillus luteus</i> is an edible ectomycorrhizal fungus (EMF). The <i>S. luteus</i> strain LS88 secretes many phytohormones, including salicylic acid (SA) and indole-3-carboxylic acid (ICA). LS88 was inoculated to the tree <i>Pinus massoniana</i> and treated with the amino acid fertilizer GGR6. Plant growth parameters, plant enzyme activities, chlorophyll contents, and element contents were analyzed. Our results show that GGR6 may help the development of <i>S. luteus</i>-<i>P. massoniana</i> ectomycorrhiza. Moreover, LS88 and GGR6 synergistically affect <i>P. massoniana</i> growth and element uptake. Phytohormone detection on the roots of LS88-inoculated <i>P. massoniana</i> seedlings showed that LS88 could significantly increase the ICA content within a week. The SA content in the roots in the inoculated group seedlings increased slightly, but the salicylic acid 2-O-β-glucoside (SAG) content decreased. Therefore, we speculate GGR6 may enhance the growth-promoting effect of EMF on plants, and LS88 affects <i>P. massoniana</i> growth through secreting phytohormones.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.646
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0180.000

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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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