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Inoculation with microbial consortia enhances the growth, nutrition and oil concentration of Ocimum sanctum

2017· article· en· W2783840126 on OpenAlexaff
E. Jyothi, D. J. Bagyaraj

Bibliographic record

VenueMedicinal Plants - International Journal of Phytomedicines and Related Industries · 2017
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsCentre for Community Based Research
Fundersnot available
KeywordsOcimumInoculationBiologyFood scienceHorticulture

Abstract

fetched live from OpenAlex

Ocimum sanctum is an important medicinal plant. The leaves are rich in eugenol, which is the active constituent of this medicinal plant. An earlier pot culture study brought out that Pantoea dispersa as the best PGPR and Glomus monosporum as the best AM fungi for inoculating Ocimum sanctum. In the present investigation, a pot culture experiment was conducted in a glasshouse, to study the effect of individual as well as microbial consortia of P. dispersa + G. monosporum on the growth of O. sanctum. The plant height, stem girth, plant dry matter and essential oil concentration and its main component eugenol were significantly higher in plants inoculated with P. dispersa + G. monosporum. The results showed that inoculation with microbial consortia, significantly increased root and shoot biomass of O. sanctum as well as eugenol, in comparison to control. It was concluded that the inoculated microbial consortia (P. dispersa + G. monosporum) interact synergistically and increased the biomaas and yield of oil in O. sanctum.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.274
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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