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Record W2891190000 · doi:10.14258/jcprm.2018033747

THE INFLUENCE OF CULTIVATION CONDITIONS ON MORPHOPHYSIOLOGICAL ACTIVITY AND CONTENT OF PHENOLIC COMPOUNDS OF ST. JOHN'S WORT (HYPERICUM PERFORATUM L.) IN VITRO CULTURE

2018· article· en· W2891190000 on OpenAlexaboutno aff
Вера Николаевна Овчинникова, Наталья Петровна Карсункина, Петр Николаевич Харченко, Natalia V. Nikiforova

Bibliographic record

Venuechemistry of plant raw material · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsnot available
Fundersnot available
KeywordsHypericum perforatumComposition (language)HypericumShootChemistryHyperforinBotanyIn vitroHorticultureBiologyFood scienceBiochemistry

Abstract

fetched live from OpenAlex

The paper discusses the joint effect of cytokine 6-BAP and different spectra when illuminated by LEDs on the morphological parameters of growth, development and the content of phenolic compounds in plants of St. John's Wort (Hypericum perforatum L.) of two genotypes – wild and cultivated (cultivar Zolotodolinskiy) – in conditions of in vitro cultivation.It is shown that the light of different spectral composition and the hormonal composition of medium influences the morphogenesis, the productivity of biomass and the synthesis of phenolic compounds by plants under in vitro cultivation conditions.It is established that the combination of the light spectrum, and the hormonal composition of nutrient medium may substantially increase the content of soluble phenolic compounds in both wild and cultural genotypes of Hypericum.The analysis of the obtained results shows a direct correlation dependence of the content of phenolic compounds on the number of shoots and their mass. The correlation between the number of shoots and the content of phenolic compounds has a direct character and strongly expressed.

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 score0.210
Threshold uncertainty score0.152

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 head0.210
Teacher spread0.197 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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