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Record W4405123670 · doi:10.5376/mpr.2024.14.0020

Study on the Correlation Between the Physiological Characteristics of <i>Dendrobium officinale</i> and Optimal Cultivation Conditions

2024· article· en· W4405123670 on OpenAlexvenueno aff
Zhenyuan Zhang, Lingjuan Wang-Li, Xiangqian Fan

Bibliographic record

VenueMedicinal Plant Research · 2024
Typearticle
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsnot available
Fundersnot available
KeywordsDendrobiumCorrelationBiologyBotanyChemistryMathematics

Abstract

fetched live from OpenAlex

This study explores the correlation between the physiological characteristics of Dendrobium officinale and its cultivation conditions, with a focus on analyzing the effects of environmental factors such as temperature, light intensity, and nutrient supply on growth rate, photosynthetic efficiency, and accumulation of active compounds in D. officinale.The study found that appropriate light and potassium treatments significantly increase anthocyanin content, enhancing the plant's metabolic properties.Additionally, the application of mycorrhizal fungi improved D. officinale's resistance to drought and disease, effectively enhancing growth quality.Case analysis further indicated that pine bark substrate exhibits a high potential for flavonoid accumulation, and different cultivation modes (such as greenhouse and bionic cultivation) also impact the active components of D. officinale in varying ways.This study provides a scientific basis for sustainable cultivation of D. officinale, revealing approaches to optimize cultivation conditions to further enhance its medicinal value in clinical applications.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.170
GPT teacher head0.403
Teacher spread0.234 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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