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Record W2975105430 · doi:10.5539/jas.v11n17p1

Evaluation of Antioxidant Activity and Some Secondary Metabolites of Purple Coneflower (Echinacea purpurea L.) in Response to Biological and Chemical Fertilizers

2019· article· en· W2975105430 on OpenAlexvenueno aff
Reza Isazadeh Hajagha, Leila Tabrizi, Ebru Kafkas, Saliha Kırıc

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsnot available
FundersCollege of Agriculture Natural Resources, University of TehranUniversity of Tehran
KeywordsFerulic acidChlorogenic acidRandomized block designCaffeic acidBiologyAzotobacterHorticultureMicrobial inoculantCatechinTraditional medicineBacteriaPolyphenolBotanyFood scienceAntioxidantMedicine

Abstract

fetched live from OpenAlex

Purple coneflower (Echinacea pupurea L.) is an ornamental-medicinal plant belonging to Asteraceae family. It has long been used as an herbal medicine. In order to study the effects of biological and chemical fertilizers on quantitative and qualitative yields of purple coneflower, an experiment was conducted at Department of Horticultural Science and Landscape, University of Tehran. The trial was arranged based on a randomized complete block design, with eight treatments and three replications. Treatments were included control (no fertilizers), nitrogen-fixing, bacteria: Azospirillum lipoferum (AL), Azotobacter chrococum (AC), phosphorus solubilizing bacterium Pseudomonas fluorecens, (PF), Glomus intrradices inoculum (GI), the mixture of the three bacteria and the mixture of the three bacteria plus the mycorrhizal inoculum. According to the results of HPLC, Catechin content was high at herbage in both years. In addition, the best results have been taken from the AL and AC with the control. Caffeic acid, chlorogenic acid and Epicatechin contents were higher during the first year of the herbage, and control, AC and AL treatments gave high value. Ferulic acid was high in the herbage during the first year and generally high values were obtained from PF and GI treatments. Quercetin content was high in plant root during the first year with AC application.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.122

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.020
GPT teacher head0.300
Teacher spread0.279 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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