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Phytochemical screening and HPTLC fingerprinting of different parts of Solanum indicum L.: A dashmool species

2021· article· en· W3127005284 on OpenAlexfundno aff
Hari Om Saxena, Ganesh Pawar, Santosh Kumar Choubey, Pranav Dhar

Bibliographic record

VenueJournal of Pharmacognosy and Phytochemistry · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
FundersIndian Council of Forestry Research and EducationTerry Fox Research Institute
KeywordsPhytochemicalGlycosideTraditional medicineChemistryTerpenoidPhenolsEthyl acetateChromatographyBotanyBiologyOrganic chemistryBiochemistryMedicine

Abstract

fetched live from OpenAlex

The objective of the study is to screen phytochemicals and develop chemical fingerprints of medicinally important Solanum indicum L. The powdered pant materials of leaf, fruit, stem and roots of S. indicum were extracted in methanol by soxhlet apparatus. Extracts were subjected to phytochemical screening and HPTLC fingerprints were developed. For development of fingerprints Cyclohexane: Ethyl acetate: Formic acid (6: 4: 1) was used as mobile phase. Phytochemical screening revealed the presence of alkaloids, cardiac glycosides, flavonoids, phenols, saponins and terpenoids in all the plant parts. Steroids were found present in leaves, fruits and roots whereas tannins were detected in leaves only. HPTLC fingerprinting of methanolic extracts of all plant parts has shown several peaks with different Rf values and peak areas. Phytoconstituents investigated have been described to have tremendous medicinal values in literature. HPTLC fingerprints would be helpful in identification, authentication and quality control of this species.

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 score0.009
Threshold uncertainty score0.239

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 head0.015
GPT teacher head0.228
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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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