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Record W2909353231 · doi:10.5539/jas.v11n2p210

Profile of Essential Oils From the Leaves of Annona Grafted

2019· article· en· W2909353231 on OpenAlexvenueno aff
Felipe Girotto Campos, Maria Aparecida Ribeiro Vieira, Daniel Barón, Márcia Ortiz Mayo Marques, Gisela Ferreira, Carmen Sílvia Fernandes Boaro

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTraditional and Medicinal Uses of Annonaceae
Canadian institutionsnot available
Fundersnot available
KeywordsAnnonaEssential oilAnnonaceaeChemistryCustard-appleBotanyChromatographyBiologyHorticulture

Abstract

fetched live from OpenAlex

Mechanical damage, during grafting, results in the formation of reactive oxygen species, which are neutralized by the enzymatic and non-enzymatic antioxidant systems which may influence the essential oil composition of grafts and rootstocks because of the formation of oxygenated terpenes, substances with higher reactivity against pathogens. Various studies have demonstrated the biological activity of Annonaceae and the important pharmacological potential of the substances produced by the genus Annona. Thus, we studied the essential oils of leaves collected from the graft (Annona × atemoya) and lateral budding from the rootstock (Annona emarginata), in the same individual, in order to characterize chemical profile. The extraction was carried out by hydrodistillation and separation, quantification and identification of the substances were performed by gas chromatography coupled to a mass spectrometer. Chemical profiles of essential oils were evaluated by principal component analysis (PCA). Annona × atemoya and Annona emarginata presented chemical profiles of essential oil with specific substances. Some substances are common in oils of both species. Germacrene D is predominant in Annona × atemoya and α and β-selinene, β-elemene and spathulenol occurred in Annona emarginata. Our results suggest that the profile of such essential oil may be another indicator for the success of the combination of these two 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 score0.426
Threshold uncertainty score0.108

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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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

Explore more

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