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Record W3200699429 · doi:10.5539/jas.v13n10p142

Seasonal Variation in the Content of Condensed Tannins in Leaves of Xylopia emarginata Mart. (Annonaceae) in Response to Phenology and Climate

2021· article· en· W3200699429 on OpenAlexvenueno aff
Patrícia Conceição Medeiros, Yule Roberta Ferreira Nunes, Juliana Pimenta Cruz, Dayse Marcielle de Souza, Marly Antonielle de Ávila, Franciellen Morais-Costa, Sônia Ribeiro Arrudas, Viviane de Oliveira Vasconcelos, Thallyta Maria Vieira, Ana Paula Venuto Moura

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTraditional and Medicinal Uses of Annonaceae
Canadian institutionsnot available
Fundersnot available
KeywordsPhenologyTanninAnnonaceaeHorticultureProanthocyanidinCondensed tanninBotanyBiologyAntioxidantPolyphenol

Abstract

fetched live from OpenAlex

Variations in the concentrations of plant secondary metabolites can occur due to the phenological stages of the plants, combined with environmental variations. Plants rich in tannins are used in folk medicine for different purposes. Xylopia emarginata Mart. (Anonaceae)-“Pindaíba” has been used to treat skin edema, bronchitis and malaria. We evaluated variations in condensed tannin (CTs) contents in relation to phenological variables in leaves of Xylopia emarginata during one year. The study took place in a Vereda in northern Minas Gerais State, Brazil. Monthly phenological observations as well as quantifications of the contents of condensed leaf tannins in ethanol and aqueous extracts were performed. The production of X. emarginata leaves occurred throughout the study, with greater budding and leaf fall in the dry season. Phenological observations were correlated with CT levels and climatic data of precipitation and temperature. There was a significant correlation (p < 0.05) between fruiting and CT levels in the extracts, which were higher during the dry season, 13.2% in the ethanol extract and 7.8% in the aqueous extract.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.138

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.254
Teacher spread0.238 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicTraditional and Medicinal Uses of AnnonaceaeFrench-language works237,207