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Record W2606372797 · doi:10.17756/jfcn.2017-035

Micro-Oxygenation and Fining Agent Treatments: Impact on Color of Moroccan Red Press Wine

2017· article· en· W2606372797 on OpenAlexfundno aff
Mohamed Ben Aziz, Laetitia Mouls, Hélène Fulcrand, Hassan Hajjaj

Bibliographic record

VenueJournal of Food Chemistry and Nanotechnology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsWineOxygenationChemistryFood scienceMedicine

Abstract

fetched live from OpenAlex

Red press wine is collected after pressing solid parts (seed and skin) of grapes pomaces. Higher pressure induces more colorful, astringent, bitter and rustic wines. This is caused by the presence of undesirable phenolic compounds. To overcome this problem, the most common practice used in wine industry is the oenological treatment which enhances the clarity, stability and the wine taste. In the present work, press wines were separately submitted to four different treatments: micro-oxygenation and the addition of three fining agents: gelatin, polyvinylpolypyrrolidone (PVPP) and pea protein. The phenolic total index decreased (8%) significantly (P<0.05) for gelatin treatment, the PVPP based formulation treatment led to the largest loss (8%) in color intensity, (12%) in redness (a*), (9%) in polymeric pigments and increasing to 9% lightness (L*). Unlike micro-oxygenation which has decreased (5%) the color intensity. For the monomeric anthocyanins, the greatest reduction of acylated and coumaroylated anthocyanins at bottling and glucoside anthocyanidins after five months of storage was observed for both basic PVPP and gelatin.

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 score0.029
Threshold uncertainty score0.121

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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
Published2017
Admission routes1
Has abstractyes

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