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Record W2020520845 · doi:10.1556/aalim.30.2001.1.9

EFFECTIVENESS OF SOME CROWN COMPOUNDS ON INHIBITION OF POLYPHENOLOXIDASE IN MODEL SYSTEMS AND IN APPLE

2001· article· en· W2020520845 on OpenAlexaff
Drago Šubarić, Vlasta Piližota, Tomislav Lovrić, Radivoje Vuković, A. Erceg

Bibliographic record

VenueActa Alimentaria · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsThe Journal of Student Science and Technology
Fundersnot available
KeywordsChemistryBrowningChlorogenic acidFood scienceCatechol oxidaseEnzymeOrganic chemistryPolyphenol oxidasePeroxidase

Abstract

fetched live from OpenAlex

Enzymatic browning is (in most cases) an undesirable reaction which usually impairs the sensory properties and chemical changes in raw fruits and vegetables after mechanical operations (such as peeling, coring or slicing). A great emphasis is put on research to develop new methods to prevent enzymatic browning especially in fresh-cut (minimally processed) fruits and vegetables. The inhibition effect of crown compounds, macrocyclic ethers, benzo-18-crown-6 with sorbic acid and benzo-18-crown-6 with potassium sorbate, on polyphenoloxidase (PPO) activity was studied. The effectiveness of these compounds was evaluated by using 3,4-dihydroxy phenylalanine (L-DOPA), and chlorogenic acid (3-o-caffeoyl-D-quinic acid), the most widespread natural PPO substrates in fruits and vegetables, as well as browning inhibition substances on the cut surface of apples. Results showed that crown compounds used in this study were effective, both as inhibitors of the oxidation of phenolic compounds (PPO substrates) in model solutions and as inhibitors of enzyme discolorations of real systems (fresh-cut apples). In the earlier published papers (V UKOVI C 'et al., 1999) the synthesis of crown compound used in this study was presented.

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 score0.881
Threshold uncertainty score0.862

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 head0.028
GPT teacher head0.246
Teacher spread0.217 · 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

Citations6
Published2001
Admission routes1
Has abstractyes

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