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Record W1998489818 · doi:10.1021/jf0116909

Effect of γ-Irradiation Combined with Washing and Waxing Treatment on Physicochemical Properties, Vitamin C, and Organoleptic Quality of<i>Citrus clementina</i>Hort. Ex. Tanaka

2002· article· en· W1998489818 on OpenAlexaff
Mostafa Mahrouz, Monique Lacroix, G. D’Aprano, Hafida Oufedjikh, Cheikh Boubekri, M. Gagnon

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsWaxingOrganolepticFood scienceIrradiationChemistryVitamin CTasteHorticultureGamma irradiationShelf lifeBiologyBiochemistryWax

Abstract

fetched live from OpenAlex

To enhance the shelf life of a late variety of Moroccan Citrus clementina (Nour), ionizing treatments were applied at 0.3 kGy, as well as washing (cold water) and waxing treatments. It has been found that, despite the irradiation treatment, the washing and waxing treatment do not improve the quality of C. clementina, but rather result in yellower peels, peel injury, and reductions of vitamin C content, acidity, and soluble solids. However, gamma-irradiation alone enhanced significantly (p <or= 0.05) the level of vitamin C and the total phenolic content and maintained the color of the C. clementina during the entire storage period (49 days at 3 +/- 1 degrees C and 84% relative humidity). Finally, sensory evaluation further confirmed the beneficial effect of gamma-irradiation. Irradiated clementines were found to be sweeter. Also, the sensorial score of irradiated (I) and washed, waxed, and un-irradiated (LC) fruits was maintained over 7 days during 21 days as compared to 14 days for unwashed, unwaxed, and un-irradiated (C) and for washed, waxed, and irradiated (LCI) fruits.

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 score0.216
Threshold uncertainty score0.214

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 head0.020
GPT teacher head0.205
Teacher spread0.185 · 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

Citations31
Published2002
Admission routes1
Has abstractyes

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