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Record W2029719941 · doi:10.1021/jf000544k

Combined Effect of Ascorbic Acid and Gamma Irradiation on Microbial and Sensorial Characteristics of Beef Patties during Refrigerated Storage

2001· article· en· W2029719941 on OpenAlexaff
M Giroux, B. Ouattara, Rabah Yefsah, Wanda Smoragiewicz, Linda Saucier, Monique Lacroix

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsAscorbic acidChemistryCitric acidFood scienceTasteOdorIrradiationLightnessOrganic chemistry

Abstract

fetched live from OpenAlex

The present study was undertaken to evaluate the effect of ascorbic acid concentrations (0.03 to 0.5%) and irradiation doses (0.5 to 4 kGy) on microbial growth, color coordinates (L, a, and b), and sensory characteristics (taste and odor) of beef patties during storage at 4 +/- 1 degrees C. Ascorbic acid was also compared to citric acid at a similar pH value in order to differentiate the effects of ascorbic acid from those of pH reduction. Results showed significant reduction (p< or = 0.05) of aerobic plate counts (APCs) and total coliforms, and a significant interaction (p< or = 0.05) between ascorbic acid and irradiation dose was observed. The irradiation treatment had detrimental effects on redness, yellowness, and hue angle values of meat. However, incorporation of ascorbic acid into the meat before irradiation resulted in significant (p< or = 0.05) stabilization of color parameters. The color improvement obtained with ascorbic acid was not related to the pH reduction. Also, no significant detrimental effect on taste or odor was found in irradiated samples containing ascorbic acid.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations92
Published2001
Admission routes1
Has abstractyes

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