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Record W3014636170 · doi:10.1111/1750-3841.15062

Plant extracts effectiveness to extend bison meat shelf life

2020· article· en· W3014636170 on OpenAlexafffund
Vipasha Sood, Wenchao Tian, Claudia Narváez‐Bravo, Susan D. Arntfield, Argenis Rodas‐González

Bibliographic record

VenueJournal of Food Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPalatabilityMetmyoglobinFood scienceShelf lifeLoinBrowningLipid oxidationBusinessChemistryBiologyAntioxidant

Abstract

fetched live from OpenAlex

The effectiveness of plant extracts (0.05% rosemary and 0.08% oregano) to extend shelf life of bison strip loin steaks in terms of color stability and consumer acceptability was studied. Steaks treated with oregano presented lower oxygen consumption, higher metmyoglobin-reducing activity (MRA), decreased lipid oxidation, and provided a stable red color with less discoloration during the retail display period than the control and rosemary treated steaks (P < 0.05). Results from consumer sensory evaluation indicated that treated steaks under study were not significantly different from the control (P > 0.05) based on palatability attributes and acceptability. However, rosemary treated steaks were more desirable and palatable than their oregano counterparts (P < 0.05). Overall, plant extracts, particularly oregano, can improve color stability of bison steaks due to its antioxidants properties and ability to increase MRA capacity in fresh bison meat without posing any negative impact on its sensory attributes. PRACTICAL APPLICATION: This study will provide valuable information to the bison meat industry on how to offer a more consistent and acceptable product (in terms of palatability and color) to consumers using plant-based natural antioxidants, without diminishing the palatability of their products. This technology can offer two more days of shelf life in retail overwrap packaging, consequently, opening the possibility for the bison industry to expand its market with a potential to reduce retail losses due to poor color stability and early browning (that is, stock out, markdowns, and waste due to expired display life).

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)0.002
metaresearch head score (Gemma)0.001
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 score0.555
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.087
GPT teacher head0.284
Teacher spread0.198 · 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

Citations15
Published2020
Admission routes2
Has abstractyes

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