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Record W3118640278 · doi:10.7939/r3-9pr6-0468

Effect of deboning time, ageing period and collagen characteristics on horse Semimembranosus meat quality

2020· article· en· W3118640278 on OpenAlexaboutno aff
Mohammad Mahbubur Rahman

Bibliographic record

VenueUniversity of Alberta Library · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Meat packing industryPeriod (music)Food scienceBiologyArt

Abstract

fetched live from OpenAlex

Horse meat is a good source of iron and unsaturated fatty acids, which make it a suitable substitute for conventional meat. To sustain its consumer acceptance in a competitive global market, ensuring that Canadian horse meat is of the highest quality is of prime importance. Currently, in Canada horse meat is harvested either through hot boning (after 2 h post mortem) of the carcass or after the carcass is completely chilled to less than 4 ºC (40 h of post mortem). Additional efficiencies in horse meat production potentially could be gained by decreasing the carcass deboning time from 40 h to 17, 26 or 30 h. To ensure that Canadian horse meat quality remains of the highest standard, modifications to the time of deboning need to be considered in light of subsequent post mortem ageing and their effect on the resultant meat quality. Semimembranosus muscles (n = 36) were collected over four consecutive weeks from the right sides of horse carcasses de-boned at 17, 26 and 30 h post mortem (n = 12 per week, 4 at each post mortem period) and steaks from the muscles were aged for 3, 30, 60 and 90 days (n = 36 per period). Meat L* (lightness) decreased (p < 0.05) while b*(yellowness) increased with increasing length of deboning time and ageing period. Purge loss increased with increasing ageing period (p < 0.05) and was highest throughout the ageing period in muscles deboned after 17 h of chilling. Warner Bratzler shear force (WBSF) decreased with length of ageing (p < 0.05). Muscle perimysium (r = -0.52, p < 0.001), muscle collagen (r = -0.35, p < 0.05) and intramuscular fat (r = -0.38, p < 0.05) contents were negatively correlated with WBSF. Perimysial collagen (r = 0.47, p < 0.05) and pyridinoline (r = 0.37, p < 0.05) concentrations and muscle pH (r = 0.46, p < 0.05) were positively correlated with WBSF. Muscle pH, perimysial collagen concentration and intramuscular fat collectively explained 53% of the total variation in WBSF, while 63% of the variation in collagen heat solubility was explained collectively by muscle weight, Ehrlich chromogen concentration, purge loss and intramuscular fat. Results indicated that deboning at 26 h post mortem did not change horse semimembranosus quality relative to current practices, but sensory analysis is needed to ascertain the full impact of the meat quality changes observed at 30, 60, and 90 d ageing. This research confirmed that collagen contributes to the WBSF of horse meat, supporting further investigation into the effects of animal age and breed on horse meat toughness.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.587

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)0.0010.000

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 head0.014
GPT teacher head0.194
Teacher spread0.180 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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