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Record W6903064003 · doi:10.7939/81731

Relationships between Canadian beef grade and intramuscular collagen characteristics in bovine m. longissimus lumborum

2025· dissertation· en· W6903064003 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsnot available
Fundersnot available
KeywordsTendernessPyridinolineConnective tissueSolubilityDivalentBeef industryLongissimusHeat stability

Abstract

fetched live from OpenAlex

Consumers’ decisions to purchase beef are determined by various factors, including meat appearance and anticipated and experienced eating satisfaction. While there are different contributions of each intramuscular component to meat quality, intramuscular connective tissue (IMCT) impacts beef tenderness as “background toughness”. IMCT is primarily composed of the protein collagen, which increases in crosslink complexity as animals age. Youthful animals primarily have immature divalent collagen crosslinks and Ehrlich Chromogen which are temperature labile. However, as animals age, the divalent crosslinks transition into a mature, trivalent crosslink pyridinoline which provides increased stability to the collagen structure throughout muscle. This results in declining collagen heat solubility as well as increased Slice Shear Force (SSF) of cooked meat. For consumers, this is undesirable for beef, as it requires extended cooking periods to allow the collagen to degrade and gelatinize. Current research has reported the impacts of pyridinoline and Ehrlich Chromogen on beef toughness; however, the effects of divalent collagen crosslinks are less understood. The objective of this study was to evaluate the relationship between beef quality grade, toughness as determined by SSF, and collagen characteristics, specifically collagen solubility and collagen divalent and trivalent crosslink quantification. Longissimus lumborum m. steak samples were randomly collected from beef carcasses (Canada AA, n= 101; Canada AAA, n= 500) and aged for 14 d. After, cooked tenderness was measured using SSF and samples were categorized into tender (SSF=0-19.9 kg), intermediate (SSF=20.0-39.9 kg), and tough (SSF>40.0) subcategories. Collagen heat solubility was measured on a frozen uncooked portion from each sample, and categorized as high or low collagen solubility, and related to collagen divalent and trivalent crosslinks quantified utilizing a novel technique. Results showed that muscles from Canada AA carcasses had greater soluble collagen and greater mean slice shear force and less insoluble collagen than muscles from Canada AAA carcasses. However, there were no differences due to collagen solubility or tenderness category. Pyridinoline, lysinonorleucine, hydroxylysinonorleucine, 5, 5’-dihydroxylysinonorleucine, and deoxypyridinoline concentrations were unaffected by and unrelated to, respectively, quality grade and collagen solubility percentage. Ehrlich’s Chromogen had a significant difference for collagen solubility percentage with high solubility having greater concentration compared to low solubility. As the longissimus lumborum muscle used in this study is a tender cut of meat located in the loin area resulting in reduced connective tissue, future research should focus on differing locations of muscle and characterization of divalent crosslinks variation with animal age to identify the relationship between collagen crosslink type and beef 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.853

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 head0.021
GPT teacher head0.193
Teacher spread0.172 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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