Changes to collagen heat solubility with post mortem ageing of beef and validation of genetic markers for collagen characteristic
Bibliographic record
Abstract
Consumer acceptability of meat is dependent on eating satisfaction, of which meat tenderness is a principal factor. While there has been much work done to improve meat quality, and grading systems are in place to evaluate meat and guarantee a superior eating experience, the characteristics of intramuscular connective tissue can still affect that experience. Intramuscular connective tissue limits the tenderness of beef that is cooked quickly due to it being principally composed of collagen, a protein which requires prolonged cooking times for its degradation. Additionally, the mature collagen cross-links pyridinoline and Ehrlich’s Chromogen further stabilize the collagen structure, leading to decreased collagen heat solubility, and have previously been associated with a marked increase in Warner Bratzler Shear Force (WBSF), an objective measure of meat toughness. Post mortem ageing of meat has been shown to decrease toughness, as the activity of enzymes responsible for the degradation of intramuscular collagen continues after slaughter. However, the use of growth promotants has been shown to have an adverse effect on meat quality and may limit the benefit of post mortem aging, and the effects of growth promotants on collagen characteristics is not well understood. In this thesis, collagen and other meat quality characteristics such as WBSF were analyzed for the longissimus thoracis muscle of 198 crossbred steers, the samples from which were aged 7 days prior to analysis. Of these animals, 149 steers were part of a steroid treatment to evaluate the effects of steroid use on meat quality and collagen characteristics. Cattle were implanted with 200 mg progesterone and 20 mg estradiol benzoate, and a terminal implant composed of 120 trenbolone acetate and 24 mg estradiol. One group received one backgrounding implant (n=16), a second group received two backgrounding implants (n=16), a third received two backgrounding implants and one terminal implant (n=16), a fourth group received one backgrounding implant and a terminal implant (n=16), and a fifth group received only a terminal implant (n=38). There were 47 animals in the control group (n=47) that received no implants. One part of each sample was refrigerated and aged for an additional 14 days for a total of 21 days to evaluate the effects of aging on collagen solubility. Results showed that steroid use was associated with reduced quality grade (P=0.01), improved yield grade (P<0.01), slower carcass cooling and pH decline, decreased carcass L* scores (lightness), and some increase in WBSF when multiple implants were used. However, there was no effect of steroids on collagen characteristics. There was some improvement of collagen solubility in the longissimus muscle if the carcass graded Canada Prime and had increased fat content, although collagen solubility decreased with animal age. WBSF was mainly associated with animal age and intramuscular fat content. There was no effect of aging on collagen solubility after 7 days post-mortem. Previous studies have identified single nucleotide polymorphisms (SNPs) within genes affecting total collagen, collagen cross-link synthesis, and collagenase activity. A genome-wide association study was designed to identify SNPs associated with collagen solubility and total collagen in 286 steers, and mature collagen crosslinks in 149 steers. In total there were 5 SNP windows associated with collagen solubility prior to aging the samples, 8 SNP windows associated with solubility after aging, and 5 windows relating to total collagen content. Further, 4 SNP windows were associated with Ehrlich’s Chromogen concentration and 10 windows were related to pyridinoline concentration. Functional analysis using Ingenuity Pathway Analysis (IPA) software identified genes within these SNP windows relating to cellular growth and proliferation, especially the proliferation of tumor cells and the metastasis of cancer. The observations suggest the possibility for marker-assisted genomic selection for collagen characteristics in beef cattle, however due to the small sample size of the study, a larger number of cattle will be needed to validate these results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".