Relationships between loin physical, meat quality and intramuscular collagen characteristics of carcasses from crossbred swine populations
Bibliographic record
Abstract
Carcass and meat characteristics are of great importance to the pork industry as they determine the ultimate returns from animals produced. Making genetic progress in these traits requires them to be measurable, heritable and have adequate additive genetic variability. Estimates of genetic parameters must therefore be assessed to determine heritability and level of additive genetic variation for use in selection programs. In the first study, phenotypic data from 500 pedigreed crossbred pigs from Duroc sires and hybrid Large White ✕ Landrace sows from two different swine genetics companies were used. Fixed effects (slaughter batch, sex and company), and a random additive effect were fitted in bivariate animal models to estimate phenotypic and genetic parameters in ASReml. Moderate heritabilities were obtained for loin compositional traits ranging from 0.21±0.10 for bone weight to 0.44±0.11 for loin eye weight with low estimates of 0.09±0.08, 0.19±0.08, 0.13±0.09 obtained for bone percent, loin weight and fat trim weight, respectively. Meat quality traits were low to moderately heritable with the highest estimate being found for intramuscular fat (0.42±0.13). The heritability estimates for percentages of heat soluble and insoluble collagen were 0.12±0.09 and 0.15±0.09, respectively, while 0.33±0.12 was found for total collagen content. Moderate heritability implies the possibility of improving these traits through selective breeding. Strong negative genetic correlations between moisture and fat traits and a further negative correlation between fat and muscling traits confirmed that selection for improved muscling over time negatively affects fat traits and may then decrease meat eating quality. The strong genetic correlations of lightness (L*) with soluble collagen (0.68±0.30) and insoluble collagen (-0.71±0.35) suggest possible pleiotropic gene effects on these traits. Warner-Bratzler shear force (WBSF) had moderate genetic correlations with insoluble collagen (0.42±0.16) and soluble collagen (-0.38±0.10), suggesting a potential relationship between some of the genes impacting these traits. Genetic correlations between WBSF and collagen characteristics indicated that despite the relative youthfulness of pigs at slaughter, genetic selection for collagen solubility may decrease WBSF. In the second study, the contributions of company, sex and loin physical and collagen characteristics to measures of pork carcass and meat quality in a Canadian context were examined. Results from this study indicated that intramuscular collagen characteristics influenced loin cooking loss and further revealed that Warner-Bratzler shear force (WBSF) values were driven more by denaturation of myofibrillar proteins than by intramuscular fat content. Means separation analysis also showed WBSF to increase with increased muscularity and reduced backfat which suggests that selection for rapid growth rate with its associated reduction in calpain activity may decrease pork tenderness. This study further implicates pH and intramuscular fat content as part of the traits influencing insoluble collagen percent indicating that deposition of fat in the perimysium may be a potential disruptor of crosslink formation. Step- wise regression indicated that pH is not a reliable sole predictor of meat quality in loin that has been frozen and then thawed and thus other variables in addition to pH are needed to reliably predict frozen/thawed pork quality. Drip loss predicted most of the variation in tenderness which indicated that pork samples in the present study may have undergone myofibrillar protein oxidation during frozen storage or dehydration during cooking. The results indicated that sex has no significant influence (p>0.05) on loin compositional and meat quality traits while source of animal has a significant (p<0.01) influence on loin composition, pH, drip loss (%), cooking loss (%) and collagen characteristics. In summary, the genetic parameters estimated in this study will make it feasible to predict response to genetic selection on loin and collagen characteristics and further add to the already established research database on meat quality traits. The results of this study also provide insights on variables with potential for predicting pork quality and suggest that although the populations studied were obtained from the same breed combinations differentiation in terms of loin compositional, meat quality and collagen characteristics would not be expected based on sex but would be expected in terms of animal origin.
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 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 | 0.001 | 0.001 |
| 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".