Genetic and phenotypic parameters for carcass and meat quality traits in commercial crossbred pigs
Bibliographic record
Abstract
\n\t\t\t\t\tPork quality and carcass characteristics are now being integrated into swine breeding objectives because of their economic value. Understanding the genetic basis for these traits is necessary for this to be accomplished. The objective of this study was to estimate phenotypic and genetic parameters for carcass and meat quality traits in 2 Canadian swine populations. Data from a genomic selection study aimed at improving meat quality with a mating system involving hybrid Landrace × Large White and Duroc pigs were used to estimate heritabilities and phenotypic and genetic correlations among them. Data on 2,100 commercial crossbred pigs for meat quality and carcass traits were recorded with pedigrees compromising 9,439 animals over 15 generations. Significant fixed effects (company, sex, and slaughter batch), covariates (cold carcass weight and slaughter age), and random additive and common litter effects were fitted in the models. A series of pairwise bivariate analyses were implemented in ASReml to estimate phenotypic and genetic parameters. Heritability estimates (±SE) for carcass traits were moderate to high and ranged from 0.22 ± 0.08 for longissimus dorsi muscle area to 0.63 ± 0.04 for trimmed ham weight, except for firmness, which was low. Heritability estimates (±SE) for meat quality traits varied from 0.10 ± 0.04 to 0.39 ± 0.06 for the Minolta b* of ham quadriceps femoris muscle and shear force, respectively. Generally, most of the genetic correlations were significant (P < 0.05) and ranged from low (0.18 ± 0.07) to high (-0.97 ± 0.35). There were high negative genetic correlations between drip loss with pH and shear force and a positive correlation with cooking loss. Genetic correlations between carcass weight (both hot and cold) with carcass marbling were highly positive. It was concluded that selection for increasing primal and subprimal cut weights with better pork quality may be possible. Furthermore, the use of pH is confirmed as an indicator for pork water-holding capacity and cooking loss. The heritabilities of carcass and pork quality traits indicated that they can be improved using traditional breeding methods and genomic selection, respectively. The estimated genetic parameters for carcass and meat quality traits can be incorporated into the breeding programs that emphasize product quality in these Canadian swine populations. \n\t\t\t\t
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".