Associations of genetic polymorphisms with reproduction and meat quality characteristics in Chinese Hebao pigs
Bibliographic record
Abstract
The Hebao pig is a Chinese breed with high fecundity and vitality and excellent meat quality. This study aimed to explore polymorphisms of genes related to reproductive characteristics (ESR and FSHβ) and meat quality (MC4R, H-FABP, and A-FABP) by polymerase chain reaction – restriction fragment length polymorphism (PCR-RFLP) in Hebao and commercial pigs (Landrace, Duroc, and Large White). Hebao and commercial pig crossbreeds were compared for fattening performance, reproduction traits, and carcass and meat quality. Piglet number per litter in pigs harboring the AA genotype for ESR was highest, with a significant difference between Landrace and Hebao pigs. For FSHβ, the AA genotype in Hebao and Duroc pigs produced the largest litter. The most abundant AA genotype in Hebao pigs produced lower backfat thickness compared with each commercial breed. Genotype distribution of H-FABP and A-FABP was significantly different between Hebao pigs and commercial pigs, reflecting Hebao pigs’ significant higher intramuscular fat (IMF). Reproduction traits of Berkshire × Hebao and Liaoning black × Hebao pigs were similar, with significant differences in individual weight at birth, weaning, and milking yield, higher in Berkshire × Hebao pigs than in Liaoning black × Hebao pigs. Hebao pigs have better fat distribution and meat quality compared with commercial breeds. In our preliminary crossbreeding study, a Berkshire and Hebao cross yielded the best hybrid pigs.
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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 | 0.001 |
| 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".