Heterosis, direct and maternal additive effects on rabbit growth and carcass characteristics
Bibliographic record
Abstract
A total of 142 male and female rabbits of two breeds, Californian (CA) and New-Zealand White (NZ), and their reciprocal crosses were used. This study aimed to estimate heterosis, direct and maternal additive effects as well as some non genetic effects on rabbit growth and carcass characteristics in order to identify the best crossbreeding plan to use for rabbit meat production under Quebec conditions. Kits used for this experiment were weaned at 5 weeks of age. Each rabbit was identified and weighed individually at weaning and at 63 days of age. During the fattening period, rabbits were placed in individual cages. Rabbits were slaughtered after 18 h fasting from feeds only. The commercial carcass including liver, kidneys and perirenal fat was weighed after 2 hours chilling at 4°C. After dissection, fore part, intermediate part and hind part of carcass were measured. Dressing out percentage was calculated as chilled carcass weight x 100/live weight. One of the hind legs was used to evaluate meat/bone ratio. Statistical analyses were performed using the procedure GLM of SAS. Results showed significant differences between breed types for individual live weight at 35 d, average daily gain, live weight at 63 d, fore part, intermediate part and hind part yields. Overall, for growth performances (ADG and live weight at 63 d) and hind part yield, breed types from NZ dams had better performances that those from CA dams. Concerning the intermediate part yield (and carcass yield, but non significantly) a different classification was observed, with better performances of CA sired breed types. There were no significant effects of breed type on commercial carcass weight, commercial carcass yield and meat/bone ratio. The lower the litter size at birth, the heavier the individual weight at weaning, at 63 d and the commercial carcass weight were. Rabbits coming from the 2 parity litters were significantly heavier at weaning and had the highest commercial carcass weight. Crossbreeding parameters were calculated from linear contrasts between breed types means. Breed NZ had positive direct effects on growth rate and 63-d body weight but negative ones on carcass yield and the proportion of intermediate part of the carcass. Maternal and heterosis effects were generally non significant.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".