Parturition body size and body protein loss during lactation influence performance during lactation and ovarian function at weaning in first-parity sows1
Bibliographic record
Abstract
We investigated the effect of body protein mass at parturition and different degrees of body protein loss in lactation on sow performance. In a 2 x 2 factorial arrangement, 77 Genex gilts were fed to achieve either a standard or high body mass at parturition and to lose either a moderate (MPL) or high (HPL) amount of protein in lactation. Pregnant gilts were fed either 24.4 MJ of ME, 266 g of CP, and 11 g of lysine/d or 34.0 MJ of ME, 436 g of CP, and 20 g of lysine/d resulting in divergent (P < 0.01) live weights (165 vs. 193 kg) and calculated protein masses (24.3 vs. 30.0 kg) and slightly different backfat depths (20.0 vs. 22.8 mm; P < 0.05) at parturition. Diets fed during lactation were formulated to deliver 731 g of CP and 37 g of lysine/d or 416 g of CP and 22 g of lysine/d to induce differential body protein mobilization. Sows were slaughtered at weaning (d 26), and the weight of the organs and the lean, fat, and bone in five primal cuts was measured. The external diameter of the eight largest follicles on each ovary was recorded, and the follicular fluid from these follicles was collected, weighed, and analyzed for estradiol. Losses in lactational live weight (26 vs. 20 kg; P < 0.01) and calculated protein mass (17.8 vs. 10.7%; P < 0.001) were greater, and the carcass lean mass at weaning was 10% lighter (P < 0.05) in HPL sows. Backfat (5.1 +/- 0.8 mm; P = 0.29) and calculated fat mass (25.8 +/- 1.5%; P = 0.84) losses did not differ between treatments. Both sow body mass (P < 0.05) and lactation protein loss (P < 0.01) affected litter growth rate. Litter growth rate decreased (P < 0.05) at the end of lactation in HPL sows once these sows had lost 10 to 12% of their calculated protein mass. Ovarian follicular development was most advanced in high body mass sows that lost the least protein; these sows had the heaviest (P < 0.05) uterine weight and highest (P < 0.05) follicular fluid estradiol concentration. Follicular development was least advanced in standard body mass sows that lost the most protein. These sows had the lowest (P < 0.05) muscle:bone ratio at weaning and likely lost the largest proportion of their muscle mass compared with the other treatments. In conclusion, ovarian function at weaning and litter performance was higher in high body mass sows and in sows that lost the least protein in lactation, suggesting that a larger lean mass may delay the onset of a decrease in performance in sows that lose protein in lactation.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".