Bibliographic record
Abstract
Abstract The task of feeding growing replacement gilts, gestating gilts and sows to maximize their future milk yield is not easy. Yet, this is particularly important when considering the great demands made by the large litters of our current hyperprolific sow genetic lines. One aspect that needs to be considered is the effect of feeding on mammary development taking place before the onset of lactation, which is a major determinant of potential milk yield. One can only attempt to stimulate mammogenesis during periods with rapid mammary development. In swine, these periods are from three months of age until puberty, from 90 days of gestation until farrowing, and throughout lactation. Early studies showed that a 20% or 26% feed restriction from 90 days of age until puberty drastically reduces mammary parenchymal tissue mass. However, in a more recent study, sow milk yield was not altered following a 10% or 20% feed restriction, or a 25% dietary fiber addition (diluting dietary energy by 5%) from 90 days of age to breeding. This absence of effect may be due to the greater feed intake of control gilts in that recent study compared with the older studies. Such a difference in feed intake was likely brought about by genetic selection for faster growing pigs, and it appeared that feed intake of growing gilts can be reduced to 2.7 kg/day without detrimental effects on their future milk yield. During prepuberty, inclusion of the phytoestrogen genistein (2.3 g/day) in the diet increases the number of mammary parenchymal cells. During late gestation, feeding very high energy levels (10.5 Mcal ME/day) may have detrimental effects on mammary development and subsequent milk production. Furthermore, feed intake throughout gestation is important because of its effect on body condition. Gilts that are too thin (< 16 mm backfat thickness) in late gestation have reduced mammary development. A 40% increase in SID Lys via inclusion of additional soybean meal to the diet of gilts from days 90 to 110 of gestation increased mammary parenchymal mass by 44%. On the other hand, providing the same 40% increase in dietary SID Lys to multiparous sows during late gestation had no significant effect on mammary parenchymal mass. These findings therefore support the use of phase-feeding during gestation of gilts only. Increasing circulating concentrations of the growth factor IGF-1 during late gestation also increased mammary parenchymal mass by 22%. Current data clearly demonstrate that feeding management before lactation can be used to improve sow milk yield.
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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 | 0.000 | 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) | 0.002 | 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".