Suckling effects in sows: importance for mammary development and productivity
Bibliographic record
Abstract
An understanding of the mechanisms regulating milk yield in sows is crucial for producers to make the best management decisions during lactation. Suckling of mammary glands by piglets is one factor that is essential for development of these glands during lactation and for the maintenance of lactation in sows. The process of mammary development is not static as the majority of it takes place in the last third of gestation, continues during lactation, is followed by involution at weaning and starts over again in the next gestation. During involution, the mammary glands undergo a rapid and drastic regression in parenchymal tissue, and this can also occur during lactation if a gland is not suckled regularly. Indeed, the pattern of regression is similar for glands that involute at weaning or during lactation. Suckling during 12 to 14 h postpartum is insufficient to maintain lactation and the process of involution that occurs in early lactation is reversible within 1 day of farrowing but is irreversible if a gland is not used for 3 days. However, milk yield from a gland which is 'rescued' within the first 24 h remains lower throughout lactation. Suckling does not only affect milk yield in the ongoing lactation, but it also seems to affect that of the next lactation. Indeed, non-suckling of a mammary gland in first-parity sows decreased development and milk yield of that gland in second parity. Nursing behaviour of piglets in early lactation was also affected, where changes were indicative of piglets in second parity being hungrier when suckling glands that were not previously used. It is not known, however, if the same effects would be seen between the second and third lactation. Furthermore, the minimum suckling period required to ensure maximal milk yield from a gland in the next lactation is not known. This review provides an update on our current knowledge of the importance of suckling for mammary development and milk yield in swine.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".