Use of recorded nursing grunts during lactation in two breeds of sows. II. Effects on sow performance and mammary development
Bibliographic record
Abstract
Primiparous lactating sows of two different genotypes [42 Genex-Meishan hybrid (MH) and 42 Yorkshire-Landrace (YL)] were exposed to recorded nursing grunts played at different intervals, and the effects on sow performance and mammary growth were studied. Sows within each breed were divided in three groups (n = 14 for each group): (1) no playbacks (control), (2) playbacks at 35-min interv als (GR35), and (3) playbacks at 40-min intervals (GR40). Recordings were played from day 110 of gestation to day 28 of lactation. Litter size was standardized to 10 ± 1 pigs within 48 h postpartum, and weight and backfat thickness of sows were recorded on day 110 of gestation, and on days 2 and 27 of lactation. Sow feed and water intakes were recorded throughout lactation. Milk samples were obtained from all sows on day 27 postpartum and jugular blood samples were obtained on day 28 for measurement of IGF -I and prolactin concentrations. Sows were slaughtered on day 28 of lactation and their mammary glands were excised to perform compositional analyses. Ovaries were also collected. The MH sows weighed less (P < 0.01) and had more backfat (P < 0.01) than YL sows. Milk from MH sows contained more dry matter (P < 0.05) and more lactose (P < 0.05) than that from YL sows. Mammary parenchymal tissue weighed less (P < 0.05) and contained less total protein (P = 0.01) and total DNA (P < 0.01) in MH than in YL sows. Sows in GR35 also had more total parenchymal DNA (P < 0.05) than control sows. Circulating concentrations of IGF-I and prolactin were not affected by breed or treatment (P > 0.1) whereas ovaries were heavier (P < 0.01) in control MH than in control YL ows. Therefore, playbacks of nursing grunts at 35-min intervals throughout lactation increased total mammary cell number without affecting hormonal or milk composition status. Key words: Auditory stimulus, lactation, mammary development, Meishan, milk, sows
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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 | 0.001 | 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) | 0.001 | 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".