PSVII-9 The Impact of Increasing Dietary Manganese on the Reproductive Performance of Sows
Bibliographic record
Abstract
Abstract The objective of this study was to determine the effect of dietary manganese (ProPath Mn, Zinpro Corporation) on the reproductive performance of sows. Sows (N = 39; 231 ± 8 kg) were randomly assigned to 1 of three dietary levels of Mn (CON: 0 ppm Mn; PRO20: 20 ppm Mn; PRO40: 40 ppm Mn). Experimental treatments were initiated at breeding and continued through 2 parities. Sows were blocked by parity within each farrowing group and dietary treatments were represented within each block. Data were analyzed as a randomized complete block design using the MIXED procedure of SAS with diet as a fixed effect and block as a random effect. Dietary treatment did not affect sow body weights (P > 0.10). Lactation feed intake was increased in PRO20 sows compared with CON and PRO40 sows (P < 0.05). PRO20 and PRO40 sows farrowed heavier piglets (CON 1.23 kg; PRO20 1.57 kg; PRO40 1.40 kg; P = 0.001) with improved average daily gain to weaning (CON 213 g/day; PRO20 237 g/day; 220 g/day; P < 0.05), compared with CON sows. Milk fat content (average from d 7 and 14 of lactation) was reduced in PRO20 (5.5%) and PRO40 sows (6.1%; P < 0.05) compared with CON sows (7.8%), possibly due to increased milk demand from the piglets. There were no significant differences in milk mineral concentrations during lactation or piglet tissue Mn-superoxide dismutase (MnSOD) activity at weaning (P > 0.10). On day 3 of lactation, prolactin concentrations were similar across treatments (P > 0.10), whereas progesterone concentrations tended to differ in response to Mn level (CON 23.70 ng/mL; PRO20 26.15 ng/mL; PRO40 22.10 ng/ml; P = 0.09). Supplementary dietary Mn throughout 2 gestation and lactation cycles led to increased birth weights and pre-weaning growth of piglets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".