Plane of nutrition during gestation affects reproductive performance and retention rate of hyperprolific sows under commercial conditions
Bibliographic record
Abstract
Defining a maternal plane of nutrition during gestation is pivotal for improving sow productivity and the cost-effectiveness of feeding. The benefits of increasing the amount of feed during late gestation have been controversial. The objective of this study was to investigate the effects of different planes of nutrition during gestation on reproductive performance of hyperprolific sows and pre-weaning litter performance. One hundred and thirty-five gestating sows were randomly assigned to one of three planes of nutrition throughout parities three and four (P4), as follows: Req - plane designed to meet requirements of prolific sows (2.3 kg per day from day 1 to 21; 1.8 kg per day from day 22 to 75; 2.3 kg per day from day 76 to farrowing); Bump - plane designed as the Req, with increased feed intake during late gestation (3.0 kg per day from day 91 to farrowing); and Maintenance - plane designed to closely meet maintenance requirements of sows (1.8 kg per day from day 1 to farrowing). All treatments were fed the same gestation diet (2.50MCal NE/kg; 0.67% SID Lysine; 15.17% CP). Sow biometrical parameters at farrowing and at weaning, and litter characteristics were recorded. Also, blood samples were collected for pre- and post-prandial serum glucose and plasma insulin, as well as triglycerides, calcium, and phosphorus analyses. Culling, stratified by cause, and retention rates were recorded in all treatments for each parity. Over two parities, Bump sows had higher weight gain and, at P4, had a higher number of piglets born alive (P < 0.05). Bump sows lost more weight between the end of gestation and weaning over two parities (P < 0.05). Maintenance sows showed reduced body condition score with a higher percentage of piglets removed throughout lactation (due to inappetence and inability to reach the udder) at P4 (P = 0.03). Pre- and post-prandial glucose levels were higher in Bump sows, as well as post-prandial insulin and phosphorus levels at P4 (P < 0.05). Bump sows also showed increased plasma triglycerides compared to the other treatments (P = 0.03). Retention rate was reduced in Maintenance compared to Bump and Req sows at parity 5 (P = 0.02). Taken together, our results indicate that higher feed intake allowance during late gestation may improve the sow's nutritional status triggering positive results on litter size of hyperprolific sows (e.g., more than 17 total born). However, body condition score must be carefully evaluated to prevent excessive weight gain during successive parities.
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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 | 0.000 | 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) | 0.000 | 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".