Effect of supplementing the diet of lactating sows with NuPro® on sow lactation performance and piglet growth
Bibliographic record
Abstract
Plante, P. A., Laforest, J.-P. and Farmer, C. 2011. Effect of supplementing the diet of lactating sows with NuPro® on sow lactation performance and piglet growth. Can. J. Anim. Sci. 91: 295–300. The impact of supplementing the diet of lactating sows with NuPro® (a source of yeast-derived proteins) on their performance and that of their piglets was studied. Treatments were: control (CTL, n=22), 30 g of NuPro per day (NuPro30, n=22), and 60 g of NuPro per day (NuPro60, n=21). The NuPro was mixed daily with 500 g of feed and provided over a 21-d lactation. Jugular blood samples were obtained from sows on days 2, 7 and 20 of lactation to measure urea concentrations. Milk samples were obtained on days 7 and 20 of lactation for compositional analyses and quantification of 5′ monophosphate nucleotides. Litter size was standardized to 10±1 at 48 h postpartum. Sow body weight loss and backfat loss during lactation were recorded, as well as the weights of piglets until day 56. Feed intakes of sows during lactation and of piglets for 5 wk post-weaning were noted. Statistical analyses were performed with PROC MIXED using an analysis of variance with one factor (three levels) according to a completely randomized design. None of the animal performance data differed among treatments (P>0.1). Standard milk composition was also similar across treatments (P>0.1). Concentrations of nucleotides in milk were greater on day 7 than on day 20 of lactation (P<0.001) but were not affected by treatments (P>0.1). In conclusion, supplementing the diet of lactating sows with NuPro did not increase nucleotide concentrations in milk and had no beneficial effects on sow or piglet performances.
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 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 | 0.001 | 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".