Dynamics of nitrogen retention in gestating gilts at two feeding levels1
Bibliographic record
Abstract
Whole-body protein deposition (Pd) is a main determinant of AA requirements of gestating gilts; however, data on the dynamics of Pd is limited. The main objective of this study was to measure whole-body Pd (pregnancy-associated and maternal) during gestation in gilts at 2 feeding levels. Changes in BW and backfat (BF) throughout gestation and subsequent lactation performance were also evaluated. We hypothesized that the effect of feed intake on maternal Pd decreases toward the end of gestation due to increased fetal nutrient demands. Fifty-one pregnant Yorkshire gilts (initial BW and BF at d 28 ± 0.5 of gestation were 168.6 ± 2.2 kg and 16.9 ± 0.8 mm, respectively) were used. Gilts were assigned to 1 of 2 feeding levels (high feeding level and low feeding level; 2.54 and 1.87 kg/d, respectively) of the same diet (3.30 Mcal ME/kg, 17.8% CP, 0.82% standard ileal digestible Lys) from d 33 to 112 ± 0.5 of gestation. Nitrogen balance observations (based on total urine collection with urinary catheters and determination of fecal N digestibility using an indigestible marker) were made at 5 distinct time periods, each 4 d in length, starting at d 38, 52, 66, 87, and 108 ± 0.5 of gestation. Pregnancy-associated Pd (fetus, mammary gland, uterus, and placenta and fluids) was calculated for each gilt and N balance period using the gestating sow model, based on actual litter size (including stillborns) and mean piglet birth weight. Maternal Pd was calculated as the difference between whole-body Pd and pregnancy-associated Pd. Across all N balance periods, whole-body and maternal Pd were consistently 40.1 ± 5.2 g/d greater ( < 0.001) for the high feeding level compared with the low feeding level. At both feeding levels, whole-body Pd increased (linear and quadratic, < 0.020) with day of gestation and maternal Pd decreased (cubic, < 0.010) with day of gestation. During lactation, maternal voluntary feed intake and litter performance were not affected by gestation feeding level. Gilts on the high feeding level lost more BW and BF during lactation ( ≤ 0.030). In summary, the effect of feeding level on whole-body and maternal Pd was constant throughout gestation. However, the gradual decline in maternal Pd with day of gestation is in contrast to that reported by the and has important implications for the factorial estimation of AA requirements of gestating gilts toward the end of gestation.
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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 | 0.000 |
| 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) | 0.001 | 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".