Effect of phytase supplementation to a high- and a low-phytate diet for growing pigs on the utilization of phosphorus and calcium
Bibliographic record
Abstract
The effect on the utilization of P and Ca of phytase supplementation to a high- and low-phytate diet for growing pigs fitted with a simple T-cannula at the distal ileum, was determined. Eight barrows, 40.6 ±1.7kg BW, were assigned to four dietary treatments according to a repeated 4×4 Latin square design (n=8). Diets were: 1) a high-phytate diet containing 20% rice bran, a rich source of phytate-P; 2) diet 1 supplemented with 2000 phytase units (FTU) per kg; 3) a low-phytate diet containing 2% rice bran; and 4) diet 3 but supplemented with 2000 FTU per kg. Other major diet ingredients were barley, wheat, soybean meal and canola meal, and chromic oxide was added as an inert marker. For high- and low-phytate diets the contents were, respectively, 0.77 and 0.51% total P, 0.48 and 0.22% phytate- P and 1.30 and 0.86% Ca, while available P contents in all diets were similar (0.23%). Feces and urine collections started at 08:00 on day 8 of each 14-day experimental period and continued for 96h. Ileal digesta were collected from 08:00 to 20:00 on days 12-14. The diets were fed at 2.4×ME maintenance requirement according to 1998 NRC standards. Meal allowances of equal amounts were offered twice daily at 08:00 and 20:00. Phytase supplementation improved (P0.05) the apparent total tract digestibilities and the amount of P and Ca retained. The improvement in P utilization was independent (P0.10) of diet phytate-P. In the large intestine net absorption of P (P0.05) occurred for all diets, while that of Ca (P0.05) only when pigs were fed the non-supplemented low-phytate diet
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".