High dose of phytase on apparent and standardized total tract digestibility of phosphorus and apparent total tract digestibility of calcium in canola meals from <i>Brassica napus</i> black and <i>Brassica juncea</i> yellow fed to growing pigs
Bibliographic record
Abstract
A total of 42 barrows weighing 19.8 ± 1.22 kg were fed seven diets to give six replicates per treatment. The experiment was conducted in a factorial arrangement with factors being (1) two canola meals (CM) types and (2) three phytase levels (0, 500, and 2500 FTU kg−1). The basal endogenous phosphorus (P) losses and standardized total tract digestibility (STTD) was calculated using the P-free method. There was no effect of CM types on feed intake and fecal P output, but an interaction effect was observed for P intake (CM × phytase; P < 0.05). Supplementation of phytase (2500 FTU kg−1) reduced (P < 0.001) fecal P output (g d−1), and the output was reduced by 58% in Brassica napus black (BNB) and 64% in Brassica juncea yellow (BJY) diets. Supplementation of phytase improved (P < 0.001) both apparent total tract digestibility (ATTD) and STTD of P in both BNB and BJY, regardless of dose. The basal endogenous P loss (EPL) was determined to be 111.28 ± 35.09 mg kg−1 of dry matter intake (DMI). There was no further improvement in STTD of P when phytase was increased from 500 to 2500 FTU kg−1 in both CM types. The ATTD of calcium (Ca) was increased (P < 0.001) in BNB and BJY when phytase was supplemented at 500 and 2500 FTU kg−1. The results, therefore, indicate that supplementation of phytase at 500 FTU kg−1 improved both ATTD and STTD of P in two CM types, but a super dose of 2500 FTU kg−1 had no additional benefit. Similarly, ATTD of Ca was increased when phytase was supplemented at 500 FTU kg−1 without further improvement at 2500 FTU kg−1.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".