250 Effects of premix carriers rich in iron, calcium, or fiber on growth performance of early-growing pigs
Bibliographic record
Abstract
Abstract The study was to evaluate the effect of premix carriers rich in iron (sand), calcium (limestone), or fiber (rice hull) on growth performance of early-growing pigs. A total of 215 pigs [initial body weight (BW) = 39.90 ± 5.06 kg) were randomly allotted to 3 dietary treatments containing 2% of different premix carriers: sand, limestone, or rice hull (30% crude fiber) using initial BW and sex as blocks (5 to 6 pigs per pen, 14 pens per treatment). The total Ca in sand, limestone, and rice hull were 4.28, 39.52, and 0.27 %, respectively, with Fe levels of 2.39, 0.20, and 0.05%, respectively. The analyzed total Ca level of the experimental diet containing sand, limestone, or rice hull was 0.69, 0.71, or 1.88 %, the analyzed total P level was 0.49, 0.49, or 0.48 %, and the analyzed total Fe level was 305, 633, or 347 ppm, respectively with 144 ppm of Fe from FeSO4·H2O in each diet. During the 28 d of the experiment, BW, feed disappearance, and fecal scores (ranging from 0 to 3 with 3 indicating watery feces) were recorded. Blood and feces were collected at the end of the experiment to measure the ATTD of dry matter (DM) and CP, serum iron concentration, hemoglobin, and red blood cell count. Data were analyzed by ANOVA using the Mixed Procedure of SAS with different premix carriers as the fixed effect. Limestone reduced the average daily gain (ADG; P < 0.05, 0.871 vs. 0.965 and 0.935 kg/d), increased feed conversion ratio (FCR; P < 0.05, 2.55 vs. 2.33 and 2.36), and aggravated diarrhea severity as reflected by greater fecal scores (P < 0.05, 1.53 vs. 1.18 and 1.19) compared with sand and rice hull as carriers. The ATTD of both DM and CP in pigs fed a premix with sand as a carrier were greater than that in rice hull- or limestone-treated pigs (P < 0.05, DM: 86.7 vs. 77.7 or 74.1%; CP: 86.1 vs. 75.0 or 73.3%). Furthermore, pigs fed a premix containing sand exhibited the greatest serum iron concentrations among treatment groups (sand, limestone, and rice hull: 2.81, 1.93, and 1.69 mg/L). However, no significant difference was observed in red blood cell count or hemoglobin concentrations among groups. In sum, excessive limestone in premix can negatively affect growth performance and fecal consistency, whereas using sand rich in iron as a carrier in premix exerted minimal impact on nutrient digestibility as opposed to limestone or rice hull.
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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) | 0.001 | 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 | 0.001 |
| 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".