Nutritional evaluation of low-phytate peas (<i>Pisum sativum</i>L.) for young broiler chicks
Bibliographic record
Abstract
This experiment determined the effects of including normal and low-phytate peas in diets fed to young broiler chickens on performance, phosphorus availability and bone strength. A total of 180, day-old, male broilers (Ross-308 line) were assigned to six treatments. The control was based on corn and soybean meal while two additional corn-based diets were formulated containing 30% of either normal or low-phytate pea providing 0.45% available phosphorus. For each of these three diets, a similar diet was formulated by reducing the amount of dicalcium phosphate to produce a diet with 0.3% available phosphorus. The total tract apparent availability (TTAA) of phosphorus was higher (p = 0.02) for broilers fed the low-phytate pea than for birds fed the normal pea diets. Birds fed diets containing the lower level of phosphorus had a higher TTAA of phosphorus (50.64 vs. 46.68%) than broilers fed diets adequate in phosphorus. Protein source had no effect on weight gain, feed intake or feed conversion. Broilers fed the low phosphorus diets had lower weight gain (p = 0.04) and feed intake (p < 0.01) than broilers fed the higher phosphorus level. Bone strength was higher (p < 0.01) for broilers fed diets based on low-phytate pea than for those fed diets based on normal pea or soybean meal. Increasing the availability of the phosphorus in peas could mean that less inorganic phosphorus would be required in order to meet the nutritional requirements of broilers. Since inorganic phosphorus sources tend to be expensive, a reduction in their use would lower ration costs. In addition, increased availability of phosphorus would reduce the amount of phosphorus excreted thus reducing the amount of phosphorus that can potentially pollute the environment.
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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".