Phytate and other nutrient components of feed ingredients for poultry
Bibliographic record
Abstract
Samples of feed ingredients were collected from poultry feed mills in the United States and Canada: corn (133), soybean meal (114), corn distillers dried grains with solubles (DDGS; 89), bakery by-product meal (95), wheat (22), wheat middlings (31), canola meal (21), and wheat shorts (15). The samples were assayed by standard wet chemical techniques for CP, fat, neutral detergent fiber (NDF), acid detergent fiber, calcium, phosphorus, phytate phosphorus, and ash. There was considerable variation found in most of the ingredient components. Forty-two of the 64 CV were above 10.0%. The calcium contents of the ingredients were the most variable, followed by the fat contents. The CP contents were the least variable. There were some fairly consistent relationships observed across samples; in general, acid detergent fiber and NDF were positively correlated, as were ash and mineral levels. Crude protein and fiber levels were positively related, except for wheat shorts, but the relationships were not strong. Phytate P was found to be positively related to ash and total P, as expected, except for corn DDGS. The fat content of corn was found to be negatively related to the NDF content. Significant (P < 0.004) linear regressions were found between phytate P and total P for corn, soybean meal, bakery by-product meal, wheat, wheat middlings, and wheat shorts. The average nonphytate P content of the ingredients was 49.8%, ranging from 38.8% for wheat middlings to 73.2% for DDGS. The phytate P content of wheat and wheat by-products could be predicted from their proximate compositions, with coefficients of determination in excess of 0.740. Predictions for the other ingredients were not as good.
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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 | 0.001 | 0.001 |
| 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".