Vitamin requirements: is there basis for re-evaluating dietary specifications?
Bibliographic record
Abstract
There has been little work conducted over the last 40 years on estimating vitamin requirements of poultry, and so consequently NRC (1994) values are still often quoted as standards. A review of this information indicates many values are estimates, or extrapolated from comparable species, or as with broiler breeders, simply not given. The current concern related to formulating vitamin levels in poultry diets is the assumption that change in genetic potential of layers and meat birds necessitates re-evaluation, and that parameters for assessing needs are now more complex than simple production metrics as used previously. Unfortunately information on maintenance needs for vitamins is lacking, and while there is now information available on vitamin content of eggs, comprehensive details of the vitamin level in poultry meat products is surprising lacking. With unprecedented egg output of modern layer strains, and ever improving feed efficiency in meat birds, vitamin intake per unit of output is continually declining. For layers the estimate is around a 1% yearly decline in vitamin intake per egg produced, while for meat birds there has been a 0.6-0.8% yearly decline per kg body gain. This reduced intake of vitamins is the basis for improved performance in layers and meat birds fed a higher than normal level of vitamins. However, an even more important basis for reevaluating vitamin needs is change in measurement criteria. Many vitamins and especially the fat soluble vitamins accumulate in eggs and meat in proportion to diet inclusion. Development of vitamin enriched designer poultry products therefore dictates elevated feeding levels of vitamins. Co-incidentally, increased levels of vitamin E in poultry products has led to the realization that increased antioxidant capacity of these tissues enhances shelf life and appearance. Of greatest impact in reevaluating diet vitamin specifications has been the effect of these nutrients on bird health and in particular immune response. For example dietary levels of vitamin E far in excess of NRC (1994) requirements have been shown to positively impact immune response in all ages of bird and also the performance of heat-stressed birds. Expectations of ever increasing performance dictate the need for continual reevaluation in determining vitamin levels within diet formulations as detailed in recent publications on optimum vitamin nutrition of poultry to improve health, welfare, performance and the quality of poultry products.
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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 | 0.036 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".