Review: Anti-nutritional effects of phytic acid in diets for pigs and poultry – current knowledge and directions for future research
Bibliographic record
Abstract
Woyengo, T. A. and Nyachoti, C. M. 2013. Review: Anti-nutritional effects of phytic acid in diets for pigs and poultry – current knowledge and directions for future research. Can. J. Anim. Sci. 93: 9–21. Plant feedstuffs contain phytic acid (PA), which is a storage form of phosphorus. Phytic acid is, however, poorly hydrolyzed by pigs and poultry, and it has a capacity to complex dietary nutrients, thereby reducing nutrient digestibility. Reduced nutrient digestibility by PA implies reduced efficiency of utilization of the nutrients and increased discharge of the unabsorbed nutrients to the environment. Phytic acid has also recently been shown to increase the endogenous nutrient losses (ENL) in pigs and poultry. Because the increased ENL in the gastrointestinal tract are associated with increased maintenance requirement for the lost nutrients and of energy spent on their secretion, an increase in ENL due to PA implies that there are other adverse effects of PA on nutrient utilization in addition to reducing nutrient digestibility. In this review, the effects of PA on performance of pigs and poultry, and on the digestibility and ENL in these animals are discussed in detail. Also, the mechanisms by which PA reduces nutrient digestibility and increases gastrointestinal ENL in pigs and poultry are discussed, and areas that need further research to gain more insight into these mechanisms are suggested.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".