Impact of Antinutritional Factors in Food Proteins on the Digestibility of Protein and the Bioavailability of Amino Acids and on Protein Quality
Bibliographic record
Abstract
Dietary antinutritional factors have been reported to adversely affect the digestibility of protein, bioavailability of amino acids and protein quality of foods. Published data on these negative effects of major dietary antinutritional factors are summarized in this manuscript. Digestibility and the quality of mixed diets in developing countries are considerably lower than of those in developed regions. For example, the digestibility of protein in traditional diets from developing countries such as India, Guatemala and Brazil is considerably lower compared to that of protein in typical North American diets (54-78 versus 88-94 %). Poor digestibility of protein in the diets of developing countries, which are based on less refined cereals and grain legumes as major sources of protein, is due to the presence of less digestible protein fractions, high levels of insoluble fibre, and/or high concentrations of antinutritional factors present endogenously or formed during processing. Examples of naturally occurring antinutritional factors include glucosinolates in mustard and canola protein products, trypsin inhibitors and haemagglutinins in legumes, tannins in legumes and cereals, gossypol in cottonseed protein products, and uricogenic nucleobases in yeast protein products. Heat/alkaline treatments of protein products may yield Maillard reaction compounds, oxidized forms of sulphur amino acids, D-amino acids and lysinoalanine (LAL, an unnatural nephrotoxic amino acid derivative). Among common food and feed protein products, soyabeans are the most concentrated source of trypsin inhibitors. The presence of high levels of dietary trypsin inhibitors from soyabeans, kidney beans or other grain legumes have been reported to cause substantial reductions in protein and amino acid digestibility (up to 50 %) and protein quality (up to 100 %) in rats and/or pigs. Similarly, the presence of high levels of tannins in sorghum and other cereals, fababean and other grain legumes can cause significant reductions (up to 23 %) in protein and amino acid digestibility in rats, poultry, and pigs. Normally encountered levels of phytates in cereals and legumes can reduce protein and amino acid digestibility by up to 10 %. D-amino acids and LAL formed during alkaline/heat treatment of lactalbumin, casein, soya protein or wheat protein are poorly digestible (less than 40 %), and their presence can reduce protein digestibility by up to 28 % in rats and pigs, and can cause a drastic reduction (100 %) in protein quality, as measured by rat growth methods. The adverse effects of antinutritional factors on protein digestibility and protein quality have been reported to be more pronounced in elderly rats (20-months old) compared to young (5-weeks old) rats, suggesting the use of old rats as a model for assessing the protein digestibility of products intended for the elderly.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".