Will Isomalto-Oligosaccharides, a Well-Established Functional Food in Asia, Break through the European and American Market? The Status of Knowledge on these Prebiotics
Bibliographic record
Abstract
This critical review article presents the current state of knowledge on isomalto-oligosaccharides, some well known functional oligosaccharides in Asia, to evaluate their potential as emergent prebiotics in the American and European functional food market. It includes first a unique inventory of the different families of compounds which have been considered as IMOs and their specific structure. A description has been given of the different production methods including the involved enzymes and their specific activities, the substrates, and the types of IMOs produced. Considering the structural complexity of IMO products, specific characterization methods are described, as well as purification methods which enable the body to get rid of digestible oligosaccharides. Finally, an extensive review of their techno-functional and nutritional properties enables placing IMOs inside the growing prebiotic market. This review is of particular interest considering that IMO commercialization in America and Europe is a topical subject due to the recent submission by Bioneutra Inc. (Canada) of a novel food file to the UK Food Standards Agency, as well as several patents for IMO production.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".