Effect of a Short-Time Germination Process on the Nutrient Composition, Microbial Counts and Bread-Making Potential of Whole Flaxseed
Bibliographic record
Abstract
The aim of this work was to investigate the germination process of whole flaxseed and its application in food matrices. Microbial counts, nutrient composition, dough mixing properties and bread-making potential of raw and germinated whole flaxseed were compared. A germination process of 1 day at 20C led to an improvement in the nutrient composition. Fatty acid profiles of whole flaxseed remained unchanged. Antioxidant capacity increased from 210 to 442 μmol Trolox equivalent/g dry matter, lignans from 12.4 to 13.7 mg/g dry matter and free essential amino acids from 115 to 331 μg/100 g dry matter. The flour processed from germinated whole flaxseed had little impact on dough mixing properties and showed good bread-making potential. Increases in the population of lactic acid bacteria (from 2.06 to 5.71 log cfu/g), Enterobacteriaceae (from 3.57 to 5.60 log cfu/g), and yeast and mold (from 2.41 to 5.43 log cfu/g) were observed after the germination process. Practical Applications Germination (or malting) is a well-known process in the barley industry and is mainly dedicated to brewing purposes. In parallel, the germination of grains is recognized to improve their nutritional value while presenting some concerns in terms of microbiological stability. The present work aimed to apply a structured germination process to whole flaxseed in order to produce flours that could be successfully used as an ingredient in food matrix formulation. Our results will help manufacturer and scientist to improve their understanding of the impact of germination process on whole flaxseed nutrient composition and of the importance of controlling microbiological growth. Ultimately, this could lead to the marketing of added-value whole flaxseed ingredients.
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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 | 0.000 | 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 | 0.001 |
| 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".