Nutritional Composition of Malted Barley Residue from Brewery
Bibliographic record
Abstract
The reuse of residue is an alternative that benefits the industries, adding value to the residue and still reducing the costs necessary with the treatment before its disposal, but it can also enrich human food. The malted barley residue (malt bagasse) is the main residue obtained in the manufacture of beer. However, it is often discarded in the environment incorrectly or used as feed. Its nutritional potential, its ease of obtaining and its low cost, are incentives for this ingredient to be used in food. The present study is aimed at carrying out the physical-chemical characterization of the malted barley residue, in order to assess its nutritional potential. Physical-chemical analysis showed that the bran from malted barley residue presented high content of fibre, proteins and minerals, mainly phosphorus, in addition to a significant amount of potassium, iron and calcium and low sodium content. Thus, the malted barley residue showed nutritional potential to be used as ingredient in food formulation, being a sustainable way of the food industry to take advantage of this residue. The malted barley residue can be an important ingredient in the production of breads, cakes and cookies, among other preparations. These would be low-cost foods, representing savings both for the beer sector, which needs to dispose off the residue, and for the food industry, in addition to contributing to the preservation of the environment. Thus, the present study shows that the reuse of malted barley residue is a sustainable practice with environmental, economic and nutritional importance.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".