A Novel Functional Fruit/Vegetable Beverage for the Elderly: Development and Evaluation of Different Preservation Processes on Functional and Enriched Components and Microorganisms
Bibliographic record
Abstract
Despite lower energy intakes with age, elderly have higher requirements for several nutrients, making them vulnerable to deficiencies that further aggravate aging chronic conditions. To manage this problem, new food formulations are needed to address the nutritional needs of the worldwide growing aging population. In the present work, we develop an innovative functional fruit/vegetable beverage for the elderly using coconut water, orange juice and carrot juice. The beverage was enriched with vitamin A and C and supplemented with omega-3 fatty acids and inulin to provide important nutritional elements to the target consumers of this study. Osmolality classified the beverage as hypertonic. Heat (TT), supercritical carbon dioxide (SC-CO2) and dimethyl dicarbonate (DMDC) treatments were applied as preservation methods, and the responses of the functional and enriched components and enzymes were evaluated. Alicyclobacillus acidoterrestris ATCC 49025 and a surrogate Escherichia coli, ATCC 25922, were inoculated in the beverage to induce spoilage and verify the effectiveness of inactivation processes on the cells. The DMDC process reduced E. coli to undetectable levels and exhibited a greater reduction of A. acidoterrestris vegetative cells, molds and yeasts. The conditions applied in the process with SC-CO2 did not show satisfactory results in reducing juice microbiota. Loss of vitamin C and A was mainly associated with the SC-CO2 treatment. The beverage received a positive acceptability evaluation among the tasters in the sensory analysis and may be introduced as a new vehicle for the consumption of functional compounds, especially by vegans and/or vegetarians and lactose-intolerant 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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".