Development of Probiotic Fruit Juices Using Lactobacillus rhamnosus GR-1 Fortified with Short Chain and Long Chain Inulin Fiber
Bibliographic record
Abstract
Typically, probiotics are consumed in dairy based products such as yogurt. However, given the rise in various diet types, non-dairy alternatives have been developed, such as inoculating fruit juices with probiotics. Lactobacillus rhamnosus GR-1 is a probiotic strain exerting a number of human health benefits such as the prevention of urinary tract infections. Therefore, the objective of this study was to determine the viability of L. rhamnosus GR-1 in apple cider, orange, and grape juice when fortified with either 4% short chain or 4% long chain inulin fiber over 72 h of fermentation and 30 days of refrigerated storage. The secondary objective was to determine consumer acceptability of apple cider and orange juice samples using the hedonic scale. All of the fruit juice samples achieved a mean viable count of at least 107 CFU/mL during 72 h of fermentation and 30 days of refrigerated storage. According to the sensory evaluation, which evaluated samples according to appearance, flavor, texture, and overall acceptability, apple cider juice with long chain inulin fiber proved to have the highest score for all characteristics except appearance. Therefore, this study indicated a potential for probiotic fruit juices as a valid alternative to dairy based probiotic products.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".