Shelf life stability of lactobacilli encapsulated in raspberry powder: Insights into non-dairy probiotics
Bibliographic record
Abstract
AIM: Study the shelf-life quality changes in raspberry juice with encapsulated lactobacilli (Lactobacillus rhamnosus NRRL B-4495 and Lactobacillus acidophilus NRRL B-442) obtained by spray drying and understand the various factors involved. METHODS AND RESULTS: Raspberry powder was obtained from spray drying lactobacilli and raspberry juice with maltodextrin as an additive. Shelf life of the powder was analyzed over a period of 30 d. Acid and bile tolerance and antibiotic resistance was compared before and after spray drying. Water activity, survival, and scanning electron microscope images were also measured during the shelf life. CONCLUSIONS AND SIGNIFICANCE: A combination of processing conditions: inlet temperature (°C), maltodextrin to juice solids ratio and inlet feed rate (ml/min) during spray drying had a significant role on the survival of lactobacilli during shelf life. Refrigerated storage provided a higher shelf-life stability with regards to CFU/g (as high as 84% on day 0 and 98% retention by the end of 30 d) compared to room temperature storage. Probiotic properties during shelf life are affected by the processing conditions and encapsulated food matrix. Thus, understanding these aspects in vitro during shelf life gives us a brief insight into the future of non-dairy probiotics.
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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) | 0.001 | 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".