Comparative analysis of different carrier agents on functional, structural, and thermal properties of spray‐dried probiotic <i>Lactobacillus casei</i> powder
Bibliographic record
Abstract
Abstract Background and Objectives The aim of this study was to investigate the effect of incorporation of different plant‐based polysaccharides (pectin, maltodextrin (MD) and gum arabic (GA)) with pea protein isolate (PPI) to obtain maximum encapsulation efficiency (EE), gastrointestinal (GI) stability and yield of probiotic Lactobacillus casei through spray drying. Several characteristics of encapsulated vegan probiotic powders were evaluated including functional, structural, and thermal characteristics. Findings The results showed that the highest EE (93.9%) and in vitro GI stability (8.58 log CFU/mL) was obtained with the powder encapsulated with PPI + GA. Variation in particle size was observed for all the samples. Confocal laser micrographs and vital staining revealed the highest viability of probiotic L. casei cells that were obtained with those encapsulated in PPI + GA. Thermal properties showed that the incorporation of GA increased the glass transition temperature up to 189.2°C, which represented a higher thermal stability of the powder. Conclusions PPI + GA coated powder was found with acceptable powder characteristics and maximum probiotic survivability. Significance and Novelty In this study, spray drying was used to encapsulate the probiotic bacteria which is a convenient and effective process for industrial applications. Characterization of the spray‐dried encapsulated probiotic powder has been done, which helps to understand the behavior of powder in terms of solubility, flowability, thermal stability, and probiotic viability. PPI was used as carrier material, which bridges the gap between already available spray‐dried products containing MD as carrier material, which could spike blood sugar levels if consumed over an extended period of time. As per the results, target product applications could include sports bars, cereals, and baking where dispersibility is not imperative.
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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".