Role of drying technology in probiotic encapsulation and impact on food safety
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The world’s urban population is expected to double by 2050. Urbanization is changing food consumption patterns, and the global market is flooded with functional foods, specifically probiotics, for their gut health advantages. Awareness about the healthy human microbiome among the consumer has prompted them to demand probiotic foods. Due to their potential health benefits, probiotics have been incorporated into several dairy and nondairy products. To overcome the hurdles associated with the low viability of the beneficial microorganism, microencapsulation of probiotic bacteria and yeast is of immense importance. Microencapsulation enhances the viability of probiotics during different processing techniques and under gastrointestinal conditions. So, it is critical to control and design the drying process technology for probiotics encapsulation to achieve higher viability. The purpose of the review is to compile the commonly utilized drying technique for probiotics with their principle, advantages, and disadvantages, mechanism of inactivation, recent research, and cost involved in the processing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| 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 it