Thermostability of Probiotics and Their <i>α</i>-Galactosidases and the Potential for Bean Products
Bibliographic record
Abstract
Soybeans and other pulses contain oligosaccharides which may cause intestinal disturbances such as flatulence. This study was undertaken to investigate α -galactosidase-producing probiotics added to frozen foods which can survive warming treatments used in thawing and consumption of the pulses. The maximum α -galactosidase activity (1.26 U/mg protein) was found in Bifidobacterium breve S46. Lactobacillus casei had the highest α -galactosidase thermostability among the various strains, with D values of 35, 29, and 9.3 minutes at 50°C, 55°C, and 60°C, respectively. The enzyme activity was less affected than viable cells by heating. However, the D values of two bacterial enzymes were lower than those of three commercial α -galactosidase-containing products. Freshly grown cells and their enzymes were more stable than the rehydrated cultures and their enzymes. Practical Application. Enzymes and cultures can be added to foods in order to enhance the digestibility of carbohydrates in the gastrointestinal tract. However since many foods are warmed, it is important that the thermostability of the enzymes be assessed. This paper provides data on the stability of α -galactosidase, which could potentially be added to food matrices containing stachyose or raffinose, such as beans.
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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".