Recent Patents on Microbial Proteases for the Dairy Industry
Bibliographic record
Abstract
This paper reviews the general characteristics of exo and endopeptidases of microbial origin currently used in the milk industry. It also includes recent patents developed either to potentiate the enzymatic activity or to improve the resulting milk derivatives. The main application of these proteases is in the cheese-making industry. Although this industry preferentially uses animal rennets, and in particular genetically engineered chymosins, it also utilizes milk coagulants of microbial origin. Enzymes derived from Rhizomucor miehei, Rhizomucor pusillus and Cryphonectria parasitica are currently used to replace the conventional milk-clotting enzymes. In addition, the dairy industry uses microbial endo and exoproteases for relatively new applications, such as debittering and flavor generation in cheese, accelerated cheese ripening, manufacture of protein hydrolysates with improved functional properties, and production of enzyme-modified cheeses. Lactic acid bacteria play an essential role in these processes, hence these bacteria and the proteases they produce are currently being investigated by the dairy industry and are the subject of many of their patent applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.016 |
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".