Comparison of the growth kinetics and proteolytic activities of <i>Chryseobacterium</i> species and <i>Pseudomonas fluorescens</i>
Bibliographic record
Abstract
The effect of temperature on the growth kinetics and proteolytic activity of Chryseobacterium joostei and Chryseobacterium bovis was determined during this study. The results were compared with the activities of Pseudomonas fluorescens, which is regarded to be a major food spoilage psychrotolerant microorganism. For the growth studies, cultures were incubated in nutrient broth in a temperature gradient incubator (from 9 to 50 °C) and separately at 4 °C, and the optical density was measured at different time intervals. Growth temperature profiles for each organism were constructed. For determination of proteolytic activity, the cultures were incubated in fat-free ultra-high temperature processed milk in the temperature gradient incubator for 72 h (temperature range as above). Cell-free extracts were used to determine the proteolytic activity using the azocasein method. Results of the growth studies showed that C. joostei had the ability to grow over a wider temperature range than C. bovis and P. fluorescens without being affected by changes in the temperature. For the proteolytic activity, C. joostei had significantly (p < 0.001) higher activity per milligram of protein at 15.5 °C, followed by C. bovis and P. fluorescens. The results showed that C. joostei potentially has an even greater spoilage capacity in milk on the basis of growth rate and proteolytic activity than did P. fluorescens.
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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) | 0.000 | 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 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".