Quantitative assessment of German Holstein dairy cattle colostrum and impact of thermal treatment on quality of colostrum viscosity and immunoglobulins
Bibliographic record
Abstract
Abstract Objective This study aimed to determine the color, fat, viscosity, IgG concentration, %Brix and refractive index of fresh postpartum colostrum of German Holstein dairy cattle and assess the impact of different thermal treatments on the visual and dynamic viscosity, in association to IgG concentration, of colostrum that can be used for pasteurization process. Results Of the total 40 fresh postpartum colostrum, the color of colostrum (ranging from white-pale yellow to yellow and dark-yellowish), fat (1.4–8.2 100 g −1 ), IgG (4–116 mg mL −1 ), %Brix (8.5–35.4%), refractive index (1.3454–1.3905 nD), visual (ranging from watery to liquid and thick) and dynamic (4.9–219 cp) viscosity, were recorded. Statistical analysis between visual and dynamic viscosity of fresh colostrum showed significant correlation coefficients ( r s = 634). Moreover, a significant correlation between viscosity and three IgG concentrations was also observed. Heat-treated colostrum showed dynamic viscosity ranged from 25 to 3066 cP, where dynamic viscosity of colostrum before- and after heat-treatment showed no significant correlation. Treated colostrum at 60 °C/60 min and 63.5 °C/30 min containing IgG concentration ≤ 80 mg mL −1 and ≤ 68 mg mL −1 showed no significant change in the viscosity and can successfully be applied for pasteurization of first postpartum colostrum.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".