Evaluation of laboratory and on-farm tests to estimate colostrum quality for dairy cows
Bibliographic record
Abstract
The objectives of this study were to evaluate different analytical methods to determine colostrum quality in dairy cattle, including one laboratory-based method (ELISA) and 4 on-farm tests. We hypothesized that the colostral IgG concentration using different analytical methods, such as ELISA (mg/mL), digital Brix refractometer (% Brix), colostrometer (specific gravity and mg/mL), an outflow funnel (seconds), and a lateral flow assay (mg/mL), were highly correlated with the reference method, radial immunodiffusion (RID; mg/mL) and would generate comparable results. Colostrum samples were collected from 209 Holstein Friesian cows on 2 commercial dairy farms in Germany. Colostrum weight and colostrum temperature were measured. Test characteristics, such as optimum thresholds, sensitivity, specificity, and area under the curve (AUC) were determined using a receiver operating characteristic curve analyses for each test. Out of 209 colostrum samples assessed by RID, 186 (89%) samples had high quality (≥50 mg IgG/mL), while 23 colostrum samples (11%) showed poor quality with IgG concentrations less than 50 mg/mL. The mean IgG concentration (±SD) was 101.3 ± 45.9 mg/mL and the range was 6.0 to 244.3 mg/mL. The Pearson correlation coefficient (r) between RID and ELISA was r = 0.78. In comparison to RID, Pearson correlation coefficients for the on-farm tests were: r = 0.79 (digital Brix refractometry), r = 0.58 (colostrometer: specific gravity), r = 0.61 (colostrometer: temperature corrected), r = 0.26 (outflow funnel) and r = 0.43 (lateral flow assay), respectively. The optimal threshold to identify high-quality colostrum using ELISA was 50.8 mg/mL with sensitivity 91.3%, specificity 92.3%, and AUC of 0.94. For the on-farm tests sensitivity ranged from 95.7% (Brix refractometry) to 60.9% (lateral flow assay). Specificity ranged from 88.6% (lateral flow assay) to 75.9% (colostrometer: temperature corrected). The AUC ranged from 0.93 (Brix refractometry) to 0.73 (outflow funnel). Based on the AUC, ELISA (0.94) and Brix refractometry (0.93) can be considered highly accurate. In conclusion, the ELISA is accurate to assess colostrum quality. Regarding the on-farm tests only the digital Brix refractometer and the colostrometer were adequate to determine colostrum quality.
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.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".