398 Effects of protein level and supplemental methionine in late-gestation on colostrum quality and passive immunity transfer in beef cattle
Bibliographic record
Abstract
Abstract The objective of this study was to evaluate the influence of metabolizable protein (MP) level and supplemental rumen-protected methionine (RPM) on colostrum quality and passive immunity transfer from beef cows fed during late-gestation. One hundred and forty-seven pregnant Angus crossbred cows and heifers were randomly assigned to one of six dietary treatments based on a 3 x 2 factorial arrangement. Diets included feeding to 90%, 100% and 110% MP requirements (NRC, 2016), offered with (without) 9 g/d of RPM. Cattle were individually fed a partially mixed ration (60% haylage/40% straw for cows; 70% haylage/30% straw for heifers) with supplements top-dressed daily for approximately 56 d prior to calving. Immediately after calving, a colostrum sample was collected from each dam for analysis of milk components, total protein, and IgG concentrations. Two d post-calving, serum samples were collected from each calf for analysis of total protein and IgG concentrations. A refractometer was used to estimate total protein as a preliminary estimate of the transfer of maternal IgG and total IgG concentrations were later determined using Radial Immunodiffusion (RID). Data were analyzed as a completely randomized block design using Proc GLIMMIX in SAS. Level of MP, RPM, and their interaction did not influence concentrations of fat, protein, BHB or SCC in colostrum (P ≥ 0.12). Supplementation of RPM decreased concentrations of MUN (45.92 vs. 54.51 ±3.17 mg/dl; P = 0.04), but did not change IgG (14.66 vs. 15.90 ±0.87 g/dl; P = 0.29). While MP level during gestation did not affect total protein or IgG concentrations in calf serum (P ≥ 0.64), providing supplemental RPM decreased total protein (5.79 vs. 6.33 ±0.13 g/dl; P = 0.002) and IgG concentrations in calf serum (3.44 vs. 4.30 ±0.25 g/dl; P = 0.01). These results suggest that providing supplemental methionine for beef cows during gestation may alter colostrum quality and decrease serum protein and IgG in offspring.
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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".