Effects of postpartum fat supplementation and source on the reproductive performance of lactating young beef cows grazing cool-season grass pastures
Bibliographic record
Abstract
ABSTRACT Objective The objective was to evaluate the effects of fat supplementation and source on reproductive performance of young lactating Angus beef cows grazing cool-season grass (CSG) pastures. Materials and Methods Over 3 yr, 36 second- and third-calving, lactating (38 ± 1.5 d postpartum) Angus cows (554 ± 15.5 kg of BW) were assigned randomly to 9 paddocks (4 cows per paddock) of CSG pastures. Each paddock was assigned randomly to a nonsupplemented control (CON) or 2 supplemented (SUP) treatments in which cows received 300 g/cow per day of supplemental fat (ether extract) from a canola seed–based (CAN) or flaxseed-based (FLX) pellet for 42 d before start of the breeding period. Data were analyzed as a randomized complete block design contrasting the effects of fat supplementation (CON vs. SUP) and fat source (CAN vs. FLX). Results and Discussion Results indicate that cows in CON had greater (P = 0.01) forage utilization and tended (P = 0.08) to have greater estimated forage DMI compared with cows in SUP, whereas no difference (P ≥ 0.76) was observed between CAN and FLX treatments. By the end of the trial, all treatments resulted in positive ADG, maintained or increased BCS and s.c. fat thickness, and reduced serum nonesterified fatty acid concentrations with no difference (P ≥ 0.20) among treatments. No differences (P ≥ 0.12) were observed for pregnancy rate, calving distribution, and calving-to-calving interval. The failure to find treatment differences in growth and reproductive performance is likely a result of greater-than-expected nutrient content (CP: 12.5 ± 2.5%; TDN: 56.5 ± 2.9%) of CSG pastures and similar nutritional status across treatments. Implications and Applications These results indicate that prebreeding fat supplementation and source had no beneficial effects on reproductive performance of young, lactating Angus beef cows grazing good quality CSG pastures.
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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 | 0.000 | 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 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".