Behavior, health, and productivity of early-lactation dairy cows supplemented with molasses in automated milking systems
Bibliographic record
Abstract
The objective of this study was to determine the effect of molasses-based liquid feed (LF) supplementation within automated milking systems (AMS) on the behavior, health, and production of early-lactation dairy cows. In 6 commercial AMS dairy herds, 390 dairy cows were randomly assigned before calving to 1 of 2 treatments, within farm, balanced by parity: (1) control group (CON) receiving a standard AMS pellet [mean = 3.9 kg/d on a dry matter (DM) basis, n = 188], or (2) same amount of standard AMS pellet (mean = 3.6 kg/d on a DM basis, n = 202) plus 1 kg/d DM of LF for multiparous cows (1.6 kg/d as fed) and 0.88 kg/d DM for primiparous cows (1.4 kg/d as fed). Across farms, cows were fed partial mixed rations similar in ingredient and nutrient composition. Cows on the LF treatment received supplementation for the first 60 d in milk (DIM). Blood samples were taken 2 times/wk for the first 3 wk postcalving to assess β-hydroxybutyrate (BHB). Samples with BHB ≥1.2 mmol/L were classified as a positive case of subclinical ketosis (SCK). Cow body condition and lameness were scored every 10 d postcalving until 60 DIM. No differences were detected between treatments for milk yield (average milk yield = 37.4 ± 1.98 kg/d) and milking frequency (average milking frequency = 3.2 ± 0.01 times/d). Similarly, no difference between treatments in daily AMS visits was detected (average AMS visits = 5.3 ± 0.3 times/d). However, CON cows experienced more AMS refusals/d than LF cows (LF = 1.6 refusals/d, CON = 2.1 refusals/d). No difference between treatments in daily rumination time was detected (average rumination time = 476 ± 10.8 min/d). Treatment was associated with the number of times cows tested positive for SCK; cows on LF had fewer repeated diagnoses of SCK, such that 15% of cows on LF had ≥3 diagnoses of SCK out of 5 tests, compared with 27% of CON cows. Cows receiving molasses tended to have lower blood BHB values at ∼15 DIM. Molasses supplementation also allowed cows to maintain a more stable body condition score, as LF cows tended to lose less body condition over the first 60 DIM compared with CON cows. Overall, the results of this study demonstrate that supplementing a molasses-based LF to AMS cows may help support the energy demands of milk production in early lactation and, thus, reduce the incidence of repeat positive SCK tests during that time period.
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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) | 0.001 | 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".