Effects of different feeding systems and sources of grain on lactation characteristics and milk components in dairy cattle
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of two different feeding systems and of four different energy sources (Grain diet) on lactation characteristics and milk composition of dairy cattle. A total of 8,808,798 test-day records from 566,736 Holstein cows in 5,183 different herds, and 416,883 test-day records from 26,973 Ayrshire cows in 652 different herds covering a period of five years were obtained from the Quebec dairy herd improvement agency (Valacta). In addition to test-day records, information on lactation, animal status, feed composition and feeding systems was also available. For both Ayrshire and Holstein cows the fixed effect of Feeding System*DIMB (Blocks of 15 days in milk) was a significant effect in predictive models of daily milk, milk-fat, protein, and lactose yields and on milk urea nitrogen (MUN) concentration. Cows served a diet prepared with a Total Mixed Ration (TMR) compared to cows served a diet in a Traditional way tended to have higher peak milk yields and appeared to have a stronger persistency after peak milk yield. TMR-fed cows also showed a tendency for higher milk-fat, protein, and lactose yields and lower MUN concentrations than Traditionally-fed ones. Significantly higher milk yields (peak to 135 days in milk) and higher milk-fat and protein yields (peak to mid-lactation) were found in TMR-fed cows compared to Traditionally-fed ones in 3rd parity Holsteins. Both milk-fat and protein-yield lactation curves of TMR-fed cows displayed a different pattern than Traditionally-fed cows. The fixed effect of the Grain diet*DIMB was found to be a significant effect in predictive models of milk and milk-protein yields of both Ayrshire and Holstein. It was also found to be a significant effect in predictive model of MUN concentration but only in 2nd parity Ayrshire. The effect was non-significant in predictive models of both milk-fat or lactose yields. A tendency for higher milk and milk-protein yields, and lower MUN values was seen when cows received Corn Grain or High Moisture Corn compared to Barley or Commercial Concentrate but no significant differences were observed. It was concluded that a tendency for higher milk and components yields can be observed when cows are fed with a TMR compared to a Traditional system.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".