Comparative Study of Lactation Curves and Milk Quality in Holstein versus Swedish Red and White-Holstein Cross Cows
Bibliographic record
Abstract
The objective of this study reported in this research paper was to compare the lactation curves of the production of milk, fat, protein, percentages of fat and protein, and somatic cell score in purebred Holstein (H) cows and Swedish Red and White (SRW) - Holstein (SxH) crossbred cows in the south-central region of the province of Cordoba, Argentina. The data set consisted of 32847 herd-test records from 1244 purebred H cows and 310 SRW x H crossbred cows, from three commercial dairy farms with cows of first to fifth or more lactations. The curves were modeled using the fourth-order Legendre orthogonal polynomials. In this study, the data of production of milk, fat production, protein production, percentage of fat, percentage of protein and somatic cell score (SCS) were analyzed. Purebred H cows had significantly higher milk production, more fat production and higher protein production levels than did SxH crossbred cows. However, SxH crossbred cows produced milk that had a higher percentage of fat and a higher percentage protein than did purebred H cows. In none of the lactations did somatic cell score differ significantly between the two breed groups. The results of our study showed that, SxH crossbred cows had significantly higher percentages of fat and protein; however, purebred H cows were significantly superior to SxH crossbred cows for the production of 305-d milk, fat, and protein. Mammary health, expressed in SCS, did not differ significantly between the two breed groups. Thus, suggest that crossbreeding Holstein purebred cows with SRW bulls can improve the composition of milk solids without affecting mammary health and, in this way, compensate substantially for any potential loss in the production and/or quality of the milk of the crossbred cows compared to H purebred cows.
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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 | 0.001 | 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".