Studies on concentration of some milk metabolic enzymes at different parities, stage of lactation and their correlation with composition and yield of milk in Red Sindhi Cows
Bibliographic record
Abstract
The study investigated the impact of parity and lactation stage on milk metabolic enzyme concentrations and their correlation with milk composition and yield in Red Sindhi cows. A total of 45 apparently healthy cows were selected from two cattle farms in Pakistan. Milk samples were collected, tested for subclinical mastitis, and analyzed for chemical composition and enzyme activity. Notably, alkaline phosphatase (ALP) activity increased significantly from 1st parity to 3rd, 4th, and beyond 4th parity during early, mid, and late lactation. Aspartate amino transferase (AST) concentration was higher from 1st to 2nd parity across all lactation stages, followed by a decrease with increasing parity. Lactate dehydrogenase (LDH) concentration varied significantly during different lactation stages and parities concentration was significantly higher during early lactation of 4th parity cows, mid lactation of cows at >4th parity, and late lactation of 1st parity cows Additionally, milk fat and solid-not-fat (SNF) content were notably higher at >4th parity and 1st parity, respectively. Density of milk decreased and total solids (TS) increased with parity. Slightly higher pH was recorded in milk at 1stand 2ndparity. Protein, ash and chloride and milk yield increased with parity and lactation stage and milk yield .has positive correlation with AST and negative correlation with LDH and ALP. Ash, Fat Protein, and lactose have positive correlation with LDH, while chloride and pH have negative correlation with AST and LDH These findings provide valuable insights for the dairy industry.
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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) | 0.000 | 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".