Milk Production, Quality Parameters, and Bacterial Colony Counts of Raw Milk from Murrah Buffaloes Reared in Mixed Crop-Livestock Systems
Bibliographic record
Abstract
This research aimed to assess the quantity and quality of raw Murrah buffalo milk in a mixed crop-livestock farming system in North Sumatra, Indonesia. The study was conducted at the Sumber Ternak Abadi livestock farm in Pagar Merbau District, North Sumatra, Indonesia, established in 2012 within an oil palm plantation. The study observed 40 lactating Murrah buffaloes. Variables included milk production and quality metrics such as total plate count in colony-forming units per ml, water content percentage, total solids, fat content, and pH. Results demonstrated a milk yield standardized to 305 days ranging from 1,200.78±490.25 to 1,505.71±589.73 kg/head/lactation. The total plate count was 2.1 x 105 ± 0.32 CFU/ml, total solids were 16.87% (w/w), fat was 5.7% (v/v), and pH was 6.73. The results confirmed that the raw Murrah buffalo milk from the observed farm meets the Indonesian National Standard for milk quality. A significant positive correlation was found between water content and total bacterial colony count (r = 0.82, p < 0.01), suggesting that higher water content in milk correlates with increased bacterial colonies.
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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) | 0.001 | 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".