Milk Production, Marketing and Quality in Meta District of Eastern Hararghe Zone, Ethiopia
Bibliographic record
Abstract
The study was conducted in Meta District of Eastern Hararge Zone Oromia Regional State, Ethiopia with the objective to assess milk production and marketing, and to determine chemical composition and microbial quality of raw cow milk. Three Rural Kebeles (RK) namely, Biftu Ganama, Oda Chafe and Waligalte Bali’na were purposively selected based on dairy production potential and accessibility. A total of 132 respondents were randomly selected from farmers (122), consumers (6) and milk collection centers (4). Interview was made using semi-structured questionnaire to collect data on milk production, constraints, marketing, milk handling practices and utensils used as milk container. The result of the study indicated that, average daily milk production, milk for marketing and consumption were 1.96±0.517 litters/day/cow, 68.9% and 31.1%, respectively. Majority of the respondents ranked feed shortage as the first constraint. Hand milking after calf suckling was practiced by all the farmers. Most of the respondents (56.6%) used a gourd container locally called “qabe” for milking, and plastic jerry can (81.96%) for milk delivery to milk collection centers. Significantly higher (P < 0.05) figures were recorded for fat, protein, total solids, solids-not-fat and lactose contents at producers level than the consumers and collection centers. Total bacterial count (TBC), coliform count (CC) and yeast and mould count (YMC) of milk samples from milk collection centers were significantly higher (P < 0.05) than milk samples from consumers and producers and did not meet quality standards set by Quality Standard Authority of Ethiopia. Therefore, we can concluded that the chemical composition of milk was satisfactory compared to the standard level, whereas the microbial quality of the milk was poor that suggests the need for better sanitary practices of milking environment and milk utensils.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".