The Scenario of Buffalo Production and Research in Bangladesh
Bibliographic record
Abstract
Background: This study aimed to characterize the scenario of buffalo production in the northern part of Bangladesh and review the published scientific literature on buffalo from Bangladesh. Methods: The study was conducted from August to December 2022. A draft questionnaire was prepared and modified before the final one based on the study's objectives. Data were collected through personal interviews with individual respondents. In addition, the review article was collected on buffalo from Google, Google Scholar, Research Gate, Scopus, Bangladesh Journal-Online (BJO), and PubMed. Results: Data was collected from 1099 animals from the northern part of the Natore and Lalmonirhat districts of Bangladesh. Most of the farmers were illiterate, and the age was above 40 years. Regarding the purpose of buffalo production, 69.16% (n=83) of the farmers narrated that they are motivated to milk with calves selling. The average herd size was about 9 and consisted of indigenous and crossbred buffaloes. Most of the farmers kept their buffalo in the Bathan. The coat color was predominantly black, with brown hair. Farmers 94.16% (n=113) practice de-worming, and the frequency was thrice a year. Wallowing is performed at least once a day in the pond or river for the thermal regulation of the buffalo. Among the farmers, 67.50% (n=81) have no training in rearing buffalo. Farmers practice natural mating by their own or neighbor bull to serve the heated cow. Sometimes it’s free, or sometimes, with payment on an average of BDT 400-500 or 3.79-4.73 US dollars. In some areas, AI is being practiced in buffalo under different organizations (LAL Teer, BRAC), and the cost of AI was recorded as about BDT 600-700 or 5.68-6.63 US dollars per cow. The average daily milk yield was 3.0 liter, whereas the lactation length was recorded at 179.9±3.84 days. The major constraints were high feed price 91.66% (n=110), shortage of land 41.08% (n=51), and lack of suitable marketing facilities 50.82% (n=62). 100% of farmers stated that they need improved grass production technology and reduced feed and medicine price; 24.16% (n=29) need good quality semen. From 2004 to 2022, 51 studies were found related to buffalo, where the highest 27.45% (n=14) belonged to performance studies, and 54.90% (n=28) studies were carried out in the southern part of Bangladesh. Conclusion: It can be concluded that buffalo has great potential with different areas of improvement. Therefore, more research is needed from different perspectives on production, reproduction, nutrition, quality of milk/meat/products, health, and sustainability of buffalo farming in Bangladesh.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".