Production and Reproductive Performance of Bhadawari Buffaloes in Uttar Pradesh, India
Bibliographic record
Abstract
Bhadawari is one of the recognized buffalo breeds of India and is famous for high fat content in their milk. Data on production and reproductive traits were collected under Network Project on Bhadawari buffaloes, at Indian Grassland and Fodder Research Institute, Jhansi, Uttar Pradesh, India. The overall least squares means (±SE) for peak yield, days to attain peak yield, lactation milk yield, lactation length, 305 days milk yield, milk yield per day of lactation, service period, calving interval and dry period were 6.96±0.10 kg, 52.8±4.1 days, 1250.5±24.6 kg, 291.4±4.9 days, 1213.5±21.6 kg, 4.30±0.06 kg, 172.4±7.7 days, 522.1±12.1 days and 241.80±11.3 days, respectively. Period of calving had a significant (p<0.05) to highly significant (p<0.01) effect on all the traits studied except service period and dry period, where it was not significant. Season of calving had a significant (p<0.05) effect or lactation length and highly significant (p<0.01) effect on lactation milk yield, 305 days milk yield and all the reproductive traits under study. The lowest calving interval, service period and dry period were observed in rainy season calvers and they differed significantly (p<0.01) with winter and summer calvers. Parity had a significant effect (p<0.05) on lactation milk yield, 305 days milk yield and milk yield per day of lactation. Pair-wise comparison revealed that lactation milk yield was highest in the 2nd lactation followed by 3rd and 4th lactation. Large coefficient of variation observed for different traits under study indicates that there is enough scope for improvement in the production and reproduction traits. Better breeding management and selection for increased performance is needed for genetic improvement of these traits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".