Genetic evaluation of different graded Holstein Friesian × Local (HF × L) crossbred breeding bulls of Bangladesh
Bibliographic record
Abstract
Objective: The aim of this study was to estimate genetic parameters, breeding value, and ranking of Holstein Friesian × Local (HF × L) crossbred sires based on multi-trait selection index information. Methods: A total of 51 HF × L crossbred breeding bulls of three different genetic groups (50%HF × 50%L, 62.5%HF × 37.5%L, and 75%HF × 25%L) managed at Central Cattle Breeding and Dairy Farm (CCBDF) were evaluated based on 4,319 half-sib progeny performance data. The descriptive statistical analysis was performed using the R package. Genetic parameters were estimated using BLUPF90 by a single-trait animal model. A selection index was constructed using adjusted breeding values multiplied by variable economic weightage for each trait. Results: 0.05). In general, better productive and reproductive performances were found with the progression of HF inheritance. Daughters of 75%HF × 25%L crossbred bulls showed the highest average performance in birth weight (27.20 ± 0.09 kg), daily milk yield (8.55 ± 0.06 l), peak milk yield (10.44 ± 0.07 l), and lactation length (233.53 ± 0.85 days).The study investigated variance components of eight productive and reproductive traits such as the birth weight of calf, age at first conception, service per conception, daily milk yield, peak milk yield, lactation length, and calving interval where estimated heritability ranged from 0.09 to 0.32. Genetic correlations among the considered traits were found to be mostly weak. Among the top 20%, breeding bulls belonged to 75%HF × 25%L and 62.5%HF × 37.5%L crossbred groups. Conclusion: This study provides insightful information on the genetic evaluation of different graded bulls that could be the basis for the proven crossbred breeding bulls' selection process at CCBDF.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".