Phenotypic Characterization of Indigenous Sheep Breeds in Saudi Arabia
Bibliographic record
Abstract
Saudi’s farm animal genetic resources have a particular role to play in managing the rural environment and assisting in maintaining wild biological diversity. Our indigenous livestock breeds are of great economic, social and cultural importance. The presence of livestock is a very positive feature for many who live in, work in or visit the countryside and livestock farming is frequently a core activity on which whole communities depend. The Kingdom has a rich and diverse population of livestock breeds sheep, goats, poultry, horses & Camel most of it are at risk. The conservation and sustainable use of genetic resources for food and agriculture is a widely supported international objective contributing to efforts to eliminate global poverty and achieve world food security. The data of the present study were collected form Noemi, Najdi and Hari breeds raised in Najd (96, 108, and 90 animals, respectively) Qassim region. Eight body measurements were studied, Wither heights (WH), Rum heights (RH), Body length (BL), Head length (HL), Heart girth (HG), Muzzle diameter (MD), Cannon circumference (CC) and Cannon length (CL). Noemi is taking the second size breed of the sheep breeds in Saudi Arabia. Hari is the smallest breed of sheep breeds in Saudi Arabia and it is the main breed in Hejaz and Asir regions which belong to the sheep with coarse hair and thick tail strain. The results of the present study on these breeds showed that Najdi breed has the biggest sizes in all body measurements 10.9% and 11.4% bigger than Noemi and Hari, Approximate respectively. By the other way in comparing Noemi’s breed with Hari breed, Noemi having the biggest sizes (10.5% Approximate) in all body measurements than Hari. Three categories of ages were presents in this study, eight, eighteen and forty-eight months. The first category eight months showed the smallest size in all body measurements by 11.2% in compare with eighteen months. No big differences were showed among eighteen and forty-eight months the different around 2% in favor of forty-eight category. In addition, the effect of sex was significant, male always have biggest body measurements in compare with female. The results showed that male have around 10.9% more in all studied measurements more than female. All the fixed effect (effect of: Age, Breed and Sex) are significant on all body measurements traits expect Cannon circumference (CC) trait. The correlations coefficients among all studied traits were moderate to high and highly significant. The highest correlation coefficient was found between RH and WH traits (0.872), and the lowest one was found between CC and HG traits (0.214).
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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 | 0.000 |
| 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".