Evaluation of trace elements in forages and their effect on gastrointestinal parasite burden in grazing sheep
Bibliographic record
Abstract
This study was designed to evaluate the trace elements (minerals) in forages fed to sheep and their effect on gastrointestinal parasite burdens. The ultimate objective was to determine the correlation between the burden of GI parasites and the level of trace minerals in sheep serum as a result of the forages they grazed on. A total of 384 faecal samples were collected from sheep in each of the districts (Sialkot and Multan) and examined quantitatively using the McMaster technique. Serum collected from them and plants were pre-treated, and spectrophotometry was used to determine the concentration of trace minerals (Mn, Co, Cu, and Zn). The level of these trace elements differed significantly (P < 0.05) in forages from both districts. In the district of Sialkot, the highest concentrations (mg/Kg) of Zn (38.53 ± 0.16) were found in Cichorium intybus, Cu (41.57 ± 0.07) in Cynodon dactylon, Mn (39.61 ± 0.05) in Parthenium hysterophorus, and Co (1.42 ± 0.03) in Coronopus didymus. In the district of Multan, the highest concentrations (mg/Kg) of Zn (39.43 ± 0.46) were found in Cichorium intybus, Cu (25.76 ± 0.36) in Cynodon dactylon, Mn (34.29 ± 0.53) in Launaea nudicaulis, and Co (1.74 ± 0.08) in Brachiaria raptens. The prevalence of GI parasites in sheep populations in district Sialkot was 34%, while in district Multan, it was 32%. In tehsil Sialkot of district Sialkot, Zn and Cu were significantly (P < 0.05) correlated with eggs per gram (EPG) of faeces, while in tehsil Multan City of district Multan, only Cu was significantly (P < 0.05) correlated with EPG. The potential mechanism behind the role of trace minerals in lowering the burdens of GI parasites requires more investigation. It is recommended that plants with high content of trace minerals should be utilized as part of comprehensive preventive and control strategies against GI parasitism in ruminant animals like sheep.
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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 | 0.001 |
| 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) | 0.000 | 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 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".