Chemical Form of Trace Minerals (Copper, Zinc and Manganese) Fed to Rams Affects Plasma Testosterone Concentrations and Semen Characteristics
Bibliographic record
Abstract
This study investigated the impacts of dietary trace mineral supplementation (copper, zinc and manganese) on plasma testosterone concentrations and semen characteristics in Afshari × Booroola merino rams. Twenty rams were equally allocated into four groups and fed for 70 days, as follows: Control (no supplemental minerals); Sulphate (sulphate forms); Hydroxychloride (30% hydroxychloride, 70% sulphate) and Amino chelate (30% chelate, 70% sulphate). Plasma testosterone concentrations, seminal plasma antioxidant enzyme activities, alkaline phosphatase and total antioxidant capacity were assessed on Days 0 and 70. On Day 70, all these end points were higher (p < 0.05) in the Hydroxychloride and Amino chelate groups compared to the other groups. Furthermore, the Sulphate group had no significant change from Day 0, whereas the Control group decreased (p < 0.05). Ejaculate volume and sperm concentration were measured in fresh semen. Sperm quality was evaluated in fresh and frozen-thawed samples, including motility, morphology, viability and membrane functionality every 14 days. From Day 42, sperm motility, viability and membrane functionality improved (p < 0.05) in the Hydroxychloride and Amino chelate groups. These parameters remained stable in the Sulphate group but declined in the Control group (p < 0.05). Notably, the Control group had the highest percentage of morphologically abnormal sperm at 70 days (p < 0.05). Additionally, the Hydroxychloride and Amino chelate groups had fewer apoptotic sperm and lower malondialdehyde concentrations compared to the Control and Sulphate groups. In conclusion, supplementation with hydroxychloride or amino chelate forms of trace minerals optimised reproductive performance in rams, with higher plasma testosterone concentrations and superior sperm quality compared to sulphate or control diets.
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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 | 0.000 | 0.002 |
| 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".