Genetic Parameter Estimation and Selection for Resistance to Gastrointestinal Nematode Parasites in Sheep—A Review
Bibliographic record
Abstract
Gastrointestinal nematodes (GINs) are a major problem affecting sheep production systems worldwide. The flocks infected with GINs can undergo significant economic losses due to a decrease in productivity, the animals' deaths, and the costs associated with treatments. The over-reliance on anthelmintics in the past years to eliminate GINs has resulted in the development of resistance against the available commercial anthelmintics. Genetically resistant animals can be used in mating systems to improve the overall flock resistance. This review aimed to summarize the estimated genetic parameters for resistance traits and genetic gains through the use of genetic/genomic selection for resistance to GINs in sheep. Heritability estimates from the literature ranged from 0.00 to 0.46 for fecal egg counts, 0.12 to 0.37 for packed cell volume/hematocrit, 0.07 to 0.26 for FAffa MAlan CHArt (FAMACHA©), from 0.10 to 0.37 for blood parameters, and 0.19 for Immunoglobulin A. Genetic correlations between traits measuring resistance to GINs and production traits ranged from negative to positive values in the literature. Genetic gains are possible when genetic/genomic selection for GIN resistance is applied. Therefore, genetic/genomic selection can be used to improve flocks' resistance to GINs as a sustainable approach in sheep production systems.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".