Epidemiology of Gastrointestinal Nematodes in Grazing Yearling Beef Cattle in Saskatchewan
Bibliographic record
Abstract
Gastrointestinal nematodes (GIN) in beef cattle can be a concern for cattle producers due to loss in profit associated with anthelmintic treatment costs and reduced production performance. There is limited current information regarding the epidemiology of GIN in grazing yearling beef cattle in western Canada. Hence, the objectives of this research were to: 1) describe the epidemiology of GIN and assess their impact on weight gain (Chapter 2), and 2) conduct a nemabiome study to determine the diversity and abundance of nematode species within Saskatchewan pastured beef cattle (Chapter 3). Seventeen cohorts of pastured yearling beef cattle were processed in the spring and fall of 2019. Animals were individually weighed, and rectal fecal samples obtained for pooled fecal egg count (FEC). A subset of calves (n = 25) in each herd was administered oral fenbendazole (Safeguard®, Merck, Canada) and a parenterally administered extended-release eprinomectin (LongRange®, Boehringer Ingelheim, Canada), while the remaining cohort was left untreated. Eggs per gram of feces (EPG) were determined in pooled fecal samples using the Modified Wisconsin Sugar Flotation Technique, and deep amplicon nemabiome sequencing of the ITS-2 DNA locus was used to describe nematode species diversity and abundance. Across all cattle (n = 867), there were differences between treatment and control groups regarding FEC (p < 0.01). In the generalized estimating equations (GEE) model, FEC decreased by 44 times over the grazing season, and FEC were 1.8 times greater on pastures located in black/gray soil versus dark brown soil zones. Areas with higher precipitation also had higher FEC. There was no significant difference (p = 0.41) in the ADG across all cattle, but differences were found in the ADG between treated and control cattle in five cohorts. Haemonchus placei was found in all spring cohorts, accounting for 30% of the L3 species composition. Hence, it was one of the dominant species together with Ostertagia ostertagi (40%) and Cooperia oncophora (26.2%). Ostertagia ostertagi (47.5%) and C. oncophora (42.0%) were the most common species recovered at the time of fall sampling. Haemonchus placei represented 5.2% of the species diversity at the time of fall sampling, which is higher than previously reported in western Canada. The lack of correlation between FEC and ADG is likely due to differences in farm-specific environmental conditions (rain, temperature), soil type and husbandry factors.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".