Molecular Investigation of Eimeria Species in Broiler Farms in the Province of Vojvodina, Serbia
Bibliographic record
Abstract
Coccidiosis is a significant poultry disease caused by the Eimeria species. This study aims to determine the prevalence of Eimeria spp. on broiler farms in Vojvodina, along with the identification of parasite species, and assess the implemented biosecurity measures. The study was conducted on 100 broiler chicken farms (28 small-sized; 34 medium-sized; 38 large-sized farms) from June 2018 to December 2021. One pooled sample of faeces was collected from three to six-week-old chickens from each farm, and assessment of biosecurity measures was carried out using a questionnaire. Using the PCR method, DNA of Eimeria was found in 59 samples (59%), while 41 samples (41%) were negative. Four species of Eimeria were identified, and their prevalence was the following: E. acervulina (37%), E. maxima (17%), E. mitis (25%) and E. tenella (48%). A significant difference (p < 0.05) was established in the number of oocysts in flocks from small-sized farms compared to medium-sized farms. It was found that regular implementation of disinfection, disinsection and deratisation measures, as well as all the biosecurity measures, can significantly reduce the occurrence of coccidiosis. These results will help to develop better strategies for the control and prevention of coccidiosis on farms.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".