Application of grain baits to control common vole Microtus arvalis (Pallas, 1778) in alfalfa crops, Serbia
Bibliographic record
Abstract
In order to compare the efficacies of conventional (cholecalciferol and bromadiolone) and new (sodium selenite) rodenticides, applied in the grain bait formulation on the whole-grain of wheat (Triticum aestivum) and triticale (Triticasecale) in alfalfa crops, experiments were conducted at two sites near Belgrade, Serbia, in the spring of 2009, using a standard EPPO method. The presence of rodent populations, their spatial distribution and density indices were evaluated by pretreatment census and rodenticide efficacy by counting active holes, 14 and 28 days after treatment. The average Microtus arvalis numbers of 158/ha and 184/ha were found to cause 7.4% and 9.6% alfalfa green biomass yield decreases, respectively. Twenty-eight days after treatment, the average efficacy of grain bait formulation (on wheat and triticale grains) of sodium selenite and cholecalciferol was 81%, while bromadiolone which had a higher efficiency, 85%, in the control of the common vole in alfalfa crops. The analysis of variance (ANOVA) showed that the origin of active substances, bases and associated interactions a.s x based on the efficacy-investigated grain baits did not have a statistically significant impact on the expression efficiency of the tested baits. Triticale grains can be used as carriers of active substances, sodium selenite, cholecalciferol or bromadiolone in preparation baits. Control of M. arvalis with the new rodenticide, sodium selenite, gave efficacy results about equal to that of cholecalciferol and bromadiolone and, therefore, provided a possible alternative rodenticide for vole control in alfalfa.
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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 | 0.000 |
| 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 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".