EFFECTS OF PRE-PLANTING INCORPORATION OR POST-PLANTING TOP-DRESSING OF ORGANIC AMENDMENTS ON BERMUDAGRASS FOR TOLERANCE TO BELONOLAIMUS LONGICAUDATUS
Bibliographic record
Abstract
The addition of organic amendments can improve several aspects of the soil environment, thereby improving tolerance to plant-parasitic nematodes and, in some cases, suppressing plant-parasitic nematodes. Two organic amendments commonly used in golf and sports turf in the United States are locally produced composts and Canadian sphagnum peat moss (CSPM). Two field trials were conducted to evaluate the impacts of these organic amendments on turf health and suppression of sting nematode, Belonolaimus longicaudatus, on bermudagrass athletic turf. One trial evaluated the effects of pre-planting incorporation of either compost or CSPM with soil to create a 20:80 amendment:soil mixture in the turf root zone. Another trial evaluated two kinds of compost blended with sand top-dressed onto the surface of established turf. Both trials evaluated effects on population density of B. longicaudatus, and on turf percent green cover. Pre-planting incorporation of organic amendments suppressed B. longicaudatus but top-dressing did not. Addition of composts by either pre-planting incorporation or blending with top-dressing improved turf percent green cover and, therefore, enhanced tolerance to B. longicaudatus.
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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 | 0.001 |
| 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) | 0.002 | 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".