Fertilizer Application Has No Effect on Large (<i>Digitaria sanguinalis</i>) or Smooth (<i>Digitaria ischaemum</i>) Crabgrass Germination and Emergence in Residential Turfgrass in a Northern Climate
Bibliographic record
Abstract
Given the importance of emergence level and timing to the competitiveness and success of annual crabgrass species in turfgrass, particularly in the context of increasing synthetic pesticide bans and the common cultural practice of fertilization, a study was conducted in a northern region of North America (Ontario, Canada) to determine the effect of fertilizer application on large and smooth crabgrass emergence in residential lawns. In petri dish experiments, we reconfirmed that KNO 3 has a significant positive effect on large and smooth crabgrass seed germination but we showed that there is only an effect on fresh seed and no effect on aged seed, suggesting that the treatment affects dormancy level and not germination per se. In two other experiments using turf cores and commercial lawn fertilizer in growth room conditions and in field trials at three sites, we confirmed this result showing that neither fall nor spring fertilizer application had any effect on the emergence level of either smooth or large crabgrass. These results have practical relevance to homeowners and turf managers in this region because they are dealing with crabgrass emerging in the spring from seed shed the previous fall. The results also show that fertilizer can be used to aid turf quality and competitiveness without impacting true infestation level (density) of crabgrass in the spring.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".