Spatial patterns of viable spore deposition of the corn ear rot pathogen, <i>Gibberella zeae</i> , in first-year corn fields
Bibliographic record
Abstract
We assessed the spatial patterns of viable spore deposition of Gibberella zeae in two years (2003 and 2004) within corn fields lacking corn or cereal debris at Aurora, New York, USA. Viable airborne spores of G. zeae were collected inside corn canopies at the levels of silks and tassels on Petri plates containing a selective medium. Spores were sampled over 27 day and night sample periods spanning silk emergence through blister stages of corn in both years. In 2003, spore sampling started at sunset on 29 July and ended at sunrise on 5 August. In 2004, sampling started at sunset on 5 August and ended at sunset on 12 August. There were 12 equidistant sample locations in 2003 covering an area of about 1400 m2 and 16 equidistant sample locations in 2004 covering an area of nearly 2100 m2. Contour plots of spore counts over entire fields revealed unique spatial patterns of spore deposition for each period. Spatial analysis by distance indices and Mantel tests were used to classify spore deposition patterns at both the silk and tassel levels during individual sample periods. The majority (92%) of the spore deposition patterns at both the silk and tassel sample levels was random; a smaller percentage (8%) was aggregated. All of the aggregated patterns were observed at night during major spore deposition events (>50 spores, on average, per plate). Spore deposition at the silk and tassel levels was spatially associated during two of the sample periods; both of these occurred during the night. In 2003, the spatial patterns for cumulative spore deposition at the silk and tassel sample levels became aggregated over time; in 2004, the patterns remained random over time. Contour maps of cumulative spore deposition could be compared with maps of disease incidence of gibberella ear rot to gain insights into the timing of infection.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".