Effects of Crop Management Practices on Current-Season Spread of <i>Potato virus Y</i>
Bibliographic record
Abstract
The current-season spread of Potato virus Y (PVY) was monitored in 19 fields under various management practices in New Brunswick, Canada, through the 2011 and 2012 growing seasons. The focus of this study was to evaluate the role of seedborne PVY inoculum, aphid vector abundance, and the numbers, timing, and types of insecticide and mineral oil sprays, and to confirm the reliability and forecasting capacity of midseason PVY testing. In each field, 100 to 110 virus-free plants were identified shortly after emergence and were assessed four times from early July to early September (after top-kill) with enzyme-linked immunosorbent assay (ELISA) and reverse-transcription polymerase chain reaction (RT-PCR) to track PVY spread. In addition, tubers harvested during development in August and after top-kill were grown-out in the greenhouse for ELISA testing. PVY spread to selected virus-free plants varied widely, ranging from 0 to 76.2% across all studied fields. Of the 19 fields over two seasons, 10 fields were planted with no detectable seedborne PVY, and they showed 0 to 8.7% (mean 2.9%) PVY spread by harvest. The remaining nine study fields with 0.9 to 5.8% seedborne PVY showed 1 to 76.2% (mean 15.2%) PVY spread by harvest. PVY spread was detected in most fields during midseason testing with ELISA and RT-PCR; all tests correlated well with final PVY rates after top-kill, though RT-PCR detection in developing tubers was most sensitive and correlated. Logistic regression modeling was used to identify major factors in PVY spread, including seedborne PVY, early-season aphid abundance, and the numbers of insecticide and mineral oil sprays. The best-fitting model, constructed using these factors as well as a measurement of July PVY incidence (ELISA July ), strongly explained PVY spread by harvest, with the most significant management factor being the number of mineral oil sprays supplemented with insecticide used during the growing season. A similar model fitted without the ELISA July did not adequately predict ultimate PVY spread. The analysis suggests that mineral oil alone was effective at lowering PVY spread, and more effective when combined with insecticide, particularly when used early in the season. No evidence was found for differences in PVY spread across the eight cultivars used or across the range of mineral oil application rates, whereas some evidence was found for differences in the effectiveness of different insecticide types.
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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 | 0.000 | 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 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".