Spatiotemporal variation in airborne sporangia of <i> <scp>P</scp> hytophthora infestans </i> : characterization and initiatives towards improving potato late blight risk estimation
Bibliographic record
Abstract
This study investigated the value of using real‐time monitoring of P hytophthora infestans airborne inoculum as a complement to decision support systems ( DSS ). The experiment was conducted during the 2010, 2011 and 2012 potato production seasons in two locations in New Brunswick, Canada. Airborne sporangia concentrations ( ASC ) of P . infestans were monitored using 16 rotating‐arm spore samplers placed 3 m above the ground. The first cases of late blight (2010 and 2011) were detected 6–7 days after the first ASC peak, and all samplers captured their first sporangia within the same week (at 3‐ and 9‐day periods). The cumulative ASC curve and the risk curves from two DSS ( PLANT ‐Plus and Pameseb Late Blight) had the same shape but different magnitudes. In both locations, the negative binomial distribution fitted the data better than the Poisson distribution, which is indicative of heterogeneity, and based on T aylor's power law, the heterogeneity increased with increasing ASC . Therefore, the present results suggest that spore‐sampling network devices may be a suitable approach for early detection of incoming inoculum and, when combined with DSS , represent a potential aid for targeting the optimal time to apply a disease‐control product. In this context, cumulative ASC can be a counterweight to the DSS risk estimate: a high risk combined with significant ASC will trigger fungicide spraying. Moreover, spore sampling can be used to assess the efficiency of management strategies by means of examining the area under the inoculum progress curve.
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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 | 0.001 | 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".