Survival of blackleg pathogen inoculum in canola stubble under simulated flooding conditions
Bibliographic record
Abstract
Blackleg of canola (Brassica napus), caused by two Leptosphaeria spp, is a significant \nconstraint to canola production worldwide except in china where only the less virulent L. \nbiglobosa has been reported. In China, the disease is caused by a less pathogenic species, \nL. biglobosa, and there is a concern that importing canola from Canada may introduce the \nvirulent L. maculans, impacting the crop there negatively. In China, canola (or rapeseed) \nproduction is centered in several eastern and central provinces where winter rapeseed is \noften followed by paddy rice that normally is flooded for weeks during late spring and \nsummer. L. maculans or L. biglobosa in diseased canola stubbles serves as the key \ninoculum source to cause blackleg, and it has been questioned if the flooding practice \nmay help suppress the inoculum. A study was initiated to determine the effect of flooding \ntemperature (12 to 40°C) and duration (2 to 12 weeks) on survival of blackleg pathogen \nin canola stubbles. Experiments were set up on a Thermogradient Plate that is capable of \nsimultaneously creating 96 independent temperature settings. Diseased stubbles with > \nscale-3 level of basal stem-canker symptoms used for the experiments were collected \nfrom a Westar canola plot in Melfort after 2011 harvest. Flooded stubbles were sampled \nevery two weeks, surface sterilized, and incubated on V8-juice medium amended with \nantibiotics for 10 days to observe pycnidia cultures of L. maculans or L. biglobosa as the \nevidence of pathogen survival. Two trials were set up in RCBD with four replications, \nand pathogen incidence data (based on 25 stubble pieces per replicated) were subject to \nANOVA. Significant reduction (P= 0.01) of pathogen incidence was observed at 2-week \nflooding treatment relative to control (non-flooded) and there was no pathogen recovery \nafter 4weeks of flooding till 12 weeks of experiment. Lower flooding temperatures of \n12oC and 16oC appeared to be slightly less effective than higher temperatures (20-40 oC) \nin reducing pathogen survival. Stubble tissues degraded sharply after 2weeks (contrast, \nP= 0.05) in response to the flooding temperature and the dry weight was reduced more \nsubstantially (40%) at higher temperatures. Virulence of any survived pathogen \npropagule after flooding is still intact and survival at any temperature or duration of \nflooding does not differentiate between L. maculans or L. biglobosa. High proportion of \nsurvived blackleg pathogen (pycnidia) from flooding were L. maculans (67%) and the \nrest L. biglobosa (33.0%) under Westar cotyledon test.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".