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Record W2112595893 · doi:10.1111/ppa.12036

Effect of flooding on the survival of <i> <scp>L</scp> eptosphaeria </i> spp. in canola stubble

2013· article· en· W2112595893 on OpenAlexafffund
Cecilia Peluola, W. G. Dilantha Fernando, C. Huvenaars, H. R. Kutcher, Rachid Lahlali, Gary Peng

Bibliographic record

VenuePlant Pathology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of SaskatchewanUniversity of ManitobaAgriculture and Agri-Food Canada
FundersCanola Council of Canada
KeywordsBlacklegCanolaBiologyLeptosphaeria maculansRapeseedFlooding (psychology)PathogenAgronomyBrassicaCropAnimal scienceHorticultureMicrobiology

Abstract

fetched live from OpenAlex

This study used a versatile temperature‐control device to assess the effect of temperature (12–40°C) and duration (2–12 weeks) of flooding on the survival of L eptosphaeria spp. in canola ( B rassica napus ) stubble. Canola basal stems with blackleg symptoms were submerged in water in small glass jars containing 20 cm 3 soil on a thermogradient plate capable of simultaneously maintaining up to 96 independent temperature regimes. Flooded stems were sampled at 2‐week intervals, surface‐sterilized, and incubated on V8‐juice agar for 10 days to recover the pathogen. Flooding for 2 weeks substantially reduced pathogen recovery relative to non‐flooded controls and the pathogen was not recovered after 6 weeks of flooding, irrespective of temperature. The pathogen was eliminated slightly more rapidly at flooding temperatures &gt;20°C than at 12–16°C. There was no difference between L eptosphaeria maculans and L . biglobosa in their ability to survive flooding. Stem tissues degraded most rapidly during the first 2 weeks of flooding, corresponding to a quick decline in pathogen survival during the same period. These results indicate that a paddy rice crop following winter rapeseed may minimize the impact of blackleg by eradicating the inoculum of L eptosphaeria spp. in stubble.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.214
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2013
Admission routes2
Has abstractyes

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