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Record W3028678080 · doi:10.1094/pdis-02-20-0262-re

Influence of Leaf Wetness Duration and Temperature on Infection of Grape Leaves by <i>Elsinoë ampelina</i> under Controlled and Vineyard Conditions

2020· article· en· W3028678080 on OpenAlexafffund
Odile Carisse, A. Levasseur, Caroline Provost

Bibliographic record

VenuePlant Disease · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsSonaca (Canada)Agriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsLeaf wetnessVineyardBiologyHorticultureConidiumFungicideInoculationAgronomyBotany

Abstract

fetched live from OpenAlex

On susceptible varieties, indirect damage to vines infected by Elsinoë ampelina range from reduced vigor to complete defoliation while, on berries, damage ranges from reduced quality to complete yield loss. Limited knowledge about the relationship between weather conditions and infection makes anthracnose management difficult and favors routine application of fungicides. The influence of leaf wetness duration and temperature on infection of grape leaves by E. ampelina was studied under both controlled and vineyard conditions. For the controlled conditions experiments, the five youngest leaves of potted vines (Vidal) were inoculated with a conidia suspension and exposed to combinations of six leaf wetness durations (from 0 to 24 h) and six constant temperatures (from 5 to 30°C). A week after each preset infection period, the percent leaf area diseased (PLAD) was assessed. At 5°C, regardless of the leaf wetness duration, no disease developed. At 10 and at 15 to 30°C, the minimum leaf wetness durations were 4 and 6 h, respectively. Above the minimum wetness duration, at temperatures from 10 to 30°C, PLAD increased linearly, with increasing leaf wetness up to 12 h, and then at a lower rate from 12 to 24 h. The optimal temperature for infection was 25°C. Relative infection was modeled as a function of both temperature and wetness duration using a Richards model (R 2 = 0.93). The predictive capacity of the model was evaluated with data collected in experimental vineyard plots exposed to natural wetness durations or artificial wetness durations created using sprinklers. In total, 264 vineyard infection events were used to validate the controlled experiments model. There was a linear relationship between the risk of infection estimated with the model and the observed severity of anthracnose (R 2 = 90); however, the model underestimated disease severity. A risk chart was constructed using the model corrected for vineyard observations and three levels of risk, with light, moderate, and severe risks corresponding to ≤5, &gt;5% to ≤25, and &gt;25% leaf area diseased, respectively. Overall, 93.9% of 132 independent observations were correctly classified, with 100, 29.4, and 9.4% of the light, moderate, and severe risks, respectively.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.158

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 head0.016
GPT teacher head0.239
Teacher spread0.224 · 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

Citations15
Published2020
Admission routes2
Has abstractyes

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