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Record W4390974713 · doi:10.3390/plants13020292

Salicylic and Jasmonic Acid Synergism during Black Knot Disease Progression in Plums

2024· article· en· W4390974713 on OpenAlexafffund
Ranjeet Shinde, Murali‐Mohan Ayyanath, Mukund R. Shukla, Walid El Kayal, Praveen K. Saxena, Jayasankar Subramanian

Bibliographic record

VenuePlants · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsJasmonic acidSalicylic acidBiologyBotanyPrunusGibberellic acidPrunus salicinaBiochemistry

Abstract

fetched live from OpenAlex

Black knot (BK) is a deadly disease of European (Prunus domestica) and Japanese (Prunus salicina) plums caused by the hemibiotrophic fungus Apiosporina morbosa. Generally, phytopathogens hamper the balance of primary defense phytohormones, such as salicylic acid (SA)–jasmonic acid (JA) balance, for disease progression. Thus, we quantified the important phytohormone titers in tissues of susceptible and resistant genotypes belonging to European and Japanese plums at five different time points. Our previous results suggested that auxin-cytokinins interplay driven by A. morbosa appeared to be vital in disease progression by hampering the plant defense system. Here, we further show that such hampering of disease progression is likely mediated by perturbance in SA, JA, and, to some extent, gibberellic acid. The results further indicate that SA and JA in plant defense are not always necessarily antagonistic as most of the studies suggest but can be different, especially in woody perennials. Together, our results suggest that the changes in phytohormone levels, especially in terms of SA and JA content due to BK infection and progression in plums, could be used as phytohormonal markers in the identification of BK-resistant cultivars.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.131

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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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 designObservational
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

Citations9
Published2024
Admission routes2
Has abstractyes

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