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Record W4399077816 · doi:10.1080/07060661.2024.2347933

Morphological and molecular characterization of <i>Neoerysiphe galeopsidis</i> causing powdery mildew on <i>Lagopsis supina</i> in central China

2024· article· en· W4399077816 on OpenAlexvenueno aff
Wanwan Zhang, Juncong Liu, Pengkun Cai, Xiao Duan, Zongbo Qiu, Zhengnan Li, Mo Zhu

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPowdery Mildew Fungal Diseases
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsPowdery mildewChinaBiologyBotanyGeographyArchaeology

Abstract

fetched live from OpenAlex

Lagopsis supina (Xia Zhi Cao) is a widely distributed and cultivated herbal plant that has been extensively used as a traditional Chinese medicine, Tibetan medicine and Mongolian medicine for disease treatments for centuries. While the bioactive compounds of L. supina are extensively studied, the fungal pathogens of this plant are still obscure. In 2021, powdery mildew signs and symptoms were observed on leaves of L. supina in Xinxiang City, Henan Province, China. However, the causal pathogen had not been identified. Therefore, morphological characteristics and molecular analysis was applied to identify the powdery mildew pathogen. The sequence of the internal transcribed spacer (ITS) region of the fungus was obtained and showed 99.83% identity with the previously reported Neoerysiphe galeopsidis. The virulence of this phytopathogen on L. supina was confirmed by utilizing Koch’s postulates. Therefore, we identified the causal pathogen as N. galeopsidis. Based on biological and molecular characterization, this is the first comprehensive report of powdery mildew caused by N. galeopsidis on L. supina in central China. The occurrence of powdery mildew disease on L. supina may detract from the plant’s medical and ornamental value. The identification and confirmation of N. galeopsidis on L. supina expands the knowledge of this causal agent and will support efforts towards future control and management of powdery mildews.

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 score0.285

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 head0.009
GPT teacher head0.187
Teacher spread0.178 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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