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Record W4361853968 · doi:10.47371/mycosci.myc51421

<i>Botrytis sinoallii</i>: a new species of the grey mould pathogen on <i>Allium crops</i> in China

2010· article· en· W4361853968 on OpenAlexaff
Jing Zhang, Lei Zhang, Guoqing Li, L. Yang, Dàohóng Jiāng, Wen-Ying Zhuang, Hung‐Chang Huang

Bibliographic record

VenueMycoscience · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsAgriculture and Agri-Food Canada
FundersHuazhong Agricultural UniversityChinese Academy of SciencesInstitute of Microbiology, Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsBiologyAlliumBotrytisBotrytis cinereaBotanyBlightBulbPotato dextrose agarPhylogenetic treeHorticultureAgarBacteriaGene

Abstract

fetched live from OpenAlex

A study was conducted to identify Botrytis spp. isolated from bulb onion, green onions, garlic, and garlic chives grown in Hubei Province of China. Based on colony morphology and conidial characteristics, 367 strains of Botrytis spp. were identified as five distinct species, namely, B. cinerea, B. squamosa, B. porri, B. byssoidea, and an undescribed Botrytis species (Botrytis sp.), which accounted for 64.3, 29.9, 3.3, 0.3, and 2.2%, respectively. The previously undescribed species is herein described as a new species, B. sinoallii sp. nov., which is characterized by production of numerous small sclerotia on potato dextrose agar. Phylogenetic analysis using partial sequences of three nuclear genes (G3PDH, HSP60, and RPB2) showed that B. sinoallii forms a unique lineage, which is closely related to B. squamosa, a well-known species on Allium crops, but distantly related to the other species of Botrytis on Allium crops, including B. cinerea, B. porri, B. aclada, B. allii, B. byssoidea, B. globosa, and B. sphaerosperma. Results of inoculation tests showed that B. sinoallii is a newly identified agent that can cause leaf blight of green onion, garlic, and garlic chives. Potential impact of B. sinoallii on production of Allium crops in China is discussed.

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)0.001
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 score0.964
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.013
GPT teacher head0.205
Teacher spread0.193 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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