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Record W4406155984 · doi:10.1111/nph.20351

An emerging fungal disease is spreading across the globe and affecting the blueberry industry

2025· article· en· W4406155984 on OpenAlexaff
Michael Bradshaw, Kelly Ivors, Janet C. Broome, Ignazio Carbone, Uwe Braun, Shirley Yang, Brooke Warres, W.O. Cline, Swarnalatha Moparthi, Alejandro K. Llanos, W. Apaza, Miao Liu, Julie Carey, Mehdi El Ghazouani, R. T. L Carvalho, Marianne Elliott, David E. Boufford, Johann de Wet, James K. Mitchell, Luis Quijada, Jamjan Meeboon, Susumu Takamatsu, Uma Crouch, Scott LaGreca, Donald H. Pfister

Bibliographic record

VenueNew Phytologist · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPowdery Mildew Fungal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
FundersNovo Nordisk FondenNovo NordiskNational Science Foundation
KeywordsPowdery mildewHerbariumBiologyIdentification (biology)OutbreakChinaGeographyAgroforestryBotany

Abstract

fetched live from OpenAlex

Powdery mildew is an economically important disease caused by c. 1000 different fungal species. Erysiphe vaccinii is an emerging powdery mildew species that is impacting the blueberry industry. Once confined to North America, E. vaccinii is now spreading rapidly across major blueberry-growing regions, including China, Morocco, Mexico, and the USA, threatening millions in losses. This study documents its recent global spread by analyzing both herbarium specimens, some over 150-yr-old, and fresh samples collected world-wide. Our findings were integrated into a 'living phylogeny' via T-BAS to simplify pathogen identification and enable rapid responses to new outbreaks. We identified 50 haplotypes, two primary introductions world-wide, and revealed a shift from a generalist to a specialist pathogen. This research provides insights into the complexities of host specialization and highlights the need to address this emerging global threat to blueberry production.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.304
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2025
Admission routes1
Has abstractyes

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