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Record W4417225941 · doi:10.1080/07060661.2025.2522459

The genetic basis of late blight resistance in potato: a comprehensive overview

2025· article· en· W4417225941 on OpenAlexafffundvenue
George Tarabain, Hannele Lindqvist‐Kreuze, Valérie Gravel, Martina V. Strömvik

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesAgriculture and Agri-Food Canada
KeywordsBlightResistance (ecology)Plant disease resistanceComponent (thermodynamics)Genome

Abstract

fetched live from OpenAlex

Potato late blight, caused by the oomycete Phytophthora infestans (Mont.) de Bary, is a global problem causing economic losses and threatening food security. Fungicide application is the traditional control method, though it is costly and harmful to the environment, and P. infestans rapidly develop fungicide resistance. Thus, breeding resistant potato varieties remain the most sustainable approach to disease management. Resistance (R) genes derived from wild Solanum species have been widely used in breeding programs, though P. infestans frequently overcomes single-gene resistance through effector evolution. While significant progress has been made in identifying resistance determinants, the molecular and evolutionary dynamics governing potato-P. infestans interactions are yet to be fully understood, limiting efforts to achieve durably resistant varieties. Recent studies aided by increasing amounts of genomics data have uncovered novel immune components, such as the PERU receptor and epidermal chloroplast immune components, offering new insights into plant immunity and potential disease management. This review summarizes the genetic factors contributing to late blight resistance in potatoes and the innovative breeding strategies to meet the challenges of this persistent agricultural disease.

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 score0.748
Threshold uncertainty score0.668

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 head0.206
Teacher spread0.191 · 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
Published2025
Admission routes3
Has abstractyes

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