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Record W4387090850 · doi:10.1038/s41467-023-41321-7

A global-temporal analysis on Phytophthora sojae resistance-gene efficacy

2023· review· en· W4387090850 on OpenAlexaffabout
Austin G. McCoy, Richard R. Bélanger, Carl A. Bradley, Daniel G. Cerritos-Garcia, Vinicius C. Garnica, Loren J. Giesler, Pablo E. Grijalba, Eduardo Guillín, María Antonia Henríquez, Yong Min Kim, Dean K. Malvick, Rashelle L. Matthiesen, Santiago X. Mideros, Zachary A. Noel, Alison E. Robertson, Mitchell G. Roth, Clarice Schmidt, Damon L. Smith, Adam Sparks, Darcy E. P. Telenko, Vanessa Tremblay, Owen Wally, Martin I. Chilvers

Bibliographic record

VenueNature Communications · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsAgriculture and Agri-Food CanadaUniversité Laval
FundersNational Institute of Food and AgricultureUnited Soybean BoardU.S. Department of Agriculture
KeywordsPhytophthora sojaeOomycetePhytophthoraBiologyBiotechnologyPlant disease resistanceOutbreakDisease managementDiseaseResistance (ecology)GeneGeneticsBotanyAgronomyMEDLINEMedicineVirology

Abstract

fetched live from OpenAlex

Plant disease resistance genes are widely used in agriculture to reduce disease outbreaks and epidemics and ensure global food security. In soybean, Rps (Resistance to Phytophthora sojae) genes are used to manage Phytophthora sojae, a major oomycete pathogen that causes Phytophthora stem and root rot (PRR) worldwide. This study aims to identify temporal changes in P. sojae pathotype complexity, diversity, and Rps gene efficacy. Pathotype data was collected from 5121 isolates of P. sojae, derived from 29 surveys conducted between 1990 and 2019 across the United States, Argentina, Canada, and China. This systematic review shows a loss of efficacy of specific Rps genes utilized for disease management and a significant increase in the pathotype diversity of isolates over time. This study finds that the most widely deployed Rps genes used to manage PRR globally, Rps1a, Rps1c and Rps1k, are no longer effective for PRR management in the United States, Argentina, and Canada. This systematic review emphasizes the need to widely introduce new sources of resistance to P. sojae, such as Rps3a, Rps6, or Rps11, into commercial cultivars to effectively manage PRR going forward.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.006
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0010.001
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 head0.081
GPT teacher head0.354
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations30
Published2023
Admission routes2
Has abstractyes

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