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Record W4323661040 · doi:10.5772/intechopen.110306

<i>Pyrenophora tritici-repentis</i>: A Worldwide Threat to Wheat

2023· book-chapter· en· W4323661040 on OpenAlexaff
H. R. Kutcher, Leandro José Dallagnol

Bibliographic record

VenueIntechOpen eBooks · 2023
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Saskatchewan
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPyrenophoraPathosystemBiologyAgronomyFungicideLeaf spotCultivarPopulationBiotechnologyHorticultureInoculationEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

The necrotrophic fungus Pyrenophora tritici-repentis is the causal agent of tan spot of wheat, also known as yellow spot. Tan spot is one of the main foliar diseases of wheat, responsible for significant yield loss worldwide. To improve tan spot management, genetic control has been investigated and resistance in some cultivars improved; however, the complexity of the pathosystem wheat - P. tritici-repentis makes integrated disease management strategies very important. In this chapter, we provide an overview of the current state of knowledge of tan spot, including a basic understanding of characterization, pathogenicity, population biology, the global distribution of races, and the genetics of the wheat - P. tritici-repentis interaction. Furthermore, we describe several strategies that can be employed to control tan spot including, seed sanitation, cultural practices, fungicide and biological controls, as well as complementary alternative measures such as fertilization for efficient disease management in wheat production systems.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.009

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 head0.036
GPT teacher head0.240
Teacher spread0.204 · 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 designNot applicable
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

Citations6
Published2023
Admission routes1
Has abstractyes

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