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Record W3197044114 · doi:10.3389/fnut.2021.703293

Wheat–Fusarium graminearum Interactions Under Sitobion avenae Influence: From Nutrients and Hormone Signals

2021· review· en· W3197044114 on OpenAlexaff
Kun Luo, Thérèse Ouellet, Huiyan Zhao, Xiukang Wang, Zhensheng Kang

Bibliographic record

VenueFrontiers in Nutrition · 2021
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersNatural Science Basic Research Program of Shaanxi ProvinceChina Postdoctoral Science Foundation
KeywordsSitobion avenaeBiologyFusariumAgronomyMycotoxinEpichloëHeterodera avenaePEST analysisBotanyEcologySymbiosisNematodeHomopteraGenetics

Abstract

fetched live from OpenAlex

The English grain aphid Sitobion avenae and phytopathogen Fusarium graminearum are wheat spike colonizers. “Synergistic” effects of the coexistence of S. avenae and F. graminearum on the wheat spikes have been shown in agroecosystems. To develop genetic resistance in diverse wheat cultivars, an important question is how to discover wheat– F. graminearum interactions under S. avenae influence. In recent decades, extensive studies have typically focused on the unraveling of more details on the relationship between wheat-aphids and wheat-pathogens that has greatly contributed to the understanding of these tripartite interactions at the ecological level. Based on the scientific production available, the working hypotheses were synthesized from the aspects of environmental nutrients, auxin production, hormone signals, and their potential roles related to the tripartite interaction S. avenae –wheat– F. graminearum . In addition, this review highlights the relevance of preexposure to the herbivore S. avenae to trigger the accumulation of mycotoxins, which stimulates the infection process of F. graminearum and epidemic of Fusarium head blight (FHB) in the agroecosystems.

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 score0.967
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.268
Teacher spread0.240 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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