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Record W7134931495 · doi:10.5376/me.2024.15.0029

Research on Insect Resistance Mechanisms in Loquat and Their Application in Pest Management

2024· article· W7134931495 on OpenAlex
Yiwei Li, Xianquan Qin, Liyu Liang, Jin Wang, Xi Wang, Hongli Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMolecular Entomology · 2024
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrated pest managementResistance (ecology)PEST analysisInsect pestInsectPest control

Abstract

fetched live from OpenAlex

Loquat ( Eriobotrya japonica ) is a valuable fruit crop with increasing global cultivation, but it faces significant challenges from pest infestations, which threaten yield and fruit quality. Enhancing insect resistance in loquat is crucial for sustainable crop protection. This study explores the mechanisms of insect resistance in loquat, focusing on plant structural defenses, phytochemical production, and genetic resistance mechanisms. Advances in molecular research, including the identification of resistance genes and breeding strategies, are also discussed. Integrated pest management (IPM) approaches that incorporate insect-resistant varieties are examined, with a case study demonstrating the effectiveness of these strategies in real-world loquat production. This study highlights the importance of developing insect-resistant loquat varieties as a sustainable solution to pest management challenges and outlines future directions for genetic enhancement and global application.

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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.044
GPT teacher head0.302
Teacher spread0.258 · 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