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Record W6957880458 · doi:10.60692/djw9r-9zv91

Chitosan as Source for Pesticide Formulations

2017· article· en· W6957880458 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsFungicidePhytophthora infestansPesticidePhytophthoraSolanaceaeNucleic acidAlternaria solaniChitinSpore

Abstract

fetched live from OpenAlex

Late blight and wilt caused by the oomycete, Phytophthora infestans, and the fungus, Fusarium solani f. sp. eumartii, respectively, are severe diseases in Solanaceae crops worldwide. Although traditional approaches to control plant diseases have mainly relied on toxic chemical compounds, current studies are focused to identify more sustainable options. Finding alternatives, a low molecular weight chitosan (LMWCh) obtained from biomass of Argentine Sea's crustaceans was assayed. In an attempt to characterize the action of LMWCh alone or in combination with the synthetic fungicide Mancozeb, the antimicrobial properties of LMWCh were assayed. In a side-by-side comparison with the SYTOX Green nucleic acid stain and the nitric oxide–specific probe, diaminofluorescein-FM diacetate (DAF-FM DA), yielded a similar tendency, revealing LMWCh-mediated cell death. The efficacy of LMWCh, Mancozeb, and the mixture LMWCh–Mancozeb was in turn tested. A synergistic effect in the reduction of F. eumartii spore germination was measured in the presence of subinhibitory dosis of 0.025 mg ml−1 LMWCh and 0.008 mg ml−1 Mancozeb. This mixture was efficient to increase the effectiveness of the single treatments in protecting against biotic stress judged by a drastic reduction of lesion area in P. infestans–inoculated tissues and activation of the potato defense responses.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.005

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 head0.034
GPT teacher head0.253
Teacher spread0.219 · 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 designBench or experimental
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

Citations0
Published2017
Admission routes1
Has abstractyes

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