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Record W41532356 · doi:10.31083/ph.2012.1144

Development of a difenoconazole/propiconazole microemulsion and its antifungal activities against Rhizoctonia solani AG1-IA

2012· article· en· W41532356 on OpenAlexaff
Pengfei Leng, Zhiming Zhang, Qian Li, Yunsong Zhang, Maojun Zhao, Guangtang Pan

Bibliographic record

Venue˜Die œPharmazie · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsPropiconazoleMicroemulsionChemistryChromatographyNuclear chemistryFungicidePulmonary surfactantBiochemistryAgronomyBiology

Abstract

fetched live from OpenAlex

According to its physical and chemical properties, the composition of difenoconazole/propiconazole microemulsion was as follows: xylene as solvent, emulsifier HSH as surfactant and methanol as cosurfactant. The optimal formulation of difenoconazole/propiconazole microemulsion was oil/SAA/water = 1/2/5 (w/w), in which the SAA consisted of emulsifier HSH and methanol with ratio of 3/2 (w/w). The cloud point of difenoconazole/propiconazole microemulsion was 70 degrees C and its effective ingredient content was 2.5% measured by High Performance Liquid Chromatography (HPLC). Its heat storage stability was studied according to the standards. The decomposition rates of the difenoconazole/propiconazole microemulsion were merely 2.45%, 2.63% respectively and met the Food and Agriculture Organization (FAO) standards of pesticide microemulsion. Investigated by Transmission Electron Microscopy (TEM) the particle size of difenoconazole/propiconazole microemulsion was 90-140 nm and its antifungal activities against Rhizoctonia solani AG1-IA were tested and compared with that of Meiyu. We found that the inhibition rates in the difenoconazole/propiconazole microemulsion treatment group were significantly higher than that of the emulsion group with the same content of effective ingredients and the study also revealed that its inhibiting ability on the formation and germination of sclerotia was significant.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.246
Teacher spread0.224 · 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 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

Citations7
Published2012
Admission routes1
Has abstractyes

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