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Record W2338360909 · doi:10.4172/2157-7471.1000339

Inhibition of Penicillium digitatum and Citrus Green Mold by Volatile Compounds Produced by Enterobacter cloacae

2016· article· en· W2338360909 on OpenAlexfundno aff
Po-Sung Chen, Yu-Hsiang Peng

Bibliographic record

VenueJournal of Plant Pathology & Microbiology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaNational Science Council
KeywordsEnterobacter cloacaePenicillium digitatumBiologyMoldEnterobacterBlue moldMicrobiologyPenicilliumBotanyHorticultureEnterobacteriaceaeCitrus fruitBiochemistryEscherichia coliGene

Abstract

fetched live from OpenAlex

Penicillium digitatum causes green mold decay on citrus fruit, resulting in severe economic losses to citrus growers and packers worldwide. The present study is to evaluate the control of citrus green mold by volatiles produced by Enterobacter cloacae. An E. cloacae strain isolated from plant rhizospheres was able to produce three volatile organic compounds, which were identified as butyl acetate, phenylethyl alcohol, and 4,5-dimethyl-1-hexene by GC/MS chromatography. The volatile compounds produced by E. cloacae inhibited conidial germination and hyphal elongation of P. digitatum and reduced green mold severity. E. cloacae cultured at temperatures ranging from 16C to 28C, at pH values 6, or in a substrate carrier (sphagnum moss, vermiculite, or perlite) provided superior control against P. digitatum. A laboratory formulation using E. cloacae and perlite protected citrus fruit from green mold up to 22 days and its effectiveness outperformed fungicide application at room temperature (~25C). The results implicate practical application of E. cloacae as a biofumigant for controlling citrus postharvest decay caused by P. digitatum. Significantly, the study provides a model for future research on how to formulate an effective biocontrol agent for disease management.

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 score0.016
Threshold uncertainty score0.551

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 head0.005
GPT teacher head0.188
Teacher spread0.184 · 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

Citations22
Published2016
Admission routes1
Has abstractyes

Explore more

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