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Record W4409725568 · doi:10.1016/j.eti.2025.104222

Electrifying greenhouse agriculture: Cold atmospheric pressure plasma technology for Pythium ultimum control

2025· article· en· W4409725568 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Technology & Innovation · 2025
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsHydro-QuébecInstitut de Recherche et de Développement en AgroenvironnementPolytechnique Montréal
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundInstitut TransMedTechMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsPythium ultimumAtmospheric pressureGreenhouseAgricultureAtmospheric-pressure plasmaPythiumEnvironmental scienceAgronomyPlasmaPhysicsMeteorologyBiologyEcologyNuclear physics

Abstract

fetched live from OpenAlex

Hydroponic growth of food plants in greenhouses is of rapidly increasing importance to assure future autonomy of food supply, especially in harsher climate zones. Greenhouse culture yields are drastically reduced by pathogenic microorganisms that cause root rot in plants. In Canada, the fungus Pythium ultimum, which can survive harsh winter conditions, has a particularly large impact on food production. In this work, we present cold physical plasma treatment of liquids with a gliding arc plasma as a novel approach for combating pythium growth in liquid media. This study is based on exploring air or other N 2 + O 2 mixtures as a parameter to identify which plasma treatment is best suited for its anti-fungal activity in different media. If sourced from renewable energy and water, the proposed treatment is intrinsically sustainable. 3 media conditions are explored: first distilled water, to identify the production of highly reactive oxygen species (ROS) and reactive nitrogen species (RNS). Second, an inoculated distilled water is used in conjunction with an ELISA assay as a quick response indicator. Third, a Sabouroud 2 % dextrose broth, is used as a culture media in which oomycetes are grown subsequent to plasma treatment, and hyphal mass is compared between untreated and treated samples. Extracting a subset of 80+ chemical reactions from the available literature and databases, a reaction scheme is proposed accounting for liquid-vapor equilibria (through Henry’s coefficients) and reaction rate analysis. The most promising plasma treatment condition was found to be using a 95 % N 2 : 5 % O 2 gas mixture with a treatment time of 30 min, reducing hyphal mass growth from 1.8 g to 0.4 g over 1 week in Sabouroud broth. The pythium degradation process was observed through scanning electron microscopy (SEM) analysis, showing that Sporangium or oogonia containing structures that terminate the pythium’s hyphae have been broken and significantly reduced after plasma treatment. • Inactivation of Pythium ultimum by cold plasma technology for the first time in industry relevant medium. • First mechanistic study on inactivation of oomycetes. • Optimization of reactivity and antifungal activity of plasma by gas composition control.

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)0.000
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 score0.157
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.004
GPT teacher head0.226
Teacher spread0.222 · 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