Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Ethylene-Vinyl Alcohol Films Containing Pure Components of Essential Oils
NAGIOS: RODERIC FUNCIONANDO

Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Ethylene-Vinyl Alcohol Films Containing Pure Components of Essential Oils

DSpace Repository

Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Ethylene-Vinyl Alcohol Films Containing Pure Components of Essential Oils

Show simple item record

dc.contributor.author Mateo Jiménez, Eva María
dc.contributor.author Gómez Pérez, José Vicente
dc.contributor.author Tarazona, Andrea
dc.contributor.author García-Esparza, María Á.
dc.contributor.author Mateo Jiménez, Fernando
dc.date.accessioned 2022-04-01T12:38:46Z
dc.date.available 2022-04-01T12:38:46Z
dc.date.issued 2021
dc.identifier.uri https://hdl.handle.net/10550/82126
dc.description.abstract The efficacy of ethylene-vinyl alcohol copolymer films (EVOH) incorporating the essential oil components cinnamaldehyde (CINHO), citral (CIT), isoeugenol (IEG), or linalool (LIN) to control growth rate (GR) and production of T-2 and HT-2 toxins by Fusarium sporotrichioides cultured on oat grains under different temperature (28, 20, and 15 °C) and water activity (aw) (0.99 and 0.96) regimes was assayed. GR in controls/treatments usually increased with increasing temperature, regardless of aw, but no significant differences concerning aw were found. Toxin production decreased with increasing temperature. The effectiveness of films to control fungal GR and toxin production was as follows: EVOH-CIT > EVOH-CINHO > EVOH-IEG > EVOH-LIN. With few exceptions, effective doses of EVOH-CIT, EVOH-CINHO, and EVOH-IEG films to reduce/inhibit GR by 50%, 90%, and 100% (ED50, ED90, and ED100) ranged from 515 to 3330 µg/culture in Petri dish (25 g oat grains) depending on film type, aw, and temperature. ED90 and ED100 of EVOH-LIN were >3330 µg/fungal culture. The potential of several machine learning (ML) methods to predict F. sporotrichioides GR and T-2 and HT-2 toxin production under the assayed conditions was comparatively analyzed. XGBoost and random forest attained the best performance, support vector machine and neural network ranked third or fourth depending on the output, while multiple linear regression proved to be the worst.
dc.language.iso eng
dc.relation.ispartof Toxins, 2021, vol. 13, num. 545, p. 1-24
dc.rights.uri info:eu-repo/semantics/openAccess
dc.source Mateo Jiménez, Eva María Gómez Pérez, José Vicente Tarazona, Andrea García-Esparza, María Á. Mateo Jiménez, Fernando 2021 Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Ethylene-Vinyl Alcohol Films Containing Pure Components of Essential Oils Toxins 13 545 1 24
dc.subject Microbiologia
dc.subject Microorganismes patògens
dc.title Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Ethylene-Vinyl Alcohol Films Containing Pure Components of Essential Oils
dc.type info:eu-repo/semantics/article
dc.date.updated 2022-04-01T12:38:46Z
dc.identifier.doi https://doi.org/10.3390/toxins13080545
dc.identifier.idgrec 151021

View       (4.635Mb)

This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search

Browse

Statistics