6533b873fe1ef96bd12d4f55

RESEARCH PRODUCT

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

Fernando MateoEva M. MateoJosé V. GómezAndrea TarazonaMaría ÁNgeles García-esparza

subject

<i>Fusarium sporotrichioides</i>Water activityHealth Toxicology and MutagenesisToxins.MicrobiologiaHT-2 toxinToxicologyMachine learningcomputer.software_genreCitralfungal growthCinnamaldehydelaw.inventionchemistry.chemical_compoundBiofilms.LinaloolAprendizaje automático (Inteligencia artificial)lawpredictive microbiologyT-2 toxinMicroorganismes patògensPolímeros.Machine learning.ethylene-vinyl alcohol copolymersEssential oilEssences and essential oils.biologyPolymers.business.industryPetri dishRbiology.organism_classificationFusarium sporotrichioidesEsencias.IsoeugenolBiofilmes.essential oil pure componentsmachine learningchemistryMedicineArtificial intelligencebusinesscomputerToxinas y antitoxinas.

description

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 &gt

yearjournalcountryeditionlanguage
2021-08-05Toxins
10.3390/toxins13080545https://www.mdpi.com/2072-6651/13/8/545