Magliulo, Raffaele (2026) Exploiting fermented foods microbiome to improve food quality and human health. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Exploiting fermented foods microbiome to improve food quality and human health
Autori:
Autore
Email
Magliulo, Raffaele
raffae.magliulo@gmail.com
Data: 3 Febbraio 2026
Numero di pagine: 160
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Agraria
Dottorato: Food Science
Ciclo di dottorato: 38
Coordinatore del Corso di dottorato:
nome
email
Barone, Amalia
ambarone@unina.it
Tutor:
nome
email
De Filippis, Francesca
[non definito]
Data: 3 Febbraio 2026
Numero di pagine: 160
Parole chiave: Fermented foods, microbiome, terroir, health benefits
Settori scientifico-disciplinari del MIUR: Area 07 - Scienze agrarie e veterinarie > AGR/16 - Microbiologia agraria
Informazioni aggiuntive: Versione NON secretata della tesi. Ciclo 38.
Depositato il: 17 Feb 2026 10:53
Ultima modifica: 12 Ago 2026 05:37
URI: https://www.fedoa.unina.it/id/eprint/16192

Abstract

Fermented foods are among the oldest biotechnologies used by humans, yet only recently we have started to examine them with the tools of contemporary microbiome science, multiomics, and artificial intelligence. This thesis sits at the intersection of food microbiology, bioinformatics, and data science. Its overarching aim is to characterise the microbiomes of fermented foods in a systematic, genome-resolved way, and to explore how these communities contribute to food quality, safety, and potential health-relevant functions. The work focuses primarily on traditional cheeses and kombucha, using shotgun metagenomics, complementary ‘omics, and explainable machine learning to move from descriptive catalogues of microbes towards predictive insights. The thesis is organised into five main chapters, followed by a general discussion that integrates the findings and outlines future directions. Each chapter builds on the previous ones, moving from a broad conceptual framework to detailed case studies, then to large-scale resources and finally to a potential model system for precision fermentation.

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