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Detection of food freshness and pesticides through chemical interaction of liquids or gases with surfaces

Author(s): Edoardo Donà (Author), Aleksandra Lobnik (Supervisor), Uroš Cvelbar (Co-Supervisor)

Year: 2025

Type: Doctoral dissertation

Food, water, and sleep form the foundation of human needs, all of which are indispensable. However, unlike sleep, food and water have historically been beyond direct human control. Since ancient times, hunter-gatherers have migrated in search of these essential resources. The advent of agriculture marked a turning point, allowing humans …

Ecological modelling of the phytoplankton community in the northern Adriatic sea

Author(s): Ivano Vascotto (Author), Janja Francé (Supervisor)

Year: 2025

Type: Doctoral dissertation

This dissertation examines the ecological dynamics of phytoplankton communities in the northern Adriatic Sea, focusing on phenology, environmental drivers, and trophodynamics. The complexity of the region, characterized by the richness of phytoplankton communities, environmental variability and intensive human activities, is not seen as an obstacle but as an opportunity to …

Micro and nano plastic in agriculture: interactions with pesticide residues and bioaccumulation in plants

Author(s): Harshit Sahai (Author), María Dolores Hernando Guil (Supervisor), Amadeo R. Fernández-Alba (Co-Supervisor), Ester Heath (Co-Supervisor)

Year: 2024

Type: Doctoral dissertation

A large body of data now exists demonstrating the influence of micro and nano plastics (MNPs) on living systems, and their detection has been documented across various ecosystems, including organisms that form part of the human diet. Nevertheless, up till now, a substantial portion of that research has been confined …

Explainable machine learning techniques for applications in life sciences

Author(s): Martin Marzidovšek (Author), Vid Podpečan (Supervisor), Patricija Mozetič (Co-Supervisor)

Year: 2024

Type: Doctoral dissertation

As ecological, agricultural, and biological disciplines face mounting challenges like biodiversity loss, food chain disruption, and climate change, leveraging machine learning (ML) to process complex and heterogeneous data becomes increasingly vital. This dissertation explores the potential of ML in combination with explainability approaches for enhancing research in life sciences, specifically …

Tracing origin of food using stable isotopes of light and heavier elements

Author(s): Staša Hamzić Gregorčič (Author), Nives Ogrinc (Supervisor), Tea Zuliani (Co-Supervisor)

Year: 2024

Type: Doctoral dissertation

This dissertation examines two main topics. The first topic is focused on the potential of strontium (Sr) isotope analysis to characterise milk and truffles as selected food commodities, traditionally important for Slovenia. The 87Sr/86Sr ratio for determining the provenance of bovine milk and truffles originating from different regions of Slovenia …

Biotechnological production of insect sex pheromones and potato virus Y infectious clone as tools in plant protection

Author(s): Mojca Juteršek (Author), Špela Baebler (Supervisor)

Year: 2023

Type: Doctoral dissertation

Rising demands for food, instigated by population growth and urbanization, are calling for advanced agricultural approaches to increase crop yields. However, the expansion of food production should not come with an unmanageable environmental cost. Plant science is therefore challenged to provide sustainable innovations for combating the detrimental effects of unfavourable …

Licit and illicit drugs in waste- and environmental waters: epidemiological and environmental implications

Author(s): Taja Verovšek (Author), Ester Heath (Supervisor)

Year: 2023

Type: Doctoral dissertation

The analysis of drug residues in waste and environmental waters offers valuable insights into the epidemiological and environmental implications of drug use. This study employs a wastewater-based epidemiology (WBE) approach to estimate the use of licit and illicit drugs and new psychoactive substances (NPS) among both general and specific populations. …

Characterization of Spirulina microalgae as a new alternative food source

Author(s): Jasmina Masten Rutar (Author), Nives Ogrinc (Supervisor), Polona Jamnik (Co-Supervisor)

Year: 2023

Type: Doctoral dissertation

A reduction in agricultural productivity associated with water scarcity and land degradation, combined with the growing world population and malnutrition highlights the need for new alternative food sources. In this challenging field, Spirulina microalgae emerges as a promising candidate thanks to its high nutritional value and beneficial effect on human …

Use of information and communication technologies, data and knowledge to increase the impact of digital environments on food choice

Author(s): Eva Valenčič (Author), Barbara Koroušić Seljak (Supervisor), Tamara Bucher (Supervisor), Clare Elizabeth Collins (Co-Supervisor), Emma Beckett (Co-Supervisor)

Year: 2023

Type: Doctoral dissertation

Food and eating environments play a crucial role in shaping consumers' food choices. As food decision-making shifts more into the digital environment, it is essential to understand the impact of this setting on consumer's dietary behaviours. Online platforms and mobile apps provide great opportunities for the promotion of healthier food …

Exploiting domain knowledge in predictive learning from food and nutrition data

Author(s): Gordana Ispirova (Author), Barbara Koroušić Seljak (Supervisor), Tome Eftimov (Co-Supervisor)

Year: 2022

Type: Doctoral dissertation

Human knowledge about food and nutrition has evolved drastically with time. With food and nutrition-related data being mass produced and easily accessible, the next step is to use Artificial Intelligence (AI) to translate data into knowledge. The majority of AI research is model-driven, and classical Machine Learning (ML) pipelines concentrate …