Carlos Marques
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Recent Grants
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Recycling of plastics to manufacture optical fibers for microplastics and water quality monitoring systems
Open Date: 2023-01-01
Close Date: 2025-01-01
Grant: Close
Rehabilitation strategies based on cloud robotics, virtual reality and smart textiles
Open Date: 2022-03-01
Close Date: 2025-03-01
Grant: Close
DigiAqua: Digitizing Aquaculture: from predictive analytics to intelligent photonics platform
Open Date: 2022-01-01
Close Date: 2024-12-01
Grant: Close
InstaBat - Innovative physical/virtual sensor platform for battery cell
Open Date: 2020-09-01
Close Date: 2023-08-01
Grant: Close
POSPORI Project - Individual Fellowships MSCA-IF-2018
Open Date: 2019-04-01
Close Date:
Articles (11)
Year:
2024
Year:
2023
Year:
2023
Cortisol monitoring in the agri-food sector is considered a valuable tool due to its direct correlation with growth, reproduction, the immune system, and overall animal welfare. Strategies to monitor this stress hormone and its correlation to food quality and security have been studied in fish farming and the livestock industry. This review discusses studies on monitoring cortisol in the food industry for the first time. The impact of cortisol on animal production, quality, and the security of food products, and the analytical procedures commonly implemented for sample pre-concentration and quantification by liquid chromatography coupled to mass spectrometry, are reviewed and discussed according to the results published in the period 2012–2022. Aquaculture, or fish farming, is the leading agri-food sector, where cortisol’s impact and usefulness are better known than in livestock. The determination of cortisol in fish not only allows for an increase in the production rate, but also the ability to monitor the water quality, enhancing the sustainable development of this industry. In cattle, further studies are needed since it has mainly been used to detect the administration of illicit substances. Current analytical control and monitoring techniques are expensive and often depend on invasive sampling, not allowing fast or real-time monitoring.
Year:
2023
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2023
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2023
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2023
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2023
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2023
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2023
Year:
2023
Collaborators (8)
Paulo Antunes
Assistant Professor
Universidade de Aveiro
Florinda Costa
Associate Professor with habilitation
Universidade de Aveiro
Humberto Varum
Professor Catedrático
Universidade do Porto Faculdade de Engenharia
Micael S. Nascimento
-
Ole Bang
Technical University of Denmark
Xuehao Hu
University of Mons
Ana C. Pereira
Universidade da Madeira
Nuno F. Santos
Universidade de Aveiro
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