Carlos Marques

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Universidade de Aveiro
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Recent Grants

Grant: Close

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

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (8)

Paulo Antunes

Assistant Professor

Universidade de Aveiro

PORTUGAL
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Florinda Costa

Associate Professor with habilitation

Universidade de Aveiro

PORTUGAL
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Humberto Varum

Professor Catedrático

Universidade do Porto Faculdade de Engenharia

PORTUGAL
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Micael S. Nascimento

-

PORTUGAL
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Ole Bang

Technical University of Denmark

DENMARK
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Xuehao Hu

University of Mons

BELGIUM
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Ana C. Pereira

Universidade da Madeira

PORTUGAL
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Nuno F. Santos

Universidade de Aveiro

PORTUGAL
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