Ana C. Pereira
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Recent Grants
Grant: Close
DC4DM - Digital Creativity for developing Digital Maturity future skills
Open Date: 2020-09-01
Close Date: 2023-08-01
Grant: Close
IMPACT III - Impacto da Tecnologia na Qualidade do Vinho Madeira
Open Date: 2018-07-01
Close Date: 2020-06-01
Grant: Close
Novos designs de sensores em fibra ótica para a deteção de compostos de AROMA
Open Date: 2018-06-01
Close Date: 2021-05-01
Grant: Close
SUPERPRO- Supervisão do processo fermentativo da cerveja lager
Open Date: 2017-09-01
Close Date: 2019-08-01
Grant: Close
EUROVITISOS - Intercâmbio de esperiências europeias em viticultura sustentável, ensino e divulgação
Open Date: 2016-01-01
Close Date: 2018-01-01
Articles (7)
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.
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2023
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2023
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2022
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2022
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2022
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2021
Year:
2020
Collaborators (2)
Jose C Marques
Associate Professor
Universidade da Madeira
Carlos Marques
Universidade de Aveiro
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