Biosens4PrecisionMastitis

Ciutat:
Poster European Corner

Nom i cognoms / Name and surname
Beatriz Prieto Simón

Afiliació / Affiliation
Universitat Rovira i Virgili

Programa de finançament europeu en que s’enmarca aquest projecte? / European funding programme in which this project is being carried out?
EU support (FP7, H2020, etc.) other than MSCA

Títol del projecte / Project title
Biosens4PrecisionMastitis: Channel-based biosensors to support a precision agriculture approach for improved bovine mastitis management

Número del projecte / Project number
PCI2020-120693-2

Breu explicació del projecte / Brief explanation of your project
Biosens4PrecisionMastitis aims to improve health and wealth of milking cows, as well as farm profitability, by developing cutting-edge biosensing technology for the early diagnosis of bovine mastitis.
Prompt detection and timely intervention is key to reduce the economical, societal and environmental impact of bovine mastitis, but bovine mastitis diagnosis faces some limitations. First, clinical mastitis is often detected by farmers via visual inspection of milk, when they observe changes in milk’s consistency and quality, such as watery milk or the presence of clots in milk. Additionally, farmers can observe that the cow’s udder is swollen, red and painful in response to inflammation. Alternatively, on-farm, somatic cell count is used as an indicator of the likeliness of milk to contain harmful bacteria, and thus can only identify potential cases. In the lab, both cell culture and PCR are used to confirm mastitis and identify the causative pathogen. These techniques though are time-consuming and expensive. More importantly, none of them allows diagnosis at the early stages of the disease, when animals are highly infective and therapies are more effective.

Enllaç a la pàgina web del projecte / Link to your project website
http://www.biosensingbovinemastitis.com/

Repte en que s’emmarca aquest projecte / Challenge within the framework of this project

Coordinen:

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Aquest projecte està cofinançat pel programa de recerca i innovació Horizon Europe de la Unió Europea sota el projecte NitRecerCat (101061189).

This project is co-funded by the European Union’s research and innovation programme Horizon Europe, under the project NitRecercat (101061189).