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MADURACIÓ: Optimization of the maturation system of beef, based on the selection of the most suitable raw material and the real-time monitoring of the conditions of the chamber

Starting date: 01/11/2018 End date: 30/09/2021
Programme: Food Quality and Technology

Financing entities:

The production of aged meat involves using the natural ageing process to obtain meat with high added value. The dry ageing process has a positive effect on tenderness, and in ageing of more than 30 days it also leads to the development of more intense aromas which can be described as “dry aged”. These are considered desirable by an ever-widening niche of consumers, and are an opportunity for slaughterhouses and cutting plants to offer this type of differentiated product. Bovine carcasses for dry ageing must have certain characteristics: the cuts must come from animals of a certain age (over 5 years) and with a specific degree of fattening (≥4 in the SEUROP category). Animals such as culled cows at the end of their reproductive cycle are likely to enter the meat production chain, significantly increasing their value and consequently providing a greater financial return for the producer, enhancing the sustainability of the system.

The company MAFRICA is planning to adapt its facilities to start a new marketing line of dry aged beef, and this project aims to develop an innovative production system for aged meat that enables real-time monitoring of the characteristics of the pieces and decisions on the end point of the process to achieve an optimal product from the sensory point of view.

The main objective is to obtain beef with a high sensory quality by means of an innovative production system for aged meat that enables the environmental technical parameters to be monitored in real time.

The specific objectives of the project are:

  1. Identify the optimal ageing conditions.
  2. Optimise the raw material selection process.
  3. Optimise a dry ageing system based on a prototype designed to monitor the technical parameters of the process in real time.
  4. Apply predictive microbiology tools to minimise the risk of growth of pathogenic microorganisms.
  5. Develop an integrated information system that facilitates decision-making during the process.

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