MEATSENSE

The goal of MEATSENSE is to start creating quality standards for horse meat based on innovation artificial intelligence (AI) techniques. Developing a specific classification system for horse meat, which does not currently exist, and starting the process of creating quality standards would be of great value for meat production companies and abattoirs.

The data used for the project comes from quality data from the channel: Production data for growth, size, channel colour, composition and classification, chemical composition, colour, texture, lipid oxidation, protein oxidation, sensory evaluation and, lastly, FTIR spectroscopy.

As a main distinctive feature, results from consumer tastings were included, which added a subjective component to the classification algorithm. That made it possible to explore innovative automatic learning algorithms, which had up to now been relegated to other sectors of the food chain, and find hidden relationships between (objective and subjective) variables. It was ultimately possible to find a direct relationship between consumer preferences and aspects of raising horses for meat, such as feeding, breeds or age of slaughter. In short, we have started down the path towards the objectification of human perception. This information will be extremely important for meat producers, because they will be able to use it in decision-making to adapt their product to market demands.

An additional aim of the project is to promote the consumption of horse meat. Because, in addition to having very healthy nutritional properties, it is one of the most sustainable and environmentally friendly livestock animals. That is because they generate less waste than other livestock animals, because of less stabling and, furthermore, their grazing contributes to forest maintenance.

Because of all that, a very ambitious project was undertaken with a clearly multidisciplinary nature that combines knowledge about animal production (UPNA-IS-FOOD), capturing and processing signals in the MIR (UPNA-ISC), and developing cutting edge techniques in artificial intelligence (AIN-SI). All of that is to obtain a reliable horse meat classification system that is efficient and useful for an emerging strategic sector in the society of Navarre.