Application of Artificial Neural Networks in Meat Production and Technology

The market of meat and meat products is growing continuously. In the sector of meat, there are many problems and challenges associated with the evaluation of meat quality at industrial level. The methods with the potential of industrial application should be accurate but also rapid, non-destructive, with no health or environment hazards, with benefits of automation and lower risk of human error. The lack of such methods represents a drawback for meat industry and the research focusing on the possible application of rapid methods is emerging. Many new promising techniques are being tested in meat science such as NIR (near infrared) and FT-IR (Fourier transformed infrared) spectroscopy, mass spectrometry, hyperand multispectral imaging techniques, machine/computer vision, biosensors, electronic noses (array of sensors), ultrasound techniques, etc. However, the enormous amount of information provided by these instruments demands an advanced data treatment approach. The artificial intelligent methods can be used for such purposes since their primary target is to distinguish objects or groups or populations. Artificial neural networks (ANN) are a well-known mathematical tool widely used and tested lately for the problems in meat production and technology. Its advantages are in the ability to handle with nonlinear data, highly correlated variables and the potential for identification of problems or classification. In particular promising applications of ANN in relation to meat sector is in carcass classification, quality control of raw material, meat processing, meat spoilage or freshness and shelf-life evaluation, detecting off-flavours, authenticity assessment, etc. In this chapter an overview of published studies dealing with the application of ANN in meat science is given. In the first part of the chapter basic concepts of artificial neural networks (ANN) are presented and described. The next part of the chapter summarizes the relevant publications on the use of ANN in case of meat production and technology issues and is divided in several paragraphs presenting the relevant research work with the most interesting applications of ANN.