V. Nachev, T. Titova, T. Stoyanchev, S. Atanassova, Ch. Damyanov. A Study of an Electronic Nose for Chicken Meat Quality Assessment Based on Multi-sensor Data Fusion and SVM Classifier

Key Words: Food quality; sensory analysis; e-nose; SVM classification; chicken meat.

Abstract. This paper discusses some more important aspects related to sensory characteristics, in particular the implementation of an „electronic nose“ system. The aim of the study is to investigate the possibilities for assessing the quality and authenticity of food products, in particular fresh chicken meat. By using multisensory  data fusion, an attempt has been made to overcome some of the difficulties and shortcomings inherent in organoleptic assessments. For the purposes of classification into classes used one-class SVM classifier. The procedure has been successfully tested to increase the accuracy of the classification by selecting the most informative sensors. The results show the potential of the proposed classifier that could be used as a quick, objective and non-destructive tool for assessing the quality of real-world recognition systems.