The paper deals with the differentiation of cultured cream butter, sweet cream butter and cultured butter from sweet cream by electronic nose (E-Nose) technology. The sensor array of the E-Nose used is composed of 10 metal oxide semiconductor type chemical sensors. Altogether, 90 butter samples were examined. Multivariate statistics as principal component analysis (PCA) and partial least square (PLS) analysis in combination with linear discriminant analysis (LDA) were used as a method for the classification of the sensor results of the E-Nose into different butter types. More than 95% of the samples were classified correctly into the three butter types.
