Читать книгу Multiblock Data Fusion in Statistics and Machine Learning - Tormod Næs - Страница 35

Sensory and consumer science is an important discipline in the assessment of food quality. It consists of a large number of measurement methods for determining the descriptive properties of products as well as the consumer liking of the same products (Lawless and Heymann, 2010). Often a product will be characterised by a number of different data types, ranging from classical descriptive sensory analysis using predefined attributes and a trained sensory panel to consumer based characterisation based on, for instance, the check-all-that-apply (CATA) method (Varela and Ares, 2012). The data sets will generally consist of a substantial number of attributes and a relatively moderate number of samples. Of special interest is estimating relations between data blocks related to liking and product characterisation. A large number of methods have been developed for this purpose as will be discussed in Chapters 7, 8 and 10 in this book (see Næs et al. (2010) for an overview). An example of a typical data structure and its related questions in sensory science is given in Example 1.4.