Tracking verbal-based methods beyond conventional descriptive analysis in food science bibliography. A statistical approach

• A bibliographic study of a base of abstracts is performed.
• Textual analysis methods are used to detect changes in the verbal-based methods.
• Multiple factor analysis for contingency tables is a favoured tool.
• Novelties and pioneer works are reported.

The usage of verbal-based methods beyond conventional descriptive analysis is increasing in sensory analysis, either as full-methods or as a complement to holistic methods. They contribute to a better understanding of the consumers’ likes and willingness, important factors to the food industry. A prime objective of this paper is to give a global vision of the scientific publications in food science related to this topic from their abstracts. Textual statistics, combining multidimensional methods such as correspondence analysis, multiple factor analysis for contingency tables and characteristic words, are proving to be useful for extracting information from the corpus of abstracts. These abstracts have evolved over time towards a higher concern for research about methodology, which has become more complex and requires sophisticated statistical methods. Sensory methods, such as free choice profile, flash profile, repertory grid, sorting task, napping, word association and CATA, have emerged or have been revitalised. New statistical methods, such as multiple factor analysis, have been introduced to analyse data issued from verbalisation tasks. However, correspondence analysis, a reference method for dealing with texts and, more generally, frequency tables, is used with too much restraint.