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Review on characteristics of trained sensory panels in food science

期刊

JOURNAL OF TEXTURE STUDIES
卷 52, 期 4, 页码 501-509

出版社

WILEY
DOI: 10.1111/jtxs.12616

关键词

panel training validation; panelists' performance; sensory evaluation; sensory methods

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The study found that the majority of trained panels have between 8 to 12 members, with training sessions lasting less than 2 hours each. Some papers conducted training and validated the effectiveness of their training, with a significant number using intensity scales as descriptive methods.
Sensory analysis has been, is, and will be one of the most important methods in judging food quality. As such, it is an evaluation tool involving human subjects with specific skills to conduct assigned series of tests. This review outlines main characteristics of 179 trained panels published in 16 selected scientific journals in the last 12 months, as well as training methods used for panelists, and type of sensory studies employed. The results reveal that two thirds of the panels have between eight and twelve members, with gender data provided in half of the papers. Overall duration of their initial training is presented only in around 20% of reviewed publications. When provided, duration was below 2 hr per session involving up to 10 sessions. One third of papers confirmed to have conducted training of the panel for methods employed, while almost half used experienced human subjects with no further data. Around 12% of all manuscripts have validated training of their sensory panel, while 20% of papers covered at least one criterion for assessment of their panels' performance. The majority of papers (80%) used descriptive methods, mainly with intensity scales. It is of note that 15% of papers used hedonic tests typical for consumer studies. Almost half of the scholars conducted their research in triplicates (41.3%) while almost one quarter (24%) provided no data on this subject. Type of food analyzed has no effects on the quality of data provided regarding panels, training, sensory methods, and replications.

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