Abstract: The quality of five different groups of commercial roast mutton samples (SS1, SS2, SS3, SS4 and SS5) was evaluated by fuzzy comprehensive sensory evaluation (FSE) and value engineering evaluation (VEE). The differences in the contribution rates of the volatile organic compounds (VOCs) in roast mutton to its sensory attributes were analyzed by gas chromatography-mass spectrometry (GC-MS) and sensory evaluation. Principal component analysis (PCA) was used to compare the differences between the results from both evaluation methods and to explore the correlation between fuzzy sensory indicators and value function scores so as to rank five groups of roast mutton. The experimental results showed that a total of 42 VOCs were identified in roast mutton by GC-MS and all VOCs could be divided into four value functional components with different attributes, terpenes and alcohols (Z1), aldehydes and sulfur-containing compounds (Z2), ethers and ketones (Z3), and aromatic and others (Z4). Function index ranked in the decreasing order: SS4 (26.18%) > SS1 (22.53%) > SS2 (19.59%) > SS3 (17.26%) > SS5 (14.43%). The result of ranking by FSE was only slightly different, SS4 > SS1 > SS2 > SS5 > SS3. PCA indicated that the results from FSE were consistent with VEE. Moreover, VEE made up for the flaw caused by boundary fuzziness in FSE, and therefore could serve as evaluation criterion in food quality monitoring. The combination of the two models can allow improved comprehensive quality evaluation of roast mutton.

Key words: fuzzy comprehensive sensory evaluation, value engineering evaluation, gas chromatography-mass spectrometry, roast mutton, principal component analysis