Silva, FredericaDuarte, Ana M.Mendes, SusanaPinto, Filipa R.Barroso, SoniaGanhão, RuiGil, Maria M.2021-08-232021-08-232020Silva, F., Duarte, A.M., Mendes, S., Pinto, F.R., Barroso, S., Ganhão, R., & Gil, M.M. (2020). CATA vs. FCP for a rapid descriptive analysis in sensory characterization of fish. Journal of Sensory Studies, 35(6). https://doi.org/10.1111/joss.126050887-82501745-459Xhttp://hdl.handle.net/10400.8/6136Authors are very grateful to FCT (Fundaç~ao para a Ciência e a Tecnologia) for the financial support of this work through the project UID/MAR/04292/2020, attributed to MARE - Marine and Environmental Sciences Centre, Politécnico de Leiria, Portugal. This work was also partially funded by the Integrated Programme of SR&TD “SmartBioR” (reference Centro-01-0145-FEDER-000018) co-funded by Centro 2020 program, Portugal2020, European Union, through the European Regional Development Fund and by project VALOREJET (16–01-03-FMP-0003), Operational Program Mar 2020, Portugal.Storing non-marketable fish aboard fishing vessels takes up valuable storage space and, consequently, it is usually discarded. Therefore, the strategy to minimize the amount of discarded fish and boost the fishing economy should entail measures to turn unexploited species into marketable fish. The use of sensory descriptive analysis is usually the first step in the characterization of foods and assess their baseline appeal to the final consumer. In this study, the sensory characterization of five unexploited fish species was conducted, using a semi-trained panel, with the objective of establishing the appeal and marketability of these species. Check-all-that-apply (CATA) and Free Choice Profiling (FCP) were used to obtain descriptive attributes. Correspondence Analysis (CA) was used to examine CATA data and to compare both sensory methods, while Principal Component Analysis (PCA) was used for FCP data analysis. The results obtained with CATA method allowed to differentiate species by appearance, odor and flavor, while appearance and odor were statistically significant descriptors in FCP. CATA method was found to be more suitable to discriminate fish species, presenting a higher discriminatory power than FCP.engCheck-all-that-apply (CATA) analysisFree Choice Profiling (FCP) analysisNon-marketable fishPrincipal Component Analysis (PCA)Sensory characterization of fishjournal article10.1111/joss.12605