Abstract
Sensometrics assesses sensory perspectives in consumer research using statistics and various methodologies. This study evaluated consumer responses to hot and cold germinated-wheat beverages in check-all-that-apply (CATA) and rate-all-that-apply (RATA) assessments using sensometric statistical approaches, including Cochran’s Q test, penalty-lift analysis, and multiple factor analysis. Hot beverages (HB) were prepared by infusion using different amounts of germinated wheat (HB_1: 0.8 g/100 mL, HB_2: 2 g/100 mL, and HB_3: 4 g/100 mL), while cold beverages (CB) were made using cooled boiled germinated wheat with varying concentrations (CB_1: 25 g/L, CB_2: 50 g/L, and CB_3: 75 g/L). Results of the CATA study suggested that consumers preferred HB_1 and CB_1 because they expressed the sensory characteristics associated with liking, including “barley tea flavor”, “neat taste”, and “nutty taste”, while “bitterish taste”, “stuffy taste”, and “astringent taste” were undesirable attributes. “Browning index”, “barley tea odor”, and “nutty taste” showed significant differences (p < 0.05) in both favorable and unfavorable rating scores. Overall, CB_1 elicited a clear taste and odor with fewer negative emotions. These findings demonstrate the usefulness of the sensometric approach combined with CATA and RATA analyses to obtain more easily interpretable results on the sensory perception of consumers to new food products.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Not applicable.
Code availability
XLSTAT software version 2021.2 (Addinsoft, Paris, France) was used for data analysis.
References
Ares G, Dauber C, Fernández E et al (2014) Penalty analysis based on CATA questions to identify drivers of liking and directions for product reformulation. Food Qual Prefer 32:65–76. https://doi.org/10.1016/j.foodqual.2013.05.014
Aung T, Kim BR, Kim MJ (2022a) Optimized roasting conditions of germinated wheat for a novel cereal beverage and its sensory properties. Foods 11:481. https://doi.org/10.3390/foods11030481
Aung T, Kim BR, Kim MJ (2022b) Comparative flavor profile of roasted germinated wheat (Triticum aestivum L.) beverages served hot and cold using electronic sensors combined with chemometric statistical analysis. Foods 11:3099. https://doi.org/10.3390/foods11193099
Aung T, Kim BR, Kim MJ (2023a) Comparative volatiles, amino acids, and phenolic compounds and characteristics of roasted germinated wheat (Triticum aestivum L.) during beverage preparation. LWT 173:114412. https://doi.org/10.1016/j.foodres.2022.110976
Aung T, Kim BR, Kwak HS, Kim MJ (2023b) Neuroimaging approach: effects of hot and cold germinated wheat beverages on electroencephalographic (EEG) activity of the human brain. Foods 12(18):3493. https://doi.org/10.3390/foods12183493
Baião LF, Rocha C, Lima RC et al (2022) Development of a Rate-All-That-Apply (RATA) ballot for sensory profiling of sea urchin (Paracentrotus lividus) gonads. Food Res Int 153:110976. https://doi.org/10.1016/j.foodres.2022.110976
Cho S, Moazzem MS (2022) Recent applications of potentiometric electronic tongue and electronic nose in sensory evaluation. Prev Nutri Food Sci 27(4):354–364. https://doi.org/10.3746/pnf.2022.27.4.354
Cochran WG (1950) The comparison of percentages in matched samples. Biometrika 37:256. https://doi.org/10.2307/2332378
Hunaefi D, Marusiva W (2021) Sensory profile of 3 in 1 instant coffee using emotional-sensory mapping, flash profile, and CATA (Check-All-That-Apply) methods. J Teknol Dan Ind Pangan 32:169–180. https://doi.org/10.6066/jtip.2021.32.2.169
Jaeger SR, Lee SM, Kim KO et al (2018) CATA and RATA questions for product-focused emotion research: five case studies using emoji questionnaires. Food Qual Prefer 68:342–348. https://doi.org/10.1016/j.foodqual.2018.04.001
Josse J, Pagès J, Husson F (2008) Testing the significance of the RV coefficient. Comput Stat Data Anal 53:82–91. https://doi.org/10.1016/j.csda.2008.06.012
Kennedy J (2010) Evaluation of replicated projective mapping of granola bars. J Sens Stud 25:672–684. https://doi.org/10.1111/j.1745-459X.2010.00302.x
Kim H, Cho M, Lee K (2009) Studies on the sensory characteristics of korean wine and imported wine. J Korean Soc Food Cult 19:593–602
Kim MK (2020) Sensory profile of rice-based snack (Nuroongji) prepared from rice with different levels of milling degree. Foods 9:685. https://doi.org/10.3390/foods9060685
Lee B-Y, Kim M-H et al (2010) Influences of roasted or non-roasted brown rice addition on the nutritional and sensory properties and oxidative stability of sunsik, Korean heated cereal powder. Korean J Food Cook Sci 26:872–886
Liu S, Sun H, Ma G et al (2022) Insights into flavor and key influencing factors of Maillard reaction products: a recent update. Front Nutr 9:2014. https://doi.org/10.3389/fnut.2022.973677
Maleš I, Pedisić S, Zorić Z et al (2022) The medicinal and aromatic plants as ingredients in functional beverage production. J Funct Foods 96:105210. https://doi.org/10.1016/j.jff.2022.105210
Meyners M (2016) Testing for differences between impact of attributes in penalty-lift analysis. Food Qual Prefer 47:29–33. https://doi.org/10.1016/j.foodqual.2014.11.001
Meyners M, Castura JC, Carr BT (2013) Existing and new approaches for the analysis of CATA data. Food Qual Prefer 30:309–319. https://doi.org/10.1016/j.foodqual.2013.06.010
Meyners M, Jaeger SR, Ares G (2016) On the analysis of Rate-All-That-Apply (RATA) data. Food Qual Prefer 49:1–10. https://doi.org/10.1016/j.foodqual.2015.11.003
Murthy SV, Fathima SN, Mote R (2022) Hydroalcoholic extract of ashwagandha improves sleep by modulating GABA/histamine receptors and EEG slow-wave pattern in in vitro-in vivo experimental models. Prev Nutri Food Sci 27(1):108–120. https://doi.org/10.3746/pnf.2022.27.1.108
Pineau N, Girardi A, Lacoste Gregorutti C et al (2022) Comparison of RATA, CATA, sorting and Napping® as rapid alternatives to sensory profiling in a food industry environment. Food Res Int 158:111467. https://doi.org/10.1016/j.foodres.2022.111467
Qannari EM (2017) Sensometrics approaches in sensory and consumer research. Curr Opin Food Sci 15:8–13. https://doi.org/10.1016/j.cofs.2017.04.001
Rini L, Lagast S, Schouteten JJ et al (2022) Impact of emotional state on consumers’ emotional conceptualizations of dark chocolate using an emoji-based questionnaire. Food Qual Prefer 99:104547. https://doi.org/10.1016/j.foodqual.2022.104547
Tatsu S, Matsuo Y, Nakahara K et al (2020) Key odorants in Japanese roasted barley tea (Mugi-Cha)—differences between roasted barley tea prepared from naked barley and roasted barley tea prepared from hulled barley. J Agric Food Chem 68:2728–2737. https://doi.org/10.1021/acs.jafc.9b08063
Tireki S (2021) A review on packed non-alcoholic beverages: Ingredients, production, trends and future opportunities for functional product development. Trends Food Sci Technol 112:442–454. https://doi.org/10.1016/j.tifs.2021.03.058
Turgut SS, Entrenas JA, Taşkın E et al (2022) Estimation of the sensory properties of black tea samples using non-destructive near-infrared spectroscopy sensors. Food Control 142:109260. https://doi.org/10.1016/j.foodcont.2022.109260
Vidal L, Antúnez L, Ares G et al (2019) Sensory product characterisations based on check-all-that-apply questions: further insights on how the static (CATA) and dynamic (TCATA) approaches perform. Food Res Int 125:108510. https://doi.org/10.1016/j.foodres.2019.108510
Vigneau E, Cariou V, Giacalone D et al (2022) Combining hedonic information and CATA description for consumer segmentation. Food Qual Prefer 95:104358. https://doi.org/10.1016/j.foodqual.2021.104358
Xia Y, Song J, Lee PY et al (2020) Impact of consumption frequency on generations of sensory product profiles using CATA questions: case studies with two drink categories. Food Res Int 137:109378. https://doi.org/10.1016/j.foodres.2020.109378
Acknowledgements
Not applicable.
Funding
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B07049760). This research was funded by the Financial Program for Self-Directed Research Capacity in 2022.
Author information
Authors and Affiliations
Contributions
TA: Methodology, Validation, Formal analysis, Investigation, Writing—original draft, review & editing, Visualization. B-RK Methodology, Validation, Formal analysis, Investigation, Visualization. M-JK: Conceptualization, Writing—original draft, review & editing, Supervision, Project administration.
Corresponding author
Ethics declarations
Conflicts of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Ethical approval
Ethical approval for the involvement of human subjects in this study was granted by the Institutional Review Board, Reference number 7001066-202002-HR-004.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Aung, T., Kim, B.R. & Kim, M.J. Check-all-that-apply (CATA)- and rate-all-that-apply (RATA)-based sensometric assessment of germinated-wheat beverages. J Food Sci Technol 61, 897–906 (2024). https://doi.org/10.1007/s13197-023-05884-z
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13197-023-05884-z