Open Access
Issue
Ciência Téc. Vitiv.
Volume 36, Number 1, 2021
Page(s) 22 - 31
DOI https://doi.org/10.1051/ctv/ctv2021360122
Published online 26 March 2021
  • Addinsoft, 2019. XLSTAT. 2019.2.2. [Google Scholar]
  • Bower J.A. 2013. Statistical methods for food science: Introductory procedures for the food practitioner. 334 p. Wiley-Blackwell, Chichester. [Google Scholar]
  • COFRAC, 2018. Guide technique d'accréditation - Analyses sensorielles et tests consommateurs. Available at: https://tools.cofrac.fr/documentation/LAB-GTA-33 (accessed on 20.12.2021) [Google Scholar]
  • Comissão Vitivinícola Regional do Dão, 2019. Anexo técnico de acreditação Nº L0230-1. Instituto Português de Acreditação. Available at: http://www.cvrdao.pt/images/documentos/ATE_L0230A1(2020-11-10).pdf (accessed on 10.12.2020) [Google Scholar]
  • Comissão Vitivinícola Regional do Dão, 2020. RI08 – Análise sensorial. Available at: http://www.cvrdao.pt/images/documentos/RI08-An%C3%A1lise%20Sensorial-02-2020.pdf (accessed on 28.08.2020) [Google Scholar]
  • E3000−18. Standard guide for measuring and tracking performance of assessors on a descriptive sensory panel., 13 pp. ASTM International, West Conshohocken. [Google Scholar]
  • EA-4/09:G2017. Accreditation for sensory testing laboratories. Available at: https://european-accreditation.org/wp-content/uploads/2018/10/ea-4-09-g-rev02-february-2017.pdf (accessed on 15.11.2020). [Google Scholar]
  • Etaio I., Albisu M., Ojeda M., Gil P., Salmerón J., Elortondo F.P., 2010a. Sensory quality control for food certification: A case study on wine. Method development. Food Control, 21, 533-541. [Google Scholar]
  • Etaio I., Albisu M., Ojeda M., Gil P., Salmerón J., Elortondo F.P., 2010b. Sensory quality control for food certification: A case study on wine. Panel training and qualification, method validation and monitoring. Food Control, 21, 542-548. [Google Scholar]
  • Gawel R., Godden P., 2008. Evaluation of the consistency of wine quality assessments from expert wine tasters. Aust. J. Grape and Wine Res., 14, 1-8. [Google Scholar]
  • ISO 3591:1977. Sensory analysis - Apparatus - Wine-tasting glass. 3 p. International Organization for Standardization, Geneva. [Google Scholar]
  • ISO 8586:2012. Sensory analysis - General guidelines for the selection, training and monitoring of selected assessors and expert sensory assessors. 28 p. International Organization for Standardization, Geneva. [Google Scholar]
  • ISO 8589:2007. Sensory analysis - General guidance for the design of test rooms. 16 p. International Organization for Standardization, Geneva. [Google Scholar]
  • ISO 11132:2012. Sensory analysis - Methodology - Guidelines for monitoring the performance of a quantitative sensory panel. 23 p. International Organization for Standardization, Geneva. [Google Scholar]
  • ISO/IEC 17025:2017. General requirements for the competence of testing and calibration laboratories. 30 p. International Organization for Standardization, Geneva. [Google Scholar]
  • Jackson R.S., 2014. Wine assessment and sensory analysis. In: Wine science: Principles and applications. 865 - 866. Jackson R.S. (ed.), Elsevier, Cambridge. [Google Scholar]
  • Kemp S.E., Hort J., Hollowood T., 2018. Descriptive analysis in sensory evaluation. 724 p. Wiley-Blackwell, Hoboken. [Google Scholar]
  • Kermit M., Almli V., 2005. Assessing the performance of a sensory panel- panelist monitoring and tracking. J. Chemom., 19, 154-161. [Google Scholar]
  • Latreille J., Mauger E., Ambroisine L., Tenenhaus M., Vincent M., Navarro S., Guinot C., 2006. Measurement of the reliability of sensory panel performances. Food Qual. Prefer., 17, 369-375. [Google Scholar]
  • Lawless H.T., 1984. Flavor description of white wine by expert and nonexpert wine consumers. J. Food Sci., 49, 120-123. [Google Scholar]
  • Lê S., Worch T., 2015. Analyzing sensory data with R. 374 p. CRC Press, Boca Raton. [Google Scholar]
  • Lea P., Næs T., Rødbotten M., 1997. Analysis of variance for sensory data. 102 p. Wiley, Chichester. [Google Scholar]
  • Lea P., Rødbotten M., Næs T., 1995. Measuring validity in sensory analysis. Food Qual. Prefer., 6, 21-326. [Google Scholar]
  • Luciano G., Næs T., 2009. Interpreting sensory data by combining principal component analysis. Food Qual. Prefer., 20, 167-175. [Google Scholar]
  • McEwan J.A., Hunter E.A., Gemert L.J., Lea P., 2002. Proficiency testing for sensory profile panels: measuring panel performance. Food Qual. Prefer., 13, 181-190. [Google Scholar]
  • Meilgaard M.C., Civille G.V., Carr B.T., 2016. Sensory evaluation techniques. 630 p. CRC Press, Boca Raton. [Google Scholar]
  • Meiselman H., 2013. The future in sensory/consumer research: Evolving to a better science. Food Qual. Prefer., 27, 208–214. [Google Scholar]
  • Microsoft, 2020. Microsoft Excel for Microsoft 365. 16.0.13628.20234 64 bits. [Google Scholar]
  • Montgomery D., 1991. Design and analysis of experiments. 684 p. John Wiley and Sons, Hoboken. [Google Scholar]
  • Neter J., Wasserman W., Kutner M.H., 1985. Applied linear statistical models. 1396 p. Irwin Inc., New York. [Google Scholar]
  • Nguyen D.Q., Le T.M., Nguyen D.H., 2014. Role of sensory evaluation in quality control: A textual point of view. In: HCMUT, Ho Chi Minh city. [Google Scholar]
  • Nordic Committee on Food Analysis (2013). NMKL Procedure No. 27: Measurement uncertainty in sensory analysis, 1-24. [Google Scholar]
  • NP ISO/IEC 17025:2018. General requirements for the competence and calibration laboratories. 37 p. International Organization for Standardization, Geneva. [Google Scholar]
  • Park J.Y., O’Mahony M., Kim, K.O., 2007. ‘Different-stimulus’ scaling errors; effects of scale length. Food Qual. Prefer., 18, 362-368. [Google Scholar]
  • Per Lea - Nofima Mat, Ås, Norway. Measurement uncertainty in sensory analysis. European Sensory Network. Available at: https://esn-network.com/research/conferences/pangborn-20090/lea-nofima/ (accessed on 21.07.2020) [Google Scholar]
  • Pinto M., Barros P., 2015. Ensaios de aptidão sensorial em química enológica. In: Química enológica - métodos analíticos. Avanços recentes no controlo da qualidade de vinhos e de outros produtos. 497-505. Curvelo Garcia A.S., Barros P. (ed.). Publindústria, Porto. [Google Scholar]
  • Rogers L., 2017. Sensory panel management: A practical handbook for recruitment, training and performance. 376 p. Elsevier Science, Cambridge. [Google Scholar]
  • Rossi F., 2001. Assessing sensory panelist performance using repeatability and reproducibility measures. Food Qual. Prefer., 12, 467-479. [Google Scholar]
  • Sit V., 1995. Analyzing ANOVA designs biometrics information handbook no 5. Available at: https://www.for.gov.bc.ca/hfd/pubs/Docs/Wp/WP07.pdf (accessed on 18.11.2020). [Google Scholar]
  • Snee R.D., 1974. Computation and use of expected mean squares in analysis of variance. J. Qual. Technol., 6, 128–137. [Google Scholar]
  • Stone H., Bleibaum R.N., Thomas H.A., 2020. Descriptive analysis. In: Sensory evaluation practices. 265. Stone H., Bleibaum R.N., Thomas H.A., Academic Press, New York. [Google Scholar]
  • Stone H., Sidel J., Oliver S., Woolsey A., Singleton R.C., 1974. Sensory evaluation by quantitative descriptive analysis. In: Descriptive sensory Analysis in practice. 23-34. Gacula M.C. (ed), Wiley-Blackwell, Scottsdale. [Google Scholar]
  • Taylor C.S., 2013. Validity and validation (understanding statistics). 206 p. Oxford University Press, New York. [Google Scholar]
  • Tomic O., Forde C., Delahunty C., Næs T., 2013. Performance indices in descriptive sensory analysis – A complimentary screening tool for assessor and panel performance. Food Qual. Prefer., 28, 122-133. [Google Scholar]
  • Tomic O., Luciano G., Nilsen A., Hyldig G., Lorensen K., Næs T., 2010. Analysing sensory panel performance in a proficiency test using PanelCheck software. Eur. Food Res. Technol., 230, 497-511. [Google Scholar]
  • Vilela A., Monteiro B., Correia E., 2015. Sensory profile of Port wines: categorical principal component analysis, an approach for sensory data treatment. Ciência Tec. Vitiv., 30, 1-8. [Google Scholar]
  • Walker J.A., 2018. Elements of Statistical Modeling for Experimental Biology. Available at: https://www.middleprofessor.com/files/applied-biostatistics_bookdown/_book/ (accessed on 20.01.2021) [Google Scholar]
  • Watson P.F., Petrie A., 2010. Method agreement analysis: A review of correct methodology. Theriogenology, 73, 1167-1179. [PubMed] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.