Proposal of a metric selection index for correspondence analysis: an application in the sensory evaluation of coffee blends
DOI:
https://doi.org/10.5433/1679-0359.2020v41n2p479Keywords:
C. arabica, C. canephora, Hellinger, Simulation.Abstract
Correspondence analysis is a multivariate dimensionality-reduction technique applied to data structured into contingency tables. The main outcome of this approach is the generation of perceptual maps aimed at the study of similarity between categorical levels. In most cases, interpretations of these similarities present subjectivity when different metrics are considered; e.g., Hellinger distance and Chi-square. Thus, in an attempt to minimize this subjectivity, the present study proposes an index that quantifies the shortest distance between those levels. A simulation study was undertaken in which the generated maps were discussed in relation to real data involving the similarity of blends formed by coffees of different species, with sensory evaluations considering the flavor and acidity attributes. In conclusion, the proposed index—named metric selection index (MSI)—made it possible to include a statistic that justifies the most suitable metric for correspondence analysis, thus preventing subjectivity in interpretations of similarities between blend types and grade classes. In the simulation studies, with the metric proposed by Hellinger distance, MSI showed stabler results regarding total inertia distribution on the first two axes.Downloads
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References
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Vidal, L., Tárrega, A., Antúnez, L., Ares, G., & Jaeger, S. R. (2015). Comparison of Correspondence Analysis based on Hellinger and chi-square distances to obtain sensory spaces from check-all-that-apply (CATA) questions. Food Quality and Preference, 43(1), 106-112. doi: 10.1016/j.foodqual.2015.03.003
Costa, A. L. A., Guimarães, C. R., & Cirillo, M. A. (2018). A new approach to simple correspondence analysis with emphasis on the violation of the independence assumption of the levels of categorical variables. Acta Scientiarum. Technology, 40(1), 1-8. doi: 10.4025/actascitechnol.v40i1.34953
Cuadras, C. M., & Cuadras, D. (2006). A parametric approach to correspondence analysis. Linear Algebra and Its Applications, 417(1), 64-74. doi: 10.1016/j.laa.2005.10.029
Galli, V., & Barbas, C. (2004). Capillary electrophoresis for the analysis of short-chain organic acids in coffee. Journal of Chromatography, 1032(1-2), 299-304. doi: 10.1016/j.chroma.2003.09.028
Infantosi, A. F. C., Costa, J. C. G. D., & Almeida, R. M. V. R. (2014). Análise de correspondência: bases teóricas na interpretação de dados categóricos em ciências da saúde. Caderno de Saúde Pública, 30(3), 473-486. doi: 10.1590/0102-311X00128513
Jaeger, S. R., Cadena, R. S., Torres-Moreno, M., Antúnez, L., Giménez, A., Hunter, D. C.,... Ares, G. (2014). Comparison of check-all-that-apply and forced-choice yes/no question format for sensory characterization. Food Quality and Preference, 35(1), 32-40. doi: 10.1016/j.foodqual.2014.02.004
Lima, T. Fº., Della Lucia, S. M., Saraiva, S. H., Carneiro, J. C. S., & Roberto, C. D. (2011). Perfil sensorial e aceitabilidade de bebidas de café tipo expresso preparadas a partir de blends de café arábica e conillon. Enciclopédia Biosfera, 7(12), 1-17. doi: 10.1590/0034-737X201562040001
Lingle, R. T. (2011). The coffee cupper´s handbook: systematic guide to the sensory evaluation of coffee´s flavor. 4nd ed. Long Beach: S.C.A.A. SCAAed.
Meyners, M., Castura, J. C., & Carr, B. T. (2013). Existing and new approaches for the analysis of CATA data. Food Quality and Preference, 30(2), 309-319. doi: 10.1016/j.foodqual.2013.06.010.
Naito, S. D. N. P. (2007). Análise de correspondência generalizada. Dissertação de mestrado, Universidade de Lisboa, Lisboa, Portugal.
Paulino, A. L. B., Cirillo, M. A., Ribeiro, D. E., Matias, G. C., & Borém, F. M. (2019). A mixed model applied to joint analysis in experiments with coffee blends using the least squares method. Revista Ciência Agronômica, 50(3), 1-8. doi: 10.5935/1806-6690.20190041
Ramos, M. F., Ribeiro, D. E., Cirillo, M. A., & Borém, F. M. (2016). Discrimination of the sensory quality of the Coffea arabica L. (cv. Yellow Bourbon) produced in different altitudes using decision trees obtained by the CHAID method. Journal of the Science of Food and Agriculture, 96(10), 3543-3551. doi: 10.1002/jsfa.7539
Rao, C. R. (1995). A review of canonical coordinates and an alternative to correspondence analysis using Hellinger distance. Questiió, 19(1), 23-63.
Ribeiro, D. E., Borém, F. M., Cirillo, M. A., Prado, M. V. B., Ferraz, V. P., Alves, H. M. R., & Taveira, J. H. S. (2016). Interaction of genotype, environment and processing in the chemical composition expression and sensorial quality of Arabica coffee. African Journal of Agricultural Research, 11(27), 2412-2422. doi: 10.5897/AJAR2016.10832
Santos, E. S. M., Rosires, D., Freitas, D. G. C., & Corrêa, F. M. (2013). Efeito de grãos conilon no perfil sensorial e aceitação de bebidas de café. Semina: Ciências Agrárias, 34(5), 2297-2306. doi: 10.5433/1679-0359.2013v34n5p2297
Vidal, L., Tárrega, A., Antúnez, L., Ares, G., & Jaeger, S. R. (2015). Comparison of Correspondence Analysis based on Hellinger and chi-square distances to obtain sensory spaces from check-all-that-apply (CATA) questions. Food Quality and Preference, 43(1), 106-112. doi: 10.1016/j.foodqual.2015.03.003
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Published
2020-03-06
How to Cite
Costa, A. S. da, Resende, M., Nakano, E. Y., Cirillo, M. A., Borém, F. M., & Ribeiro, D. E. (2020). Proposal of a metric selection index for correspondence analysis: an application in the sensory evaluation of coffee blends. Semina: Ciências Agrárias, 41(2), 479–492. https://doi.org/10.5433/1679-0359.2020v41n2p479
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