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151 158 ISO (2003): Sensory analysis — Methodology — General guidance for establishing a sensory profile . International Organization for Standardization, Geneva, Switzerland
In case of spices or crude drugs of medicinal- and aromatic plant origin, sensory characteristics, especially odour, has great commercial importance. The instrumental sensory analysis the so-called 'electronic nose' has proved to be a significant, new and quick method in chemometry. The sensor signal responses (data recorded by the electronic nose instrument) of the electronic nose were evaluated by statistical methods, including principal component analysis (PCA) and canonical discriminant analysis (CDA) and the combination of these methods by applying the discriminant analysis on the first eight principal components. The aim of this paper is the comparative analysis of the above evaluation methods as data processing tools of the sensor signal response of the electronic nose (chemosensor array). The essential oil of oregano (Origanum vulgare subsp. hirtum) selected line No. 10 was compared to the oil distilled from the selected line No. 11; and dried root samples of lovage (Levisticum officinale) harvested at different times from the two- and three-year-old population, were investigated with electronic nose (NST-3320, AppliedSensor Sweden AB). Principal component analysis, as a first step of the evaluation, did not clearly distinguish either oregano or lovage samples. Further statistical evaluation of the original sensor signal responses of the electronic nose with canonical discriminant analysis improved the separation power of the model. The best separation could be achieved by the combination of the two methods, whereby canonical discriminant analysis was applied to the first eight principal components, which described 99% of the differences. In all cases more than 92%, while in several experiments 100% of cross-validated grouped cases were classified correctly. Based on the results, the application of the electronic nose and the combination of multivariate methods, PCA and CDA, could be an appropriate tool either for identification of cultivar to accelerate selection process or to distinguish crude drugs of different age or different harvesting period.
): Sensory analysis — Identifcation and selection of descriptors for establishing a sensory profle by a multidimensional approach. ISO 11035:1994. Sensory analysis — Identifcation and selection of
1985 Geösel, A., Sipos, L., Stefanovitsné-Bányai, É, Kókai, Z. & Győrfi, J. (2011): Antioxidant, polyphenol and sensory analysis of
, A., Sipos , L., Stefanovits-Bányai , É., Kókai , Z. & Gyorfi , J. (2011): Antioxidant, polyphenol and sensory analysis of Agaricus bisporus and Agaricus subrufescens cultivars. Acta Alimentaria , 40 , 33
( Delwiche, 2012 ). The involvement of people with visual disability in sensory analysis of fruits showing defects allowed the blind consumer’s acceptance to ‘go beyond the appearances’ ( Bartolini et al., 2015 , 2017 ). To overcome the consumers
were expressed as degrees Brix (°Brix). The titratable acidity (TA) of fruit juice samples was evaluated according to EN 12147: 1996 ( EN, 1996 ) using 0.1 N NaOH and phenolphthalein indicator. 2.3 Sensory analysis Sensory tests were carried out in the
the internal standard. 2.7 Sensory analysis A group of 10 professionally trained tasters (5 men and 5 women, aged 20–30 years) participated in the sensory analysis. The different meads were evaluated using Quantitative Descriptive Analysis (QDA) on a
Qual. Pref., 2011, 22 (5), 486–489. 13 Torri, L., Piochi, M., Monteleone, E.: Descriptive sensory analysis and consumers’ preference for dietary fibre- and
), and browning index (BI) were calculated. 2.2.7 Sensory analysis Sensory analysis was conducted according to the Turkish Standard ( TS 5546, 2009 ). A total of 8 panellists (aged between 23 and 44 years) evaluated samples for flavour, odour, colour
