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The present study investigated how sighted and blind sensory assessors evaluated the quality of various apple varieties: Regal Prince (Gala Must), Jonagold Schneica (Jonica), Watson Jonathan, Golden Reinders and Generos. A total of 80 sighted and 12 blind people participated in the study, in three groups (sighted people without blindfolds, sighted people with blindfolds, blind people). The preference of sensory attributes (size, shape, colour, texture, taste and odour) was evaluated on a six-category scale. The data were analysed using single-factor (ANOVA, LSD95%, 99%) and multi-factor (Cluster analysis, ANOVA, LSD95%, 99%) evaluation. The results showed that blind and sighted assessors made similar judgements on external attributes perceptible by touch (size, shape), but differed in their evaluation of certain quality factors (flavour, taste), resulting in opponent patterns of preference on some apple varieties (Generos, Jonagold Schneica). A further conclusion of the experiment is that there was less deviation between the judgements of sighted assessors when they saw the apples than when they were blindfolded. The background of this phenomenon might be explained by the uncertainty and disturbed perception, which lead to inconsistent judgements.

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Near-infrared (NIR) spectrophotometers with different optical arrangements were used to measure the diffusely reflected electromagnetic radiation of different types of food additives in polyethylene (PE) foils. Eight compounds, frequently used in food process – but also in other industries –, were measured by different NIR spectrophotometers. The detected (‘as is’) and mathematically transformed (by scatter correction, second derivative combined with smoothing) NIR spectra were processed with multivariate data analysis (MDA). In this matter, unsupervised methods like principal component analysis (PCA) and cluster analysis (CA) were used, which techniques do not require prior information and reference measurements. The aim of the present study was to distinguish food additives by the help of the applied chemometric methods based on NIR spectra detected via the PE foils. Results indicated that distinction of different food additives and compounds with NIR methods is possible not only with the conventional sample preparations and handlings, but also without breaking the packaging.

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International Review of Applied Sciences and Engineering
Authors: Norbert Novák, Péter Miklós Kőmíves, Mónika Harangi-Rákos, and Károly Pető

Policy Report 34 , Halle , German National Academy of Sciences Leopoldina , 2017 , p. 80 . [32] J. Szenderák , “ Correlation clustering: Analysis of major agricultural commodity markets ,” Int. J. Eng. Manag. Sci. , vol. 3 , no. 3 , pp. 288

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Five statistical procedures including: simple correlation, multiple linear regression, cluster analysis, factor analysis and principal components analysis were used to study the influence of wheat/flour quality tests on end-use performance. Different statistical procedures identify different quality test to be in good correlation with bread yield and specific bread volume confirming the complexity of wheat quality determination. Factor analysis and principal components analysis identified three group of parameters named: protein quantity and quality, extensigraph readings and alpha-amylase activity which explain 73.6% (factor analysis) and 82.54% (PCA) of the total variability in the dependent structure.

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Samples of sweet wines from the Canary Islands belonging to the Denominations of Origin of La Palma and Lanzarote islands were analysed in relation to chemical parameters. The main chemical parameters analysed demonstrated that these wines fulfil all the legal requirements, since the content of all components tested falls below the maximum concentration admissible. Applying techniques of multivariate analysis (principal component, discriminant and cluster analysis), a complete differentiation could be achieved between the wines according to the island of production using only alcohol degree and isobutanol, which are chemical parameters related to the elaboration process.

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On self-explaining roads drivers automatically drive according to the expected behavior and speed. In order to create this type of roads, within a given road category the layout should be homogenous, whereas a remarkable difference should exist between road categories. Using a sample of 500 persons, the paper analyses, which road categories are identified and distinguished by road users.A picture sorting task was completed to find out how road users group 45 different road scenes, and how these groups correspond to the road categories according to current standards.In addition, an analysis of a questionnaire survey was used to determine how individual road scene images are grouped on the basis of chosen speeds, and how this grouping corresponds to road categories. For processing of speed data, cluster analysis was used.The result of both surveys show that road users can clearly distinguish only 4–5 road categories. The paper compares these results with the design guidelines of some countries.

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Six coloured and six non-coloured waxy rice varieties were analyzed by determining amylose, fat, and protein content, pasting, and thermal properties. Significant differences in protein content as well as pasting properties between coloured and non-coloured waxy rice were identified. It was demonstrated that protein may have a main influence on pasting and thermal properties of waxy rice. In addition, the optimal linear relationship between protein and pasting or thermal properties was found by combining RVA and DSC data using Principal component analysis (PCA). Typical indicators, which can classify coloured and non-coloured waxy rice, could be identified by Hierarchical cluster analysis (HCA). In pasting properties, trough and consistency viscosity were typical indicators; in thermal properties, enthalpy and stop temperature were typical indicators.

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In this study, six commercial cherry tomato cultivars were analysed for variations in biochemical and technological parameters. Significant differences were observed among cultivars with respect to their technological and functional quality attributes. About 2.48-fold variation in titratable acidity, 2.47-fold variation in total phenolics, 4.13-fold variation in total carotenoid and 7.68-fold variation in lycopene contents were recorded. The total antioxidant activity and respiration rate were also found to vary about 1.85-fold and 1.48-fold, respectively. The highest antioxidant activity and total phenolic content were found in the Cherry tomato hybrid no.1 followed by Pusa cherry tomato-1. Hierarchical cluster analysis revealed that Cherry tomato hybrid no. 1, Pusa cherry tomato-1, and Nagmoti cultivars were abundantly rich in phytochemical and bioactive compounds.

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Nine phenolic compounds (gallic acid, (+)catechin, vanillic and caffeic acid, p-coumaric acid, resveratrol, myricetin, quercitrin and quercetin) of fourteen Eger (Hungarian) young red wines were investigated using high-performance liquid chromatography in order to obtain data on the 2003 vintage. The grapes were harvested at different sites of the wine-district, vinified with same technology, but stored under different conditions (glass holder or 5-10 years old oak barrel). Same varietal wines originating from different sites of Eger wine-region showed considerable alterations in some phenolic components, and we found distinction in polyphenol content of different varietal wines originating from the same harvesting site. Cluster analysis was performed to acquire information about the similarity among the measured wines. Our study provides new data of polyphenol composition for Eger (Hungary) pure varietal red wines, and the results contribute to better identification of Hungarian red wines on the basis of geographical location.

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In recent years, there have been many changes in the food market, which have greatly transformed our approach to food chain supervision. The increasing complexity of the food chain (e.g. globalization of food trade, expansion of raw materials and additives, technical advancement), the frequent changes in food consumption trends and the phenomenon of food crime belong to the most challenging issues for food chain control institutions. These factors require the re-evaluation of the role of consumers in the food chain. The overall aim of this research was to explore consumers’ risk perception and risk avoidance for a more efficient, targeted risk communication. In the survey 1003, face-to-face interviews were made using questionnaire. The statistical analysis of data was followed by the identification and characterization of 4 relevant target groups with cluster analysis method: disinterested youngsters (17.0%), conscious elders (39.4%), food adepts (27.5%), and soul of the family (16.1%). Results indicated, that the Hungarian society can be segmented regarding to food associated risk perception and avoidance. It has been also proven, that risk perception is influenced by demographic factors. Furthermore, we have also managed to conclude that efficient risk communication would require a well-aimed and focused communication strategy.

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