6 research outputs found

    Development of nanoporous alumina-based electromembrane system

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    Master'sMASTER OF SCIENC

    Interlaboratory comparison of the intensity of drinking water odor and taste by two-way ordinal analysis of variation without replication

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    A case study of ordinal data from human organoleptic examination (sensory analysis) of drinking water obtained in an interlaboratory comparison of 49 ecological laboratories is described. The recently developed two-way ordinal analysis of variation (ORDANOVA) is applied for the first time for the treatment of responses on the intensity of chlorine and sulfurous odor of water at 20 and 60 degrees C, which is classified into the six categories from 'imperceptible' to 'very strong'. The one-way ORDANOVA is used for the analysis of the 'salty taste' intensity of the water. A decomposition of the total variation of the ordinal data and simulation of the multinomial distribution of the data-relative frequencies in different categories allowed the determination of the statistical significance of the difference between laboratories in classifying chlorine or sulfurous odor intensity by categories, while the effect of temperature was not significant. No statistical difference was found between laboratories on salty taste intensity. The capabilities of experts to identify different categories of the intensity of the odor and taste are also evaluated. A comparison of the results obtained with ORDANOVA and ANOVA showed that ORDANOVA is a more useful and reliable tool for understanding categorical data such as the intensity of drinking water odor and taste

    Ordinal Analysis of Variation of Sensory Responses in Combination with Multinomial Ordered Logistic Regression vs. Chemical Composition: A Case Study of the Quality of a Sausage from Different Producers

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    The newly developed statistical technique of two-way ordinal analysis of variation (ORDANOVA) was applied for the first time to sensory responses in combination with multinomial ordered logistic regression of a response category vs. chemical composition. A corresponding tutorial is provided. As a case study, samples of a sausage from different producers, purchased at the same time from a market, were compared based on sensory responses of experienced experts. A decomposition of total variation of the ordinal data and simulation of the multinomial distribution of the relative frequencies of the responses in different categories showed a statistically significant difference between the producers’ samples, and an insignificant difference between the experts’ responses related to the same sample. The capabilities of experts were also evaluated. The influence of chemical composition of a sausage sample on the probability of a response category was modeled using multinomial ordered logistic regression of the response on mass fractions of the main sausage components. This statistical technique can be helpful for understanding sources of variation of sensory responses on food quality properties. It is also promising for a revision of specification limits for chemical composition, as well as for the prediction of sensory properties when the chemical composition of the product is subject to quality control

    CCQM-K131 Low-polarity analytes in a multicomponent organic solution: polycyclic aromatic hydrocarbons (PAHs) in acetonitrile

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    Solutions of organic analytes of known mass fraction are typically used to calibrate the measurement processes used to determine these compounds in matrix samples. Appropriate value assignments and uncertainty calculations for calibration solutions are critical for accurate measurements. Evidence of successful participation in formal, relevant international comparisons is needed to document measurement capability claims (CMCs) made by national metrology institutes (NMIs) and designated institutes (DIs). To enable NMIs and DIs to update or establish their claims, in 2015 the Organic Analysis Working Group (OAWG) sponsored CCQM-K131 "Low-Polarity Analytes in a Multicomponent Organic Solution: Polycyclic Aromatic Hydrocarbons (PAHs) in Acetonitrile". Polycyclic aromatic hydrocarbons (PAHs) result from combustion sources and are ubiquitous in environmental samples. The PAH congeners, benz[a]anthracene (BaA), benzo[a]pyrene (BaP), and naphthalene (Nap) were selected as the target analytes for CCQM-K131. These targets span the volatility range of PAHs found in environmental samples and include potentially problematic chromatographic separations. Nineteen NMIs participated in CCQM-K131. The consensus summary mass fractions for the three PAHs are in the range of (5 to 25) μg/g with relative standard deviations of (2.5 to 3.5) %. Successful participation in CCQM-K131 demonstrates the following measurement capabilities in determining mass fraction of organic compounds of moderate to insignificant volatility, molar mass of 100 g/mol up to 500 g/mol, and polarity pKow < −2 in a multicomponent organic solution ranging in mass fraction from 100 ng/g to 100 μg/g: (1) value assignment of primary reference standards (if in-house purity assessment carried out), (2) value assignment of single and/or multi-component organic solutions, and (3) separation and quantification using gas chromatography or liquid chromatography
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