12 research outputs found

    Trends in the application of chemometrics to foodomics studies

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    Some problems in quantitiative mid-infrared spectroscopy

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    Quantitative analysis of potential adulterants of extra virgin olive oil using infrared spectroscopy

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    The determination of food authenticity and the detection of adulteration are problems of increasing importance in the food industry. This is especially so for ‘value-added’ products, where the potential financial rewards for substitution with a cheaper ingredient are high. In this paper, the potential of infrared spectroscopy as a rapid analytical technique for the quantitative determination of adulterants in extra virgin olive oil is demonstrated. The method uses Fourier transform infrared spectroscopy, combined with attenuated total reflectance and partial least squares regression. Model systems comprising two types of ‘contaminant’ oil — refined olive and walnut — are investigated

    Multivariate analysis of electromyographic (EMG) frequency spectra to characterise mastication

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    On five separate occasions, eight volunteers were asked to consume five edible gels with known texture and flavour properties. The electrical activity of their temporal and masseter muscles was recorded using electromyography (EMG). The electrode voltages were sampled at a rate of 1 kHz, starting when each volunteer began to masticate, and terminating when the volunteer indicated that the gel's flavour could no longer be perceived. Data from the mastication phase (first 20 s) were Fourier transformed to give a power spectrum in the frequency domain. Upon visual examination, the low frequency (< 10 Hz) region was found to contain spectral features that differ between volunteers, and the differences were generally consistent between sessions. Principal component analysis (PCA) supported this finding, by showing some clustering of the scores from different volunteers. However, when PCA was applied to the whole of the frequency range, the clustering became much more pronounced, indicating that higher frequencies also contribute to the distinction between volunteers. Clusters of readings from each volunteer were almost entirely separated using internally cross-validated canonical variate analysis (CVA), showing that each individual demonstrated characteristic and consistent mastication behaviour. Finally, a statistically significant association was found between the integrated power spectrum and the concentration of flavour compound in the gels; however, a similar relationship was discovered to exist between the flavour and the texture, as determined by cutting and compression. Hence, it was not possible to determine conclusively whether flavour alone has an effect on mastication characteristics

    Using induced chlorophyll production to monitor the physiological state of stored potatoes (Solanum tuberosum L.)

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    A Visible/Near-infrared (Vis/NIR) spectrometer equipped with a fibre-optic probe was used to stimulate and measure chlorophyll production in potato tubers, at low levels that produce no visible greening in the skin. Subtle responses to changes in the light stimulus were also tracked. When used with a static experimental setup, these measurements are precise. However, the technique is very sensitive to the exact geometry of the tuber-probe arrangement, and careful positioning of the probe is crucial. Complementary studies established that tissue under the apical buds (‘eyes’) has greater capacity to produce chlorophyll than other locations on the tuber surface. A long-term study of multiple tubers suggested that different cultivars behave differently in terms of the rate of chlorophyll production. These behavioural differences may be related to the batch dormancy status; validating this potential relationship is the focus of ongoing work

    Texture analysis of Red Delicious fruit: Towards multiple measurements on individual fruit

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    The sensory texture of Red Delicious apples was studied using single point and time–intensity (TI) methods together with penetrometers and in vivo techniques. Testing was performed in two trials on a per fruit basis, not with fruit batches. The standard penetrometer was significantly correlated (p < 0.05) to sensory hardness, juiciness, mealiness, crunchiness and degree of breakdown, but not to skin toughness. Facial muscle activity during chewing was collected with electromyography (EMG) together with spit outs for individuals. Parameters such as work done during chewing were extracted from the full EMG signals, and some were found to be related significantly (p < 0.05) to the penetrometer data and to sensory hardness. The aspect ratio of expectorated particles related significantly (p < 0.05) to sensory hardness and skin toughness. Principal component analysis shows that 76% of the variance in the combined data set was explained by seven components in Trial 1 and 73% by six components in Trial 2. The first component in both trials was described, principally by hardness, mealiness and the penetrometer value. The second component was described by the EMG signal parameters in Trial 1, and the apple skin properties in Trial 2. Sensory terms hardness, mealiness, crunchiness and juiciness were inter-correlated which may indicate that the texture of Red Delicious apples is perceived as mainly one-dimensional

    Application of chemometrics to the 1H NMR spectra of apple juices: discrimination between apple varieties

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    Discrimination between apple juices produced from different varieties (Spartan, Bramley, Russet) has been achieved by applying principal components analysis (PCA) and linear discriminant analysis to 1H NMR spectra of the juices. The use of covariance and correlation matrix PCA methods was investigated and different regions of the spectrum were analysed in view of the large range of signal intensities. All the methods gave a high success rate of classification, with at least 24 out of 26 samples being correctly assigned when five principal components were used. Under optimum conditions a 100% success rate was achieved. Examination of the principal component loadings showed that the levels of malic acid and sucrose were two important chemical variables, but variations in the composition of the minor constituents were also found to make a significant contribution to the discrimination
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