Abstract:Results presented in this paper show the ability to analyze vegetable oils with very cheap and easy method based on fluorescence spectroscopy. We have recorded, with a very simple experimental set up, fluorescence spectra for several vegetable oils at excitation wavelength <i>λ<sub>ex</sub></i> = 370 nm. After deconvolution, using a Lorentzian profile, and identification of the stripes forming the spectra, a normalization of the intensities was made with respect to the vitamin E band wi… Show more
“…The aim of PCA is to reduce the large number of parameters influencing the measures to a much smaller number of principal components (PCs) that capture the vast majority of variance in the data. This approach considerably reduces the dimensionality of the original data, enabling effective visualization, regression and classification of multivariate data [16]. For the PCA, samples were considered as individuals while the variables were the normalized fluorescence intensities (R_1, R_2, R_3), PV, K 232 , K 270 and Acidity.…”
Section: Chemometric Methodsmentioning
confidence: 99%
“…Consequently, VOO spectrum shows several broad emission peaks. To highlight the main emission peaks, a deconvolution is performed for each fluorescence spectrum of VOO according to the method described in our previous works [17]. [18].…”
A simple setup using a 365 nm LED coupled to a USB spectrometer through an optical fibre, in a front-face fluorescence configuration, was used to investigate the ability of fluorescence spectroscopy technique to discriminate between varieties of olive oil. To achieve this task, Virgin Olive Oils (VOO) from two major Tunisian olive cultivars known as Chetoui and Chemlali were used. Spectral analysis showed a clear separation between these two VOO varieties. A one-way ANOVA attests that this discrimination is significant. The Principal Components Analyses (PCA) showed that the normalized fluorescence intensities are the good parameters for this discrimination. This observation strengthens the potential of our spectral parameters to perform reliable analysis.
“…The aim of PCA is to reduce the large number of parameters influencing the measures to a much smaller number of principal components (PCs) that capture the vast majority of variance in the data. This approach considerably reduces the dimensionality of the original data, enabling effective visualization, regression and classification of multivariate data [16]. For the PCA, samples were considered as individuals while the variables were the normalized fluorescence intensities (R_1, R_2, R_3), PV, K 232 , K 270 and Acidity.…”
Section: Chemometric Methodsmentioning
confidence: 99%
“…Consequently, VOO spectrum shows several broad emission peaks. To highlight the main emission peaks, a deconvolution is performed for each fluorescence spectrum of VOO according to the method described in our previous works [17]. [18].…”
A simple setup using a 365 nm LED coupled to a USB spectrometer through an optical fibre, in a front-face fluorescence configuration, was used to investigate the ability of fluorescence spectroscopy technique to discriminate between varieties of olive oil. To achieve this task, Virgin Olive Oils (VOO) from two major Tunisian olive cultivars known as Chetoui and Chemlali were used. Spectral analysis showed a clear separation between these two VOO varieties. A one-way ANOVA attests that this discrimination is significant. The Principal Components Analyses (PCA) showed that the normalized fluorescence intensities are the good parameters for this discrimination. This observation strengthens the potential of our spectral parameters to perform reliable analysis.
“…This study was planned to characterise buffalo and cow ghee and the detection of their adulteration using Fluorescence spectroscopy. It has proved to be a nondestructive and efficient tool for the analysis of beta‐carotene in milk and edible oils (Sikorska et al ; Kongbonga et al ; Ullah et al ), and monitoring the manufacturing processes of dairy products (Andersen and Mortensen ; Karoui and Blecker ; Ahmad et al ; Shaikh and O’Donnell ). Furthermore, the presence of vitamins A, B 12 , D, E, K and CLA was investigated in both ghee types through a comparative analysis of their spectra.…”
Fluorescence spectroscopy has been utilised to characterise ghee extracted from buffalo and cow milk. Using an excitation wavelength of 320 nm, emission spectra of buffalo and cow ghee; vitamins A, B 12 , D, E, K; and conjugated linoleic acid (CLA) were acquired by using spectrofluorometer. The bands at 390, 440, 480 and 525 nm were assigned to fat-soluble vitamins, CLA, vitamin A and beta-carotene. Moreover, spectra of vitamins and CLA confirmed their presence in both ghee types. The spectral differences were highlighted through principle component analysis that has been applied for the detection of adulteration of cow milk in buffalo ghee.
“…Fluorescence and quenching phenomena of foodstuffs can make up a complex fingerprint of the sample. Fluorescence spectroscopy applied directly on food samples has among others been suggested for analysis of sugar [7], yoghurt [8], cheese [9], oils [10,11], honey [12] and distilled beverages [13]. Yet the use of fluorescence spectroscopy for beer analysis has only been investigated by a few.…”
Classification of a series of Australian beers was performed using synchronous scanning fluorescence spectroscopy and emission-excitation matrices based on the IR fingerprint regions. The results indicate that synchronous scanning fluorescence spectroscopy is a robust and valuable method to discriminate between Australian lager beers based on their brand name. In addition, a subsequent spoiling study revealed that when beers are opened and stored at 4 • C for 4 weeks, the results demonstrated that the beers were not statistically different. The methods and techniques outlined may be of interest to brewing companies and microbrewers to determine the unique beer spectrum.
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