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首页> 外文期刊>Spectrochimica acta, Part A. Molecular and biomolecular spectroscopy >Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis
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Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis

机译:热氧化过程可加速与葵花籽油混合的橄榄油的降解,并通过同步荧光光谱法和化学计量分析对其进行区分

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We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25 degrees C) and the other group was thermally treated in a thermostatic water bath at 75 degrees C for 8 h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720 nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20 nm, 40 nm, 60 nm and 80 nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20 nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25 degrees C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration. (C) 2015 Elsevier B.V. All rights reserved.
机译:我们已经研究了热处理对从掺有葵花籽油的EVOO样品中分离出的纯特级初榨橄榄油(EVOO)样品的影响。使用两组样品。一组在室温(25摄氏度)下进行分析,另一组在75摄氏度的恒温水浴中与空气接触并暴露在光线下进行热处理8小时,以促进氧化。然后用同步荧光光谱法测量所有样品。通过在250至720nm范围内改变激发波长来获得荧光光谱。为了优化激发和发射波长之间的差异,尝试了四个恒定的差异波长,即20nm,40nm,60nm和80nm。偏最小二乘判别分析(PLS-DA)用于区分纯油和掺假油。发现20 nm的差异是最佳的,在该差异下,判别模型显示了最佳结果。最好的PLS-DA模型是使用差异光谱(75-25摄氏度)构建的模型,该模型能够在掺假水平为2%的情况下从掺假油中区分出纯净油。此外,建立了PLS回归模型以量化掺假水平。同样,最好的模型是使用差异光谱构建的模型,其预测误差为掺假的1.75%。 (C)2015 Elsevier B.V.保留所有权利。

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