Using Raman spectroscopy and an exponential equation approach to detect adulteration of olive oil with rapeseed and corn oil

Lima, Thaís Karine de; Musso, Maurizio; Menezes, Durval Bertoldo

doi:10.1016/j.foodchem.2020.127454

Cited by 64 publications

(31 citation statements)

References 27 publications

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“…New technologies or methods should be developed to meet the increasing requirements for rapid and nondestructive determination. Several advanced optical technologies have been studied and reported in meat quality evaluation with satisfying results, such as computer vision [14,15] , near-infrared (NIR) spectroscopy [16][17][18] and Raman spectroscopy [19][20][21] .…”

Section: Introduction mentioning

confidence: 99%

Quick assessment of chicken spoilage based on hyperspectral NIR spectra combined with partial least squares regression

Jiang

et al. 2021

International Journal of Agricultural and Biological Engineering

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Pseudomonas spp. and Enterobacteriaceae are dominant spoilage bacteria in chicken during cold storage (0°C-4°C). In this study, high resolution spectra in the range of 900-1700 nm were acquired and preprocessed using Savitzky-Golay convolution smoothing (SGCS), standard normal variate (SNV) and multiplicative scatter correction (MSC), respectively, and then mined using partial least squares (PLS) algorithm to relate to the total counts of Pseudomonas spp. and Enterobacteriaceae (PEC) of fresh chicken breasts to predict PEC rapidly. The results showed that with full 900-1700 nm range wavelength, MSC-PLS model built with MSC spectra performed better than PLS models with other spectra (RAW-PLS, SGCS-PLS, SNV-PLS), with correlation coefficient (R P ) of 0.954, root mean square error of prediction (RMSEP) of 0.396 log 10 CFU/g and residual predictive deviation (RPD) of 3.33 in prediction set. Based on the 12 optimal wavelengths (902

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Section: Introduction mentioning

confidence: 99%

Quick assessment of chicken spoilage based on hyperspectral NIR spectra combined with partial least squares regression

Jiang

et al. 2021

International Journal of Agricultural and Biological Engineering

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“…Raman spectroscopy is one of the most powerful techniques for the identification of molecules by their "fingerprint" scattering spectrum [1,2]. It is a fast, simple, highly reproducible, and nondestructive detection tool, which can be utilized either quantitatively or qualitatively in the determination of low-concentration matters mixed with other molecules or dissolved in liquids [3][4][5][6][7]. is technique has been employed widely in the research fields of biochemistry and physics and in the various practical applications in the detection of specially interested substance [6,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Optical Feedback for Sensitivity Enhancement in Direct Raman Detection of Liquids

Liu

et al. 2021

Journal of Spectroscopy

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Detection of low-concentration molecules in liquids has been a challenge in sensing technologies. Raman spectroscopy is an effective approach for trace detection, which is in fact a “volume-excitation” and “volume-collection” technique in the analysis of liquid samples. However, for the commonly employed one-pass excitation and back-scattering detection scheme, a large portion of both the excitation laser energy and the Raman-scattering light energy is wasted without efficient reuse or collection. In this consideration, we demonstrate a broadband optical feedback scheme by a curved high-reflection mirror for both the excitation and the Raman-scattering light, so that the excitation and the forward-propagating Raman signal can be back-reflected and collected with a high efficiency. Using the “F+2f” design, where F and f are the focal lengths of the focusing lens and curved reflection mirror, respectively, we were able to not only produce two focuses of the excitation laser beam but also extend the Raman interaction by a doubled distance. For the detection of pure ethanol molecules and the R6G molecules in water with a concentration of 10−3 M, the Raman signal was enhanced by a factor of about 5.6. The optical feedback scheme and discovered optical mechanisms supply effective improvements to the Raman spectroscopic measurements on liquid samples.

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“…Olive oil, which is wrongly considered the most beneficial for human health, is the most often adulterated vegetable oil. A large number of studies are devoted to the detection of falsification of olive oil using optical spectroscopy methods such as fluorescence and UV and visible spectroscopy [2], Raman spectroscopy [3], combination of near and mid IR spectroscopy [4], etc. But olive oil is inferior to flaxseed oil in the content of essential polyunsaturated fatty acids, among which the content of alpha-linolenic (omega-3) acid can reach 64 %.…”

Section: Introductionmentioning

confidence: 99%

Variables Selection in the Ultraviolet, Visible and Near Infrared Range for Calibration of a Mixture of Vegetable Oils by Absorbance Spectra

Ходасевич

Borisevich

2021

Prib. metody izmer.

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The aim of the work was a multivariate calibration of the concentration of unrefined sunflower oil, considered as adulteration, in a mixture with flaxseed oil. The relevance of the study is due to the need to develop a simple and effective method for detecting the falsification of flaxseed oil which is superior in the content of essential polyunsaturated fatty acids to olive oil. A few works only are devoted to identifying adulteration of flaxseed oil, unlike olive oil.Multivariate calibration carried out using a model based on the principal component analysis, cluster analysis and projection to latent structures of absorbance spectra in UV, visible and near IR ranges. Calibration uses three methods for spectral variables selection: the successive projections algorithm, the method of searching combination moving window, and method for ranking variables by correlation coefficient.The application of the successive projections algorithm, ranking variables by correlation coefficient and searching combination moving window makes it possible to reduce the value of the root mean square error of prediction from 0.63 % for wideband projection to latent structures to 0.46 %, 0.50 %, and 0.03 %, respectively.The developed method of multivariate calibration by projection to latent structures of absorbance spectra in UV, visible and near IR ranges using the spectral variables selection by searching combination moving window is a simple and effective method of detecting adulteration of flaxseed oil.

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Using Raman spectroscopy and an exponential equation approach to detect adulteration of olive oil with rapeseed and corn oil

Cited by 64 publications

References 27 publications

Quick assessment of chicken spoilage based on hyperspectral NIR spectra combined with partial least squares regression

Quick assessment of chicken spoilage based on hyperspectral NIR spectra combined with partial least squares regression

Optical Feedback for Sensitivity Enhancement in Direct Raman Detection of Liquids

Variables Selection in the Ultraviolet, Visible and Near Infrared Range for Calibration of a Mixture of Vegetable Oils by Absorbance Spectra

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