Detection of plant oil addition to cheese by synchronous fluorescence spectroscopy

Dankowska, Anna; Małecka, Maria; Kowalewski, Wojciech

doi:10.1007/s13594-015-0218-5

Cited by 41 publications

(17 citation statements)

References 27 publications

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“…The same researchers also applied SF spectroscopy for detecting plant oil addition to cheese (Dankowska et al 2015). They reported that the applied model could predict the level of adulteration with the RMSEP and RMSECV values of 1·5 and 1·8%, respectively (Dankowska et al 2015).…”

Section: Resultsmentioning

confidence: 99%

“…Dankowska et al (2014) reported the lowest LOD for adulteration of butter with palm and coconut oils as 5·5%. In their study about detecting plant oil addition to cheese using SF spectra, the lowest LOD values of 3·0 and 4·4% were reported for two different Δ λ values (Dankowska et al 2015). In the light of the previous information, it was shown that SF spectroscopy worked well in predicting the level of detection of cow milk addition to buffalo milk with high R 2 values and acceptable prediction errors and LOD values.…”

Section: Resultsmentioning

confidence: 99%

“…This enables a simplified spectrum providing information on several fluorophores. SF spectroscopy also minimises spectral overlaps and has greater selectivity which make it an attractive method for the analysis of complex systems (Patra & Mishra, 2002;Sikorska et al 2005;Sadecka & Tothova, 2007) This method was reported to work well in food classification, discrimination and analysis as well as detection of adulteration of food (Sikorska et al 2005;Blecker et al 2012;Dankowska et al 2014Dankowska et al , 2015Liu et al 2014). However, to the best of our knowledge, there is no study using SF spectroscopy for detecting the authenticity of buffalo milk.…”

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confidence: 99%

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Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods

Velioglu

Ercioglu

Boyaci

2017

Journal of Dairy Research

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This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods

Velioglu

Ercioglu

Boyaci

2017

Journal of Dairy Research

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“…Synchronous fluorescence and UV spectroscopies are techniques that are quick and avoid sample preparation steps apart from dilution; therefore they are simpler, less costly, and quicker than other widely used techniques. Numerous investigations prove the ability of fluorescence spectroscopy [11][12][13][14][15][16][17][18][19][20] and UV spectroscopy [21,22] to detect food adulteration.…”

Section: Introductionmentioning

confidence: 99%

Data fusion of fluorescence and UV spectroscopies improves the detection of cocoa butter adulteration

Dankowska

2017

Euro J Lipid Sci & Tech

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The fraudulent addition of cheaper plant oils to cocoa butter is a real issue for the chocolate industry. The potential of fluorescence and UV and data fusion of these spectroscopies for the detection of cocoa butter adulteration with cocoa butter equivalents (CBEs) is investigated here. Principal component regression (PCR) models have been used to calculate the level of adulteration. A classification model has been built with the help of the principal component analysis (PCA) and the linear discriminant analysis (LDA). The LDA analysis has been applied to fluorescence intensities and UV spectra of cocoa butter, cocoa butter equivalents, and their mixtures in order to examine classification ability. The best prediction ability of adulteration was obtained for PCR data fusion models with the lowest errors of calibration (RMSEC) and validation (RMSEV) of 3.7 and 4.7%. The best performance of the PCA‐LDA analysis has been observed for data fusion of fluorescence and UV intensities measurements at wavelength intervals of 10 and 30 nm. The LDA shows that data fusion can achieve 95.2% correct classifications (sensitivity) in the validation data set, while the corresponding results for individual spectroscopies range from 66.7–90.5%. The results demonstrate that fluorescence and UV spectroscopies complement each other, giving a synergistic effect for the detection of cocoa butter adulteration with cocoa butter equivalents. Practical applications: The aim of this research is to develop a quick and cheap method of discriminating between cocoa butter and cocoa butter equivalents. The obtained results are satisfactory for classification of genuine cocoa butter and cocoa butter equivalents and for detection of cocoa butter adulterations with cheaper cocoa butter equivalents. The method is an important technical support of public health against profit‐driven practices. Application of fluorescence and UV spectroscopies to the detection of cocoa butter adulteration with cocoa butter equivalent and the synergy between both spectroscopies are investigated. The best prediction ability of MLR models i obtained for the data fusion model with the errors of calibration and validation of 3.7 and 4.7%. Compared to individual spectroscopies, data fusion shows better discrimination ability of PCA‐LDA model with the highest classification accuracy equal 100.0 and 95.2% in the calibration and validation data sets. The results show that fluorescence and UV spectroscopies give a synergistic effect for the detection of cocoa butter adulteration.

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“…For example, fluorescence properties of aromatic amino acids of proteins (Dufour et al, 1994;Lakowicz et al, 1983), heterocyclic aromatic amines (Sahar et al, 2010) and retinol (Dufour et al, 1990) have been reported. Recently quality of cereal & cereal products (Zekovic et al, 2012), milk (Yazdi and Corredig, 2012), eggs, olive oil (Tena et al, 2012), fish (Olsen et al, 2006;Hassoun and Karoui, 2015), fruit spirits (Tomkova et al, 2015), cheese (Dankowska et al, 2015) and meat (Sahar et al, 2009a,b;Sahar and Dufour, 2015) has been assessed using fluorescence spectroscopy. Similarly this techniques has been used to detect the adulteration in extra virgin olive oil (Guzman et al, 2015), authentication of walnut oil (Li et al, 2015), classification of honey (Lenhardt et al, 2015) screening of fruits and vegetable and identification of microbes (Yoshimura et al, 2014) to ensure food safety.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of thermal changes in meat by synchronous fluorescence spectroscopy

Sahar

Rahman

Kondjoyan³

et al. 2016

Journal of Food Engineering

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Detection of plant oil addition to cheese by synchronous fluorescence spectroscopy

Cited by 41 publications

References 27 publications

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods

Data fusion of fluorescence and UV spectroscopies improves the detection of cocoa butter adulteration

Monitoring of thermal changes in meat by synchronous fluorescence spectroscopy

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