Determination of butter adulteration with margarine using Raman spectroscopy

Uysal, Reyhan Selin; Boyaci, İsmail Hakkı; Geniş, Hüseyin Efe; Tamer, Uğur

doi:10.1016/j.foodchem.2013.06.061

Cited by 86 publications

(38 citation statements)

References 27 publications

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“…Potential of ESM based on Raman spectroscopy to detect olive oil adulteration was shown in this study. 179 Adulteration of milk powder with melamine was determined quantitatively by using portable Raman spectroscopy coupled with PLS regression. Using PCA made it possible to obtain a clear separation of oil samples according to their different mono-unsaturated fatty acid, polyunsaturated fatty acid, and saturated fatty acid contents.…”

Section: Fermentation Productsmentioning

confidence: 99%

Dispersive and FT-Raman spectroscopic methods in food analysis

et al. 2015

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Raman spectroscopy is a powerful technique for molecular analysis of food samples. A fingerprint spectrum can be obtained for a target molecule by using Raman technology, as specific signals are obtained for chemical bonds in the target. In this way, food components, additives, processes and changes during shelf life, adulterations and numerous contaminants such as microorganisms, chemicals and toxins, can also be determined with or without the help of chemometric methods. The studies included in this review show that Raman spectroscopy has great potential for food analyses. In this review, we aim to bring together Raman studies on components, contaminants, raw materials, and adulterations of various food, and attempt to prepare a database of Raman bands obtained from food samples.

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Section: Fermentation Productsmentioning

confidence: 99%

Dispersive and FT-Raman spectroscopic methods in food analysis

et al. 2015

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“…It has also been possible to detect multiple adulterants including ammonium sulfate, dicyandiamide, melamine and urea in milk powder using Raman chemical imaging (Qin et al 2013). Milk fat adulteration is also a very common concern, however, several techniques have been developed to detect the adulteration based on Butyro Refractometer (Arora et al 1996), fluorescence spectroscopy (Ntakatsane, Liu, & Zhou, 2013), derivative spectroscopy (Jirankalgikar & De, 2014) and Raman spectroscopy (Uysal, Boyaci, Genis, & Tamer, 2013).…”

Section: Milk Adulteration With Other Compoundsmentioning

confidence: 99%

Common milk adulteration and their detection techniques

2016

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Food adulteration is a global concern and developing countries are at higher risk associated with it due to lack of monitoring and policies. However, this is one of the most common phenomena that has been overlooked in many countries. Unfortunately, in contrast to common belief, milk adulterants can pose serious health hazards leading to fatal diseases. This paper presents a detailed review of common milk adulterants as well as different methods to detect the adulterants both qualitatively and quantitatively. This study is organized to be an 'adulterant based' study instead of 'techniques based' one, where qualitative detection for most of the common adulterants are enlisted and quantitative detection methods are limited to few major adulterants of milk. Apart from regular techniques, recent development in these detection techniques have also been reported. Nowadays milk is being adulterated in more sophisticated ways that demands for cutting edge research for the detection of the adulterants. This review intends to contribute towards the common knowledge base regarding possible milk adulterants and their detection techniques.

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“…PLSR has also been used to predict dioxin content in fi sh meal samples using GC-FID profi les (BASSOMPIERRE et al, 2007), for the prediction of caffeine and chlorogenic acid content in instant coffee mixtures from IR and NIR spectra (FABIÁN et al, 1994), and for the prediction of adulteration level of caprine and ovine milk with bovine milk from pyrolysis mass spectrometry data (GOODACRE, 1997). Recently, PLSR was applied to develop a NIR based method for rapid prediction of sugar content of sugarcane plants (TAIRA et al, 2013) and for prediction of the adulteration level of butter with margarine using Raman spectroscopy (UYSAL et al, 2013).…”

Section: Partial Least Squares Regression (Plsr)mentioning

confidence: 99%

Trends in the application of chemometrics to foodomics studies

Khakimov¹,

Gürdeniz²,

Engelsen³

2015

Acta Alimentaria

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There is an ever-increasing trend in advanced food analysis and foodomics to use more and more sophisticated analytical platforms that generate large and complex data structures, which in turn require more and more sophisticated data analysis tools for converting data into information. The choice of multivariate chemometric methods is primarily determined by the design of the study, type of the data, and the conclusions sought. In order to validate multivariate models, scientists are required to have basic chemometric knowledge and to be familiar with the variance structure of the investigated data. This review outlines some of the key aspects of applying common chemometric methods used within foodomics and provides selected examples of current applications. The review aims to provide simple insight into various multivariate methods and to illustrate pros and cons of unsupervised and supervised methods. The main analytical platforms used in foodomics are briefl y discussed from the application point of view and the utilization of the generated data is illustrated. In addition, advanced data pre-processing tools, prior to multivariate analysis, are explained and relevant tools are demonstrated.

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Determination of butter adulteration with margarine using Raman spectroscopy

Cited by 86 publications

References 27 publications

Dispersive and FT-Raman spectroscopic methods in food analysis

Dispersive and FT-Raman spectroscopic methods in food analysis

Common milk adulteration and their detection techniques

Trends in the application of chemometrics to foodomics studies

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