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

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 cur...

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Veröffentlicht in:Journal of dairy research 2017-05, Vol.84 (2), p.214-219
Hauptverfasser: Durakli Velioglu, Serap, Ercioglu, Elif, Boyaci, Ismail Hakki
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container_title Journal of dairy research
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creator Durakli Velioglu, Serap
Ercioglu, Elif
Boyaci, Ismail Hakki
description 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.
doi_str_mv 10.1017/S0022029917000073
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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.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><pmid>28325170</pmid><doi>10.1017/S0022029917000073</doi><tpages>6</tpages></addata></record>
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subjects adulterated products
Animals
Authenticity
Buffalo
buffalo milk
Buffaloes
CAD
calibration
Cattle
Chemistry
Classification
Computer aided design
Cow's milk
cows
Dairy industry
Dairy products
Design of experiments
detection limit
Discriminant analysis
Female
Fluorescence
fluorescence emission spectroscopy
Fluorescence spectroscopy
Food
Food Contamination - analysis
foods
least squares
Least-Squares Analysis
Limit of Detection
Mathematical models
Mean square values
Methods
Milk
Milk - chemistry
Milk - classification
Multivariate analysis
Nitrogen
prediction
Principal Component Analysis
Principal components analysis
raw materials
Reproducibility of Results
Root-mean-square errors
Scientific papers
Spectrometry, Fluorescence - methods
Spectroscopy
title 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
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