Chemometric Tools and Ftir-Atr Spectroscopy Applied in Milk Adulterated with Cheese Whey (original) (raw)
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An assessment of Fourier Transform Infrared spectroscopy to identify adulterated raw milk in Brazil
International Journal of Dairy Technology, 2011
The aim of this study was to evaluate the application of the methodology of Fourier Transform Infrared spectroscopy (FT-IR) to the identification of adulterated raw milk. A reference spectrum with 800 representative samples of the study area was built. Through the analysis of principal components, equations with a distinct number of factors were developed. For the validation test, 100 adulterated samples were used at three different concentrations of sodium bicarbonate, sodium citrate and non-acid cheese whey. Results indicate that the FT-IR can be used for the identification of adulterated milk with 0,05% and 0,075% of sodium bicarbonate and citrated respectively.
Journal of the Brazilian Chemical Society, 2018
The objective of this study was to use Fourier transform infrared (FTIR) spectroscopy combined with multivariate analysis to identify adulterations in raw milk and in samples from producers. Five levels of concentration of sodium bicarbonate, sodium hydroxide, hydrogen peroxide, starch, sucrose and urea were used. A total of 620 samples previously adulterated, frozen and lyophilized were analyzed in FTIR-attenuated total reflection (ATR) equipment and 15 peaks of the spectra were obtained. With the multiple linear regression method for samples adulterated with sodium bicarbonate, sucrose and urea, a coefficient greater than 75% was obtained, and with artificial neural networks all adulterated samples obtained a percentage of correctness greater than 76.6%, making it possible to identify adulterants from 0.1%. Of the 249 samples of producers analyzed, 2.4% were adulterated. With the use of FTIR allied to the multivariate analysis as a screening method, it was possible to obtain a satisfactory classification for the adulterated samples in this study.
2010
The authenticity of milk and milk products is important and has extended health, cultural, and financial implications. Current analytical methods for the detection of milk adulteration are slow, laborious, and therefore impractical for use in routine milk screening by the dairy industry. Fourier transform infrared (FT-IR) spectroscopy is a rapid biochemical fingerprinting technique that could be used to reduce this sample analysis period significantly. To test this hypothesis we investigated 3 types of milk: cow, goat, and sheep milk. From these, 4 mixtures were prepared. The first 3 were binary mixtures of sheep and cow milk, goat and cow milk, or sheep and goat milk; in all mixtures the mixtures contained between 0 and 100% of each milk in increments of 5%. The fourth combination was a tertiary mixture containing sheep, cow, and goat milk also in increments of 5%. Analysis by FT-IR spectroscopy in combination with multivariate statistical methods, including partial least squares (PLS) regression and nonlinear kernel partial least squares (KPLS) regression, were used for multivariate calibration to quantify the different levels of adulterated milk. The FT-IR spectra showed a reasonably good predictive value for the binary mixtures, with an error level of 6.5 to 8% when analyzed using PLS. The results improved and excellent predictions were achieved (only 4-6% error) when KPLS was employed. Excellent predictions were achieved by both PLS and KPLS with errors of 3.4 to 4.9% and 3.9 to 6.4%, respectively, when the tertiary mixtures were analyzed. We believe that these results show that FT-IR spectroscopy has excellent potential for use in the dairy industry as a rapid method of detection and quantification in milk adulteration.
A straightforward and quick technique for discovery and measurement of milk corruption has been created utilizing mid-infrared (MIR) spectrometers. Milk samples was purchased from local supermarkets and spiked with tap water, hydrogen peroxide, glucose, urea and formaldehyde in different concentrations in milk. Spectral data was collected using mid-infrared (MIR) spectrometers. Partial least-square regression (PLSR) has been used to estimate adulteration level and results showed high coefficients of determination (R 2 ) and standard error of predication (SEP). The use of Fourier transform infrared (FTIR) spectroscopy coupled with chemo metric techniques to differentiate of milk adulteration. These results proved that FTIR spectroscopy in combination with multivariate calibration can be used for the detection of milk adulteration. The proposed technique is quick, non-dangerous, straightforward and simple to utilize.
FTMIR-PLS as a promising method for rapid detection of adulteration by waste whey in raw milk
Dairy Science & Technology, 2015
In this paper, we propose a feasible, sample preparation free and fast validated methodology for the detection and quantitative analysis of Minas Frescal cheese waste whey as an adulterant in raw milk using mid-infrared spectroscopy with Fourier transform (FTMIR) along with the chemometric technique of partial least squares (PLS). The PLS model was built in accordance with Brazilian and international guidelines and was analytically validated through the estimate of figures of merit parameters, in accordance with ASTM E1655-05 standard. This model showing an effective and feasible method for quality control of raw milk can be adopted for the quality control by regulatory agencies, as shown by the satisfactory results obtained for all estimated figures of merit with no systematic errors and low errors, with R=0.99.
Microchemical Journal, 2021
Adulteration of higher priced milks with cheaper ones to obtain extra profit can be the cause of adverse health effects as well as economic loss. In this study, it was aimed to differentiate goat-cow and buffalo-cow milk mixtures and also to estimate the critical quality parameters of these milks by the evaluation of Fourier-transform infrared (FTIR) spectroscopic data with chemometric methods. Raw goat and buffalo milks were mixed with cow milk at 1-50% (v/v) concentrations and FTIR spectra of the pure and mixed samples were obtained at 4000-650 cm − 1. Orthogonal partial least square discriminant analysis (OPLS-DA) resulted in differentiation of goat-cow and buffalo-cow milk mixtures with 93% and 91% correct classification rates, respectively. Detection level for mixing is determined as higher than 5% for both milks. Total fat, protein, lactose and non-fat solid contents were predicted from FTIR spectral data of the combination of three types of milks by partial least square models with R 2 values of 0.99. As a result, FTIR spectroscopy provides rapid and simultaneous detection of adulteration and prediction of quality parameters regardless of the milk type.
This paper proposed a new screening method for the simultaneous detection of five common adulterants in raw cow milk by using attenuated total reflectance (ATR) mid infrared spectroscopy and multivariate supervised classification (partial least squares discrimination analysis -PLSDA). The method was able to detect the presence of the adulterants water, starch, sodium citrate, formaldehyde and sucrose in milk samples containing from one up to five of these analytes, in the range of 0.5-10% w/v. A multivariate qualitative validation was performed, estimating specific figures of merit, such as false positive and false negative rates, selectivity, specificity and efficiency rates, accordance and concordance. The proposed method does not need any sample pretreatment, requires a small amount of sample (30 lL), is fast and simple, being suitable for the control of raw milk in a dairy industry or for the quality inspection of commercialized milk.
This paper proposed a new screening method for the simultaneous detection of five common adulterants in raw cow milk by using attenuated total reflectance (ATR) mid infrared spectroscopy and multivariate supervised classification (partial least squares discrimination analysis -PLSDA). The method was able to detect the presence of the adulterants water, starch, sodium citrate, formaldehyde and sucrose in milk samples containing from one up to five of these analytes, in the range of 0.5-10% w/v. A multivariate qualitative validation was performed, estimating specific figures of merit, such as false positive and false negative rates, selectivity, specificity and efficiency rates, accordance and concordance. The proposed method does not need any sample pretreatment, requires a small amount of sample (30 lL), is fast and simple, being suitable for the control of raw milk in a dairy industry or for the quality inspection of commercialized milk.
The Application of FTIR Spectroscopy and Chemometrics for the Authentication Analysis of Horse Milk
International Journal of Food Science
Expensive milk such as horse’s milk (HM) may be the target of adulteration by other milk such as goat’s milk (GM) and cow’s milk (CM). FTIR spectroscopy in combination with chemometrics of linear discriminant analysis (LDA) and multivariate calibrations of partial least square regression (PLSR) and principal component regression (PCR) was used for authentication of HM from GM and CM. Milk was directly subjected to attenuated total reflectance (ATR) spectral measurement at midinfrared regions (4000-650 cm-1). Results showed that LDA could make clear discrimination between HM and HM adulterated with CM and GM without any misclassification observed. PLSR using 2nd derivative spectra at 3200-2800 and 1300-1000 cm-1 provided the best model for the relationship between actual values of GM and FTIR predicted values than PCR. At this condition, R 2 values for calibration and validation models obtained were 0.9995 and 0.9612 with RMSEC and RMSEP values of 0.0093 and 0.0794. PLSR using normal...
Journal of agricultural and food chemistry, 2014
Forty-one samples of skim milk powder (SMP) and nonfat dry milk (NFDM) from 8 suppliers, 13 production sites, and 3 processing temperatures were analyzed by NIR diffuse reflectance spectrometry over a period of 3 days. NIR reflectance spectra (1700-2500 nm) were converted to pseudoabsorbance and examined using (a) analysis of variance-principal component analysis (ANOVA-PCA), (b) pooled-ANOVA based on data submatrices, and (c) partial least-squares regression (PLSR) coupled with pooled-ANOVA. ANOVA-PCA score plots showed clear separation of the samples with respect to milk class (SMP or NFDM), day of analysis, production site, processing temperature, and individual samples. Pooled-ANOVA provided statistical levels of significance for the separation of the averages, some of which were many orders of magnitude below 10(-3). PLSR showed that the correlation with Certificate of Analysis (COA) concentrations varied from a weak coefficient of determination (R(2)) of 0.32 for moisture to m...