Detection of animal fats in butter by differential scanning calorimetry: A pilot study

Comparing Different Chemometric Approaches to Detect Adulteration of Cold-Pressed Flaxseed Oil with Refined Rapeseed Oil Using Differential Scanning Calorimetry

Flaxseed oil is one of the best sources of n-3 fatty acids, thus its adulteration with refined oils can lead to a reduction in its nutritional value and overall quality. The purpose of this study was to compare different chemometric models to detect adulteration of flaxseed oil with refined rapeseed oil (RP) using differential scanning calorimetry (DSC). Based on the melting phase transition curve, parameters such as peak temperature (T), peak height (h), and percentage of area (P) were determined for pure and adulterated flaxseed oils with an RP concentration of 5, 10, 20, 30, and 50% (w/w). Significant linear correlations (p ≤ 0.05) between the RP concentration and all DSC parameters were observed, except for parameter h1 for the first peak. In order to assess the usefulness of the DSC technique for detecting adulterations, three chemometric approaches were compared: (1) classification models (linear discriminant analysis-LDA, adaptive regression splines-MARS, support vector machine-SVM, and artificial neural networks-ANNs); (2) regression models (multiple linear regression-MLR, MARS, SVM, ANNs, and PLS); and (3) a combined model of orthogonal partial least squares discriminant analysis (OPLS-DA). With the LDA model, the highest accuracy of 99.5% in classifying the samples, followed by ANN > SVM > MARS, was achieved. Among the regression models, the ANN model showed the highest correlation between observed and predicted values (R = 0.996), while other models showed goodness of fit as following MARS > SVM > MLR. Comparing OPLS-DA and PLS methods, higher values of R2X(cum) = 0.986 and Q2 = 0.973 were observed with the PLS model than OPLS-DA. This study demonstrates the usefulness of the DSC technique and importance of an appropriate chemometric model for predicting the adulteration of cold-pressed flaxseed oil with refined rapeseed oil.

Detection of goat body fat adulteration in pure ghee using ATR-FTIR spectroscopy coupled with chemometric strategy

Ghee forms an important component of the diet of human beings due to its rich flavor and high nutritive value. This high priced fat is prone to adulteration with cheaper fats. ATR-FTIR spectroscopy coupled with chemometrics was applied for determining the presence of goat body fat in ghee (@1, 3, 5, 10, 15 and 20% level in the laboratory made/spiked samples). The spectra of pure (ghee and goat body fat) and spiked samples were taken in the wavenumber range of 4000-500 cm^-1. Separated clusters of pure ghee and spiked samples were obtained on applying principal component analysis at 5% level of significance in the selected wavenumber range (1786-1680, 1490-919 and 1260-1040 cm^-1). SIMCA was applied for classification of samples and pure ghee showed 100% classification efficiency. The value of R² was found to be >0.99 for calibration and validation sets using partial least square method at all the selected wavenumber range which indicate that the model was well developed. The study revealed that the spiked samples of goat body fat could be detected even at 1% level in ghee.

Multivariate statistical analysis treatment of DSC thermal properties for animal fat adulteration

The adulteration of edible fats is a kind of fraud that impairs the physical and chemical features of the original lipid materials. It has been detected in various food, pharmaceutical and cosmeceutical products. Differential scanning calorimetry (DSC) is the robust thermo-analytical machine that permits to fingerprint the primary crystallisation of triacylglycerols (TAGs) molecules and their transition behaviours. The aims of this study was to assess the cross-contamination caused by lard concentration of 0.5-5% in the mixture systems containing beef tallow (BT) and chicken fat (CF) separately. TAGs species of pure and adulterated lipids in relation to their crystallisation and melting parameters were studied using principal components analysis (PCA). The results showed that by using the heating profiles the discrimination of LD from BT and CF was very clear even at low dose of less than 1%. Same observation was depicted from the crystallisation profiles of BT adulterated by LD doses ranging from 0.1% to 1% and from 2% to 5%, respectively. Furthermore, CF adulterated with LD did not exhibit clear changes on its crystallisation profiles. Consequently, DSC coupled with PCA is one of the techniques that might use to monitor and differentiate the minimum adulteration levels caused by LD in different animal fats.

A rapid reversed-phase thin layer chromatographic protocol for detection of adulteration in ghee (clarified milk fat) with vegetable oils

Detection of milk fat adulteration with foreign fats/oils continues to be a challenge for the dairy industry as well as food testing laboratories, especially in the present scenario of rampant adulteration using the scientific knowledge by unscrupulous persons involved in the trade. In the present investigation a rapid reversed-phase thin layer chromatographic (RP-TLC) protocol was standardized to ascertain the purity of milk fat. RP-TLC protocol did not show any false positive results in the genuine ghee (clarified butter fat) samples of known origin. Adulteration of ghee with coconut oil up to 7. 5 %, soybean oil, sunflower oil and groundnut oil up to 1 %, while, designer oil up to 2 % level could be detected using the standardized RP-TLC protocol. The protocol standardized is rapid and convenient to use.

Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages by Fourier transform infrared (FTIR) spectroscopy and chemometrics

Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages was developed by Fourier transform infrared (FTIR) spectrometry combined with chemometrics. Transmittance spectra ranging from 400 to 4000 cm⁻¹ of 73 Halal and 78 non-Halal Chinese ham sausages were measured. Sample preparation involved finely grinding of samples and formation of KBr disks (under 10 MPa for 5 min). The influence of data preprocessing methods including smoothing, taking derivatives and standard normal variate (SNV) on partial least squares discriminant analysis (PLSDA) and least squares support vector machine (LS-SVM) was investigated. The results indicate removal of spectral background and baseline plays an important role in discrimination. Taking derivatives, SNV can improve classification accuracy and reduce the complexity of PLSDA. Possibly due to the loss of detailed high-frequency spectral information, smoothing degrades the model performance. For the best models, the sensitivity and specificity was 0.913 and 0.929 for PLSDA with SNV spectra, 0.957 and 0.929 for LS-SVM with second derivative spectra, respectively.

Analysis of pork adulteration in beef meatball using Fourier transform infrared (FTIR) spectroscopy

Meatball is one of the favorite foods in Indonesia. The adulteration of pork in beef meatball is frequently occurring. This study was aimed to develop a fast and non destructive technique for the detection and quantification of pork in beef meatball using Fourier transform infrared (FTIR) spectroscopy and partial least square (PLS) calibration. The spectral bands associated with pork fat (PF), beef fat (BF), and their mixtures in meatball formulation were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure PF and BF. For quantitative analysis, PLS regression was used to develop a calibration model at the selected fingerprint regions of 1200-1000 cm(-1). The equation obtained for the relationship between actual PF value and FTIR predicted values in PLS calibration model was y = 0.999x + 0.004, with coefficient of determination (R(2)) and root mean square error of calibration are 0.999 and 0.442, respectively. The PLS calibration model was subsequently used for the prediction of independent samples using laboratory made meatball samples containing the mixtures of BF and PF. Using 4 principal components, root mean square error of prediction is 0.742. The results showed that FTIR spectroscopy can be used for the detection and quantification of pork in beef meatball formulation for Halal verification purposes.

Authenticity Assessment of Dairy Products

The authenticity of dairy products has become a focal point, attracting the attention of scientists, producers, consumers, and policymakers. Among many others, some of the practices not allowed in milk and milk products are the substitution of part of the fat or proteins, admixtures of milk of different species, additions of low-cost dairy products (mainly whey derivatives), or mislabeling of products protected by denomination of origin. A range of analytical methods to detect frauds have been developed, modified, and continually reassessed to be one step ahead of manufacturers who pursue these illegal activities. Traditional procedures to assess the authenticity of dairy products include chromatographic, electrophoretic, and immunoenzymatic methods. New approaches such as capillary electrophoresis, polymerase chain reaction, and isotope ratio mass spectrometry have also emerged alongside the latest developments in the former procedures. This work intends to provide an updated and extensive overview since 1991 on the principal applications of all these techniques together with their advantages and disadvantages for detecting the authenticity of dairy products. The scope and limits of different tools are also discussed.

Comparative differential scanning calorimetric analysis of vegetable oils: I. Effects of heating rate variation

The melting curves of 11 vegetable oils have been characterised. Vegetable oil samples that were cooled at a constant rate (5 degrees C/min) from the melt showed between one and seven melting endotherms upon heating at four different heating rates (1, 5, 10 and 20 degrees C/min) in a differential scanning calorimeter (DSC). Triacylglycerol (TAG) profiles and iodine value analyses were used to complement the DSC data. Generally, the melting transition temperature shifted to higher values with increased rates of heating. The breadth of the melting endotherm and the area under the melting peak also increased with increasing heating rate. Although the number of endothermic peaks was dependent on heating rate, the melting curves of the oil samples were not straightforward in that there was no correlation between the number of endothermic peaks and heating rates. Multiple melting behaviour in DSC experiments with different heating rates could be explained by: (1) the melting of TAG populations with different melting points; and (2) TAG crystal reorganisation effects. On the basis of the corollary results obtained, vegetable oils and fats may be distinguished from their offset-temperature (Toff) values in the DSC melting curves. The results showed that Toff values of all oil samples were significantly (p < 0.01) different in the melting curves scanned at four different scanning rates. These calorimetric results indicate that DSC is a valuable technique for studying vegetable oils.

Recent developments in food characterization and adulteration detection: technique-oriented perspectives

This review covers mainly publications that appeared in Analytical Abstracts (Royal Society of Chemistry) from January 1990 to February 2001. The number of publications on this topic continues to grow, and during the past three years (1998-2000) about 150 reviews and/or overviews have been published in the area of food. Numerous techniques and food matrices or chemical components are presented and discussed in these reviews. The present review is intentionally limited to eight techniques or classes of techniques and intends to be a "technique by technique" presentation of "what was used" or "what is used" to characterize food products and to detect their possible adulteration. The present review focuses on the following techniques: microscopic analysis; HPLC; GC, GC-(MS, FTIR); UV-visible spectrophotometry; AAS/AES, ICP-(AES, MS); IRMS, GC-IRMS, GC-C-IRMS; DSC; IR, mid-IR, and NMR (202 references). Emphasis is placed as much as possible on chemometrical treatment of analytical data, which are commonly used to achieve the final objective, either food characterization or adulteration detection. Finally, a brief description is given of the new generation of analytical systems that combine powerful analytical techniques and powerful computer software for a best extraction of the information from analytical data.

Use of differential scanning calorimetry (DSC) as a new technique for detection of adulteration in honeys. 1. Study of adulteration effect on honey thermal behavior

Differential scanning calorimetry (DSC) was used to study the thermal behavior of authentic honeys (Lavandula, Robinia, and Fir honeys) and industrial sugar syrups. Thermal or thermochemical parameters such as the glass transition temperature (Tg), enthalpies of fusion (DeltaH(fus)), and heat capacity variation (DeltaC(p)) were measured. The syrups and honeys showed significant differences in thermal phenomena, as well as in their amplitude and position on the temperature scale. Results showed good reproducibility of the method for all samples studied. The effect of adulteration of honey with different amounts of syrup (5, 10, 20, 40, and 60%) was investigated. A linear relationship was found between the percentage of added syrup and the glass transition temperature. A similar relationship was obtained from the enthalpy of fusion results in the temperature range of 40-90 degrees C. Under applied conditions, the effects of adulteration of honeys by industrial syrups appeared to be detectable from a level as low as 5%.

Trends in research for alternate uses of milk fat

During the past 2 yr, sales of butter have increased, and the inventory of milk fat in the US has decreased. However, still fresh in memory are the large inventories of butter and low prices for milk fat. Although economic peaks and valleys are a result of consumer preferences, research in the area of milk lipids is very active. This paper is a limited review of the continuing research trends and technological advances in the field of lipids, particularly milk fat. The modification of milk fat composition through cattle nutrition, fractionation by melt crystallization and supercritical fluid extraction, blending, interesterification, and glycerolysis as well as the emerging importance of analysis of lipids are some of the areas for which active research promises future advances in milk fat technology.