Development of mathematical model for prediction of adulteration levels of cow ghee with vegetable fat using image analysis

Retardation of oxidative rancidity in ghee adding orange peel powder at different storage temperature

This study is aimed to determine and compare the antioxidant activity of Orange Peel Powder (OPP) in ghee at different temperatures (4 °C, 25 °C and 60 °C) for divergent storage periods (0, 7, 14 and 21 days). To compare the antioxidant potentiality, synthetic antioxidant BHA (Butylated Hydroxy Anisole) is used. Twelve ghee samples were prepared where one was control, another one was BHA treated and the rest ten were admixing OPP in ghee at different ratios. After sensory evaluation three highest scored ghee samples (0.5%. 1.0% and 1.5%) were selected. Samples were analyzed for peroxide (PV), thiobarbituric acid (TBA), free fatty acids (FFA) value and radical scavenging activity. Though storage temperature and storage period were increased OPP treated ghee samples peroxide, TBA and FFA values were lowered significantly compared to control samples. Moreover, 1.0% and 1.5% OPP treated ghee samples such values were lowered than BHA treated ghee samples and all these are on the favor of ghee quality. OPP treated ghee samples' DPPH quench potentiality is also stronger than BHA treated ghee samples. Therefore, OPP is a great source of antioxidants and this can be used in ghee as a natural source of antioxidants.

How Chemometrics Can Fight Milk Adulteration

Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.

Green tea catechin loaded niosomes: formulation and their characterization for food fortification

The main aim of this study was to deliver green tea catechins with enhanced bioavailability using niosomal system. Catechins-loaded niosomes were prepared using food grade surfactant, Tween 60 and membrane stabilizers namely, lauryl alcohol, cetyl alcohol and cholesterol by thin film hydration technique. Catechins-loaded niosomes exhibited a hydrodynamic diameter of 58.48 nm with a narrow size distribution (PDI = 0.13) and zeta potential of - 31.75 mV, suggestive for homogeneity and good stability. Niosomes entrapped about 85.82% of catechin and showed sustained release under simulated GI conditions. Morphology of niosomal vesicles were carried out using scanning electron microscopy-energy X-ray dispersion spectroscopy, transmission electron microscopy and atomic force microscopy. Fourier-transform infrared spectroscopy and High-performance liquid chromatography analysis confirmed successful encapsulation of catechins. Antioxidant activity of catechins was retained in the niosomal form. Fortification of milk with catechins loaded niosomes showed no significant changes on sensory, physicochemical properties and exhibited higher antioxidant property.

Assessing Compositional and Quality Parameters of Unconcentrated and Refractive Window Concentrated Milk Based on Color Components

In this study, a multiple linear regression equation was developed to measure and predict quality parameters of unconcentrated and concentrated milk based on color components. The viscosity, density, pH, moisture, and fat content could be measured using image processing technology. The multiple linear regression model had a good fitting on experimental data considering the limited errors (0.00–1.12%), standard deviation (0.000–0.043), and root mean square error (0.0007–0.3721). Therefore, these models can be used to predict the quality parameters of milk, including fat percentage, pH, viscosity, density, and moisture content, based on color components of unconcentrated and concentrated milk. The maximum and minimum of color change were 12.28 and 5.96, respectively. The values of browning index were also well-predicted and were within the standard limits. The non-destructive and quick procedure that proposed in this study showed a percentage of accuracy in assessing and predicting the quality parameters milk based on color components. Overall, the color correlates with different compositional and physical characteristics, and provide a possible internet of things (IoT)-based approach to accompany the conventional approaches in the future after further evaluation at large scale for various types of milks subjected to various processes.

A barcode-DNA analysis method for the identification of plant oil adulteration in milk and dairy products

In the present work, a barcode-DNA analysis method is described for the detection of plant oil adulteration in milk and dairy products. The method relies on the fact that plant DNA should not be present in readily detectable amounts in a dairy product unless it contains undeclared plant material. Thus, a universal plant barcode is chosen as the target to be amplified from dairy samples. Accordingly, barcode PCR-CE (PCR-capillary electrophoresis) assays are described, which do not require preliminary information on the species source of the adulterant oil type. Two PCR-CE assays, one operating on the plastid trnL (UAA) intron and the other targeting its inner P6 loop in nested format, were shown to detect corn, soybean, rapeseed and sunflower oils in clarified butter, milk and yogurt. Both barcodes are robustly amplified with extremely conserved primers. While the intron provides the species discrimination ability, the P6 loop provides superior detection sensitivity.