Rapid detection and quantification of soya bean oil and common sugar in bovine milk using attenuated total reflectance-fourier transform infrared spectroscopy

Rapid discrimination of Panax ginseng powder adulterated with various root plants by FT-IR spectroscopy coupled with multivariate analysis

Panax ginseng powder adulterated with other root plants (arrowroot, bellflower, and lance asiabell) was discriminated using Fourier transform infrared (FT-IR) spectroscopy, combined with multivariate analysis. Principal component analysis visually diagnosed the adulteration by showing two distinct clusters based on presence of adulteration. Wavenumber regions (1000 cm-1 and 3300 cm-1) selected from the loading plot associated with the vibration of OH and CH bond in ginsenoside and aromatic compounds. A quantitative model for the content of ginsenosides and specific aromatic compounds as indicators of pure ginseng powder, was developed based on partial least square regression analysis. The performance of the prediction model preprocessed with the Savizky-Golay 1st derivative was improved to R2 of 0.9650, 0.9635, and 0.9591 for Rb1, Rc, and β-Panasinsene, respectively. Therefore, FT-IR technology makes it possible to rapidly authenticate pure ginseng product based on the ginsenoside contents and aroma compound.

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.

Rapid detection and quantification of sucrose adulteration in cow milk using Attenuated total reflectance-Fourier transform infrared spectroscopy coupled with multivariate analysis

Adulteration of milk to gain economic benefit has become a common practice in recent years. Sucrose is illegally added in milk to reconstitute its compositional requirement by improving the total solid contents. The present study is aimed to use FTIR spectroscopy in combination with multivariate chemometric modelling for the differentiation and quantification of sucrose in cow milk. Pure milk and adulterated milk spectra (0.5-7.5% w/v) were observed in the spectral region 4000-400 cm^-1. Principal component analysis (PCA) was used for the discrimination of pure milk and adulterated milk. Soft independent modelling of class analogy (SIMCA) was able to classify test samples with a classification efficiency of 100%. Partial least square regression (PLS-R) and principle component regression (PCR) models were established for normal spectra, 1st derivative and 2nd derivative for the quantification of sucrose in milk. PLS-R model (normal spectra) in the combined wavenumber range of 1070-980 cm^-1 showed the best prediction based on parameters like coefficient of determination (R²) (Cal: 0.996; Val: 0.993), RMSE (Cal: 0.15% w/v; Val: 0.20% w/v), RE% (Cal: 4.9% w/v; Val: 5.1% w/v) and RPD (13.40). This method has a detection level of 0.5% w/v sucrose adulteration.

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.