How Chemometrics Can Fight Milk Adulteration

Combining capillary electrophoresis and chemometric tools for the straightforward determination of imidazolinone herbicides in plant-based milks

BACKGROUND

Highly polar herbicides, such as imidazolinones, are used for weed control to increase agricultural productivity and crop quality. However, their misapplication can lead to residues in ready-to-eat food with a potential health risk for consumers. Hence, the fast determination of these herbicides is necessary for timely action. In this work, an eco-friendly method based on capillary zone electrophoresis combined with chemometrics was used for the determination of imazapyr and imazamox in vegetable-based beverages such as soy and quinoa milk.

RESULTS

The analytical strategy consisted of only three steps: (i) protein precipitation prior to sample injection (ii) data pre-processing to reduce the background and make corrections on electrophoretic times shift, and (iii) resolution of fully overlapped capillary electrophoresis (CE) peaks by the well-known partial least square (PLS) algorithm, which extracts quantitative information attributed to the analytes. The method was successfully applied in the concentration range between 1.00 and 100 μg L-1 with coefficient of determination of the calibration (R2 cal) and prediction (R2 pred) > 0.90, residual prediction deviation of calibration (RPDcal) and of prediction (RPDpred) > 3, and relative error of prediction (REP) > 11 in the analyzed sample matrices, in the three built methods (quinoa samples, soy samples, and joint quinoa and soy samples).

CONCLUSION

The proposed methodology offers a simple and quick alternative for determining imidazolinones at trace concentrations in vegetable beverages, such as quinoa and soy milk, without complex sample preparation. The results were consistent with those obtained using more complex techniques, confirming the applicability of this method. © 2024 Society of Chemical Industry.

Rapid analysis technologies with chemometrics for food authenticity field: A review

In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.

Recent Advances in the Determination of Milk Adulterants and Contaminants by Mid-Infrared Spectroscopy

The presence of chemical contaminants, toxins, or veterinary drugs in milk, as well as the adulteration of milk from different species, has driven the development of new tools to ensure safety and quality. Several analytical procedures have been proposed for the rapid screening of hazardous substances or the selective confirmation of the authenticity of milk. Mid-infrared spectroscopy and Fourier-transform infrared have been two of the most relevant technologies conventionally employed in the dairy industry. These fingerprint methodologies can be very powerful in determining the trait of raw material without knowing the identity of each constituent, and several aspects suggest their potential as a screening method to detect adulteration. This paper reviews the latest advances in applying mid-infrared spectroscopy for the detection and quantification of adulterants, milk dilution, the presence of pathogenic bacteria, veterinary drugs, and hazardous substances in milk.

Application of ATR-FTIR Incorporated with Multivariate Data Analysis for Discrimination and Quantification of Urea as an Adulterant in UHT Milk

Urea is naturally present in milk, yet urea is added intentionally to increase milk's nitrogen content and shelf life. In this study, a total of 50 Ultra heat treatment (UHT) milk samples were spiked with known urea concentrations (0-5 w/v%). Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy with principal component analysis (PCA), discriminant analysis (DA), and multiple linear regression (MLR) were used for the discrimination and quantification of urea. The PCA was built using 387 variables with higher FL > 0.75 from the first PCA with cumulative variability (90.036%). Subsequently, the DA model was built using the same variables from PCA and demonstrated the good distinction between unadulterated and adulterated milk, with a correct classification rate of 98% for cross-validation. The MLR model used 48 variables with p-value < 0.05 from the DA model and gave R2 values greater than 0.90, with RMSE and MSE below 1 for cross-validation and prediction. The DA and MLR models were then validated externally using a test dataset, which shows 100% correct classification, and the t-test result (p > 0.05) indicated that the MLR could determine the percentage of urea in UHT milk within the permission limit (70 mg/mL). In short, the wavenumbers 1626.63, 1601.98, and 1585.5534 cm-1 are suitable as fingerprint regions for detecting urea in UHT milk.

Implementation of Chemometrics and Other Techniques as Means of Authenticity and Traceability to Detect Adulteration in Foods for the Protection of Human Health

The authenticity of foods of plant and animal origin is key to safeguarding both quality and safety aspects without jeopardizing consumers' health [...].