Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies

Testing adulterated liquid-egg: developing rapid detection techniques based on colorimetry, electrochemistry, and interfacial fingerprinting

To develop rapid detection techniques for liquid eggs' adulteration, three types of adulterations were considered: water dilution, manipulation of yolk ratio in whole egg, and blending different varieties of egg white or yolk. Objective: Establish detection techniques utilizing colorimetry, electrochemistry, and interfacial fingerprinting for these adulterations, respectively. Results: Colorimetry allows for detection (1 min·sample-1) of water dilution through linear (R2 ≥ 0.984) and exponential fitting (R2 ≥ 0.992); Electrochemistry enables detection (6 min·sample-1, R2 ≥ 0.979) of the adulteration of yolk ratio in whole egg; Interfacial fingerprinting technique effectively detects (detection duration: 10 min·sample-1, detection limit: 1.0-10.0 wt%) the adulteration of different varieties of egg white. Subsequently, through 3D-fluorescence microscopy (interface height variation: 22.49-573.45 μm), interfacial tension variation (65.54-35.48 mN·m-1), contact angle variation (89.7°-32.9°), particle size range (free water: 0.94-14.29 μm; protein aggregation: 6.57-10.76 μm), and etc., interfacial fingerprinting mechanism was elucidated. This research contributes novel insights into the detection of adulteration in liquid eggs.

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers' health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.

Spectroscopic technologies and data fusion: Applications for the dairy industry

Increasing consumer awareness, scale of manufacture, and demand to ensure safety, quality and sustainability have accelerated the need for rapid, reliable, and accurate analytical techniques for food products. Spectroscopy, coupled with Artificial Intelligence-enabled sensors and chemometric techniques, has led to the fusion of data sources for dairy analytical applications. This article provides an overview of the current spectroscopic technologies used in the dairy industry, with an introduction to data fusion and the associated methodologies used in spectroscopy-based data fusion. The relevance of data fusion in the dairy industry is considered, focusing on its potential to improve predictions for processing traits by chemometric techniques, such as principal component analysis (PCA), partial least squares regression (PLS), and other machine learning algorithms.

Mass spectrometry-based protein and peptide profiling for food frauds, traceability and authenticity assessment

The ever-growing use of mass spectrometry (MS) methodologies in food authentication and traceability originates from their unrivalled specificity, accuracy and sensitivity. Such features are crucial for setting up analytical strategies for detecting food frauds and adulterations by monitoring selected components within food matrices. Among MS approaches, protein and peptide profiling has become increasingly consolidated. This review explores the current knowledge on recent MS techniques using protein and peptide biomarkers for assessing food traceability and authenticity, with a specific focus on their use for unmasking potential frauds and adulterations. We provide a survey of the current state-of-the-art instrumentation including the most reliable and sensitive acquisition modes highlighting advantages and limitations. Finally, we summarize the recent applications of MS to protein/peptide analyses in food matrices and examine their potential in ensuring the quality of agro-food products.

FTIR spectroscopy with chemometrics for determination of tylosin residues in milk

BACKGROUND

Contamination of milk by antibiotic residues represents risks to the health of consumers; therefore they should be monitored. The objective of this study was to propose a methodology for the determination of tylosin residues directly in fluid milk based on mid-infrared spectroscopy associated with chemometrics, using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy associated with multilayer perceptron network (MLP) and partial least squares (PLS).

RESULTS

MLP was shown to be adequate for the discrimination of milk samples contaminated with tylosin below or equal to or above the maximum residue limit (MRL), with an accuracy greater than 99%, using FTIR spectra data. PLS was shown to be appropriate for the prediction of the very low concentrations (0-100 μg L^-1 ) of tylosin residues in milk using FTIR spectra data. PLS models with high correlation coefficients (R > 0.99) were generated.

CONCLUSION

FTIR with chemometrics proved to be a non-destructive, efficient and low-cost method for the investigation and quantification of tylosin residues directly in fluid milk. © 2020 Society of Chemical Industry.

Analysis of A1-type and A2-type β-casein in Maiwa Yak and Pien-niu milk by HPLC-high-resolution MS and tandem MS

In this study, a peptide-based method employing ultra high performance liquid chromatography electrostatic field orbitrap high-resolution mass spectrometry and triple quadrupole mass spectrometry was developed for quantification of A1-type and A2-type β-casein in milk from Yak, cows, and their offspring of crosses, Pien-niu. The specific peptides of A1-type and A2-type β-casein were screened and confirmed by protein software after analysis of high-resolution mass spectrometry. The multiple reaction monitoring method was established based on the qualitative results, and isotope-label peptides were used as internal standards. The linear correlation coefficients of this method were >0.99. The relative standard deviations of repeatability test were 0.2-3.6%. The recovery rate ranged from 93.3 to 114.4% with relative standard deviations <6% at three different spiking levels. The method was applied to analyze 45 milk samples from different species. The results showed that β-casein in Yak and Pien-niu milk was about 30% higher than that in cow milk. Furthermore, the β-casein in the Yak milk only contains A2-type β-casein. A1-type and A2-type β-casein coexist in most samples of Pien-niu and cow milk, a few samples contain only one type of β-casein. These results provide further understanding in nutritional value of milk from Yak and Pien-niu.

Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies

Detection of the presence of milk powder in liquid whole milk is challenging due to their similar chemical components. In this study, a sensitive and robust approach has been developed and tested for potential utilization in discriminating adulterated milk from liquid whole milk by analyzing the intact protein and hydrolyzed peptide using ultra‐performance liquid chromatography with quadrupole time‐of‐flight mass spectrometer (UPLC‐QTOF‐MS) fingerprints combined with data fusion. Two different datasets from intact protein and peptide fingerprints were fused to improve the discriminating ability of principle component analysis (PCA). Furthermore, the midlevel data fusion coupled with PCA could completely distinguish liquid whole milk from the milk. The limit of detection of milk powder in liquid whole milk was 0.5% (based on the total protein equivalence). These results suggested that fused data from intact protein and peptide fingerprints created greater synergic effect in detecting milk quality, and the combination of data fusion and PCA analysis could be used for the detection of adulterated milk.