Bovine milk powder adulteration with vegetable oils or fats revealed by MALDI-QTOF MS

Validation of the Methods for the Non-Milk Fat Detection in Artificially Adulterated Milk with Palm Oil

Dairy products are among the most adulterated food products. Due to the current high price of milk fat, it has been replaced by low-cost oils, especially those oils that have the same fatty acid profile as milk fat. This study intends to confirm the lowest level of palm oil added to milk and validate various methods for detecting palm oil in milk, including gas chromatography, reverse-phase high performance liquid chromatography, and Fourier transform infrared. Different amounts of palm oil were prepared in the final liquid milk using five treatments of fresh milk cream and an emulsion of palm oil. The results of this study showed that the values of the saponification number decreased with the increase in the percentages of added palm oil. There was no decrease under the limits of the Egyptian standards until the addition of 50% palm oil. The iodine number is less sensitive than the saponification number in the detection of palm oil. Butyro refractometer reading is unable to detect the palm oil in milk. The fatty acid profile in milk determined by gas chromatography correlated well with the addition of palm oil. Furthermore, there is a positive relationship between the level of added palm oil and the β-sitosterol content as measured by reverse-phase high-performance liquid chromatography. There was no relationship between the behavior of the spectra resulting from Fourier transform infrared spectroscopy and the presence of palm oil.

Biomolecular Profiling by MALDI-TOF Mass Spectrometry in Food and Beverage Analyses

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has frequently been applied to the analysis of biomolecules. Its strength resides not only in compound identification but particularly in acquiring molecular profiles providing a high discriminating power. The main advantages include its speed, simplicity, versatility, minimum sample preparation needs, and a relatively high tolerance to salts. Other benefits are represented by the possibility of automation, high throughput, sensitivity, accuracy, and good reproducibility, allowing quantitative studies. This review deals with the prominent use of MALDI-TOF MS profiling in food and beverage analysis ranging from the simple detection of sample constituents to quantifications of marker compounds, quality control, and assessment of product authenticity. This review summarizes relevant discoveries that have been obtained with milk and milk products, edible oils, wine, beer, flour, meat, honey, and other alimentary products. Marker molecules are specified: proteins and peptides for milk, cheeses, flour, meat, wine and beer; triacylglycerols and phospholipids for oils; and low-molecular-weight metabolites for wine, beer and chocolate. Special attention is paid to sample preparation techniques and the combination of spectral profiling and statistical evaluation methods, which is powerful for the differentiation of samples and the sensitive detection of frauds and adulterations.

A Comparative Study of Milk Fat Extracted from the Milk of Different Goat Breeds in China: Fatty Acids, Triacylglycerols and Thermal and Spectroscopic Characterization

Goat milk (GM) is an excellent alternative to cow milk and has recently been used in commercial infant formula preparation due to its superior fat composition. Here, the fatty acid (FA) composition, triacylglycerol (TAG) molecular species, thermal behavior and infrared spectra of extracted milk fat from the milk of the two main breeds of dairy goat bred in China (Guanzhong GM (GZG) and Xinong Saanen GM (XSG)) are investigated. Gas chromatography, Fourier-transform infrared spectroscopy, differential scanning calorimetry and ultra-performance convergence chromatography with quadrupole time-of-flight mass spectrometry are applied. The obtained results evidence significant fat compositional differences based on the breed that produced the considered GM. The major FAs in both GM fats were capric (C10:0), myristic (C14:0), palmitic (C16:0), stearic (C18:0) and oleic (C18:1 n-9c). GZG presented a higher content of medium-chain saturated FAs, while XSG had higher unsaturated FAs with higher ratios of L/Ln and n-6/n-3. A total of 339 and 359 TAGs were detected and quantified in GZG and XSG, and the major TAGs were those of m/z 740.6712 (14.10 ± 0.27%) and m/z 684.6094 (10.94 ± 0.02%), respectively. Milk TAGs of GZG and XSG showed 24–54 and 26–54 total acyl carbon numbers with a 0–4 and 0–5 double bond number at 68 and 72 various retention times, respectively. Thermal analysis showed that all GM fat samples melted below normal body temperature. Infrared spectra revealed higher absorption values of GZG milk fat. This study provides valuable information to the dairy industry sector about GM fat produced in China, assessing the appropriateness of Chinese GM fat to be applied in Chinese infant formula.

A Comprehensive Review of Lipidomics and Its Application to Assess Food Obtained from Farm Animals

Lipids are one of the major macronutrients essential for adequate growth and maintenance of human health. Their structure is not only complex but also diverse, which makes systematic and holistic analyses challenging; consequently, little is known regarding the relationship between phenotype and mechanism of action. In recent years, rapid advancements have been made in the fields of lipidomics and bioinformatics. In comparison with traditional approaches, mass spectrometry-based lipidomics can rapidly identify as well as quantify >1,000 lipid species at the same time, facilitating comprehensive, robust analyses of lipids in tissues, cells, and body fluids. Accordingly, lipidomics is now being widely applied in various fields, particularly food and nutrition science. In this review, we discuss lipid classification, extraction techniques, and detection and analysis using lipidomics. We also cover how lipidomics is being used to assess food obtained from livestock and poultry. The information included herein should serve as a reference to determine how to characterize lipids in animal food samples, enhancing our understanding of the application of lipidomics in the field in animal husbandry.

Significantly Different Lipid Profile Analysis of Litopenaeus vannamei under Low-Temperature Storage by UPLC-Q-Exactive Orbitrap/MS

Low-temperature storage is one of the most important preservation methods for aquatic product storage. However, the effects of low-temperature storage on the lipid profiles of shrimp are unclear. Herein, UPLC-Q-Exactive Orbitrap/MS combined with LipidSearch software was applied to analyze the effect of three low storage temperatures (4 °C, -2 °C, and -18 °C) on the lipidomics of Litopenaeus vannamei. A total of 15 lipid classes were analyzed, and PC, PE, DG, and TG accounted for vast majority of peak areas. Furthermore, 531 individual lipid variables enriched in 12 metabolic pathways were identified via bioinformatics analysis methods. A total of 56 significantly different lipid molecular species (55 belonging to PC, PE, DG, and TG) were selected as potential biomarkers of lipid oxidation via correlational analysis between physical properties (texture and color) and individual lipid variables. The results indicated that the three low storage temperatures caused different effects on the lipidomics profile of L. vannamei, and PC, PE, DG, and TG could become potential focuses in further studies of lipid oxidation in L. vannamei.

Simple chromogenic test for detection of adulterated milk with vegetable oil at village milk collection center- A preliminary study

In the present investigation, a novel chromogenic test has been developed to ascertain the presence of vegetable oil in milk. This standardized protocol did not show any false-positive results in the genuine milk samples. Adulteration of milk with vegetable oil @ 1% level could be detected by this chromogenic test protocol. This said protocol is convenient to use in the rural dairy industry especially rural-based milk collection centers; as no costly instrument or trained manpower is required for this said test.

MALDI-TOF Mass Spectrometry Applications for Food Fraud Detection

Chemical analysis of food products relating to the detection of the most common frauds is a complex task due to the complexity of the matrices and the unknown nature of most processes. Moreover, frauds are becoming more and more sophisticated, making the development of reliable, rapid, cost-effective new analytical methods for food control even more pressing. Over the years, MALDI-TOF MS has demonstrated the potential to meet this need, also due to a series of undeniable intrinsic advantages including ease of use, fast data collection, and capability to obtain valuable information even from complex samples subjected to simple pre-treatment procedures. These features have been conveniently exploited in the field of food frauds in several matrices, including milk and dairy products, oils, fish and seafood, meat, fruit, vegetables, and a few other categories. The present review provides a comprehensive overview of the existing MALDI-based applications for food quality assessment and detection of adulterations.

Analysis of lipidomics profile of rice and changes during storage by UPLC-Q-extractive orbitrap mass spectrometry

Rice is one of major staple food worldwide; however, lipid profile of rice and changes during storage remain unclear. Herein, an UPLC-Q-Exactive Orbitrap/MS method was applied for comprehensive lipidomics analysis of rice during storage. A total of 21 subclasses of 277 lipids including fatty acid (36 species), (O-acyl)-1-hydroxy fatty acid (6 species), diglyceride (16 species), triglyceride (89 species), lysophosphatidylcholine (4 species), phosphatidylcholine (14 species), phosphatidylethanolamine (28 species), phosphatidylglycerol (6 species), phosphatidylinositol (11species), cardiolipin (4 species), ceramide (8 species), hexosylceramide (20 species), dihexosylceramide (2 species), trihexosylceramide (1 species), sitosterol ester (1species), acyl hexosyl campesterol ester (5 species), acyl hexosyl sitosterol ester (6 species), digalactosyldiacylglycerol (6 species), monogalactosyldiacylglycerol (9 species), monogalactosylmonoacylglycerol (2 species), and sulfoquinovosyldiacylglycerol (3 species), were first identified in rice during storage. In addition, ceramide, fatty acid, (O-acyl)-1-hydroxy fatty acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, lysophosphatidylcholine, and diglyceride were quantified. Furthermore, statistical analysis of all lipids was performed based on MetaboAnalyst software. The results showed that 22 lipids were significantly different between fresh and stored (360 and 540 days storage) rice demonstrating that lipid composition changed during storage. These different lipids involved 11 metabolic pathways, of which linoleic acid metabolism, glycerophospholipid metabolism, and cutin, suberine and wax biosynthesis were the most relevant. Our study provides useful information for lipidomics profile of rice during storage.

Robust Fourier transformed infrared spectroscopy coupled with multivariate methods for detection and quantification of urea adulteration in fresh milk samples

Urea is added as an adulterant to give milk whiteness and increase its consistency for improving the solid not fat percentage, but the excessive amount of urea in milk causes overburden and kidney damages. Here, an innovative sensitive methodology based on near-infrared spectroscopy coupled with multivariate analysis has been proposed for the robust detection and quantification of urea adulteration in fresh milk samples. In this study, 162 fresh milk samples were used, those consisting 20 nonadulterated samples (without urea) and 142 with urea adulterant. Eight different percentage levels of urea adulterant, that is, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, and 1.70%, were prepared, each of them prepared in triplicates. A Frontier NIR spectrophotometer (BSEN60825-1:2007) by Perkin Elmer was used for scanning the absorption of each sample in the wavenumber range of 10,000-4,000 cm-1, using 0.2 mm path length CaF2 sealed cell at resolution of 2 cm-1. Principal components analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and partial least-squares regressions (PLSR) methods were applied for the multivariate analysis of the NIR spectral data collected. PCA was used to reduce the dimensionality of the spectral data and to explore the similarities and differences among the fresh milk samples and the adulterated ones. PLS-DA also showed the discrimination between the nonadulterated and adulterated milk samples. The R-square and root mean square error (RMSE) values obtained for the PLS-DA model were 0.9680 and 0.08%, respectively. Furthermore, PLSR model was also built using the training set of NIR spectral data to make a regression model. For this PLSR model, leave-one-out cross-validation procedure was used as an internal cross-validation criteria and the R-square and the root mean square error (RMSE) values for the PLSR model were found as 0.9800 and 0.56%, respectively. The PLSR model was then externally validated using a test set. The root means square error of prediction (RMSEP) obtained was 0.48%. The present proposed study was intended to contribute toward the development of a robust, sensitive, and reproducible method to detect and determine the urea adulterant concentration in fresh milk samples.

Mass spectrometry-based lipidomics in food science and nutritional health: A comprehensive review

With the advance in science and technology as well as the improvement of living standards, the function of food is no longer just to meet the needs of survival. Food science and its associated nutritional health issues have been increasingly debated. Lipids, as complex metabolites, play a key role both in food and human health. Taking advantages of mass spectrometry (MS) by combining its high sensitivity and accuracy with extensive selective determination of all lipid classes, MS-based lipidomics has been employed to resolve the conundrum of addressing both qualitative and quantitative aspects of high-abundance and low-abundance lipids in complex food matrices. In this review, we systematically summarize current applications of MS-based lipidomics in food field. First, common MS-based lipidomics procedures are described. Second, the applications of MS-based lipidomics in food science, including lipid composition characterization, adulteration, traceability, and other issues, are discussed. Third, the application of MS-based lipidomics for nutritional health covering the influence of food on health and disease is introduced. Finally, future research trends and challenges are proposed. MS-based lipidomics plays an important role in the field of food science, promoting continuous development of food science and integration of food knowledge with other disciplines. New methods of MS-based lipidomics have been developed to improve accuracy and sensitivity of lipid analysis in food samples. These developments offer the possibility to fully characterize lipids in food samples, identify novel functional lipids, and better understand the role of food in promoting healt.

Discrimination of bovine milk from non-dairy milk by lipids fingerprinting using routine matrix-assisted laser desorption ionization mass spectrometry

An important sustainable development goal for any country is to ensure food security by producing a sufficient and safe food supply. This is the case for bovine milk where addition of non-dairy milks such as vegetables (e.g., soya or coconut) has become a common source of adulteration and fraud. Conventionally, gas chromatography techniques are used to detect key lipids (e.g., triacylglycerols) has an effective read-out of assessing milks origins and to detect foreign milks in bovine milks. However, such approach requires several sample preparation steps and a dedicated laboratory environment, precluding a high throughput process. To cope with this need, here, we aimed to develop a novel and simple method without organic solvent extractions for the detection of bovine and non-dairy milks based on lipids fingerprint by routine MALDI-TOF mass spectrometry (MS). The optimized method relies on the simple dilution of milks in water followed by MALDI-TOF MS analyses in the positive linear ion mode and using a matrix consisting of a 9:1 mixture of 2,5-dihydroxybenzoic acid and 2-hydroxy-5-methoxybenzoic acid (super-DHB) solubilized at 10 mg/mL in 70% ethanol. This sensitive, inexpensive, and rapid method has potential for use in food authenticity applications.

Economically Motivated Food Fraud and Adulteration in Brazil: Incidents and Alternatives to Minimize Occurrence

Brazil is one of the world's largest food producers. Adulteration of foods is often reported and represent an important potential threat to food safety. Because of this, reduction of the vulnerability of foods to adulteration is of high priority to Brazil. This study analyzes economically motivated food fraud and adulterations in Brazil between 2007 and 2017, based on academic journal reports. In addition, alternatives are proposed to minimize these incidents through good practices, traceability systems and the development of methods to detect food fraud and adulteration. Complex supply chains for foods of animal origin, such as milk and dairy products, were the main targets of food fraud and adulterations. Other products prone to fraudulent activities were vegetable oils, especially olive oil, which are high value products. Meat and fish, as well as their respective by-products, were also involved in some food fraud and adulteration, especially substitution. Cases of extraneous ingredient addition were also reported in the coffee and tea sectors. Comprehensive food fraud and adulteration prevention requires the enforcement of regulatory systems, increased sampling and monitoring, training of food producers and handlers, and development of precise, rapid, and cost-effective methods of fraud detection. The availability of robust methods to identify the chemical constituents of foods could be a decisive step, both to detect and prevent fraud in producer countries and to open up new markets to these products. The results of this study can be used to analyze food safety risks and prioritize target areas for food research and policy-making in order to enforce food safety regulations in Brazil.

PRACTICAL APPLICATION

A food fraud and adulteration review was conducted based on scientific literature in Brazil. Milk and its products were the main targets of food fraud and adulterations. Food fraud and adulteration causes and suggestions for good practice are presented. The results can be used to analyze food safety and protect consumer rights.

Raman spectroscopy coupled with chemometric methods for the discrimination of foreign fats and oils in cream and yogurt

The adulteration of milk fat in dairy products with cheaper non-milk based fats or oils is frequently encountered in the dairy industry. In this study, Raman spectroscopy with chemometric was used for the discrimination of foreign fats and oils in milk cream and yogurt. Firstly, binary mixtures of cream and oils (corn and sunflower oil), and vegetable fat blends which are potentially or currently used by the dairy industry were prepared. All fat or oil samples and their binary mixtures were examined by using Raman spectroscopy. Then, fat content of skim milk was adjusted to 3% (w/w) by the milk fat, external oils or fats, and binary mixtures, and was used in yogurt production. The lipid fraction of yogurt was extracted and characterized by Raman spectroscopy. The spectral data were then pre-processed and principal component analysis (PCA) was performed. Raman spectral data showed successful discrimination for about the source of the fats or oils. Temperature effect was also studied at six different temperatures (25, 30, 40, 50, 60 and 70 °C) in order to obtain the best spectral information. Raman spectra collected at higher temperatures were more intense. Obtained results showed that the performance of Raman spectroscopy with PCA was very promising and can be expected to provide a simple and quick way for the discrimination of foreign fats and oils in both milk cream and yogurt. Fermentation and yogurt processing affected clustering of fat samples by PCA, probably depending on some lipolysis or production of new products that can affect the Raman scattering. However, those changes did not affect differentiation of samples by Raman spectroscopy.

Adulteration identification in raw milk using Fourier transform infrared spectroscopy

Adulteration of milk is a common practice that concerns regulatory agencies, industry, and the population. Despite the growing need for checking adulteration, the current methods employed generally have low performance and are highly dependent on manual labor. This study aims to calibrate and validate a compact equipment (MilkoScan FT1) that adopts a Fourier transform infrared spectroscopy methodology to monitor adulteration in raw milk. Almost 2500 milk samples were used for reference spectrum construction and 1650 samples were used to validate the identification of the following five most commonly used adulterants (at three different concentrations each): (1) cornstarch, (2) sodium bicarbonate, (3) sodium citrate, (4) formaldehyde, and (5) saccharose, plus the additions of two levels of water or whey. To define the calibration with the best performance in milk adulteration identification, 12 calibrations involving 8, 10, 12, 14, 16, or 18 factors, with one or two outlier eliminations, were developed. The results of sensitivity and specificity analyses, as well as Kruskal-Wallis and Dunn multiple comparison tests, revealed that the calibration that best identified the adulterants was the one involving 14 factors, with a single elimination of outliers, exhibiting for all adulterants simultaneously, 84% sensitivity and 100% specificity. The calibration showed excellent sensitivity to cornstarch (>98%), sodium bicarbonate (100%), sodium citrate (99%), and formaldehyde (>84%), indicating that this calibration has good capacity for adulteration detection. Thus, this methodology is a viable option for the dairy industry to identify adulteration of raw milk.

Challenges and opportunities of bovine milk analysis by mass spectrometry

Bovine milk and its products (e.g. cheese, yoghurt) are an important part of human diet with beneficial effects for all ages. Although analyses of different milk components (e.g. proteins, lipids) pose huge challenges, the use of mass spectrometric (MS)-based techniques is steadily improving our understanding of the complexity of the biological traits that effect milk yield and its components to meet the global demand arising from population growth. In addition, different milk constituents have various applications in veterinary research and medicine, including early disease diagnosis. The aim of the review is to present an overview of the progress made in MS-based analysis of milk, and suggest a multi-pronged MS strategy to better explore different milk components for translational and clinical utilities.

Rapid detection of whey in milk powder samples by spectrophotometric and multivariate calibration

A rapid method for the detection and quantification of the adulteration of milk powder by the addition of whey was assessed by measuring glycomacropeptide protein using mid-infrared spectroscopy (MIR). Fluid milk samples were dried and then spiked with different concentrations of GMP and whey. Calibration models were developed using multivariate techniques, from spectral data. For the principal component analysis and discriminant analysis, excellent percentages of correct classification were achieved in accordance with the increase in the proportion of whey samples. For partial least squares regression analysis, the correlation coefficient (r) and root mean square error of prediction (RMSEP) in the best model were 0.9885 and 1.17, respectively. The rapid analysis, low cost monitoring and high throughput number of samples tested per unit time indicate that MIR spectroscopy may hold potential as a rapid and reliable method for detecting milk powder frauds using cheese whey.

Ultrahigh resolution mass spectrometry and accurate mass measurements for high-throughput food lipids profiling

In the present study, accurate mass measurements by ultrahigh resolution mass spectrometry with Orbitrap-Exactive working at resolving power R: 100,000 (m/z 200, full width at half maximum) with an accuracy better than 2 ppm in all the mass range (m/z 200 to 2000) were used to show a detailed molecular composition of diverse edible oils and fats. Flow injection was used to introduce samples into the mass spectrometer, obtaining a complete analysis of each sample in less than 10 min, including blanks. Meticulous choice of organic solvents and optimization of the ion source and Orbitrap mass analyzer parameters were carried out, in order to achieve reproducible mass spectra giving reliable elemental compositions of the lipid samples and to prevent carry over. More than 200 elemental compositions attributable to diacylglycerols, triacylglycerols (TAGs), and their oxidation products have been found in the spectra of food lipids from different origin. Several compounds with very close molecular mass could only be resolved through ultrahigh resolution, allowing detailed and robust TAG profiling with a high characterization potential.