Composition of bovine milk fat globules by confocal Raman microscopy

In situ single-droplet analysis of emulsified fat using confocal Raman microscopy: insights into crystal network formation within spatial resolution

Fat crystallization is one of the predominant factors influencing the structure and properties of fat-containing emulsions. In the present study, the role of emulsifiers on fat crystallization dynamics within droplet multiphase systems was evaluated via single-droplet analysis, taking advantage of the non-destructive properties of confocal Raman microscopy. Palm oil droplets dispersed in water were used as a model system, due to palm oil's well-known crystallization properties. Emulsion droplets of the same size were generated using two different emulsifiers (Whey Protein Isolate and Tween 60), at various concentrations. Fast and slow cooling treatments were applied to affect fat crystallisation and network formation as well as droplet morphology, and crystallization dynamics. Raman imaging analysis demonstrated that the chemical structure and concentration of the emulsifier significantly influenced both crystal nucleation within the droplets, as well as the spatial distribution and morphology of the fat crystal network. Additionally, analysis of the spectra of the crystallized phase provided essential information regarding the impact of the emulsifiers on the microstructure, degree of structural order, and structural arrangements of the fat crystal networks. Furthermore, by performing single droplet analysis during cooling it was possible to observe shape distortions in Tween 60 stabilized droplets, as a consequence of the formation of a three-dimensional network of fat crystals that strongly interacted with the interface. On the other hand, the droplets retained their shape when whey proteins were absorbed at the interface. Confocal Raman microscopy, in combination with polarized light microscopy, is, therefore, a well-suited tool for in situ, single-droplet analysis of emulsified oil systems, providing essential information about emulsified fat crystallization dynamics, contributing to better understanding and designing products with enhanced structure and function.

Identifying Chemical Differences in Cheddar Cheese Based on Maturity Level and Manufacturer Using Vibrational Spectroscopy and Chemometrics

Cheese is a nutritious dairy product and a valuable commodity. Internationally, cheddar cheese is produced and consumed in large quantities, and it is the main cheese variety that is exported from Australia. Despite its importance, the analytical methods to that are used to determine cheese quality rely on traditional approaches that require time, are invasive, and which involve potentially hazardous chemicals. In contrast, spectroscopic techniques can rapidly provide molecular information and are non-destructive, fast, and chemical-free methods. Combined with partner recognition methods (chemometrics), they can identify small changes in the composition or condition of cheeses. In this work, we combined FTIR and Raman spectroscopies with principal component analysis (PCA) to investigate the effects of aging in commercial cheddar cheeses. Changes in the amide I and II bands were the main spectral characteristics responsible for classifying commercial cheddar cheeses based on the ripening time and manufacturer using FTIR, and bands from lipids, including β'-polymorph of fat crystals, were more clearly determined through changes in the Raman spectra.

Hybrid Raman and Laser-Induced Breakdown Spectroscopy for Food Authentication Applications

The issue of food fraud has become a significant global concern as it affects both the quality and safety of food products, ultimately resulting in the loss of customer trust and brand loyalty. To address this problem, we have developed an innovative approach that can tackle various types of food fraud, including adulteration, substitution, and dilution. Our methodology utilizes an integrated system that combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. Although both techniques emerged as valuable tools for food analysis, they have until now been used separately, and their combined potential in food fraud has not been thoroughly tested. The aim of our study was to demonstrate the potential benefits of integrating Raman and LIBS modalities in a portable system for improved product classification and subsequent authentication. In pursuit of this objective, we designed and tested a compact, hybrid Raman/LIBS system, which exhibited distinct advantages over the individual modalities. Our findings illustrate that the combination of these two modalities can achieve higher accuracy in product classification, leading to more effective and reliable product authentication. Overall, our research highlights the potential of hybrid systems for practical applications in a variety of industries. The integration and design were mainly focused on the detection and characterization of both elemental and molecular elements in various food products. Two different sets of solid food samples (sixteen Alpine-style cheeses and seven brands of Arabica coffee beans) were chosen for the authentication analysis. Class detection and classification were accomplished through the use of multivariate feature selection and machine-learning procedures. The accuracy of classification was observed to improve by approximately 10% when utilizing the hybrid Raman/LIBS spectra, as opposed to the analysis of spectra from the individual methods. This clearly demonstrates that the hybrid system can significantly improve food authentication accuracy while maintaining the portability of the combined system. Thus, the successful implementation of a hybrid Raman-LIBS technique is expected to contribute to the development of novel portable devices for food authentication in food as well as other various industries.

Magnetic Fe3O4@COF@Ag SERS substrate combined with machine learning algorithms for detection of three quinolone antibiotics: Ciprofloxacin, norfloxacin and levofloxacin

Quinolone antibiotics have good antibacterial properties and are commonly used antibiotics in the dairy industry. Currently, the problem of excessive antibiotics in dairy products is very serious. As an ultra-sensitive detection technology, Surface-Enhanced Raman Scattering (SERS) was applied to the detection of quinolone antibiotics in this work. In order to classify and quantify three antibiotics (Ciprofloxacin, Norfloxacin, Levofloxacin) with highly similar molecular structures, a combination of magnetic COF-based SERS substrate and machine learning algorithms (PCA-k-NN, PCA-SVM, PCA-Decision Tree) was used. The classification accuracy of the spectral dataset could reach 100% and the results of LOD calculation were: CIP: 5.61 × 10^-9M, LEV: 1.44 × 10^-8M, NFX: 1.56 × 10^-8M. This provides a new method for the detection of antibiotics in dairy products.

Analysis of Milk Microstructure Using Raman Hyperspectral Imaging

Optical spectroscopic analysis of the chemical composition of milk in its natural state is complicated by a complex colloidal structure, represented by differently sized fat and protein particles. The classical techniques of molecular spectroscopy in the visible, near-, and mid-infrared ranges carry only bulk chemical information about a sample, which usually undergoes a destructive preparation stage. The combination of Raman spectroscopy with confocal microscopy provides a unique opportunity to obtain a vibrational spectrum at any single point of the sample volume. In this study, scanning confocal Raman microscopy was applied for the first time to investigate the chemical microstructure of milk using samples of various compositions. The obtained hyperspectral images of selected planes in milk samples are represented by three-dimensional data arrays. Chemometric data analysis, in particular the method of multivariate curve resolution, has been used to extract the chemical information from complex partially overlaid spectral responses. The results obtained show the spatial distribution of the main chemical components, i.e., fat, protein, and lactose, in the milk samples under study using intuitive graphical maps. The proposed experimental and data analysis method can be used in an advanced chemical analysis of natural milk and products on its basis.

Extraction of structurally intact and well-stabilized rice bran oil bodies as natural pre-emulsified O/W emulsions and investigation of their rheological properties and components interaction

The isolated plant oil bodies (OBs) have shown promising applications as natural pre-emulsified O/W emulsions. Rice bran OBs can be used as a new type plant-based resource with superior fatty acids composition and abundant γ-oryzanol. This paper investigated the method of extracting structurally intact and stable rice bran OBs. Due to the adequate steric hindrance and electrostatic repulsion effects, rice bran OBs extracted by NaHCO₃ medium had smaller particle size, better physical stability, and natural structure. The protein profile of NaHCO₃-extracted rice bran OBs showed oleosin-L and oleosin-H, while exogenous proteins in PBS and enzyme-assisted- extracted rice bran OBs could interact with interfacial proteins through hydrophobic forces to aggregate adjacent OBs, further remodeling the OBs interface. It was also found that the small-sized rice bran OBs could adsorb on the interface of the larger-sized rice bran OBs like Pickering stabilizers. Rice bran OBs exhibited pseudoplastic fluids characteristic, but underwent a transition from solid-like to liquid-like behavior depending on the extraction method. The disorder of NaHCO₃-extracted rice bran OBs protein molecules increased their surface hydrophobicity. The random coil structure favored more proteins adsorption at the interface of rice bran OBs extracted by PBS. Enzyme-assisted extraction of rice bran OBs had the highest content of β-sheet structure, which facilitated the stretching and aggregation of protein spatial structure. It was also confirmed the hydrogen bonding and hydrophobic interaction between the triacylglycerol or phospholipid and proteins molecules, and the membrane compositions of rice bran OBs differed between extraction methods.

Rapid quantification of goat milk adulteration with cow milk using Raman spectroscopy and chemometrics

As goat milk has a higher economic value compared to cow milk, the phenomenon of adulterating goat milk with cow milk appears in the market. In this study, the potential of Raman spectroscopy along with chemometrics was investigated for the authentication and quantitation of liquid goat milk adulterated with cow milk. First, the results of principal component analysis (PCA) showed that there were differences between the Raman spectra of cow and goat milk, which made quantitative experiments possible. For quantification, three different brands of cow milk and goat milk were selected randomly and adulterated goat milk with cow milk at the proportion of 5-95%. 342 samples were used for the construction of the partial least squares regression (PLSR) model with 80% for the calibration set and 20% for the prediction set. The PLSR model showed excellent performance in quantifying the level of adulteration, for the prediction set, with a coefficient of determination (R²) of 0.9781, root mean square error (RMSE) of 3.82%, and a ratio of prediction to deviation (RPD) of 6.8. The results demonstrated the potential of Raman spectroscopy as a rapid, low cost and non-destructive analytical tool for detecting adulteration in goat milk.

Preliminary Investigation on the Relationship between Raman Spectra of Beef and Metmyoglobin and Metmyoglobin Reductase Activity

A hand-held Raman spectroscopic device was used as a rapid nondestructive testing device to predict the metmyoglobin (MetMb) and metmyoglobin reductase activity (MRA) values on the surface layer of fresh beef. Longissimus dorsi muscles were from 10 young bulls (Holstein-Friesian) from two different cattle farms (group A = 5 and B = 5). The Raman spectra of 100 samples were correlated with the MetMb and MRA values using partial least squares regression (PLSR). Two groups could be discriminated, and the separate correlation models were better than the joint correlation model for the fresh beef. The coefficients of determination are R² = 0.81 (group A) and R² = 0.87 (group B) for MetMb and R² = 0.80 (group A) and R² = 0.85 (group B) for MRA. The results show the usefulness of Raman spectra in predicting the inner traits such as MetMb and MRA during meat storage. In conclusion, it is feasible to determine the MetMb and MRA values by Raman spectroscopy. Color is an important indicator of beef freshness and can vary depending on the age, sex, and breed of the cow. They play a very important role in human nutrition. The color of meat is an important indicator of meat freshness, and many researchers are already investigating the causes of color changes. The research was conducted in this environment.

The effect of emulsifier type on the secondary crystallisation of monoacylglycerol and triacylglycerols in model dairy emulsions

Dairy emulsions contain an intrinsically heterogeneous lipid phase, whose components undergo crystallisation in a manner that is critical to dairy product formulation, storage, and sensory perception. Further complexity is engendered by the diverse array of interfacially-active molecules naturally present within the serum of dairy systems, and those that are added for specific formulation purposes, all of which interact at the lipid-serum interface and modify the impact of lipid crystals on dairy emulsion stability. The work described in this article addresses this complexity, with a specific focus on the impact of temperature cycling and the effect of emulsifier type on the formation and persistence of lipid crystals at lipid-solution interfaces. Profile analysis tensiometry experiments were performed using single droplets of the low melting fraction of dairy lipids, in the presence and absence of emulsifiers (Tween 80 and whey protein isolate, WPI) and during the temperature cycling, to study the formation of monoacylglycerol (MAG) crystals at the lipid-solution interface. Companion experiments on the same lipid systems, and at the same cooling and heating rates, were undertaken with synchrotron small angle X-ray scattering, to specifically analyse the effect of emulsifier type on the formation of triacylglycerol (TAG) crystals at the lipid-solution interface of a model dairy emulsion. These two complementary techniques have revealed that Tween 80 molecules delay MAG and TAG crystal formation by lowering the temperature at which the crystallisation occurs during two cooling cycles. WPI molecules delay the crystallisation of MAGs and TAGs during the first cooling cycle, while MAG crystals form without delay during the second cooling cycle at the same temperature as MAG crystals in an emulsifier free system. The crystallisation of TAGs is inhibited during the second cooling cycle. The observed differences in crystallisation behaviour at the interface upon temperature cycling can provide further insight into the impact of emulsifiers on the long-term stability of emulsion-based dairy systems during storage.

Evaluation of the changes in human milk lipid composition and conformational state with Raman spectroscopy during a breastfeed

Human milk fat forms the main energy source for breastfed infants, and is highly variable in terms of concentration and composition. Understanding the changes in human milk lipid composition and conformational state during a breastfeed can provide insight into lipid synthesis and secretion in the mammary gland. Therefore, the aim of this study was to evaluate human milk fatty acid length, degree of unsaturation (lipid composition) and lipid phase (lipid conformational state) at different stages during a single breastfeed (fore-, bulk- and hindmilk). A total of 48 samples from 16 lactating subjects were investigated with confocal Raman spectroscopy. We did not observe any significant changes in lipid composition between fore-, bulk and hindmilk. A new finding from this study is that lipid conformational state at room temperature changed significantly during a breastfeed, from almost crystalline to almost liquid. This observation suggests that lipid synthesis in the mammary gland changes during a single breastfeed.

Variation in milk fat globule size and composition: A source of bioactives for human health

Milk fat globules (MFGs) are secreted from the mammalian gland and are composed of a triacylglycerol core surrounded by a triple membrane structure, the milk fat globule membrane (MFGM). The MFGM contains complex lipids and proteins reported to have nutritional, immunological, neurological and digestive functions. Human and ruminant milk are shown to share a similar MFG structure but with different size, profile and abundance of protein and polar lipids. This review summarizes the reported data on human, bovine, caprine and ovine MFG composition and concentration of bioactive components in different MFG-size fractions. A comprehensive understanding of compositional variations between milk from different species and MFG size fractions may help promote various milk sources as targeted supplements to improve human development and health. MFG size and MFGM composition are species-specific and affected by lactation, diet and breed (or maternal origin). Purification and enrichment methods for some bioactive proteins and lipids present in the MFGM have yet to be established or are not scaled sufficiently to be used to supplement human diets. To overcome this problem, MFG size selection through fractionation or herd selection may provide a convenient way to pre-enrich the MFG fraction with specific protein and lipid components to fulfill human dietary and health requirements.

Milk Fat Globule Membrane Proteome and Micronutrients in the Milk Lipid Fraction: Insights into Milk Bioactive Compounds

Milk lipids are composed of milk fat globules (MFGs) surrounded by the milk fat globule membrane (MFGM). MFGM protects MFGs from coalescence and enzymatic degradation. The milk lipid fraction is a “natural solvent” for macronutrients such as phospholipids, proteins and cholesterol, and micronutrients such as minerals and vitamins. The research focused largely on the polar lipids of MFGM, given their wide bioactive properties. In this review we discussed (i) the composition of MFGM proteome and its variations among species and phases of lactation and (ii) the micronutrient content of human and cow’s milk lipid fraction. The major MFGM proteins are shared among species, but the molecular function and protein expression of MFGM proteins vary among species and phases of lactation. The main minerals in the milk lipid fraction are iron, zinc, copper and calcium, whereas the major vitamins are vitamin A, β-carotene, riboflavin and α-tocopherol. The update and the combination of this knowledge could lead to the exploitation of the MFGM proteome and the milk lipid fraction at nutritional, biological or technological levels. An example is the design of innovative and value-added products, such as MFGM-supplemented infant formulas.

Raman spectroscopy based characterization of cow, goat and buffalo fats

In this study, Raman spectroscopy has been utilized to characterize buffalo, cow and goat fat samples by using laser wavelengths at 532 and 785 nm as excitation sources. It has been observed that Raman spectra of cow fats contain beta-carotene at 1006, 1156 and 1520 cm^-1, which are absent in buffalo and goat fats. The Raman bands at 1060, 1080, 1127 and 1440 cm^-1 represent the saturated fatty acids, and their concentration is found relatively higher in buffalo fats than cow and goat. Similarly, the Raman band at 1650 cm^-1 represent conjugated linoleic acid (CLA) which shows its relatively higher concentration in goat fats than cow and buffalo. The Raman band at 1267 cm^-1 represent unsaturated fatty acids, which shows its relatively higher concentration in goat fats than cow and buffalo. The Raman bands at 838, 870 and 1060 cm^-1 depict relatively higher concentration of vitamin D in buffalo fats than cow and goat. Principal component analysis has been applied to highlight the differences among three fat types which based upon the concentration of fatty acids, CLA and vitamin D.

Discrimination of milk species using Raman spectroscopy coupled with partial least squares discriminant analysis in raw and pasteurized milk

BACKGROUND

Heat treatment is the most common practice for the microbiological safety of milk; hence, determination of the heat treatment of milk is essential. Also, mislabeling or adulteration of expensive milk samples, like ewe or goat milk, with cow's milk is a growing problem in the dairy market. Thus, the determination of the authenticity of milk samples has crucial importance for both producers and consumers. The aim of this study was to discriminate milk samples using Raman spectroscopy with partial least squares discriminant analysis (PLS-DA), first with regard to whether the milk was heat-treated or not, and second with regard to species (cow, goat, ewe, mixture (adulterated)) in both raw and pasteurized milk.

RESULTS

First, discrimination of milk samples as raw or pasteurized was achieved using PLS-DA. Both in calibration and prediction models, high sensitivity and specificity values were obtained for raw and pasteurized milk samples. Second, the proposed method also discriminated milk samples according to their species (cow, goat, ewe, and mixture) for both raw and pasteurized milk. In both calibration and prediction models, the sensitivity and specificity values were above 0.857 and 0.897 respectively. Also, the accuracy values were above 0.915. The results obtained denote satisfactory accurate classification of the samples.

CONCLUSION

The results suggest that Raman spectroscopy coupled with PLS-DA can be successfully used to discriminate milk samples according to heat treatment (raw/pasteurized) and their species within 20 s per sample. It was seen that Raman spectra provide valuable information to be used especially for discrimination of milk samples according to their origin. © 2020 Society of Chemical Industry.

Raman spectroscopy: A rapid method to assess the effects of pasture feeding on the nutritional quality of butter

The animal diet is a critical variable affecting the composition and functionality of dairy products. As "Grass-Fed" labeling becomes more prominent on the market, rapid and label-free methods for verification of feeding systems are required. This work proposes the use of Raman spectroscopy to study the effects of 3 different experimental cow feeding systems-perennial ryegrass pasture, perennial ryegrass with white clover pasture, and an indoor total mixed ration diet (TMR)-on the nutritional quality of sweet cream butter. The results demonstrate that Raman spectroscopy coupled with multivariate analysis is a promising approach to distinguish butter derived from pasture or conventional TMR feeding systems. A Pearson correlation analysis confirmed high positive correlations between the spectral bin at 1,657 cm^-1, ascribed to the stretching vibrations of C=C bonds, and concentrations of α-linolenic acid and conjugated linolenic acid (CLA) in butter, and in general with the concentration of n-3 and n-3+CLA fatty acids and polyunsaturated fatty acids in the samples. The yellow color indicative of the presence of carotenoids in butter, which has previously been suggested as a biomarker of pasture or "Grass-Fed" feeding, was also positively correlated with the data obtained from the Raman spectra. Raman spectroscopy could also be used to accurately predict indicators of the nutritional quality of butter, such as the thrombogenic index, which showed a strong negative correlation with the spectral bin at 3,023 cm^-1.

Determination of milk fat authenticity in ultra-filtered white cheese by using Raman spectroscopy with multivariate data analysis

Cheese is one of the most widely consumed food products in the world. However, the increasing demand for nutritionally enhanced or functional products by the cheese industry has created new approaches that partially or fully replace milk fat. With this, new methods of adulteration have also been noted, potentially leading to these fully/partially-replaced products being offered as cheese. In this study, Raman spectroscopy was used to determine origins of fats in margarine, corn, and palm oils present in white and ultra-filtered cheese samples. Raman spectra were evaluated with partial least square-discriminant (PLS-DA) and PLS to identify fat/oil origins and adulteration ratios. The coefficients of determination and limits of detection for margarine, and corn and palm oil adulteration were found to be 0.990, 0.993, 0.991 and 3.38%, 3.36% and 3.59%, respectively.

Investigation of the Applicability of Raman Spectroscopy as Online Process Control during Consumer Milk Production

Online detection of product defects using fast spectroscopic measurements is beneficial for producers in the dairy industry since it allows readjustment of product characteristics or redirection of product streams during production. Raman spectroscopy has great potential for such application due to the fast and simple measurement. Its suitability as online sensor for process control was investigated at typical control points in consumer milk production being raw milk storage, standardization, and heat treatment. Additionally, the appropriateness of Raman spectroscopy to act as indicator for product application parameters was investigated using the example of barista foam. To assess the suitability of a pure online system, the merit of Raman spectra was evaluated by a principal component analysis (PCA). Thereby, proteolytic spoilage due to the presence of extracellular enzymes of Pseudomonas sp. was detected and samples based on the applied heat treatment (extended shelf life (ESL) and ultra-high temperature (UHT)) could be separated. A correlation of the content of free fatty acids and foam stability with spectra of the respective milk samples was found, allowing a prediction of the technofunctional quality criterion “Barista” suitability of a UHT milk. The results underlined the suitability of Raman spectroscopy for the detection of deviations from a defined product standard of consumer milk.

Detection of lard in butter using Raman spectroscopy combined with chemometrics

There is a contentious need for robust and rapid methodologies for maintaining the authenticity of foods and food additives. The current paper presented a new Raman spectroscopy-based methodology for detection and quantification of lard in butter. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully performed for the classification and discrimination of butter and lard-adulterated samples. Strong discrimination pattern was observed in the HCA analysis. Also, partial least squares regression and principal component regression (R² = 0.99) were applied for quantification of lard in butter samples. Quite favorable prediction capabilities were observed in the cross-validation of PLS and PCR analysis for the adulteration levels between 0% and 100% lard fat (w/w). Raman spectroscopy coupled chemometrics was employed effectively for quantification of lard fat in butter fat samples with easy, robust, effective, low-cost and reliable application in the quality control of butter.

Applicability of Confocal Raman Microscopy to Observe Microstructural Modifications of Cream Cheeses as Influenced by Freezing

Confocal Raman microscopy is a promising technique to derive information about microstructure, with minimal sample disruption. Raman emission bands are highly specific to molecular structure and with Raman spectroscopy it is thus possible to observe different classes of molecules in situ, in complex food matrices, without employing fluorescent dyes. In this work confocal Raman microscopy was employed to observe microstructural changes occurring after freezing and thawing in high-moisture cheeses, and the observations were compared to those obtained with confocal laser scanning microscopy. Two commercially available cream cheese products were imaged with both microscopy techniques. The lower resolution (1 µm/pixel) of confocal Raman microscopy prevented the observation of particles smaller than 1 µm that may be part of the structure (e.g., sugars). With confocal Raman microscopy it was possible to identify and map the large water domains formed during freezing and thawing in high-moisture cream cheese. The results were supported also by low resolution NMR analysis. NMR and Raman microscopy are complementary techniques that can be employed to distinguish between the two different commercial formulations, and different destabilization levels.

Characterization of desi ghee obtained from different extraction methods using Raman spectroscopy

In this study, the potential of Raman spectroscopy has been utilized to characterize the methods direct cream (DC), milk butter (MB) and milk skin (MS) used for the extraction of desi ghee from buffalo and cow milk. Raman spectra from six types of ghee samples extracted by above methods were acquired using two laser wavelengths of 532 and 785 nm. The Raman spectra of cow ghee revealed that it contains three bands of beta-carotene at 1005, 1156 and 1520 cm^-1 which differentiated it from buffalo ghee. To highlight small spectral differences, statistical analysis through principal component analysis (PCA) has been performed on the Raman spectra of ghee samples to reach subsequent conclusion. Based on the variations in molecular composition of cow ghee samples, it has been found that DC method retain relatively higher concentration of beta-carotene and MB method contain higher concentration of conjugated linoleic acid (CLA) and fatty acids than MS method. Similarly, DC & MS methods were found best for retaining relatively higher concentration of CLA and fatty acids in buffalo ghee as compared to MB method which retains relatively higher concentration of fatty acids.

Evaluation of the quality of local butters: A new approach based on Raman spectroscopy and supported by the classical pycnometer method

In this study, the quality of the local Romanian butters was investigated using the classical pycnometer and optic microscopy methods, combined with Raman spectroscopy. We used a pool of 10 samples with different characteristics, and analyzed them by the three aforementioned methods. Pycnometric measurements showed a direct correlation between the fat content and the density values of the samples. Raman spectroscopy validated the results from the pycnometric measurements and the optical microscopy and indicated several other properties, such as protein content, hydration, saturation level of the polycarbonate chains, as well as the total cis isomer content and the type of arrangement preferred by the aliphatic chains (polymorphic transition). The methods employed in the present study have a strong potential to become analytical tools for the food industry and food safety agencies in order to assess the quality of butters and margarines, in a fast and cost-effective manner.

Fractionation and characterisation of hard milk fat crystals using atomic force microscopy

The hard milk fat (HMF) fraction of milk fat was isolated via dry, thermal fractionation, followed by a solvent washing process. The resulting HMF crystals were visibly free of entrapped liquid fat, and subsequently characterised by thermal analysis, X-ray diffraction, and electron microscopy. The HMF crystals were found to be mostly β' and β'₂ crystalline structures, with a lamellar thickness of 42.7-44.1 Å. Additionally, crystal size was determined to be ≥1 μm in length and 0.4-1 μm in width. Atomic force microscopy (AFM) was used to further characterise the HMF crystals. AFM enabled 3D mapping and visualisation of crystal layering, as well as simple determination of layer thickness (∼4.2 ± 0.8 nm); a value in close agreement with the results obtained via X-ray analysis. The AFM characterisation approach provides a simple method of characterising HMF crystals, without suffering the limitations of other widely used techniques.

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.

Through-packaging analysis of butter adulteration using line-scan spatially offset Raman spectroscopy

Spectroscopic techniques for food quality analysis are limited to surface inspections and are highly affected by the superficial layers (skin or packaging material) of the food samples. The ability of spatially offset Raman spectroscopy (SORS) to obtain chemical information from below the surface of a sample makes it a promising candidate for the non-destructive analysis of the quality of packaged food. In the present study, we developed a line-scan SORS technique for obtaining the Raman spectra of packaged-food samples. This technique was used to quantify butter adulteration with margarine through two different types of packaging. Further, the significant commercial potential of the developed technique was demonstrated by its being able to discriminate between ten commercial varieties of butter and margarine whilst still in their original, unopened packaging. The results revealed that, while conventional backscattering Raman spectroscopy cannot penetrate the packaging, thus preventing its application to the quality analysis of packaged food, SORS analysis yielded excellent qualitative and quantitative analyses of butter samples. The partial least-square regression analysis predictive values for the SORS data exhibit correlation coefficient values of 0.95 and 0.92, associated with the prediction error 3.2 % and 3.9 % for cover-1 & 2, respectively. The developed system utilizes a laser line (ca. 14-cm wide) that enables the simultaneous collection of a large number of spectra from a sample. Thus, by averaging the spectra collected for a given sample, the signal-to-noise ratio of the final spectrum can be enhanced, which will then have a significant effect on the multivariate data analysis methods used for qualitative and/or qualitative analyses. This recently presented line-scan SORS technique could be applied to the development of high-throughput and real-time analysis techniques for determining the quality and authenticity various packaged agricultural products.

Heating Effects of Desi Ghee Using Raman Spectroscopy

Raman spectroscopy as a fast and nondestructive technique has been used to investigate heating effects on Desi ghee during frying/cooking of food for the first time. A temperature in the range of 140-180℃ has been investigated within which Desi ghee can be used safely for cooking/frying without much alteration of its natural molecular composition. In addition, heating effects in case of reuse, heating for different times, and cooking inside pressure cookers are also presented. An excitation laser at 785 nm has been used to obtain Raman spectra and the range of 540-1800 cm^-1 is found to contain prominent spectral bands. Prominent variations have been observed in the Raman bands of 560-770 cm^-1, 790-1160 cm^-1, and 1180-1285 cm^-1 with the rise in temperature. The spectral variations have been verified using classifier principal component analysis. It has been found that Desi ghee can be reused if heated below 180℃ and it can be heated up to 30 min without any appreciable molecular changes if a controlled heating can be managed.

Single-Drop Raman Imaging Exposes the Trace Contaminants in Milk

Better milk safety control can offer important means to promote public health. However, few technologies can detect different types of contaminants in milk simultaneously. In this regard, the present work proposes a single-drop Raman imaging (SDRI) strategy for semiquantitation of multiple hazardous factors in milk solutions. By developing SDRI strategy that incorporates the coffee-ring effect (a natural phenomenon often presents in a condensed circle pattern after a drop evaporated) for sample pretreatment and discrete wavelet transform for spectra processing, the method serves well to expose typical hazardous molecular species in milk products, such as melamine, sodium thiocyanate and lincomycin hydrochloride, with little sample preparation. The detection sensitivity for melamine, sodium thiocyanate, and lincomycin hydrochloride are 0.1 mg kg^-1, 1 mg kg^-1, and 0.1 mg kg^-1, respectively. Theoretically, we establish that the SDRI represents a novel and environment-friendly method that screens the milk safety efficiently, which could be well extended to inspection of other food safety.

Feasibility of discrimination of dairy creams and cream-like analogues using Raman spectroscopy and chemometric analysis

Dairy cream and its analogues with sunflower oil, coconut oil and palm oil in different milk fat/vegetable fat ratios were prepared and analysed using Raman spectroscopy. The linear discriminant analysis was conducted in order to classify the samples. Samples were well separated and displayed distinguishing linear arrangement along the principal component that expressed the variation in lipid unsaturation. Good separation of sunflower oil and milk fat samples was obtained in contrast to the samples with coconut and palm oil, where the substantial overlapping occurred. The method permitted classifying of the samples in terms of the type of fat used. Calibrated model was extremely sensitive (100%) for dairy cream. The results indicated that it is possible to consider the Raman spectroscopy coupled with chemometric analysis as a rapid way for the detection of dairy cream adulteration with sunflower, coconut and palm oils.

Label-free in situ imaging of oil body dynamics and chemistry in germination

Plant oleosomes are uniquely emulsified lipid reservoirs that serve as the primary energy source during seed germination. These oil bodies undergo significant changes regarding their size, composition and structure during normal seedling development; however, a detailed characterization of these oil body dynamics, which critically affect oil body extractability and nutritional value, has remained challenging because of a limited ability to monitor oil body location and composition during germination in situ Here, we demonstrate via in situ, label-free imaging that oil bodies are highly dynamic intracellular organelles that are morphologically and biochemically remodelled extensively during germination. Label-free, coherent Raman microscopy (CRM) combined with bulk biochemical measurements revealed the temporal and spatial regulation of oil bodies in native soya bean cotyledons during the first eight days of germination. Oil bodies undergo a cycle of growth and shrinkage that is paralleled by lipid and protein compositional changes. Specifically, the total protein concentration associated with oil bodies increases in the first phase of germination and subsequently decreases. Lipids contained within the oil bodies change in saturation and chain length during germination. Our results show that CRM is a well-suited platform to monitor in situ lipid dynamics and local chemistry and that oil bodies are actively remodelled during germination. This underscores the dynamic role of lipid reservoirs in plant development.

Effects of freeze drying and spray drying on the microstructure and composition of milk fat globules

Freeze drying and spray drying are conventional methods for converting milk into powder in the dairy industry.

Bovine milk fat globule membrane proteins are affected by centrifugal washing processes

The impact of washing on the release of proteins from the milk fat globule membrane (MFGM) was examined by applying washing procedures with different degrees of stringency to milk fat globule (MFG) surfaces in simulated milk ultrafiltrate buffer solution. Three washing methods, M1 (3000g, 5 min, three washes), M2 (3750g, 15 min, one wash), and M3 (15000g, 20 min, three washes) were chosen. MFG ζ-potential increased after M3 washing (P < 0.05), suggesting surface damage. For M1, in which the native MFG surface was least damaged, cluster of differentiation 36 (CD 36) and periodic acid schiff 6/7 proteins were more strongly bound to the MFGM compared with other major membrane proteins. For M3, CD 36 together with fatty acid-binding protein was more strongly bound to the MFGM. Washing by centrifugation and redispersal of the fat globules damaged the MFGM, with release into the aqueous phase of some membrane-associated proteins. The current results show the impact of washing processes on retention of functional MFGM proteins.