Identification of milk mixtures by 1H NMR profiling

Structural Properties of Casein Micelles with Adjusted Micellar Calcium Phosphate Content

Micellar calcium phosphate (MCP) content of skim milk was modified by pH adjustment followed by dialysis. Turbidity, casein micelle size and partitioning of Ca and caseins between the colloidal and soluble phases of milk were determined. Protein structure was characterised by Fourier transform infrared (FTIR) spectroscopy and proton nuclear magnetic resonance (1H NMR), whereas organic and inorganic phosphorus were studied by phosphorus-31 nuclear magnetic resonance (31P NMR). The sample with the lowest MCP content (MCP7) exhibited the smallest particle size and turbidity, measuring 83 ± 8 nm and 0.08 ± 0.01 cm-1, respectively. Concentrations of soluble caseins increased with decreasing MCP levels. At ~60% MCP removal, FTIR analysis indicated a critical stage of structural rearrangement and 31P NMR analysis showed an increase in signal intensity for Ca-free Ser-P, which further increased as MCP concentration was further reduced. In conclusion, this study highlighted the importance of MCP in maintaining micellar structure and its impact on the integrity of casein micelle.

Geographical classification of opium samples from Myanmar and Afghanistan by NMR profiling and chemometrics

This study presents a new strategy to discriminate between opium samples obtained from different geographical regions. Nuclear magnetic resonance (NMR) profiling and chemometrics were applied to geographical classification of opium originating from Myanmar and Afghanistan, which are two major opium producing countries in the world. A total of 50 Myanmar and 46 Afghanistan authentic opium samples were analyzed by 1 H-NMR, and the chemical profiles were characterized. Different sample preparation procedures, data processing methods, and chemometrics were compared to obtain the best classification effect. It was found that drying and the addition of buffer solutions were unnecessary for classification purposes; thus, the gum opium samples were extracted directly with CD3 OD, which shortened sample preparation time. A full discrimination between the two geographical origins was achieved by 1 H-NMR profiling and orthogonal partial least squares discriminant analysis. All 30 opium samples were classified correctly by the developed orthogonal partial least squares discriminant analysis model. Compared with traditional chromatography and mass spectrometry profiling methods, the 1 H-NMR profiling method was faster (with instrument analysis time of less than 3 min) and reproducible. This study provides new insights into the applying of NMR profiling and chemometrics to rapid drug profiling analysis.

Applications of Solution NMR Spectroscopy in Quality Assessment and Authentication of Bovine Milk

Nuclear magnetic resonance (NMR) spectroscopy is emerging as a promising technique for the analysis of bovine milk, primarily due to its non-destructive nature, minimal sample preparation requirements, and comprehensive approach to untargeted milk analysis. These inherent strengths of NMR make it a formidable complementary tool to mass spectrometry-based techniques in milk metabolomic studies. This review aims to provide a comprehensive overview of the applications of NMR techniques in the quality assessment and authentication of bovine milk. It will focus on the experimental setup and data processing techniques that contribute to achieving accurate and highly reproducible results. The review will also highlight key studies that have utilized commonly used NMR methodologies in milk analysis, covering a wide range of application fields. These applications include determining milk animal species and feeding regimes, as well as assessing milk nutritional quality and authenticity. By providing an overview of the diverse applications of NMR in milk analysis, this review aims to demonstrate the versatility and significance of NMR spectroscopy as an invaluable tool for milk and dairy metabolomics research and hence, for assessing the quality and authenticity of bovine milk.

Milk metabolome reveals pyrimidine and its degradation products as the discriminant markers of different corn silage-based nutritional strategies

The purpose of this study was to evaluate the effect of 6 different feeding systems (based on corn silage as the main ingredient) on the chemical composition of milk and to highlight the potential of untargeted metabolomics to find discriminant marker compounds of different nutritional strategies. Interestingly, the multivariate statistical analysis discriminated milk samples mainly according to the high-moisture ear corn (HMC) included in the diet formulation. Overall, the most discriminant compounds, identified as a function of the HMC, belonged to AA (10 compounds), peptides (71 compounds), pyrimidines (38 compounds), purines (15 compounds), and pyridines (14 compounds). The discriminant milk metabolites were found to significantly explain the metabolic pathways of pyrimidines and vitamin B₆. Interestingly, pathway analyses revealed that the inclusion of HMC in the diet formulation strongly affected the pyrimidine metabolism in milk, determining a significant up-accumulation of pyrimidine degradation products, such as 3-ureidopropionic acid, 3-ureidoisobutyric acid, and 3-aminoisobutyric acid. Also, some pyrimidine intermediates (such as l-aspartic acid, N-carbamoyl-l-aspartic acid, and orotic acid) were found to possess a high discrimination degree. Additionally, our findings suggested that the inclusion of alfalfa silage in the diet formulation was potentially correlated with the vitamin B₆ metabolism in milk, being 4-pyridoxic acid (a pyridoxal phosphate degradation product) the most significant and up-accumulated compound. Taken together, the accumulation trends of different marker compounds revealed that both pyrimidine intermediates and degradation products are potential marker compounds of HMC-based diets, likely involving a complex metabolism of microbial nitrogen based on total splanchnic fluxes from the rumen to mammary gland in dairy cows. Also, our findings highlight the potential of untargeted metabolomics in both foodomics and foodomics-based studies involving dairy products.

Metabolic Profiling of Rumen Fluid and Milk in Lactating Dairy Cattle Influenced by Subclinical Ketosis Using Proton Nuclear Magnetic Resonance Spectroscopy

Simple Summary

Ketosis metabolic research is extremely rare in Korea. This study aimed to compare the rumen fluid and milk metabolites between healthy and subclinical ketosis-diagnosed lactating dairy cattle. Six Holstein cows were allocated into two groups based on whether they fit the criteria for subclinical ketosis, and their rumen fluid and milk samples were collected from the stomach tube and pipeline milking system. Rumen fluid and milk samples metabolites were analyzed using proton nuclear magnetic resonance spectroscopy. They were identified and quantified using the Chenomx NMR Suite 8.4 software and statistical analysis was performed using Metaboanalyst 5.0. In rumen fluid, ruminant energy source metabolites (acetate, glucose, and propionate) were significantly higher in the healthy group, whereas in milk, ketone body metabolites (3-hydroxybutyrate and acetoacetate) were significantly higher in the subclinical ketosis-diagnosed group. This report will serve as a reference guide for future studies on ketosis metabolomics in Korea.

Abstract

Ketosis metabolic research on lactating dairy cattle has been conducted worldwide; however, there have been very few Korean studies. Biofluids from lactating dairy cattle are necessary to study ketosis metabolic diseases. Six Holstein cows were divided into two groups (healthy (CON) and subclinical ketosis diagnosed (SCK)). Rumen fluid and milk samples were collected using a stomach tube and a pipeline milking system, respectively. Metabolites were determined using proton nuclear magnetic resonance (NMR) spectroscopy and they were identified and quantified using the Chenomx NMR Suite 8.4 software and Metaboanalyst 5.0. In the rumen fluid of the SCK group, butyrate, sucrose, 3-hydroxybutyrate, maltose, and valerate levels were significantly higher than in the CON group, which showed higher levels of N,N-dimethylformamide, acetate, glucose, and propionate were significantly higher. Milk from the SCK group showed higher levels of maleate, 3-hydroxybutyrate, acetoacetate, galactonate, and 3-hydroxykynurenine than that from the CON group, which showed higher levels of galactitol, 1,3-dihydroxyacetone, γ-glutamylphenylalanine, 5-aminolevulinate, acetate, and methylamine. Some metabolites are associated with ketosis diseases and the quality of rumen fluid and milk. This report will serve as a future reference guide for ketosis metabolomics studies in Korea.

Metabolomic Markers of Storage Temperature and Time in Pasteurized Milk

The current date labeling system for pasteurized milk is based on the predicted growth of spoilage microorganisms, but inherent inaccuracies and the inability to account for environmental factors (e.g., temperature fluctuations) contribute to household and retail food waste. Improved shelf-life estimation can be achieved by monitoring milk quality in real-time. In this study, we identify and quantify metabolites changing over storage temperature and time, the main factors affecting milk stability. Pasteurized 2% fat milk was stored at 4, 10, 15, and 20 °C. Metabolite change was analyzed using untargeted and targeted nuclear magnetic resonance (NMR) metabolomics approaches. Several metabolites correlated significantly to storage time and temperature. Citric acid decreased linearly over time at a temperature-dependent rate. Ethanol, formic acid, acetic acid, lactic acid, and succinic acid increased non-linearly after an initial period of minimal increase. Butyric acid exhibited strong inverse temperature dependencies. This study provides the first analysis of the effect of time and temperature on the concentration of key metabolites during milk storage. Candidate molecules for shelf-life monitoring have been identified, and the results improve our understanding of molecular changes during milk storage. These results will inform the development of real-time shelf-life indicators for milk, helping to reduce milk waste.

Detection of bovine milk adulteration in caprine milk with N-acetyl carbohydrate biomarkers by using 1H nuclear magnetic resonance spectroscopy

In a return to tradition, the popularity of caprine milk is on the rise. However, particularly in countries with developed dairy industries based on bovine milk, there is the risk of adulteration with bovine milk, which is a cheaper alternative. Thus, a rapid, robust, and simple method for the detection of bovine milk added to caprine milk is necessary, and ¹H nuclear magnetic resonance spectroscopy appears to provide a solution. A matrix of 115 pure and artificially adulterated pasteurized milk samples was prepared and used to discover biomarkers of bovine milk that are independent of chemical and biological variation caused by factors such as genetics, diet, or seasonality. Principal component analysis and orthogonal projections to latent structures discriminant analysis of pure bovine milk and pure caprine milk revealed spectral features that were assigned to the resonances of 4 molecules. Of these, the peaks corresponding to protons in the N-acetylglucosamine and N-acetylgalactosamine acetyl moieties showed significant applicability for our method. Receiver operating characteristic curve analysis was used to evaluate the performance of the peak integrals as biomarkers of adulteration. This approach was able to distinguish caprine milk adulterated with 5% of bovine milk with 84.78% accuracy and with 10% of bovine milk an excellent 95.65% accuracy. This study demonstrates that N-acetyl carbohydrates could be used as biomarkers for the detection of bovine milk in caprine milk and could help in protecting caprine milk authenticity.

Exploration of metabolite profiles in the biofluids of dairy cows by proton nuclear magnetic resonance analysis

Studies that screen for metabolites produced in ruminants are actively underway. We aimed to evaluate the metabolic profiles of five biofluids (ruminal fluid, serum, milk, urine, and feces) in dairy cow by using proton nuclear magnetic resonance (1H-NMR) and provide a list of metabolites in each biofluid for the benefit of future research. We analyzed the metabolites in five biofluids from lactating cows using proton nuclear magnetic resonance imaging; 96, 73, 88, 118, and 128 metabolites were identified in the five biofluids, respectively. In addition, 8, 6, 9, and 17 metabolites were unique to ruminal fluid, serum, milk, and urine, respectively. The metabolites present at high concentrations were: acetate, propionate, and butyrate in ruminal fluid; lactate, glucose, and acetate in serum; and lactose, guanidoacetate, and glucitol in milk. In addition, the following metabolites were present at high concentrations: hippurate, urea, and trimethylamine N-oxide in urine and acetate, propionate, and butyrate in feces. The score plots of the principal component analysis did not show clear distinctions among the five biofluid samples. The purpose of this study was to verify the ability of our metabolomics approaches to identify metabolites in the biofluids of dairy cows.

Simple and Rapid (Extraction) Protocol for NMR Metabolomics-Direct Measurement of Hydrophilic and Hydrophobic Metabolites Using Slice Selection

Investigating the metabolic profiles of solid sample materials with solution nuclear magnetic resonance (NMR) spectroscopy requires the extraction of these metabolites. This is commonly done by using two immiscible solvents such as water and chloroform for extraction. Subsequent solvent removal makes these extraction procedures very time-consuming. To shorten the preparation time of the NMR sample, the following protocol is proposed: the metabolites from a solid or liquid sample are extracted directly in the NMR tube, the NMR tube is centrifuged, and the metabolite profiles in the aqueous and organic phases are determined by using slice-selective proton NMR experiments. This protocol was tested with 11 black teas and 11 green teas, which can be easily distinguished by their metabolic profiles in the aqueous phase. As a test case for liquid samples, 29 milk samples were investigated. The geographical origin of the diaries where the milk was processed could not be determined unequivocally from the metabolic profiles of the hydrophilic metabolites; however, this was easily seen in the lipid profiles. As shown for the different test samples, the extraction protocol in combination with slice-selection NMR experiments is suitable for metabolic investigations. Because samples are rapidly processed, this approach can be used to explore different extraction strategies for metabolite isolation.

An NMR Metabolomics Approach to Investigate Factors Affecting the Yoghurt Fermentation Process and Quality

A great number of factors can influence milk fermentation for yoghurt production such as fermentation conditions, starter cultures and milk characteristics. It is important for dairy companies to know the best combinations of these parameters for a controlled fermentation and for the desired qualities of yoghurt. This study investigates the use of a ¹H-NMR metabolomics approach to monitor the changes in milk during fermentation from time 0 to 24 h, taking samples every hour in the first 8 h and then at the end-point at 24 h. Three different starter cultures (L. delbrueckii ssp. bulgaricus, S. thermophilus and their combination) were used and two different heat treatments (99 or 105 °C) were applied to milk. The results clearly show the breakdown of proteins and lactose as well as the concomitant increase in acetate, lactate and citrate during fermentation. Formate is found at different initial concentrations depending on the heat treatment of the milk and its different time trajectory depends on the starter cultures: Lactobacillus cannot produce formate, but needs it for growth, whilst Streptococcus is able to produce formate from pyruvate, therefore promoting the symbiotic relationship between the two strains. On the other hand, Lactobacillus can hydrolyze milk proteins into amino acids, enriching the quality of the final product. In this way, better insight into the protocooperation of lactic acid bacteria strains and information on the impact of a greater heat treatment in the initial matrix were obtained. The global chemical view on the fermentations provided using NMR is key information for yoghurt producers and companies producing starter cultures.

Chemometric analysis combined with FTIR spectroscopy of milk and Halloumi cheese samples according to species' origin

Food adulteration is an issue of major concern, as numerous foodstuffs and beverages do not follow their labeling. Our research interest is in the field of authenticity of dairy products and particularly cheese. Adulteration of dairy products is a well-known phenomenon, and there are numerous published studies specifically on the authenticity of cheese. In fact, substitution of a portion of fat and/or proteins, adulteration with milk of other species' origin, and mislabeling of ingredients are some of the main issues that the science of dairy products' authenticity is regularly facing. Discrimination of dairy products can be determined through several chemical or microbiological methods as presented in the literature. In addition, chemometric analysis is an important tool for interpretation of a huge load of measurements. The aim of this study is to discriminate between various milk samples, which is the primary ingredient of dairy products. Milk samples with different trademarks were analyzed. That data was combined with Halloumi cheese samples for chemometric discrimination of species' origin. The innovative point of this study is the fact that it is the first time that a research study related to dairy products includes Halloumi cheese which is a traditional Cypriot cheese, not well-studied until now. The first step of the methodology was the freeze-drying via lyophilization of the samples. Fourier transformed infrared spectroscopy (FTIR) was chosen for their chemical characterization. Moreover, interpretation of the measurements was carried out by chemometric analysis using SIMCA software. For this study, FTIR data combined with chemometrics have given a very good discrimination of the samples according to their species' origin. Chemometric methods such as PCA and OPLS-DA have been used with great success. In the future, this model will be studied regarding geographical origin of the samples.

Metabolomics comparison of rumen fluid and milk in dairy cattle using proton nuclear magnetic resonance spectroscopy

Objective

The metabolites that constitute the rumen fluid and milk in dairy cattle were analyzed using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and compared with the results obtain for other dairy cattle herds worldwide. The aim was to provide basic dataset for facilitating research on metabolites in rumen fluid and milk.

Methods

Six dairy cattle were used in this study. Rumen fluid was collected using a stomach tube, and milk was collected using a pipeline milking system. The metabolites were determined by ¹H-NMR spectroscopy, and the obtained data were statistically analyzed by principal component analysis, partial least squares discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0.

Results

The total numbers of metabolites in rumen fluid and milk were measured to be 186 and 184, and quantified as 72 and 109, respectively. Organic acid and carbohydrate metabolites exhibited the highest concentrations in rumen fluid and milk, respectively. Some metabolites that have been associated with metabolic diseases (acidosis and ketosis) in cows were identified in rumen fluid, and metabolites associated with ketosis, somatic cell production, and coagulation properties were identified in milk.

Conclusion

The metabolites measured in rumen fluid and milk could potentially be used to detect metabolic diseases and evaluate milk quality. The results could also be useful for metabolomic research on the biofluids of ruminants in Korea, while facilitating their metabolic research.

Nuclear Magnetic Resonance-Based Metabolomic Comparison of Breast Milk and Organic and Traditional Formula Milk Brands for Infants and Toddlers

In recent years, new formula milk (FM) products based on milk from farms that strictly adhere to the "organic farming" practices became available. However, little is known about the differences in nutritional profile of these organic formulae with respect to traditional ones. We comprehensively evaluated the metabolite profiles of FM with nuclear magnetic resonance (NMR)-based metabolomic analysis. Five commercial brands of organic and nonorganic formula liquid milk for infants (0-12 months) and toddlers (1-3 years) were analyzed, together with human milk (HM) samples. Proton NMR (¹H NMR) spectroscopy mapped molecular characteristics of FM linked to different production techniques, and identified differences between FM and HM samples. We performed a metabolic fingerprint analysis using multivariate and univariate statistical techniques. A clear distinction is found among different commercial brands of the FM samples. In addition, several differences in metabolomic profiles of FM have been found in comparison with HM for the first time. Notably, it was possible to identify, both in the formulations for toddlers and for infants, metabolites that vary in concentration between the formulae produced with milk obtained according to organic farming techniques, and those produced using nonorganic milk. In particular, organic and nonorganic formulations are differentiated by the levels of glucose, methionine, o-phosphocholine, butyrate, hippurate, creatine, and dimethyl sulfone. Importantly, the HM appeared to differ from both organic and nonorganic brands in a context of metabolites. These findings inform efforts to design FM in ways that closely mimic HM, and guide research to differentiate organic and traditional FM.

Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

Evaluation of sample preparation methods for NMR-based metabolomics of cow milk

The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.

NMR metabolomic fingerprinting distinguishes milk from different farms

A fast and reproducible protocol for milk Nuclear Magnetic Resonance (NMR) metabolomic fingerprinting was developed, allowing for an accurate discrimination among milk samples from large-scale distribution, as well as among milk sample from different farms located in the same restricted geographical area. Seasonal variations in milk composition and correlations with cows' nutritional patterns are also assessed, underlining relationships between feeding and metabolites. The most important difference was related to the use of silage feeding. This finding is relevant to assess the suitability of milk for different dairy products. A prominent example is parmesan cheese, the preparation protocol of which excludes milk from silage-fed cows.

The application of NMR-based milk metabolite analysis in milk authenticity identification

BACKGROUND

Milk is an important food component in the human diet and is a target for fraud, including many unsafe practices. For example, the unscrupulous adulteration of soymilk into bovine and goat milk or of bovine milk into goat milk in order to gain profit without declaration is a health risk, as the adulterant source and sanitary history are unknown. A robust and fit-for-purpose technique is required to enforce market surveillance and hence protect consumer health. Nuclear magnetic resonance (NMR) is a powerful technique for characterization of food products based on measuring the profile of metabolites. In this study, 1D NMR in conjunction with multivariate chemometrics as well as 2D NMR was applied to differentiate milk types and to identify milk adulteration.

RESULTS

Ten metabolites were found which differed among milk types, hence providing characteristic markers for identifying the milk. These metabolites were used to establish mathematical models for milk type differentiation. The limit of quantification (LOQ) of adulteration was 2% (v/v) for soymilk in bovine milk, 2% (v/v) for soymilk in goat milk and 5% (v/v) for bovine milk in goat milk, with relative standard deviation (RSD) less than 10%, which can meet the needs of daily inspection.

CONCLUSION

The NMR method described here is effective for milk authenticity identification, and the study demonstrates that the NMR-based milk metabolite analysis approach provides a means of detecting adulteration at expected levels and can be used for dairy quality monitoring. © 2016 Society of Chemical Industry.

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.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 3. Untargeted metabolomics

Metabolomic investigation of milk from cows with bovine mastitis has revealed major changes in carbohydrates, lipids, amino acids, nucleotides and bile acids.

NMR-based metabolite profiling of human milk: A pilot study of methods for investigating compositional changes during lactation

Low-molecular-weight metabolites in human milk are gaining increasing interest in studies of infant nutrition. In the present study, the milk metabolome from a single mother was explored at different stages of lactation. Metabolites were extracted from sample aliquots using either methanol/water (MeOH/H2O) extraction or ultrafiltration. Nuclear magnetic resonance (NMR) spectroscopy was used for metabolite identification and quantification, and multi- and univariate statistical data analyses were used to detect changes over time of lactation. Compared to MeOH/H2O extraction, ultrafiltration more efficiently reduced the interference from lipid and protein resonances, thereby enabling the identification and quantification of 36 metabolites. The human milk metabolomes at the early (9-24 days after delivery) and late (31-87 days after delivery) stages of lactation were distinctly different according to multi- and univariate statistics. The late lactation stage was characterized by significantly elevated concentrations of lactose, choline, alanine, glutamate, and glutamine, as well as by reduced levels of citrate, phosphocholine, glycerophosphocholine, and N-acetylglucosamine. Our results indicate that there are significant compositional changes of the human milk metabolome also in different phases of the matured lactation stage. These findings complement temporal studies on the colostrum and transitional metabolome in providing a better understanding of the nutritional variations received by an infant.

Applications of NMR in dairy research

NMR is a robust analytical technique that has been employed to investigate the properties of many substances of agricultural relevance. NMR was first used to investigate the properties of milk in the 1950s and has since been employed in a wide range of studies; including properties analysis of specific milk proteins to metabolomics techniques used to monitor the health of dairy cows. In this brief review, we highlight the different uses of NMR in the dairy industry.

Exploring human breast milk composition by NMR-based metabolomics

Breast milk is a complex fluid evolutionarily adapted to satisfy the nutritional requirements of growing infants. In addition, milk biochemical and immunological components protect newborns against infective agents in the new environment. Human milk oligosaccharides, the third most abundant component of breast milk, are believed to modulate the microbiota composition, thus influencing a wide range of physiological processes of the infant. Human milk also contains a number of other bioactive compounds, the functional role of which has not yet been clearly elucidated. In this scenario, NMR-based metabolic profiling can provide a rapid characterisation of breast milk composition, thus allowing a better understanding of its nutritional properties.

NMR-Based Milk Metabolomics

Milk is a key component in infant nutrition worldwide and, in the Western parts of the world, also in adult nutrition. Milk of bovine origin is both consumed fresh and processed into a variety of dairy products including cheese, fermented milk products, and infant formula. The nutritional quality and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining a better understanding of how milk composition is linked to nutritional or quality traits.