Nuclear Magnetic Resonance Applications on Bovine Milk

Version	Summary	Created by	Modification	Content Size	Created at	Operation
1		Alberto Ceccon	--	4636	2023-09-14 14:14:33	\|
2	layout & references	Sirius Huang	-42 word(s)	4594	2023-09-15 05:29:58	\|

This entry is adapted from the peer-reviewed paper 10.3390/foods12173240

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.

milk nuclear magnetic resonance metabolomics chemometrics

1. Introduction

Nuclear magnetic resonance (NMR) spectroscopy has proven to be a powerful tool for the analysis of milk and dairy products, given its unique ability to simultaneously detect and identify small molecules within complex matrices, such as milk ^[1]. NMR was initially employed by Odeblad and Westing in the 1950s to investigate milk properties and allowed the identification of distinct components of human milk: lactose from milk plasma and milk fat ^[2]. Since then, NMR spectroscopy has been extensively utilized in various studies, providing valuable insights into the composition, structure, and properties of milk, including the content of key components such as fat, protein, lactose, and minerals. One of the main advantages of NMR spectroscopy in milk analysis is its non-destructive nature, allowing for repeated measurements on the same sample over time and facilitating quality assessment throughout the production process ^[3]. Additionally, its inherent quantitative nature allows it to be used for quantitative metabolomic analysis of milk.

Metabolomics is an emerging tool in milk research; it gives valuable information about the health status and feeding system of the cow, the milk technological process and shelf-life, and eventually the nutritional quality of the milk. It offers reliable indicators and biomarker compounds that can be used for milk quality assessment and authentication. Over the past two decades, NMR has emerged as one of the most commonly used analytical techniques in milk metabolomic research, alongside gas chromatography coupled with mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS) ^[1]. Moreover, NMR-based milk metabolomics is continuously evolving as a promising approach offering high-throughput and comprehensive coverage of metabolites ^[4]^[5]^[6]^[7]^[8].

2. NMR Applications on Bovine Milk: Quality Assessment

NMR spectroscopy has been widely applied in studies of milk quality assessment. Various studies have shown the capability of NMR in determining the composition of bovine milk ^[9]^[10], distinguishing milk from different animal species ^[11], different farms ^[12], and discerning milk from different feeding systems ^[13]^[14] Moreover, NMR analysis enables the evaluation of the nutritional value of milk ^[15]^[16], monitoring the milk quality during processing and storage ^[9]^[15]^[17]^[18], and assessing the technological properties of milk ^[19]^[20].

2.1. Milk Composition

The pioneering study by Hu et al. ^[10] in 2004 holds a significant place in the literature as the first investigation to characterize the chemical composition of whole bovine milk using NMR spectroscopy without any additive or sample pretreatment. In the study, several milk metabolites were assigned to perform both one-dimensional (¹H, ¹³C) and two-dimensional (¹H-¹³C, ¹H-¹⁵N, ¹H-³¹P) NMR experiments. Notably, they identify two compounds, creatine and N-acetyl carbohydrates, for the first time in milk through NMR analysis. It was observed that the addition of 10% D₂O assisted in adjusting the lock and shims, thereby improving the resolution and sensitivity of the NMR spectra. However, the study demonstrated that even without pretreatment, milk can be analyzed for the assignment and quantification of a large number of metabolites ^[10]. Additionally, the study revealed that non-homogenized milk showed broader signals in the ¹H-NMR spectra compared to homogenized milk. This broadening effect was attributed to the presence of larger fat globules in non-homogenized milk, which results in signal broadening and reduced NMR signal sensitivity. This finding later influenced NMR-based milk analysis, allowing for the monitoring of milk fat globule size and stability, as well as the assessment of milk homogenization quality. In their following study published in 2007 ^[21], fatty acids and various milk compounds were successfully quantified by 2D-NMR analysis of whole milk with the addition of 10% D₂O. The authors stated that the study has been reported as the first study using 2D-NMR for the quantification of food components ^[21]. Overall, these studies have contributed to the development of the application of NMR in milk studies.

Foroutan et al. ^[22] conducted a comprehensive study on the chemical composition of bovine milk, employing a multi-platform approach that encompassed targeted and quantitative metabolomics through NMR, LC-HRMS, LC-MS/MS, and inductively coupled plasma-mass spectrometry (ICP/MS). This study, conducted in 2019, reported the largest number of metabolites quantified in bovine milk at that time, including the identification of some new compounds in milk such as lysophosphatidylcholine (18:2), phosphatidylcholine (28:1), and triglyceride (48:3) ^[9]. In total, 296 milk metabolites and metabolite species were quantified and validated using both quantitative metabolomics and literature mining approaches. The authors successfully identified 2355 unique metabolite structures in milk, and the data are readily accessible through a web-accessible database called the Milk Composition Database (MCDB).

2.2. Milk Origin

The pioneering NMR technique has been successfully applied to distinguish milk types according to their animal species origin. Andreotti et al. ^[11] managed to differentiate bovine milk from sheep and goat milk through fatty acid composition using ¹³C-NMR spectroscopy combined with fuzzy logic analysis. Moreover, Garcia et al. ^[23] optimized a ³¹P-NMR fingerprinting approach (with validation on GC) to differentiate milk samples from different animal species (bovine, human, camel, and mare) through their phospholipid (PL) profiles. This method enabled the identification and quantification of multiple PLs in milk samples, facilitating the discrimination of milk according to their animal origin ^[23]. Bruschetta et al. ^[24] also highlighted the effectiveness of ³¹P-NMR fingerprinting in differentiating milk samples from various animal species (e.g., cow, sheep, goat, mare, and donkey). They observed similar ³¹P-NMR profiles among milk from the same animal species, irrespective of the breed, age, or lactation of the animal ^[25]. Moreover, Wei et al. ^[26] conducted a comparative study on the chemical composition of milk from five different mammals, including bovine, human, goat, yak, and donkey. They investigated the PL composition of milk samples using ³¹P-NMR and LC-MS, as well as the fatty acid composition using GC. The study revealed variations in the concentrations and composition of PLs and the size of fat globules among milk samples from different animal groups. Interestingly, human milk exhibited a fat globule size similar to that of bovine milk. These findings suggest that NMR analysis could be utilized to optimize infant formulas to more closely resemble human milk in terms of PLs and milk fat globule structure, thereby ensuring the nutritional quality of such formulas ^[26].

2.3. Milk from Different Feeding Systems

Recent studies have utilized NMR spectroscopy to investigate the relationship between milk cow feeding patterns and milk composition and quality. O’Callaghan et al. ^[27] conducted a study comparing pasture feeding systems to indoor feeding systems and their effects on the milk metabolome using ¹H-NMR metabolomics combined with multivariate data analysis. In the study, milk samples were collected from three commonly practiced feeding systems in Ireland: Pasture perennial ryegrass, perennial ryegrass with white clover, and an indoor total mixed ration consisting of maize and grass silage. The milk samples from cows on the two different pasture feeding systems exhibited similar metabolomes throughout the entire lactation period. In contrast, a significant difference was observed between the milk samples from cows in the indoor silage feeding system and the pasture feeding system. For instance, milk samples from pasture feeding had a higher hippuric acid content, while milk from silage feeding had higher urea content ^[27]. The increased concentration of urea in milk can have a negative impact on milk protein quality, as it is the main source of non-protein nitrogen content in milk ^[27]. Thus, the authors stated that hippuric acid could serve as a biomarker for milk from pasture-based feeding regimes since its presence in milk is correlated with forage feeding. Conversely, Lanza et al. ^[13] reported a higher concentration of hippuric acid in milk from maize silage feeding compared to hay feeding. In the study, both the milk polar fraction and fatty acids of milk samples from three different feeding regimes were analyzed using ¹H-NMR and GC-MS, respectively. Milk samples from lucerne hay feeding were found to have considerably higher levels of polyunsaturated fatty acids (PUFA) compared to those from maize silage or maize silage partially replaced with grass–legume silage feeding systems. Furthermore, the NMR milk polar metabolomic profile was found to be less sensitive to alterations in the cow’s diet compared to the milk FA profile. Indeed, the authors noted that the overall metabolomic profile of milk remained largely unaltered when maize silage was partially substituted with a grass–legume silage mixture. However, a significant change was observed only when maize silage was completely replaced with hay ^[13]. These studies highlight the reliability and precision of NMR in assessing the impact of feeding practices on milk quality.

2.4. Milk Technological Process

Recent NMR techniques have shown significant potential for monitoring milk quality and shelf life during various processing applications and subsequent storage. D. Zhu et al. conducted studies addressing two relatively unexplored aspects in the field: The impact of vat pasteurization ^[28] and the effect of freeze-drying ^[29] processes on milk quality under different storage conditions. Both studies employed untargeted metabolomics using ¹H-NMR and MS-based techniques, followed by multivariate analysis. In the study on vat pasteurization, the authors observed no significant changes in the milk metabolite profile following the pasteurization process. However, during subsequent refrigerated storage (4 °C), the concentration of free fatty acids and some organic acids (such as succinic acid, ribonic acid, and galactonic/gluconic acid) increased, while the concentration of pantothenic acid (vitamin B5) decreased ^[28]. In the study on freeze-drying, by using ¹H-NMR and ¹³C-NMR combined with MS, the authors monitored the effect of the freeze-drying process and different storage conditions (varying temperatures and durations) on the milk metabolome over a period of 224 days. Multivariate analysis of the combined data showed that the freeze-drying process had a slight effect on the content of milk metabolites. Additionally, stable metabolome profiles were observed in freeze-dried milk samples stored in the fridge (4 °C) or in the freezer (−20 °C). In contrast, significant changes in the content of some milk metabolites were detected in freeze-dried milk samples stored at room temperature (20 °C), including decreased concentrations of riboflavin, orotic acid, and acetyl carbohydrates, increased concentrations of fatty acids, threonic acid (an oxidized product of ascorbic acid), and uridine ^[29]. Indeed, the authors highlighted that both vat pasteurization and freeze-drying are effective and mild preservation methods that cause only minor changes in the milk metabolome ^[28]^[29].

Innovative processing applications and their effects on milk quality have also been studied using NMR. Lemos et al. ^[30] focused on the application of NMR-based metabolomics to investigate the effects of hyperbaric preservation on the quality of high-pressure pasteurized (HPP) milk. The study monitored the impact of storage on the metabolic profile of HPP milk stored at an uncontrolled room temperature (~20 °C) with three different pressure levels (50, 75, and 100 MPa) and a storage period of 40 days. For comparison, two control groups were stored at either room temperature or refrigeration (4 °C) under atmospheric pressure. Visual NMR spectra evaluation revealed significant differences between milk samples subjected to hyperbaric storage and the control groups, even after just three days of storage. From the analysis of the NMR spectra, milk samples stored at room temperature showed indications of spoilage, including increased levels of lactate and butyrate; therefore, they were not included in the data analysis. Moreover, milk samples stored under hyperbaric conditions showed broad peaks in both aliphatic and aromatic regions due to an increase in soluble protein levels over time, which was mainly attributed to HPP treatment. This increase in protein content was associated with higher protein digestibility and higher nutritional value. The authors emphasized the potential of NMR-based metabolomics as a powerful tool for monitoring the effects of hyperbaric preservation of HPP milk quality and shelf life ^[30]. In another study, Yang et al. ^[31] investigated the effects of single- and double-cycled hydrostatic pressure treatment on whole and skimmed milk samples with high bacterial loads. They utilized ¹H-NMR for metabolic profiling, GC-MS for the analysis of fatty acids and volatile compounds, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for protein profiling. The study revealed that skimmed milk is more sensitive to high-pressure treatment compared to whole milk, indicating the possible baroprotective effect of milk fat on milk micelles. Additionally, multi-cycled hydrostatic pressure treatment was more effective in microbial inactivation compared to single-cycle treatment, resulting in better preservation of milk quality ^[31]. Overall, these studies conclude that NMR-based metabolomics can be used to monitor milk quality during processing and storage, making it a valuable tool for shelf-life studies of milk.

2.5. Milk Nutritional and Technological Quality

The NMR method has been successfully used for the evaluation of the nutritional and technological quality of bovine milk. Sundekilde et al. ^[20] investigated the relationship between the metabolic profile and technological properties of bovine milk by using NMR-based metabolomics. In the study, skimmed milk samples were classified based on their coagulation properties, which had previously been characterized as either good or poor-coagulating milk. The samples were analyzed using ¹H-NMR and ¹³C-NMR spectroscopy combined with multivariate analysis. The authors found a positive correlation between the coagulation properties of milk and the concentrations of lactose and choline. On the other hand, they observed a negative correlation between carnitine and citrate and the coagulation properties of milk ^[20]. Therefore, the authors suggested that NMR-based metabolomics could be a rapid classification method to differentiate milk according to its coagulation properties. In a subsequent study, Sundekilde et al. ^[19] examined the correlation between milk metabolites and their protein content and how they affect the coagulation properties of milk. The study revealed that specific metabolites related to milk protein content, such as choline, creatinine, and carnitine, showed notable differences between non-coagulating and well-coagulating milk samples, indicating their potential use as indicators of milk quality in terms of coagulation properties ^[19].

The regulation of infant formula requires a detailed declaration of ingredients on the label, as the formulation plays a crucial role in the healthy growth of infants. An untargeted ¹H-NMR approach was used by Zhao et al. ^[32] to determine the nutritional value and compliance of the infant formulas with regulatory requirements. The low-molecular-weight organic compounds in whole bovine milk and commercial infant formulas from different brands were investigated. The study revealed significant differences between milk and infant formulas, as well as the presence of some metabolites that were not declared on the label ^[32]. Moreover, the authors highlighted the importance of determining choline, creatine, and certain nucleotides/nucleosides by NMR, as these milk compounds have beneficial bioactivities for infants and hence can be used as marker compounds to validate the nutritional value of infant formula ^[32].

2.6. Milk Cow Health Status

The health and metabolic status of dairy cows strongly influence milk composition and, consequently, the quality of milk. Luangwilai et al. ^[33] conducted a study in which they characterized and differentiated 46 milk metabolites in raw milk obtained from healthy cows, as well as cows with subclinical and clinical mastitis, using untargeted ¹H-NMR. Mastitis inflammation in cows, which leads to an extremely high somatic cell count, was found to be correlated with variations in the milk metabolome. This resulted in significantly increased concentrations of various free amino acids and organic acids in milk. Moreover, the authors reported that increased levels of alanine, valerate, and N-acetylglucosamine in milk can be used as new potential biomarkers for diagnosing mastitis in cows ^[33]. In another study, Sunds et al. ^[34] investigated glycosidase enzymatic activities in mastitis milk and their effects on milk composition using untargeted ¹H-NMR metabolomics. The presence of certain glycosidases was associated with mastitis inflammation, which had a substantial impact on the milk metabolite profile. The enzymatic activities led to increased levels of free sugars and decreased levels of lactose. Additionally, higher concentrations of fat, protein, and free amino acids were observed, with the latter being attributed to the proteolytic activities of microorganisms due to mastitis ^[34]. Followingly, the mechanisms of mastitis inflammation were explained by C. Zhu et al. ^[22] through milk metabolomics using untargeted ¹H-NMR. The study provided quantitative information on milk metabolites by comprehensively analyzing both milk and serum samples. They characterized and quantified 54 milk metabolites; a greater number compared to previous reports in the literature. The variations in metabolites between serum and milk samples were analyzed to understand the metabolic pathway of mastitis in milk ^[22]. In a different study, Xu et al. ^[35] investigated the biological pathways of negative energy balance in dairy cows by using ¹H-NMR combined with LC-MS through integrated analysis. They focused on the metabolite profile of milk serum obtained from cows in the second week of lactation. Milk samples from cows experiencing negative energy balance showed various alterations in the milk metabolic profile. The authors suggested that the combination of NMR with LC-MS as a complementary technique can provide integrated and reliable information about the energy status of dairy cows and, consequently, the nutritional value of milk ^[35].

3. NMR Applications on Bovine Milk: Authenticity

NMR has emerged as a reliable method for verifying the authenticity of bovine milk. It has been employed as an analytical tool for assessing the authenticity of organic milk ^[36]^[37], determining the composition of reconstituted milk ^[38]^[39], detecting adulteration in milk powder ^[40]^[41], and identifying milk adulteration with melamine ^[42]. In addition, time-domain NMR has been applied in the assessment of milk quality and authenticity ^[16]^[43].

3.1. Bovine Milk Authenticity

Erich et al. studied the fat composition of milk to assess the authenticity of organic milk. In the study, ¹H-NMR and ¹³C-NMR methods were used in combination with stable isotope-ratio mass spectrometry (IRMS) and gas chromatography (GC). Visual NMR spectra comparison combined with chemometric models revealed that organic milk exhibited stronger signals on the bis-allyl methylene groups of α-linolenic acid, the carboxyl group of butyric acid, and the long-chain fatty acids than conventional milk samples ^[36]. Moreover, chemometric analysis (PCA and various classification methods) applied to NMR data combined with stable-isotope data of milk protein and fat (obtained from IRMS) and α-linolenic acid content (quantified using GC) allowed to differentiate organic milk from conventional milk samples ^[36]. Tsiafoulis et al. ^[37] analyzed the lipid fraction of lyophilized organic and conventional milk samples using both targeted and untargeted NMR approaches, with a particular interest in the potential health benefits of organic milk for human consumption. From 1D and 2D-NMR spectra, significantly higher concentrations of conjugated linoleic acid (CLA), linoleic and α-linolenic acids, and overall unsaturated fatty acid content were measured in organic milk. Those molecules are associated with the better nutritional value of organic milk, providing human health benefits upon consumption ^[37].

Renou et al. ^[44] conducted a study to determine the source of milk from two distinct regions—mountainous and plain—where cows were fed with a combination of pasture and silage. Milk fatty acid composition was studied using ¹³C-NMR spectroscopy, whereas the milk aqueous fraction was studied by IRMS as a complementary method. Discriminant analyses considering two factors—geographic origin and feeding—were performed based on five variables: Relative proportions of monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), ¹⁸O/¹⁶O, and deuterium/hydrogen ratios. The study revealed that the level of PUFA in mountain milk was considerably higher than in plain milk, while MUFA and SFA levels did not differ significantly between the two regions. As a result, milk from cows that grazed on pasture had a higher concentration of MUFA compared to milk from cows fed silage. In addition to the impact of feeding practices on milk fatty acid composition, the study conducted by Renou et al. ^[44] found that oxygen isotope ratios were more influenced by geographical location.

Furthermore, Sacco et al. ^[45] employed NMR in combination with IRMS to assess the authenticity of milk from Southern Italy. This innovative approach was compared to traditional spectroscopic and chromatographic techniques. The ¹H-NMR spectra of milk samples from Southern Italy showed some differences when compared to milk from foreign countries, which were also confirmed from 2D-NMR molecular assignments. The ¹H-NMR spectra of southern Italian milk samples displayed two peaks at 1.32 and 4.11 ppm, which represent CH- and CH₃-signals of lactic acid, respectively. In contrast, these peaks were absent in foreign milk samples. Thus, foreign milk showed a higher glycerol and sugar content, as well as a different amino acid composition, compared to Southern Italian milk. These differences in milk metabolites were attributed to distinct feeding systems. Additionally, a multivariant statistical analysis using the variables from the most discriminating peaks and isotope ratios confirmed clear differentiation between milk samples from Southern Italy and those from foreign countries ^[45]. These studies revealed that NMR combined with IRMS provides a more precise approach for geographical origin determination and authenticity assessment of milk compared with traditional techniques ^[44]^[45]. Furthermore, Tenori et al. ^[12] made significant advancements in determining the geographical origin of milk using NMR-based metabolomics. Their approach successfully distinguished milk samples from different farms and brands within the same area and region. However, they emphasized the need to consider seasonal variations that can impact milk composition ^[12]. Overall, NMR can provide a fast and dependable way to detect the geographical origin of milk, which can be particularly relevant for EU-regulated geographically indicated milk products.

3.2. Bovine Milk Adulteration

NMR spectroscopy has been effectively used in adulteration studies to identify the presence of milk from various other sources in bovine milk. Lamanna et al. ^[38] conducted a study using ¹H-NMR metabolomics to detect the amount of sheep milk in bovine milk as a means to detect adulteration. The study involved preparing a milk mixture of sheep milk and bovine milk at different concentrations. By analyzing the aqueous fraction of milk samples, the study identified spectral differences in metabolites such as citrate, lactate, and protein content, enabling the differentiation of pure bovine milk from pure sheep milk. Moreover, a combination of ¹H-NMR metabolic profiles and multilinear regression statistical analysis allowed the determination of the relative concentration of each milk type in the milk mixture ^[38].

Furthermore, Li et al. ^[46] applied 1D and 2D-NMR experiments combined with chemometrics to distinguish between bovine, goat, and soy milk. The study identified specific metabolites that differentiate these milk types, such as higher levels of N-acetyl carbohydrates, ethanolamine, citrate, and lecithin in bovine milk compared to goat milk. On the other hand, lower levels of acetate, carnitine, and creatine were found in bovine milk. Additionally, the presence of D-sucrose was identified as a biomarker for the adulteration of bovine milk with soymilk ^[46]. This method proved effective in detecting bovine milk adulteration, even at low concentrations (as low as 2% (v/v)) ^[46]. Another study highlights the importance of N-acetyl carbohydrates as a significant biomarker for detecting bovine milk adulteration in caprine milk using ¹H-NMR with multivariate data analysis ^[39]. Moreover, the study conducted by Cui et al. ^[41] focused on the adulteration of ultra-high temperature processing (UHT) milk with reconstituted milk using NMR metabolite profiling. The study employed 1D and 2D-NMR experiments with chemometrics to develop a method for identifying UHT and reconstituted milk samples. Through their analysis, the authors identified L-carnitine, succinate, and acetate as biomarkers that could be used to detect the adulteration of UHT with reconstituted milk. Indeed, NMR metabolite profiling can be an effective tool for detecting possible adulteration. This is particularly relevant because UHT milk and reconstituted milk share similarities in their production processes, making it challenging to differentiate them using traditional methods ^[41].

A study conducted by Lachenmeier et al. ^[42] delved into the issue of adulteration of bovine milk-based infant formula with melamine, a compound that can have adverse health effects on infants. In order to detect melamine, the study compared the effectiveness of solution NMR and high-resolution magic angle spinning (HR-MAS). The experiments were performed on 400 MHz and 700 MHz NMR spectrometers, respectively. Results obtained from the NMR experiments were then compared with the most commonly used LC-MS/MS method. The study found that both NMR spectroscopy techniques were sensitive in detecting melamine adulteration in infant formula, thanks to the distinct singlet peak of the NH₂ groups of melamine (resonating at 5.93 ppm), which do not overlap with other signals from milk metabolites. However, the reference LC-MS/MS procedure was the most sensitive, with LOD = 0.005 mg kg⁻¹ (expressed as the amount of detected melamine per kg of infant formula), followed by HR-MAS and solution-state NMR (LOD = 0.69 and 33.3 mg kg⁻¹, respectively) ^[43]. Nevertheless, the authors highlighted certain advantages of NMR and HRMAS over the LC-MS/MS procedure. These advantages include the minimal time required for sample preparation compared to the more complex preparation steps involved in LC-MS/MS and the possibility of performing non-targeted analysis.

In another study, the ability of NMR to detect adulterated bovine milk powder samples was exploited by Bergana et al. ^[40]. The samples were collected worldwide and artificially spiked with the most common adulterants in milk, such as melamine, dicyandiamide, urea, sucrose, maltodextrin, ammonium sulfate, soy protein isolates, and whey protein concentrate. The study found that ¹H-NMR combined with conformity index analysis (i.e., a statistical approach used to assess the level of adulteration in a sample) allowed for the detection of low concentrations of all adulterants (0.005–5% w/w), especially for melamine (0.005% w/w), which exhibited a distinct and characteristic signal at 5.95–5.96 ppm in the NMR spectrum ^[40]. The study concluded that NMR spectroscopy is a powerful and rapid method for ensuring authenticity and detecting adulteration in bovine milk powder.

Beyond high-resolution NMR applications in milk analysis, the use of low-resolution time domain NMR (TD-NMR) has gained attention for online milk processing and quality control in the dairy industry ^[47]^[48]. TD-NMR offers practicality, portability, and relatively low instrumental costs, making it suitable for industrial settings. Unlike high-resolution NMR, TD-NMR does not require cryogenic liquids and enables rapid routine NMR analysis in a non-invasive manner. This allows for online NMR analysis directly through the milk packaging, facilitating real-time monitoring and quality control during milk production. Soyler et al. ^[49] have effectively utilized a low-field benchtop ¹H-NMR (43 MHz) instrument to observe the enzymatic hydrolysis of lactose in milk under continuous flow mode. NMR spectra of the reaction were acquired every seven minutes over a total period of 280 min, allowing the tracking of lactose consumption by monitoring the β-lactose peak. However, the signals from the α-lactose site, which include lactose, glucose, and galactose, were concealed due to signal overlap, and the signals from β-galactose, and β-glucose were hidden by the suppressed water signals. Despite those challenges posed by signal overlap at the low magnetic field strength, the researchers were still able to monitor the enzymatic reaction by exploiting the constant anomeric ratio between the α- and β-anomers of lactose throughout the monitored period ^[49]. This demonstrates the potential of benchtop NMR at the industrial level for online control of residual lactose concentration in lactose-free milk products, which is particularly relevant for meeting regulatory specifications regarding lactose content in milk.

In the field of milk adulteration and quality control, ¹H TD-NMR has also been utilized. Santos et al. ^[43] applied ¹H TD-NMR combined with T₂ relaxation measurements and chemometric methods to detect adulteration in milk samples. The milk samples were artificially adulterated with common adulterants (water, whey, urea, etc.) at different concentrations in the range from 5% to 50% v/v. The adulteration level in milk samples could be detected through the T₂ relaxation time, as higher concentrations of adulterated samples exhibited longer relaxation times compared to control samples. This trend was consistently observed across all milk samples adulterated with various adulterants at the same concentration level ^[43]. In another study, Coimbra et al. ^[16] successfully detected formaldehyde adulteration in bovine milk using ¹H TD-NMR during refrigerated storage (0 and 48 h). The T₂ relaxation curves showed that changes in relaxation times were directly proportional to the concentration of added formaldehyde, with higher concentrations of formaldehyde resulting in increased T₂ relaxation times. The authors explained that the addition of formaldehyde caused coagulation of casein in adulterated milk samples during storage, leading to alterations in water and fat mobility and consequently increased T₂ relaxation times. Such studies highlight the effectiveness and reliability of TD-NMR in the online assessment of milk quality and authenticity.

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