The ¹H HR-NMR Methods for the Evaluation of the Stability, Quality, Authenticity, and Shelf Life of Foods

Definition

¹H High-Resolution Nuclear Magnetic Resonance (¹H HR-NMR) spectroscopy is a powerful analytical methodology used in various fields, including food science. In the food science field, NMR combined with the principles of metabolomics can provide detailed information about a food’s molecular composition, structure, dynamics, and interactions within food matrices, making it invaluable for assessing changes during storage, processing, and shelf life. This entry aims to list the main applications of one-dimensional ¹H HR-NMR methods in the field of food science, such as their use in the assessment of the stability, quality, authenticity, and shelf life of food samples. Several kinds of foods are taken into consideration to give a huge overview of the potentiality of the methods.

1. Introduction

¹H High-Resolution Nuclear Magnetic Resonance (¹H HR-NMR) spectroscopy is a versatile analytical methodology that exploits the magnetic properties of certain atomic nuclei. It has widespread applications in different scientific areas, such as chemistry [1], biochemistry [2,3], medicine [4,5,6], and materials science [7]. In recent decades, this methodology has also been largely used in the fields of health, environment, and food science, with a high amount of research papers produced [8,9,10]. In these fields, the nuclear methodology is often combined with the principles of metabolomics [11], where the metabolic profile of a biological system (e.g., cells, tissues, or biofluids) is studied. The so-called NMR-based metabolomics approach helps in identifying and quantifying small molecules, providing insights into metabolic pathways and changes in response to various external conditions [12]. NMR-based metabolomics has several unique advantages over other metabolomics techniques such as gas chromatography (GC) and mass spectrometry (MS), which is why it is increasingly being adopted in various fields. First of all, it is a more uniform detection system and can be used directly for the identification and quantification of metabolites, even in vivo [11]. Its non-destructive nature, relatively short times, and ability to measure samples such as urine directly are the most promising features of NMR. Another major advantage of NMR is the ease of quantifying all compounds, since a single internal standard can quantify all degraded metabolites without requiring calibration curves for each compound. Finally, the NMR specimen needs no physical or chemical treatment before analysis, only the adjustment of solution conditions such as temperature, pH, and salt concentration [11]. In the latter case, general sample preparation (biological or food) involves three basic steps: (1) The first step involves rapid sample collection and freezing to quench metabolism and preserve metabolites. Samples are typically stored at −80 °C to avoid degradation. (2) The second step involves extracting methods. The choice of extraction method depends on the function and the polarity of the metabolites to be extracted. If both polar and lipophilic metabolites are to be extracted, methanol and chloroform extraction can be used to separate metabolite classes. (3) Optimization of the solution for NMR spectroscopy is the third step. This typically involves buffering the pH of the sample to minimize chemical shift variation of the NMR resonance (e.g., 100 mM phosphate buffer, pH = 7.00), adding deuterium oxide (D₂O) to provide frequency locking to the spectrometer, and adding an internal chemical shift (and intensity) standard such as sodium 3-(trimethylsilyl)propionate 2,2,3,3-d4 (TSP) [11]. In food science, the NMR-based metabolomics approach is also known as Foodomics [13]. It can be employed for several applications which include, above all, analyzing the composition and measuring the physicochemical properties and functionality of food matrices [9]. Laghi et al. [13] clearly explain the reason why, in several areas of the food industry and food science, a Foodomics approach can be adopted, and the main reason is that the metabolome can be considered the last step of the omics pathway, which includes the genome, transcriptome, and proteome. Thus, it is the best representation of a food’s phenotype, providing a significant view of all the metabolites that may have an effect on or interact with the organism [13]. There is another important aspect that can and must be taken into consideration when dealing with NMR spectroscopy in the Foodomics field: it can be employed for the evaluation of the stability, quality, authenticity, and shelf life of food samples. This is highly important based on the increased demand from consumers for high-quality foods, quality that should be guaranteed during the period between purchase and consumption [14]. In the narrative review by Ciampa et al. [8], the authors perfectly explain the advantages of using ¹H-NMR metabolomics in food quality determination compared to other traditional methods, and why the food industry should pay attention to this emerging approach. First, the NMR method can assess and guarantee the quality of foodstuff through its capability to offer qualitative, as well as quantitative, knowledge about food samples, with high reproducibility. At the same time, compared with the other methods, it is more green, as it operates following the green chemistry guidelines for sample preparation [8]. NMR provides direct, non-destructive information on sample composition and concentration with confidence. Due to (1) the low cost per sample, (2) minimal sample preparation, (3) the simultaneous identification and quantification of compounds, (4) the combination of targeted and non-targeted analysis to ensure the presence of intended ingredients and the absence of impurities or adulterants, and (5) the advanced statistical models available to assess authenticity of origin, species purity, adulteration, production process control, sample similarity, etc., NMR is becoming a strategic tool for industries to assess and ensure food safety and quality to avoid fraud, contamination, adulteration, etc. Thus, this entry aims to give a summary and an overview of the applications of one-dimensional (1D) ¹H HR-NMR in the field of food quality analysis, also including food stability, authenticity, and shelf life, exploring, above all, two of the most used approaches in the food science field.

2. The ¹H HR-NMR Methods

NMR can provide detailed information about the molecular structures, compositions, and dynamics of the compounds present in a sample [15,16]. For example, some general methods used in NMR’s application, including during the assessment of the stability, quality, authenticity, and shelf life of food samples, are listed here: (1) Chemical Shift Analysis (CSA) [17]. Each type of nucleus in a molecule (N, C, H, and P) gives rise to a characteristic set of Chemical Shifts (CSs) in the NMR spectrum. In Organic Chemistry, a CS refers to the position of an NMR signal in relation to a standard reference signal, such as the TSP. It is measured in parts per million (ppm) and indicates the electronic environment surrounding a specific atom. CSs are highly reproducible, sensitive parameters with far-reaching utility in characterizing the structure and dynamics of a diverse range of biomolecules [18]. By comparing the chemical shift values observed in the NMR spectrum of a food sample to reference data or databases, it is possible to identify the types of compounds present. The chemical shift values are influenced by the electronic environment of the nuclei and can be indicative of the molecular structure. In NMR spectra, CSs are also sensitive to changes in molecular environments, providing information about the type and location of atoms within a molecule. Monitoring changes in chemical shifts over time can reveal alterations in the composition of food sample extracts and identify potential degradation products [19]. By acquiring NMR spectra of food samples at different time points, any shifts in the chemical shift values that indicate changes in the molecular composition or structure can be monitored. At the same time, it is necessary to keep in mind that factors such as pH, the presence of paramagnetic cations, and ionic strength often cause variations in CSs, which can be problematic for data analysis [9].

CSA helps to assess the quality of food samples by confirming the absence or presence of certain expected compounds. Unexpected peaks or shifts may indicate contamination or the presence of unwanted compounds. In summary, the use of chemical shift analysis in NMR for food analysis serves as a powerful tool for the qualitative assessment of food samples. (2) Peak Intensity and Area Analysis. In an NMR spectrum, especially in 1D experiments, each peak’s size is representative of the number of nuclei that compete in the characterization of that peak. The evaluation of the peak’s size is possible through an integration method that measures the area under the peak. It is also possible to obtain relative information about the number of nuclei without adopting an integration method: A single signal associated, for example, with three hydrogen atoms would be about three times larger than a single signal associated with a single hydrogen atom. This intensity is proportional to the area under the peak [20], and exists when the considered chemical groups of the same molecule have the same concentration.

The area under an NMR peak is calculated by integrating the signal over a specific range of frequencies. This area represents the total number of nuclei contributing to that particular signal [21]. The integration process involves summing up the individual intensities (signal heights) at each point within the peak. In general, the area under an NMR peak is a more reliable measure of the quantity of a particular species in the sample compared to peak height, as it accounts for the entire signal. However, for qualitative analysis, peak heights are often used as they are easier to measure directly from the spectrum. Changes in peak intensity or integrated peak areas indicate variations in the concentrations of specific compounds [22]. It is important to note that while peak intensity and area correlate with the abundance of nuclei in the sample, they do not directly provide quantitative information about the concentration of the corresponding compound unless the sample concentration is known and properly calibrated [23,24]. For quantitative analysis, additional techniques are typically employed. For accurate quantification, an internal standard of known concentration and purity is usually added to the sample [23,24]. The ratio of the integrated signal of the analyte to the internal standard is used to calculate the concentration of the analyte. The internal standard should ideally have a non-overlapping signal with the analyte, be chemically inert, and have similar relaxation properties to the analyte. External calibration curves are often used to relate the signal intensity of the analyte to its concentration. This involves running a series of standards with known concentrations through the sample and plotting the integrated signal against the concentration.

3. Chemical Shift Analysis (CSA) for Food Analysis

CSA can indeed be applied to evaluate the stability of food samples, encompassing their quality, authenticity, and shelf life. It can be useful for the following aspects: (1) the identification of components, providing a fingerprint of the sample; (2) monitoring changes in molecular profile composition; and (3) structural elucidation in combination with other NMR experiments such as bidimensional (2D) NMR spectroscopy. In summary, chemical shift analysis in NMR spectroscopy can be a valuable tool for monitoring food samples by providing insights into changes in the compositions, structures, and concentrations of key components [25]. When we deal with all these aspects concerning foods, NMR by itself is not enough, and it becomes necessary to couple it with metabolomics, which is mainly used for the discrimination of sample groups or to highlight significant clusters of unknown samples by using statistical models [26]. The latter may be either targeted (supervised), untargeted (unsupervised), or both, according to the specific application [27]. The supervised method focuses on molecular compound identification by comparing the 1D ¹H NMR spectrum of a metabolite mixture with a 1D ¹H NMR spectrum contained in a specific database such as Chenomx (https://www.chenomx.com/ (accessed on 29 August 2024)). Generally, further validation can be performed through the acquisition of the 2D NMR spectra [28]. The unsupervised metabolomics method is based on the appropriate identification of a defined set of metabolites in samples (biological or food samples) [28] to build up a molecular dataset composed of the assigned metabolites. The molecular dataset is then analyzed by using specific statistical data analysis tools or packages (see, for example, R Project for Statistical Computing) to verify how well-targeted metabolites contribute to separating the control group from the rest of the experiment (the phenotype of interest group) [28]. Untargeted studies aim to compare, measure, and identify as many signals as possible in a set of spectra, and generally, the metabolite ID’s identification of these signals is performed using databases [28]. This approach is very interesting, above all, in the identification of unknown biomarkers in research studies [28]. Unfortunately, a lot of signals detected in untargeted studies cannot be identified since their spectra are not present in databases, although these are constantly expanded by new metabolites. Correlating changes in chemical shifts with stability parameters enables researchers to assess the quality, stability, authenticity, and shelf life of food products. For example, Ciampa and Picone [29] developed a model able to predict the kinetics of the evolution of different compounds related to fish freshness using fish stored at different temperatures by exploiting chemical shift analysis in ¹H HR-NMR-based metabolomics approach experiments.

The quality and the freshness of fish are highly perishable and, thus, fish food samples are characterized by a short shelf life. The storage temperature of the fish and the time between the catching and the storage in the fish market are fundamental parameters that can both define and influence the degree of freshness, and as a consequence, the nutritional quality too. Through both chemical and physical indices it is possible to estimate the freshness and the quality of food, as described by Ciampa and Picone [29]. In this research work, the authors highlighted how different temperatures during storage and shelf life (+4 °C and 0 °C) affected the metabolic profile of two species of fish samples: red mullet (Mullus barbatus) and bogue (Boops boops). In particular, ¹H HR-NMR was used to study how the metabolic profile changed during fish spoilage. The kinetic model was estimated using HR-NMR spectroscopy data and it was useful to predict how different compounds related to fish freshness, such as trimethylamine (TMA-N), change over time. TMA is known to be a volatile compound responsible for the characteristic “fishy” odor and is often associated with seafood. It is produced by the degradation of trimethylamine N-oxide (TMAO), which is naturally present in fish and other marine organisms. TMAO is converted to TMA by enzymes produced by bacteria present in the fish, or by endogenous enzymes released upon tissue damage or spoilage [30]. Temperature, pH, storage conditions, and the presence of bacteria are factors that influence the rate of TMA formation in fish. The formation of TMA is often considered an indicator of fish freshness. Fresh fish typically have low levels of TMA, while higher levels indicate the onset of spoilage. Therefore, TMA levels are frequently used as a quality control measure in the seafood industry. Consumption of fish with elevated levels of TMA may lead to an unpleasant odor and taste (Figure 1). Moreover, its presence in spoiled fish can be an indication of potentially harmful bacterial growth, which could pose health risks if consumed. Thus, to ensure food safety and quality, it is essential to handle and store fish properly, maintaining appropriate temperatures and minimizing the time between catch and consumption. Additionally, cooking fish thoroughly can help mitigate the risk of consuming harmful bacteria and reduce the formation of TMA. The determination and quantification of TMA, according to the AOAC Internation, is performed by using a colorimetric reference method. Together with TMA, the exploitation of Adenosine Triphosphate (ATP) catabolites is also an indicator of freshness; in this context, we talk about the K-index, which is usually determined by HPLC [24]. In another paper by Ciampa et al. [31], a monodimensional NMR methodology was adopted for aqueous fish extracts as an alternative method to assess both freshness indexes: TMA and K-index. According to EuroChem guidelines, requirements such as linearity, accuracy, specificity, precision, detection limits, and range of linearity and quantification have been checked to validate the proposed method. The obtained results indicate that the methodology proposed by Ciampa et al. [31] satisfies all the validation requirements as much as the most commonly used methods. In addition, the NMR-based method is faster and more repeatable, and at the same time, it allows us to avoid the use of toluene, formaldehyde, and picric acid, which are dangerous solvents and reagents.

When we deal with the term “quality”, we also include another important aspect, which is food authenticity. The latter is important if we take into consideration the DOP (Designation of Protected Origin) and IGP (Typical Geographic Indications) of foods. The main applications of NMR metabolomics in food authenticity are listed in

Table 1. Applications of NMR metabolomics in food authenticity.

	Application	Example	References
Geographical Origin and Traceability	The metabolic profile of a food product is often influenced by its geographical origin. NMR metabolomics can be used to verify the claimed origin of products like wine, olive oil, coffee, honey, and tea.	Wines from different regions have distinct metabolite profiles due to variations in soil, climate, and grape variety. NMR can detect these differences, confirming whether a wine is truly from a specified region.	[32,33,34,35,36,37]
Detection of Adulteration	NMR metabolomics is highly effective in detecting adulteration, where a product is diluted or mixed with lower-quality ingredients.	MR can identify the addition of cheaper oils in high-quality olive oil by detecting unusual metabolites that should not be present in pure samples.	[38,39,40,41,42,43]
Identification of Organic vs. Conventional Farming	The metabolic profiles of products grown through organic farming can differ from those grown using conventional farming methods. NMR metabolomics can help authenticate claims of organic production.	Organic vegetables might have different levels of certain metabolites compared to conventionally grown ones due to the absence of synthetic fertilizers and pesticides.	[44,45,46,47,48,49]
Authentication of Processing Methods	The way a product is processed can significantly alter its metabolic profile. NMR metabolomics can be used to authenticate products based on specific processing methods.	In coffee, the metabolite profile differs significantly between washed and dry-processed beans. NMR can be used to confirm whether a batch of coffee has been processed as claimed.	[25,50,51,52,53,54]
Varietal Identification	Different varieties of the same product, such as apples, grapes, or tomatoes, have unique metabolic signatures. NMR can be used to verify whether the claimed variety matches the actual variety of the product.	In tea, different varieties of Camellia sinensis (the plant used to produce tea) can be distinguished by their specific metabolite profiles, which NMR can accurately identify.	[55,56,57,58,59]

.

For all food, a significant concern is ensuring its authenticity [26,27,60,61,62,63]. In their recent work, Lolli and Caligiani [26] summarized the main applications of NMR in the field of food authentication for different foodstuffs, highlighting in this way the high versatility of the methodology.

4. Peak Intensity and Area Analysis for Food Quantity Analysis

As stated in the Introduction, changes in peak intensity or integrated peak areas can indicate variations in the concentrations of specific compounds. At the same time, tracking the intensity or area of specific NMR peaks associated with key components in food extracts helps to assess further changes in these components over time. Generally, this approach is called quantitative NMR (qNMR) and it is a specific application of NMR spectroscopy that focuses on the precise and accurate quantification of the chemical compounds within a sample. Unlike qualitative NMR, which is primarily used for structural elucidation, qNMR is optimized to measure the concentrations of specific molecules, often with high precision and accuracy.

The NMR signal area is directly proportional to concentration, and this “response” is the same for all molecules. The qNMR method requires only that (a) the sample be completely dissolved in a fully deuterated solvent; (b) it contains NMR-active nuclides; and (c) a certain amount of care and attention be given to the acquisition and processing of the data. The concentration of a chemical species in an NMR experiment can be determined by one of two methods: (1) absolute integral and (2) internal standard. In the first case, a reference standard solution of known concentration is required to determine an NMR “response factor” for a nuclide under a given set of experimental conditions. In the second case, a spectrum signal is generated. Its “concentration” is determined with respect to a real standard of known concentration [64,65]. These advantages make qNMR suitable for use in food chemistry for the quality control of a wide variety of complex matrices. For example, Burton et al. [54] developed a specific methodology based on qHNMR for the authentication of pure coffee (100% arabica or robusta) and used it to predict the percentage of robusta in blends of 292 coffee samples.

Due to its peculiarity, qNMR has also become prominent as a favored fatty acid characterization methodology, since it makes it possible to obtain and predict the composition and the ratio of fatty acids in oil samples. Furthermore, through this methodology it is even possible to monitor the occurrence of hydrolysis, oxidation, or deterioration processes, as far as to classify edible oils [66]. An interesting application of qNMR in the study of lipids concerns the adulteration of oil, such as essential oils (EOs). EOs have always been part of the herbal tradition and are used not only to create perfumes and enrich cosmetics, but also for therapeutic purposes. For this reason, they are widely used and due to their large profit, they are frequently adulterated [62]. Truzzi et al. [65] applied qNMR to quantify vegetable oils that are used to adulterate and dilute EOs through the quantification of both ¹H and ¹³C glycerol backbone signals, which are present in each vegetable oil containing triglycerides [65].

Lipids are crucial components of foods and cells and are subject to oxidation in many ways, which can adversely affect food quality and human health. Therefore, it is important to find ways to control and reduce the oxidation of lipids in order to improve their stability [67]. The process of lipid oxidation occurs in three stages: initiation with the formation of free radicals, propagation when the free radicals’ chain reactions start, and termination with the formation of non-radical products (Figure 2A). A study conducted by Merkx et al. [68] used ¹H NMR spectroscopy to evaluate lipid oxidation products in emulsion foods, such as mayonnaise, which is particularly prone to oxidation. An efficient and reproducible procedure was developed to obtain samples in which the ¹H NMR signals of oxidation products could be clearly observed (Figure 2B,C). NMR signals of hydroperoxides were specifically identified for fatty acids and isomers. The use of selective ¹H NMR pulses allowed the accurate and rapid measurement of hydroperoxides and aldehydes, with a sensitivity range from 0.03 mmol/kg [68]. Storage temperature was found to have a significant effect on lipid oxidation mechanisms through exploratory multivariate modeling of quantitative ¹H NMR profiles.

Dietary fatty acid intake has received considerable attention regarding its nutritional aspects. For proper nutrition and a healthy lifestyle, the major public health institutes recommend a balanced daily intake of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). Unfortunately, the nature of the effect of fatty acids on human health has been questioned by current lipid intake guidelines in Western industrialized countries [69]. The Western diet [70,71,72] includes high consumption of SFAs. This has been associated with cardiovascular disease (CVD) and coronary heart disease (CHD). However, the lack of a clear association between SFA intake and CVD has been reported in recent work by Siciliano et al. [69]. In the lipid fractions of foods, portions of SFAs, MUFAs, and PUFAs are present either as a fraction of free fatty acids or as structural components of acylglycerol fractions. In addition, some important aspects of foods are regulated by the composition and structural nature of fatty acid chains [69]. For instance, in meat and its related products, the total fatty acid content of the edible parts of the musculature, called marbling fat, has a strong influence on the physical and chemical properties of the food, e.g., consistency, mouthfeel, firmness, and juiciness [69]. Regarding meat, qNMR spectroscopy for the determination and quantification of the fatty acid chain profiles of lipids in pork products during maturation has been proposed by Siciliano et al. [69]. Two typical Mediterranean PDO salamis produced in Calabria, a region in the south of Italy, were selected as case studies. The fatty acid chain profiles of the total lipid extracts were obtained by quantitative NMR analysis. Transesterification of the total lipid extracts provided fatty acids as their methyl esters (FAME). This allowed quantification of the fatty acid acyl chains in the acylglycerol and free fatty acid (FFA) fractions. Oleyl chains predominated and high amounts of polyunsaturated fatty acid chains were observed in all cases. It was also possible to estimate the main nutritional parameters of fermented dry meat products using the proposed spectroscopic method [69].

Another interesting application of qNMR concerns the quantification of polyols in sugar-free foodstuffs by Scettri and Schievano [73]. The control of polyol levels in sugar-free foods is important for nutrition information and quality control. As reported by Lenhart and Chey [74], high levels of polyols (especially mannitol) can cause intolerance symptoms, so monitoring is important for consumer health. Furthermore, for the food industry, polyol monitoring is important for sugar substitution research [73]. Therefore, the aim of Scettri and Schievano [73] was to develop and validate an NMR method for identifying and quantifying six polyols (sorbitol, mannitol, xylitol, erythritol, maltitol, and isomalt) often present in different combinations in sugar-free products. The qNMR method was found to be easy to apply directly to water-suspended solutions without further treatment. The findings show that the method provides a fast and reliable tool to monitor single sweetening agents with good sensitivity and precision [73].

To conclude the overview of the different applications of qNMR, highlighting, above all, the importance of the peak intensity and area analysis in assessing the stability, quality, and shelf life of food samples, a work by Shumilina et al. [75] can be cited. This work is about the monitoring of qualitative and quantitative changes in fish by-products, with special attention paid to salmon (Salmon salar) fish samples due to their commercial importance. This research evaluated the freshness of salmon by-products using a multiparametric approach. Changes in trimethylamine and biogenic amine concentrations were compared with the K-index, and safe temperatures and storage times of salmon by-products were proposed. The K-index, which indicates the presence of enzymatic autolytic mechanisms already active immediately after capture, can be used as a parameter for assessing freshness [31,76]. The process is dependent on the catabolic activities that degrade adenosine 5′-triphosphate (ATP) into its catabolites: adenosine 5′-diphosphate (ADP), adenosine 5′-monophosphate (AMP), and inosine 5′-monophosphate (IMP) into inosine (HxR) and hypoxanthine (Hx). The investigation revealed the presence of significant bioactive metabolites, including phosphocreatine, taurine, and anserine, in extracts of salmon heads, backbones, and viscera. It was established that salmon by-products can be stored for up to seven days at 4 °C without notable alterations in the concentrations of major metabolites or the formation of deleterious compounds. The storage period is reduced to three days at 10 °C due to the accelerated formation of undesirable degradation compounds, such as biogenic amines. The trituration of heads was demonstrated to shorten their storage time (in terms of TMA formation) by 2–3 days. The K-index freshness indicator has been correlated with the formation of these unwanted metabolites [72].

5. Future Perspectives

NMR is a robust tool for assessing the stability, quality, authenticity, and shelf life of foods, offering detailed insights into the metabolic composition of food products. By providing a unique metabolic fingerprint, it helps in verifying geographical origin, detecting adulteration, identifying varieties, and authenticating processing methods. Despite its high cost and complexity, the comprehensive and non-destructive nature of NMR makes it a valuable methodology that can aid the fight against food fraud and ensure the authenticity of high-value food products. At the same time, this is possible as the methodology exhibits the ability to evaluate the stability and quality of food samples through chemical shift, peak intensity, and area analysis. Both qualitative and quantitative analysis can evaluate different aspects, most of which are related to the nutritional aspects of foods. These aspects are important as they meet the consumers’ need to have safe and healthy foods on their tables every day. Hence, the analysis of nutrients at the molecular level is a further challenge concerning human health for NMR and NMR-based metabolomics. So-called Nutrimetabolomics [77] is a field of study focusing on the analysis of small molecules in biological samples such as blood, urine, and tissue, to understand the relationship between diet, metabolism, and health [78]. It is a combination of different disciplines such as nutrition, metabolomics, and systems biology, and it aims to identify and quantify the metabolic response of an individual to dietary interventions [79]. In this context, NMR spectroscopy has been widely used and it is becoming a powerful key analytical tool in human nutritional studies [4,78,80,81,82,83,84].