Application of 1H NMR for the characterisation and authentication of ‘‘Tonda Gentile Trilobata” hazelnuts from Piedmont (Italy)

Geographical origin determination of the PDO hazelnut (cv. Giresun Tombul) by chemometric analysis of FT-NIR and Raman spectra acquired from shell and kernel

Turkey is the leading producer of hazelnuts, contributing to 62% of the total global production. Among 18 distinct local hazelnut cultivars, Giresun Tombul is the only cultivar that has received Protected Designation of Origin denomination from the European Comission (EC). However, there is currently no practical objective method to ensure its geographic origin. Therefore, in this study NIR and Raman spectroscopy, along with chemometric methods, such as principal component analysis, PLS-DA (partial least squares-discriminant analysis), and SVM-C (support vector machine-classification), were used to determine the geographical origin of the Giresun Tombul hazelnut cultivar. For this purpose, samples from unique 118 orchards were collected from eight different regions in Turkey during the 2021 and 2022 growing seasons. NIR and Raman spectra were obtained from both the shell and kernel of each sample. The results indicated that hazelnut samples exhibited distinct grouping tendencies based on growing season regardless of the spectroscopic technique and sample type (shell or kernel). Spectral information obtained from hazelnut shells demonstrated higher discriminative power concerning geographical origin compared to that obtained from hazelnut kernels. The PLS-DA models utilizing FT-NIR (Fourier transform near-infrared) and Raman spectra for hazelnut shells achieved validation accuracies of 81.7% and 88.3%, respectively, while SVM-C models yielded accuracies of 90.9% and 86.3%. It was concluded that the lignocellulosic composition of hazelnut shells, indicative of their geographic origin, can be accurately assessed using FT-NIR and Raman spectroscopy, providing a nondestructive, rapid, and user-friendly method for identifying the geographical origin of Giresun Tombul hazelnuts. PRACTICAL APPLICATION: The proposed spectroscopic methods offer a rapid and nondestructive means for hazelnut value chain actors to verify the geographic origin of Giresun Tombul hazelnuts. This could definitely enhance consumer trust by ensuring product authenticity and potentially help in preventing fraud within the hazelnut market. In addition, these methods can also be used as a reference for future studies targeting the authentication of other shelled nuts.

NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review

Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts.

Corylus avellana "Nocciola Piemonte": metabolomics focused on polar lipids and phenolic compounds in fresh and roasted hazelnuts

The common hazel plant (Corylus avellana L., Betulaceae) is one of the most popular tree nuts widespread in Europe and Asia. In Italy, there are different cultivars among which the cultivar affording the valuable hazelnut "Tonda Gentile Trilobata," also known as "Tonda Gentile delle Langhe," covered by the Protected Geographical Indication (PGI) label "Nocciola Piemonte" (NP), known for its sweetness, cooked-bread aroma, and the low intensity of the burnt aroma. In order to obtain a detailed and in-depth characterization of the polar fraction of fresh (NPF) and roasted (NPR) kernels of NP the analysis of the n-butanol extracts by liquid chromatography coupled to electrospray ionization and high-resolution mass spectrometry (LC-ESI/HRMS) was carried out. Moreover, to evaluate the quantitative distribution of the most representative polar lipids in NPF and NPR, the analysis by liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) was performed. To unambiguously identify the phenolic compounds highlighted by the LC-ESI/HRMS profiles, they were isolated from the n-butanol extract and characterized by Nuclear Magnetic Resonance (NMR) experiments. Finally, the ability of the isolated compounds to exert radical scavenging activity and to inhibit the lipid peroxidation induced by H2O2 or H2O2/Fe2+ was tested by Trolox Equivalent Antioxidant Capacity (TEAC) and thiobarbituric acid reactive substances (TBARS) assays, respectively. The LC-ESI/HRMS allowed to ascertain the presence of phenolic compounds and multiple classes of polar lipids including phospholipids, glycolipids, sphingolipids, and oxylipins. The quantitative analysis highlighted in NPR fraction a lipid content three times higher than in NPF, evidencing lyso-phospholipids and phospholipids as the most represented lipid classes in both NPF and NPR, together accounting for 94 and 97% of the considered lipids, respectively. Furthermore, phytochemical analysis permitted to identify flavonoid and diarylheptanoid derivatives. In particular, quercetin 3-O-β-D-galactopyranosyl-(1→2)-β-D-glucopyranoside and myricetin-3-O-α-L-rhamnopyranoside showed the highest antioxidant activity, exhibiting TEAC values similar to that of quercetin, used as reference compound (2.00 ± 0.03 and 2.06 ± 0.03 mM vs 2.03 ± 0.03 mM, respectively). Moreover, most of the tested compounds were found to reduce lipid peroxidation induced by H2O2 and H2O2/Fe2+ more than curcumin used as positive control, with myricetin-3-O-α-L-rhamnopyranoside determining 44.4 % and 34.1 % inhibition percentage, respectively.

Corylus avellana L. Aroma Blueprint: Potent Odorants Signatures in the Volatilome of High Quality Hazelnuts

The volatilome of hazelnuts (Corylus avellana L.) encrypts information about phenotype expression as a function of cultivar/origin, post-harvest practices, and their impact on primary metabolome, storage conditions and shelf-life, spoilage, and quality deterioration. Moreover, within the bulk of detectable volatiles, just a few of them play a key role in defining distinctive aroma (i.e., aroma blueprint) and conferring characteristic hedonic profile. In particular, in raw hazelnuts, key-odorants as defined by sensomics are: 2,3-diethyl-5-methylpyrazine (musty and nutty); 2-acetyl-1,4,5,6-tetrahydropyridine (caramel); 2-acetyl-1-pyrroline (popcorn-like); 2-acetyl-3,4,5,6-tetrahydropyridine (roasted, caramel); 3-(methylthio)-propanal (cooked potato); 3-(methylthio)propionaldehyde (musty, earthy); 3,7-dimethylocta-1,6-dien-3-ol/linalool (citrus, floral); 3-methyl-4-heptanone (fruity, nutty); and 5-methyl-(E)-2-hepten-4-one (nutty, fruity). Dry-roasting on hazelnut kernels triggers the formation of additional potent odorants, likely contributing to the pleasant aroma of roasted nuts. Whiting the newly formed aromas, 2,3-pentanedione (buttery); 2-propionyl-1-pyrroline (popcorn-like); 3-methylbutanal; (malty); 4-hydroxy-2,5-dimethyl-3(2H)-furanone (caramel); dimethyl trisulfide (sulfurous, cabbage) are worthy to be mentioned. The review focuses on high-quality hazelnuts adopted as premium primary material by the confectionery industry. Information on primary and secondary/specialized metabolites distribution introduces more specialized sections focused on volatilome chemical dimensions and their correlation to cultivar/origin, post-harvest practices and storage, and spoilage phenomena. Sensory-driven studies, based on sensomic principles, provide insights on the aroma blueprint of raw and roasted hazelnuts while robust correlations between non-volatile precursors and key-aroma compounds pose solid foundations to the conceptualization of aroma potential.

Is It Possible to Produce Certified Hazelnut Plant Material in Sicily? Identification and Recovery of Nebrodi Genetic Resources, in vitro Establishment, and Innovative Sanitation Technique From Apple Mosaic Virus

Eight Sicilian cultivars of hazelnut (Corylus avellana L.), namely-Curcia, Nociara Collica, Panottara Collica, Panottara Galati Grande, Parrinara, Panottara Baratta Piccola, Enzo, and Rossa Galvagno, registered into the Italian Cultivar Register of fruit tree species in 2017 were selected from Nebrodi area and established in vitro. The aim of the work was to carry out the sanitation of the cultivars and get virus-free plants from the most important viral pathogen threat, the apple mosaic virus. Virus-free plant material is essential for the production of certified plants from Sicilian hazelnut cultivars, complying the CE (cat. CAC) quality and the technical standards established in 2017 for voluntary certification by the Italian Ministry of Agricultural, Food and Forestry Policies (MIPAAF). In this study, we investigated the possibility of establishing in vitro true-to-type and virus-free hazelnut plantlets via the encapsulation technology of apexes. The in vitro shoot proliferation rates were assessed for the different cultivars, sampling periods, temperature treatments, and type of explant used for culture initiation. Viability, regrowth, and conversion rates of both conventional meristem tip culture (MTC) and not conventional (MTC combined with the encapsulation technology) sanitation techniques were evaluated.

NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.

Innovative methodological approach using CIELab and dye screening for chemometric classification and HPLC for the confirmation of dyes in cassava flour: A contribution to product quality control

A variety of methods for producing cassava flour exist, resulting in very heterogeneous products that exhibit various colours, textures, granulometries, and flavours. To improve its attractiveness to consumers, some producers dye cassava flour with turmeric or tartrazine; however, this practice is illegal in Brazil. In this study, cassava flour samples were collected and evaluated for possible adulteration by the addition of dyes. Flours were analysed by CIELab and dye screening (paper chromatography and the turmeric-identification method) and a classification tree was developed using these data. Positive results for curcuminoid pigments or tartrazine were confirmed by HPLC-DAD or HPLC-UV-Vis, respectively. The developed approach is an innovative alternative chemometric-analysis method that facilitates highly practical screening; adulterated cassava flour, a product of great human-food importance, can be identified using CIELab parameters.

Food Profiling: Determination of the Geographical Origin of Walnuts by 1H NMR Spectroscopy Using the Polar Extract

Walnuts, with their health-promoting ingredients, are among the most popular nuts, and practicable methods for determining their geographical origin are needed to tackle food fraud. Authentic walnut samples (235, Juglans Regia L.) from different harvest years (2016-2019) and countries were analyzed by ¹H NMR spectroscopy in combination with chemometric methods to determine their geographical origin. Two sample groups were analyzed at a time with a support vector machine algorithm to obtain two-class classifier models. In total, nine two-class models were built (e.g., Germany/China, France/Germany, and USA/Switzerland), and a repeated nested cross-validation was performed. The models obtained showed high accuracies from 78.0% (±2.3%) to 96.6% (±0.6%). Furthermore, identification of potential chemical markers in the walnut extract was performed.

An effective chromatographic fingerprinting workflow based on comprehensive two-dimensional gas chromatography - Mass spectrometry to establish volatiles patterns discriminative of spoiled hazelnuts (Corylus avellana L.)

The volatile fraction of hazelnuts encrypts information about: cultivar/geographical origin, post-harvest treatments, oxidative stability and sensory quality. However, sensory features could be buried under other dominant chemical signatures posing challenges to an effective classification based on pleasant/unpleasant notes. Here a novel workflow that combines Untargeted and Targeted (UT) fingerprinting on comprehensive two-dimensional gas-chromatographic patterns is developed to discriminate spoiled hazelnuts from those of acceptable quality. By flash-profiling, six hazelnut classes are defined: Mould, Mould-rancid-solvent, Rancid, Rancid-stale, Rancid-solvent, and Uncoded KO. Chromatographic fingerprinting on composite 2D chromatograms from samples belonging to the same class (i.e., composite class-images) enabled effective selection of chemical markers: (a) octanoic acid that guides the sensory classification being positively correlated to mould; (b) ƴ-nonalactone, ƴ-hexalactone, acetone, and 1-nonanol that are decisive to classify OK and rancid samples; (c) heptanoic and hexanoic acids and ƴ-octalactone present in high relative abundance in rancid-solvent and rancid-stale samples.

The Inorganic Component as a Possible Marker for Quality and for Authentication of the Hazelnut's Origin

The inorganic component of hazelnuts was considered as a possible marker for geographical allocation and for the assessment of technological impact on their quality. The analyzed samples were Italian hazelnuts of the cultivar Tonda Gentile Romana and Turkish hazelnuts of the cultivars Tombul, Palaz and Çakildak. The hazelnuts were subjected to different drying procedures and different conservative methods. The concentration of 13 elements, namely Ba, Ca, Cu, Fe, K, Mg, Mn, Na, Ni, P, Sn, Sr and Zn, were quantified by inductively coupled plasma optical emission spectroscopy (ICP-OES). All the samples were previously digested in a microwave oven. Before proceeding with the analysis of the samples, the whole procedure was optimized and tested on a certified reference material. The results show that the inorganic component: (i) can represent a fingerprint, able to identify the geographical origin of hazelnuts, becoming an important quality marker for consumer protection; (ii) is strongly influenced by the treatments undergone by the investigated product during all the processing stages. A pilot study was also carried out on hazelnuts of the cultivar Tonda Gentile Trilobata Piemontese, directly harvested from the plant during early development to maturity and analyzed to monitor the element concentration over time.

NMR-based metabolic study of leaves of three species of Actinidia with different degrees of susceptibility to Pseudomonas syringae pv. actinidiae

Bacterial canker of Actinidia, caused by the bacterium Pseudomonas syringae pv. actinidiae (Psa), is the most serious disease of these plants worldwide. Leaves of three species of Actinidia, namely A. chinensis var. chinensis, A. chinensis var. deliciosa and A. arguta, having different degrees of tolerance to Psa, were analyzed by Nuclear Magnetic Resonance spectroscopy. Aqueous extracts of leaves were studied and several metabolites, classified as organic acids, amino acids, carbohydrates, phenols and other metabolites, were identified by 1D and 2D NMR experiments and quantified. The metabolic profiles of these species were compared through univariate statistical analysis ANOVA and multivariate PCA. Levels of metabolites with known antibacterial activity, such as caffeic and chlorogenic acids, were observed to be higher in the A. arguta samples. Moreover, these metabolites have different Pearson correlation patterns among the three Actinidia species, suggesting a difference at the phenylpropanoid biosynthetic pathway.

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.

1H NMR Spectroscopy for Determination of the Geographical Origin of Hazelnuts

A total of 262 authentic samples was analyzed by ¹H NMR spectroscopy for the geographical discrimination of hazelnuts ( Corylus avellana L.) covering samples from five countries (Germany, France, Georgia, Italy, and Turkey) and the harvest years 2013-2016. This article describes method development starting with an extraction protocol suitable for separation of polar and nonpolar metabolites in addition to reduction of macromolecular components. Using the polar fraction for data analysis, principle component analysis was applied and used to monitor sample preparation and measurement. Several machine learning algorithms were tested to build a classification model. The best results were obtained by a linear discrimination analysis applying a random subspace algorithm. The division of the samples in a trainings set and a test set yielded a cross validation accuracy of 91% for the training set and an accuracy of 96% for the test set. The identification of key features was carried out by Kruskal-Wallis test and t test. A feature assigned to betaine exhibits a significant level for the classification of all five countries and is considered a possible candidate for the development of targeted approaches. Further, the results were compared to a previously published study based on LC-MS analysis of nonpolar metabolites. In summary, this study shows the robustness and high accuracy of a discrimination model based on NMR analysis of polar metabolites.

Authentication of an Italian PDO hazelnut ("Nocciola Romana") by NIR spectroscopy

Common hazelnuts are widely present in human diet all over the world, and their beneficial effects on the health have been extensively investigated and demonstrated. Different in-depth researches have highlighted that the harvesting area can define small variations in the chemical composition of the fruits, affecting their quality. As a consequence, it has become relevant to develop methodologies which would allow authenticating and tracing hazelnuts. In the light of this, the present work aims to develop a non-destructive method for the authentication of a specific high-quality Italian hazelnut, "Nocciola Romana," registered with a protected designation of origin (PDO). Thus, different samples of this fruit have been analyzed by near-infrared (NIR) spectroscopy and then classification models have been built, in order to distinguish between the PDO fruits and the hazelnuts not coming from the designated region. In particular, two different classification approaches have been tested, a discriminant one, partial least squares-discriminant analysis, and a class-modeling one, soft independent modeling of class analogies. Both methods led to very high prediction capability in external validation on a test set (classification accuracy in one case, and sensitivity and specificity in the other, all higher than 92%), suggesting that the proposed methodologies are suitable for a rapid and non-destructive authentication of the product.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

Nutrimetabolomics: An Update on Analytical Approaches to Investigate the Role of Plant-Based Foods and Their Bioactive Compounds in Non-Communicable Chronic Diseases

Metabolomics is the study of low-weight molecules present in biological samples such as biofluids, tissue/cellular extracts, and culture media. Metabolomics research is increasing, and at the moment, it has several applications in the food science and nutrition fields. In the present review, we provide an update about the most frequently used methodologies and metabolomic platforms in these areas. Also, we discuss different metabolomic strategies regarding the discovery of new bioactive compounds (BACs) in plant-based foods. Furthermore, we review the existing literature related to the use of metabolomics to investigate the potential protective role of BACs in the prevention and treatment of non-communicable chronic diseases, namely cardiovascular disease, diabetes, and cancer.

Food Fingerprinting: Metabolomic Approaches for Geographical Origin Discrimination of Hazelnuts (Corylus avellana) by UPLC-QTOF-MS

Ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used for geographical origin discrimination of hazelnuts (Corylus avellana L.). Four different LC-MS methods for polar and nonpolar metabolites were evaluated with regard to best discrimination abilities. The most suitable method was used for analysis of 196 authentic samples from harvest years 2014 and 2015 (Germany, France, Italy, Turkey, Georgia), selecting and identifying 20 key metabolites with significant differences in abundancy (5 phosphatidylcholines, 3 phosphatidylethanolamines, 4 diacylglycerols, 7 triacylglycerols, and γ-tocopherol). Classification models using soft independent modeling of class analogy (SIMCA), linear discriminant analysis based on principal component analysis (PCA-LDA), support vector machine classification (SVM), and a customized statistical model based on confidence intervals of selected metabolite levels were created, yielding 99.5% training accuracy at its best by combining SVM and SIMCA. Forty nonauthentic hazelnut samples were subsequently used to estimate as realistically as possible the prediction capacity of the models.

The Chemical and Genetic Characteristics of Szechuan Pepper (Zanthoxylum bungeanum and Z. armatum) Cultivars and Their Suitable Habitat

Szechuan peppers, famous for their unique sensation and flavor, are widely used as a food additive and traditional herbal medicine. Zanthoxylum bungeanum and Z. armatum are both commonly recognized as Szechuan peppers, but they have different tastes and effects. The chemical components, genetic characteristics, and suitable habitat of six cultivars were analyzed in this study. The results indicated that Z. armatum contained a larger proportion of volatile oil, whereas Z. bungeanum produced a more non-volatile ether extraction. The average content of volatile oil and non-volatile ether extract of Z. armatum were 11.84 and 11.63%, respectively, and the average content of volatile oil and non-volatile ether extract of Z. bungeanum were 6.46 and 14.23%, respectively. Combined with an internal transcribed spacer 2 (ITS2) sequence characters and chemical PCA results, six cultivars were classified into their own groups, for the two species in particular. The temperature in January and July were the most significant ecological factors influencing the contents of the Z. armatum volatile oil. However, annual precipitation, temperature in January and relevant humidity had a significant positive correlation with the content of non-volatile ether extract in Z. bungeanum. Thus, the most suitable areas for producing Z. bungeanum cultivars ranged from the Hengduan Mountains to the Ta-pa Mountains, and the regions suitable for Z. armatum cultivars were found to be in the Sichuan Basin and Dalou-Wu mountains. The predicted suitable habitat could be used as a preliminary test area for Szechuan pepper cultivar production.

Impact of Roasting on Identification of Hazelnut (Corylus avellana L.) Origin: A Chemometric Approach

Hazelnuts belonging to different cultivars or cultivated in different geographic areas can be differentiated by their chemical profile; however, the roasting process may affect the composition of raw hazelnuts, thus compromising the possibility to identify their origin in processed foods. In this work, we characterized raw and roasted hazelnuts (Tonda Gentile Trilobata, TGT, from Italy and from Chile, Tonda di Giffoni from Italy, and Tombul from Turkey), as well as hazelnuts isolated from commercial products, with the aim to discriminate their cultivar and origin. The chemometric evaluation of selected chemical parameters (proximate composition, fatty acids, total polyphenols, antioxidant activity, and protein fingerprint by SDS-PAGE) permitted us to identify hazelnuts belonging to different cultivars and, concerning TGT samples, their different geographic origin. Also commercial samples containing Piedmontese TGT hazelnuts were correctly assigned to TGT cluster. In conclusion, even if the roasting process modifies the composition of roasted hazelnuts, this preliminary model study suggests that the identification of their origin is still possible.

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters.

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements.

Metabolic profiling by (1)H NMR of ground beef irradiated at different irradiation doses

This work describes a metabolic profiling study of non-irradiated and irradiated beef (at 2.5, 4.5 and 8 kGy) using (1)H NMR and chemometrics. The assignment of all major NMR signals of the aqueous/methanolic extracts was performed. A comprehensive multivariate data analysis proved the ability to distinguish between the irradiated and non-irradiated beef. Classification trees revealed that three metabolites (glycerol, lactic acid esters and tyramine or a p-substituted phenolic compound) are important biomarkers for classification of the irradiated and non-irradiated beef samples. Overall, the achieved metabolomic results show that the changes in the metabolic profile of meat provide a valuable insight to be used in detecting irradiated beef. The use of the NMR-based approach simplifies sample preparation and decrease the time required for analysis, compared to available official analytical procedures.

Analysis of different European hazelnut (Corylus avellana L.) cultivars: authentication, phenotypic features, and phenolic profiles

Hazelnuts exhibit functional properties due to their content in fatty acids and phenolic compounds that could positively affect human health. The food industry requires precise traits for morphological, chemical, and physical kernel features so that some cultivars could be more suitable for specific industrial processing. In this study, agronomical and morphological features of 29 hazelnut cultivars were evaluated and a detailed structural characterization of kernel polyphenols was performed, confirming the presence of protocatechuic acid, flavan-3-ols such as catechin, procyanidin B2, six procyanidin oligomers, flavonols, and one dihydrochalcone in all the analyzed cultivars. In addition, an innovative methodology based on the MALDI-TOF mass spectrometric analysis of peptide/protein components extracted from kernels was developed for the authentication of the most valuable cultivars. The proposed method is rapid, simple, and reliable and holds the potential to be applied in quality control processes. These results could be useful in hazelnut cultivar evaluation and choice for growers, breeders, and food industry.