Characterization of wines by nuclear magnetic resonance: a work study on wines from the Basilicata region in Italy

We explored the possibility of differentiating Italian wines produced in different regions by means of nuclear magnetic resonance (NMR) techniques. Ten commercial red Aglianico wines were selected from different areas of the Basilicata region in the south of Italy. Some important components of these wines were identified by the assignments of their (1)H and (13)C resonances using one- and two-dimensional homonuclear and heteronuclear NMR experiments. These data were compared with those obtained from 10 Aglianico wines produced in Campania, another southern Italian region. Differences were found among the wines according to their geographical origin and vintage. A fine discrimination of Aglianico wines from Basilicata and Campania was obtained, suggesting that the selected NMR parameters may be a valuable tool for wine authenticity control.     

Toward the determination of the geographical origin of Emmental(er) cheese via high resolution MAS NMR: a preliminary investigation

We tested the potential of High-Resolution MAS NMR spectroscopy to study 20 samples of Emmental cheeses from 7 different geographical regions. Principal component analysis (PCA) and discriminant analysis (DA) were used to analyze the data set of 1H HRMAS NMR spectra and succeeded in grouping the studied samples according to their geographical origins.     

1H NMR based metabolic profiling in the evaluation of Japanese green tea quality

Classification of tea quality is now mainly performed according to the sensory results by professional tea tasters. However, this evaluation method is inconsistent in differentiating their qualities. A combination of a (1)H NMR technique and a multivariate analysis was introduced to the quality evaluation of green tea by means of a metabolomic technique. A broad range of metabolites were detected by (1)H NMR spectrometry. The principal component analysis (PCA) was used to reduce the complexity of the (1)H NMR spectra data set and provided the quality discrimination result. It offered an extensive clue for classification and quality assessment without any prepurification method. A set of green teas from a Japanese tea contest were analyzed by (1)H NMR to classify the quality with respect to that judged by tea tasters and to conceive a quality prediction model. Metabolic profiling and fingerprinting of (1)H NMR spectra of green teas with different quality were studied. PCA showed a separation between the high- and the low-quality green teas. The taste marker compounds contributing to the discrimination of tea quality were identified. Reliable prediction models were obtained by the partial least-squares projection to latent structure (PLS) analysis together with a preprocessing filter of both orthogonal signal correction (OSC) and a combination between OSC and wavelet transform algorithms.     

Application of cryoprobe 1H nuclear magnetic resonance spectroscopy and multivariate analysis for the verification of corsican honey

Proton nuclear magnetic resonance spectroscopy ((1)H NMR) and multivariate analysis techniques have been used to classify honey into two groups by geographical origin. Honey from Corsica (Miel de Corse) was used as an example of a protected designation of origin product. Mathematical models were constructed to determine the feasibility of distinguishing between honey from Corsica and that from other geographical locations in Europe, using (1)H NMR spectroscopy. Honey from 10 different regions within five countries was analyzed. (1)H NMR spectra were used as input variables for projection to latent structures (PLS) followed by linear discriminant analysis (LDA) and genetic programming (GP). Models were generated using three methods, PLS-LDA, two-stage GP, and a combination of PLS and GP (PLS-GP). The PLS-GP model used variables selected by PLS for subsequent GP calculations. All models were generated using Venetian blind cross-validation. Overall classification rates for the discrimination of Corsican and non-Corsican honey of 75.8, 94.5, and 96.2% were determined using PLS-LDA, two-stage GP, and PLS-GP, respectively. The variables utilized by PLS-GP were related to their (1)H NMR chemical shifts, and this led to the identification of trigonelline in honey for the first time.     

Geographical characterization of polyfloral and acacia honeys by nuclear magnetic resonance and chemometrics

The importance of geographical origin determination is an increasing and pressing requirement for all foods. Honey is one of the largest studied foods due to its nutritional and medicinal properties in a correct diet. In this paper, a total of 41 honey samples (polyfloral and acacia) from different countries have been analyzed in terms of (1)H NMR spectroscopy coupled with multivariate statistical methods. Unsupervised principal component analysis resulted as an efficient tool in distinguishing (1)H NMR spectra of polyfloral and acacia honey samples and for geographical characterization of the latter ones. Hierarchical projection to latent structures discriminant analysis was successfully applied for the discrimination among polyfloral honey samples of different geographical origins. (13)C NMR spectroscopy was applied to honey samples with the aim to investigate possible sugar isoforms differentiation. Our preliminary data indicated a different isoforms ratio between betaFP and betaFF only for polyfloral Argentinean samples, while Hungarian samples showed resonance shifts for some carbons of alphaFF, betaFP, betaFF, and alphaGP isoforms for both varieties. These data confirmed the potentiality of (13)C spectroscopy in food characterization, especially in sugar-based foods.     

Characterization of Italian Durum Wheat Semolina by Means of Chemical Analytical and Spectroscopic Determinations

Proton high‐resolution magic angle spinning nuclear magnetic resonance (¹H HR‐MAS NMR) has been applied for the analysis of two cultivars of durum wheat produced in different Italian geographical areas. Furthermore, on the same samples, isotopic ratios were measured by mass spectrometry (IRMS). The application of chemometrics to these results permitted the discrimination of semolina by cultivar and geographical origin. A similar approach has been applied to the results obtained from chemical analyses. The comparison showed that NMR spectroscopy can provide a faster method for the detection of differences among the durum wheat semolina according to geographical and varietal origin. Furthermore, IRMS data are suitable to provide information about the geographical origin of samples. This present investigation is part of an extensive research project to find a scientific method capable of classifying wheat foods for the assignment of a “denomination of origin” trademark.     

Classification of edible oils by employing 31P and 1H NMR spectroscopy in combination with multivariate statistical analysis. A proposal for the detection of seed oil adulteration in virgin olive oils

A combination of (1)H NMR and (31)P NMR spectroscopy and multivariate statistical analysis was used to classify 192 samples from 13 types of vegetable oils, namely, hazelnut, sunflower, corn, soybean, sesame, walnut, rapeseed, almond, palm, groundnut, safflower, coconut, and virgin olive oils from various regions of Greece. 1,2-Diglycerides, 1,3-diglycerides, the ratio of 1,2-diglycerides to total diglycerides, acidity, iodine value, and fatty acid composition determined upon analysis of the respective (1)H NMR and (31)P NMR spectra were selected as variables to establish a classification/prediction model by employing discriminant analysis. This model, obtained from the training set of 128 samples, resulted in a significant discrimination among the different classes of oils, whereas 100% of correct validated assignments for 64 samples were obtained. Different artificial mixtures of olive-hazelnut, olive-corn, olive-sunflower, and olive-soybean oils were prepared and analyzed by (1)H NMR and (31)P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of adulteration as low as 5% w/w, provided that fresh virgin olive oil samples were used, as reflected by their high 1,2-diglycerides to total diglycerides ratio (D > or = 0.90).     

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.     

Geographical characterization of italian extra virgin olive oils using high-field (1)H NMR spectroscopy.

1H high-field nuclear magnetic resonance (NMR) was used to analyze 216 extra virgin olive oils collected in three years (1996, 1997, and 1998) in different Italian areas in order to evaluate the potential contribution of this technique to the geographical characterization of olive oils. A statistical procedure performed on the intensity of selected NMR peaks has been proposed. Tree clustering analysis of NMR data performed without any a priori hypothesis showed the existence of reliable parameters able to group the olive oils according to the location of olive oil production. Linear discriminant analysis applied to selected NMR parameters of olive oils of the same year of production allowed the grouping of samples according to their geographical origin with only very few errors. Moreover, a satisfactory grouping is reached by combining the NMR data of olive oils from two different years (1996 and 1997). Operating on appropriate sampling, a careful analysis of data yielded the conclusion that the place of olive production could be singled out as a discriminating factor regardless of the cultivars from which the olive oils are derived.     

1H NMR metabolite fingerprint and pattern recognition of mullet (Mugil cephalus) bottarga

Nuclear magnetic resonance (NMR) spectroscopy combined with multivariate data analysis (MVA) was used to investigate the molecular components of the aqueous extract of samples of bottarga, that is, salted and dried mullet (Mugil cephalus) roe, manufactured in Sardinia (Italy) from mullets of known and unknown geographical provenience. Principal component analysis (PCA) applied to the processed (1)H NMR spectra indicated that samples tend to cluster according to their geographical origin and also on the basis of storage and manufacturing procedures. The most important metabolites that characterized grouping of samples are the free amino acids methionine (Met), glutamate (Glu), histidine (His), phenylalanine (Phe), tyrosine (Tyr), and isoleucine (Ile); trimethylamine (TMA) and dimethylamine (DMA), both biomarkers of degradation; nucleotides and derivatives; choline (Cho) and phosphorylcholine (P-cho); and lactate (Lac).     

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.     

Chemical characterization of Cuban propolis by HPLC-PDA, HPLC-MS, and NMR: the brown, red, and yellow Cuban varieties of propolis

Sixty-five samples of propolis were collected from eleven regions of Cuba; methanolic extracts of propolis were prepared from all samples, and a classification method was developed using a combination of NMR, HPLC-PDA, and HPLC-ESI/MS techniques. The analysis of (1)H and (13)C NMR spectra and chromatographic profiles of all propolis extracts allowed the definition of three main types of Cuban propolis directly related to their secondary metabolite classes: brown Cuban propolis (BCP), rich in polyisoprenylated benzophenones, red Cuban propolis (RCP), containing isoflavonoids as the main constituents, and yellow Cuban propolis (YCP), probably with aliphatic compounds. Subsequently, the principal compounds of the brown and red types were characterized by HPLC-ESI/MS analysis. Instrumental techniques used are complementary; NMR was shown to be a quick and informative tool for the rapid analysis of crude propolis polar extracts and allowed the identification of the main class of secondary metabolites, while LC-PDA and LC-MS techniques were useful tools for qualitative and quantitative analysis of marker compounds of Cuban propolis.     

中国农村一二三产业融合度与省际比较分析

推进农村一二三产业融合发展对于实现产业兴旺、增加农民收入、助力乡村振兴具有重要意义。该研究基于产业延伸、功能拓展、业态丰富、利益联结、城乡融合等5个维度构建了农村一二三产业融合评价指标体系,测度了省际农村一二三产业融合水平。研究发现:1)2013至2018年间,中国农村一二三产业融合度波动上升,由0.481增至0.516,且总体呈现“东高西低”特征,地理梯度特征明显。2)各地区农村一二三产业融合的优势维度和潜力维度均表现出较大差异,且5个维度中未见绝对优势维度,不同路径均能有效推动融合。3)从各地区维度间贡献率发展来看,东、西部地带维度分散,中部地带维度收敛,差异化发展趋势已然呈现。基于研究结果,建议进一步跟踪中国各地区农村一二三产业融合进程;改进“三农”统计方式,实现部门数据对接和定期公开;结合该研究提出的评价体系找准比较优势,发展优势维度,培育潜力维度,因势利导、因地制宜选准符合地方实际的融合路径。     

Chemometric classification of Apulian and Slovenian wines using 1H NMR and ICP-OES together with HPICE data

High-performance ion chromatography exclusion, inductively coupled plasma emission spectroscopy, and nuclear magnetic resonance (NMR) measurements were carried out in combination with chemometrics on 33 wine samples coming from three Slovenian wine-growing regions and from Apulia (southern Italy). The chemometric classification of wines according to their geographical origin was obtained with a nearly 100% degree of achievement. The discriminating potential of the (1)H NMR and of the other analytical determinations has been estimated separately. The best prediction of wines has been obtained with NMR data.     

Chemical profile of white wines produced from 'Greco bianco' grape variety in different Italian areas by nuclear magnetic resonance (NMR) and conventional physicochemical analyses

In this study the characterization of white wines produced from the monovarietal 'Greco bianco' grape variety is presented for the first time. A total of 40 commercial wines, from two different southern Italian regions, Calabria and Campania, from the same grape variety and two different vintages, were investigated. The analyses were performed by means of chromatographic methods, conventional analyses, and nuclear magnetic resonance (NMR) spectroscopy. No differentiation was observed according to the year of production but a significant discrimination was achieved using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). In particular, PLS-DA allowed the selection of compounds (total acidity; citric, malic, succinic, and lactic acids; total polyphenol index; glucose and proline/arginine ratio) useful for differentiating the studied wines on the basis of geographical origin.     

1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas

(1)H NMR spectroscopy was used to investigate the metabolic differences in wines produced from different grape varieties and different regions. A significant separation among wines from Campbell Early, Cabernet Sauvignon, and Shiraz grapes was observed using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The metabolites contributing to the separation were assigned to be 2,3-butanediol, lactate, acetate, proline, succinate, malate, glycerol, tartarate, glucose, and phenolic compounds by PCA and PLS-DA loading plots. Wines produced from Cabernet Sauvignon grapes harvested in the continental areas of Australia, France, and California were also separated. PLS-DA loading plots revealed that the level of proline in Californian Cabernet Sauvignon wines was higher than that in Australian and French Cabernet Sauvignon, Australian Shiraz, and Korean Campbell Early wines, showing that the chemical composition of the grape berries varies with the variety and growing area. This study highlights the applicability of NMR-based metabolomics with multivariate statistical data sets in determining wine quality and product origin.     

Updating a synchronous fluorescence spectroscopic virgin olive oil adulteration calibration to a new geographical region

Detecting and quantifying extra virgin olive adulteration is of great importance to the olive oil industry. Many spectroscopic methods in conjunction with multivariate analysis have been used to solve these issues. However, successes to date are limited as calibration models are built to a specific set of geographical regions, growing seasons, cultivars, and oil extraction methods (the composite primary condition). Samples from new geographical regions, growing seasons, etc. (secondary conditions) are not always correctly predicted by the primary model due to different olive oil and/or adulterant compositions stemming from secondary conditions not matching the primary conditions. Three Tikhonov regularization (TR) variants are used in this paper to allow adulterant (sunflower oil) concentration predictions in samples from geographical regions not part of the original primary calibration domain. Of the three TR variants, ridge regression with an additional 2-norm penalty provides the smallest validation sample prediction errors. Although the paper reports on using TR for model updating to predict adulterant oil concentration, the methods should also be applicable to updating models distinguishing adulterated samples from pure extra virgin olive oil. Additionally, the approaches are general and can be used with other spectroscopic methods and adulterants as well as with other agriculture products.     

In vivo 31P and 1H HR-MAS NMR spectroscopy analysis of the unstarved Aporrectodea caliginosa (Lumbricidae)

This study demonstrates that ³¹P and ¹H high resolution-magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR), a recently developed NMR technique, can be applied to the in vivo analysis of metabolites from an unstarved earthworm. The endogeic earthworm Aporrectodea caliginosa was cut into lengths and then the different body parts (anterior, middle, posterior) with the gut content were analyzed. With the HR-MAS NMR, metabolites show well-resolved signals, whereas, with conventional NMR, spectra are highly dependent on the gut content. ³¹P HR-MAS NMR has been used to evaluate the effect of an acute exposure of the earthworm to glyphosate. Our observations support a low toxicity of the herbicide and suggest that glyphosate could be trapped in the cutaneous mucus. Earthworms could therefore play a role in horizontal dispersion and stabilization of glyphosate in the drilosphere. Phosphorylated metabolites, such as phospholombricine and lombricine, were clearly identified and their amount measured during experiments. The ¹H HR-MAS NMR method offers the opportunity to measure, on the same sample and simultaneously, both the hydrosoluble metabolites and lipids. The data on lipid location and relative succinate concentration shed light on the physiological and metabolic functions of the different body parts of the earthworm.     

A multianalytical approach for determining the geographical origin of ginseng using strontium isotopes, multielements, and 1H NMR analysis

Asian ginseng (Panax ginseng C.A. Meyer) is widely used as an Oriental medicine in the East Asian regions, particularly Korea and China. In the study, the strontium isotope ratios ((87)Sr/(86)Sr), multielements, and metabolite profiles of 35 ginseng samples collected from Korea and China were examined in an attempt to develop a method to distinguish the origin of ginsengs from the two countries. A multivariate statistical approach was performed to analyze the multielements and the (1)H nuclear magnetic resonance (NMR) data. Results of a t-test for Mg, Fe, Al, and Sc showed significant variation between Korean and Chinese ginsengs, indicating potential tracers for discriminating them. Discriminating between the ginsengs from the two countries was generally successful when both the (87)Sr/(86)Sr ratios and rare earth element (REE) contents were used together. Moreover, principal component analysis (PCA) derived from the (1)H NMR data revealed a significant separation between the ginsengs originating from the two countries. The major metabolites responsible for differentiation were sugars such as glucose, xylose, and sucrose. The results suggest that this multiplatform approach offers a comprehensive method to distinguish the origin of ginsengs.