Revealing the metabonomic variation of rosemary extracts using 1H NMR spectroscopy and multivariate data analysis

The molecular compositions of rosemary ( Rosmarinus officinalis L.) extracts and their dependence on extraction solvents, seasons, and drying processes were systematically characterized using NMR spectroscopy and multivariate data analysis. The results showed that the rosemary metabonome was dominated by 33 metabolites including sugars, amino acids, organic acids, polyphenolic acids, and diterpenes, among which quinate, cis-4-glucosyloxycinnamic acid, and 3,4,5-trimethoxyphenylmethanol were found in rosemary for the first time. Compared with water extracts, the 50% aqueous methanol extracts contained higher levels of sucrose, succinate, fumarate, malonate, shikimate, and phenolic acids, but lower levels of fructose, glucose, citrate, and quinate. Chloroform/methanol was an excellent solvent for selective extraction of diterpenes. From February to August, the levels of rosmarinate and quinate increased, whereas the sucrose level decreased. The sun-dried samples contained higher concentrations of rosmarinate, sucrose, and some amino acids but lower concentrations of glucose, fructose, malate, succinate, lactate, and quinate than freeze-dried ones. These findings will fill the gap in the understanding of rosemary composition and its variations.     

Determining the geographic origin of wheat using multielement analysis and multivariate statistics

The element contents of wheat from four major wheat-producing regions of China were analyzed and used in multivariate statistical analysis to classify wheat according to geographical origin. The concentrations of 15 elements (Be, Na, Mg, Al, K, Ca, V, Mn, Fe, Cu, Zn, Mo, Cd, Ba, and Th) in 240 samples from the 2007/2008 and 2008/2009 harvests were determined by inductively coupled plasma mass spectrometry. The analysis of variance and linear discriminant analysis were applied to classify wheat origin, and the effects of region, variety, and harvest year on the element contents were analyzed in this study. It was concluded that the multielement analysis is a promising method to provide reliable origin information for wheat, although the element profiles and discriminant models were affected by wheat varieties, harvest years, and agricultural practices.     

Multielement analysis of Canadian wines by inductively coupled plasma mass spectrometry (ICP-MS) and multivariate statistics

Trace element fingerprints were deciphered for wines from Canada's two major wine-producing regions, the Okanagan Valley and the Niagara Peninsula, for the purpose of examining differences in wine element composition with region of origin and identifying elements important to determining provenance. Analysis by ICP-MS allowed simultaneous determination of 34 trace elements in wine (Li, Be, Mg, Al, P, Cl, Ca, Ti, V, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb, Sr, Mo, Ag, Cd, Sb, I, Cs, Ba, La, Ce, Tl, Pb, Bi, Th, and U) at low levels of detection, and patterns in trace element concentrations were deciphered by multivariate statistical analysis. The two regions were discriminated with 100% accuracy using 10 of these elements. Differences in soil chemistry between the Niagara and Okanagan vineyards were evident, without a good correlation between soil and wine composition. The element Sr was found to be a good indicator of provenance and has been reported in fingerprinting studies of other regions.     

Metabolite profiling of Angelica gigas from different geographical origins using 1H NMR and UPLC-MS analyses

Angelica gigas obtained from different geographical regions was characterized using (1)H nuclear magnetic resonance (NMR) spectroscopy and ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) followed by multivariate data analyses. Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) score plots from (1)H NMR and UPLC-MS data sets showed a clear distinction among A. gigas from three different regions in Korea. The major metabolites that contributed to the discrimination factor were primary metabolites including acetate, choline, citrate, 1,3-dimethylurate, fumarate, glucose, histamine, lactose, malate, N-acetylglutamate, succinate, and valine and secondary metabolites including decursin, decursinol, nodakenin, marmesin, 7-hydroxy-6-(2R-hydroxy-3-methylbut-3-ethyl)coumarin in A. gigas roots. The results demonstrate that (1)H NMR and UPLC-MS-based metabolic profiling coupled with chemometric analysis can be used to discriminate the geographical origins of various herbal medicines and to identify primary and secondary metabolites responsible for discrimination.     

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.     

Metabolite profiling using (1)H NMR spectroscopy for quality assessment of green tea, Camellia sinensis (L.)

A set of 191 green teas from different countries was collected and analyzed by (1)H NMR. It was proposed to establish if the teas could be discriminated according to the country of origin or with respect to quality. Both principal component analysis (PCA) and cluster analysis were applied to the data. Some separation of Chinese and non-Chinese teas was observed. The present results did not allow allocation of samples to individual countries, but cluster analysis suggested that it might be possible with an augmented sample set. The PCA did show a separation between the Longjing type (highest quality Chinese tea) and most other Chinese teas and indicated some metabolites that could be responsible for the difference. Longjing teas showed higher levels of theanine, gallic acid, caffeine, epigallocatechin gallate, and epicatechin gallate and lower levels of epigallocatechin when compared with other teas. These compounds have been mentioned previously in connection with quality, but it was also shown that higher levels of theogallin (5-galloyl quinic acid), theobromine, 2-O-(beta-l-arabinopyranosyl)-myo-inositol and some minor sugar-containing compounds were found in Longjing teas while higher levels of fatty acids and sucrose were found in the other teas. These new markers could prove to be useful for the authentication of bulk tea.     

Application of (1)h NMR and multivariate statistics for screening complex mixtures: quality control and authenticity of instant coffee

Principal components analysis (PCA) followed by linear discriminant analysis (LDA) of the nuclear magnetic resonance (NMR) spectra from 98 instant spray-dried coffees, obtained from 3 different producers, correctly attributed 99% of the samples to their manufacturer. Blind testing of the PCA model with a further 36 samples of instant coffee resulted in a 100% success rate in identifying the samples from the 3 manufacturers. Coffees from one manufacturer were also assigned into 2 groups using these techniques, and the compound 5-(hydroxymethyl)-2-furaldehyde was identified as the primary marker of differentiation.     

基于同步辐射微CT研究不同利用年限水稻土团聚体微结构特征

同步辐射微CT (SRμ-CT)可以无损获取高分辨率、强对比度的内部结构图像,是研究土壤团聚体三维微结构的有效手段.本研究采集了种植水稻20 a和40 a后表层土壤团聚体样品,应用SRμ-CT扫描获取了9μm分辨率的团聚体内部结构图像,然后应用CT图像处理方法和3DMA-Rock软件观察并定量分析了团聚体微结构特征.随着种植水稻年限的增加,土壤有机质含量和全氮含量显著增加,团聚体孔隙数量和孔隙度显著增加,比表面积显著增大.种植水稻20 a的土壤团聚体呈现致密的黏闭结构,而种植水稻40 a的土壤团聚体具有由团粒状小团聚体构成的复杂多孔微结构.结果表明随着种植年限的增加,团聚体微结构和土壤质量明显改善.     

Investigations of La Rioja terroir for wine production using 1H NMR metabolomics

In this study, La Rioja wine terroir was investigated by the use of (1)H NMR metabolomics on must and wine samples. Rioja is a small wine region in central northern Spain which can geographically be divided into three subareas (Rioja Alta, Rioja Baja, and Rioja Alavesa). The winemaking process from must, through alcoholic and malolactic fermentation, was followed by NMR metabolomics and chemometrics of nine wineries in the Rioja subareas (terroirs). Application of interval extended canonical variate analysis (iECVA) showed discriminative power between wineries which are geographically very close. Isopentanol and isobutanol compounds were found to be key biomarkers for this differentiation.     

Bioactive compounds in cod (Gadus morhua) products and suitability of 1H NMR metabolite profiling for classification of the products using multivariate data analyses

This work investigates the suitability of (1)H NMR spectroscopy to identify the fate of some bioactive compounds in seafood submitted to several processing conditions and examines the possibility of using (1)H NMR spectroscopy profiling to classify such products. Perchloric acid extracts of cod white muscle from newly killed and (i) unprocessed, (ii) boiled, and (iii) fried fillets and from (iv) frozen fillets, (v) the frozen fillets after thawing, and (vi) their drip loss and from (vii) rehydrated cod klippfish (n = 5) were analyzed by 500 MHz (1)H NMR spectroscopy. It was possible to identify taurine, betaine, anserine, creatine, and trimethylamine oxide (TMAO) in all extracts examined, and frozen fish was recognizable by the presence of dimethylamine (DMA). None of the heating procedures seemed to induce the loss of bioactive compounds from the fillet, but freezing and thawing did: the compounds were lost in what is known as drip loss. About 80% of the samples were correctly classified using a probabilistic neural network procedure having as inputs the scores of the first 20 principal components of the principal component analysis of a selected region of the NMR spectra.     

Verification of silage type using near-infrared spectroscopy combined with multivariate analysis

The ability to authenticate the feed given to animals has become a major challenge in animal production, where the diet fed to the animal is one of the most important production factors affecting the composition of milk and meat from cattle, sheep, and goats. Hence, there is currently an increased consumer demand for information on herbivore production factors and particularly the animal diet. The aim of this study was to evaluate the reliability and accuracy of near-infrared (NIR) reflectance spectroscopy as a tool to verify and authenticate the type of silage used as fed for ruminants. Grain silage (GrS, n = 94), grass and legume silage (GLegS, n = 121), and sunflower silage (SunS, n = 50) samples were collected from commercial farms and analyzed in the visible and NIR regions (400-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), partial least-squares discriminant analysis (PLS1-DA), and linear discriminant analysis (LDA) models were used as methods to verify the different silage types. The classification models based on the NIR data correctly classified more than 90% of the silage samples according to their type. The results from this study showed that NIR spectra combined with multivariate analysis could be used as a tool to objectively authenticate silage samples used as a feed for ruminants.     

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.     

Quality evaluation and prediction of Citrullus lanatus by 1H NMR-based metabolomics and multivariate analysis

(1)H NMR spectrometry in combination with multivariate analysis was considered to provide greater information on quality assessment over an ordinary sensory testing method due to its high reliability and high accuracy. The sensory quality evaluation of watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) was carried out by means of (1)H NMR-based metabolomics. Multivariate analyses by partial least-squares projections to latent structures-discrimination analysis (PLS-DA) and PLS-regression offered extensive information for quality differentiation and quality evaluation, respectively. The impact of watermelon and rootstock cultivars on the sensory qualities of watermelon was determined on the basis of (1)H NMR metabolic fingerprinting and profiling. The significant metabolites contributing to the discrimination were also identified. A multivariate calibration model was successfully constructed by PLS-regression with extremely high reliability and accuracy. Thus, (1)H NMR-based metabolomics with multivariate analysis was considered to be one of the most suitable complementary techniques that could be applied to assess and predict the sensory quality of watermelons and other horticultural plants.     

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.     

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).     

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.     

Isotopomer analysis of nitrous oxide accumulated in soil cultivated with tea (Camellia sinensis) in Shizuoka,central Japan

Nitrous oxide (N₂O) is a greenhouse gas that is destroying the stratospheric ozone to an increasing degree. Because of nitrogenous fertilizer application, agricultural soil is an important contributor of global N₂O. In Japan, tea fields are amended with the highest level of N fertilizers among agricultural soils, causing soil acidification and large N₂O flux. In soil, microbes play key roles in producing and consuming N₂O. A previous study investigated net N₂O production in tea fields using N₂O flux measurement and soil incubation, which are indirect methods to analyze relevant processes of N₂O production and consumption in soil. In the present study, to analyze N₂O concentrations and isotopomer ratios (bulk nitrogen and oxygen isotope ratios, δ¹⁵N^bulk and δ¹⁸O, and intramolecular ¹⁵N site preference, SP) and to reveal most probable microbial production processes and consumption (N₂O reduction to N₂) process of N₂O, soil gas was collected from a tea field (pH 3.1–4.5) at 10–50 cm depths using a silicone tube. The combination of fertilization, precipitation, and temperature rise produced significantly high N₂O concentrations. During the period of high N₂O concentration (above 5.7 ppmv), SP, the difference in ¹⁵N/¹⁴N ratio between central (α) and terminal (β) nitrogen position in the linear N₂O molecule (^βN^αNO) showed low values of 1.4‰–9.8‰, suggesting that the contribution of bacterial denitrification (nitrifier-denitrification and bacterial denitrifier-denitrification) was greater than that of bacterial nitrification or fungal denitrification. High SP values of 15.0‰–20.1‰ obtained at 10, 35, and 50 cm depths on 31 May 2011 (after one of fertilizations) during which soil temperatures were 15.8 °C–17.9 °C and water-filled pore space (WFPS) was 0.73–0.89 suggest that fungal denitrification and bacterial nitrification contributed to N₂O production to a degree equivalent to that of bacterial denitrification.     

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.     

Volatile response of four apple varieties with different coatings during marketing at room temperature

Five experimental coatings with different resistance to gas exchange were used with freshly harvested and 20-week commercially stored apples of Delicious, Fuji, Braeburn, and Granny Smith varieties. The coated or noncoated apples were held at 20 degrees C for up to 4 weeks. The gas partial pressures inside the fruits with the various coatings ranged from 1 to 25 kPa CO(2) and from 20 to 1 kPa O(2). Volatile evaporation rates were measured, as also were the volatiles compositions in the fruit. The coatings with intermediate gas resistance (carnauba-shellac mixture and candelilla) gave intermediate values of CO(2) and O(2) in the internal atmosphere in Delicious, Fuji, and Braeburn apples and the highest concentrations of butyl acetate and 2-methylbutyl acetate in the fruits. The coatings with the highest gas resistance (shellac and shellac-protein) caused high internal CO(2) and low O(2), resulting in anaerobic fermentation in Braeburn and Granny Smith apples and relatively high amounts of low-molecular-weight ethyl esters trapped within the fruit. A small portion of the alcohols were evaporated from fruits compared to esters, this attributed to their high Henry's law coefficients.     

A comparison of four different raw humus types in Norway using chemical degradations and CPMAS 13C NMR spectroscopy

Crust, felty, greasy and granular raw humus were analysed by wet chemical methods and by ¹³C NMR. The amounts of amino acids, monosaccharides and aliphatic dicarboxylic acids were determined and the yields compared with the ¹³C NMR spectra. Protein carbon constitutes 9–13%, polysaccharide carbon 8–19% dicarboxylic acids 1–2% and free carboxylic acid groups 2–4% of the total sample carbon. Degradation of greasy raw humus yields half the amount of monosaccharides and twice the amount of aliphatic dicarboxylic acids found in the other raw humus types. This result is confirmed by ¹³C NMR. Forty to fifty percent of the soil carbon is unaccounted for among the degradation products identified. Based on estimates of ¹³C NMR data, the unknown part consists of aliphatic carbon, where the C:O ratio ranges between 1 1.1:1 and 1.8:1. All data indicate great similarity between crust and felty raw humus, whereas greasy raw humus differs clearly from those two. Granular raw humus gives approximately the same amount of degradation products as crust and felty raw humus but differs in its ¹³C NMR spectrum. The relative proportions of all compounds identified, including aliphatic dicarboxylic acids, are approximately constant, indicating a difference in degree rather than kind of the four raw humus types.