Monitoring a commercial fermentation with proton nuclear magnetic resonance spectroscopy with the aid of chemometrics

NMR in the Service of Wine Differentiation

NMR is a swift and highly reproducible spectrometric technique that makes it possible to obtain spectra containing a lot of information about the sample analyzed. This approach helps major components be described in complex mixtures such as wine in just one analysis. Analysis of wine metabolites is very often used to understand the impact of geographical origin or variety on wine quality. NMR is often used for tracing the geographical origin of wine. Research on NMR metabolic effects of geographical origin is of great importance as the high added value of wines results from compliance with state legislation on the protected denomination of origin (PDO) and protected geographical indication (PGI) for the administration of the appellation of wines. A review of NMR with emphasis on SNIF-NMR in the analysis of wine authenticity is given. SNIF-NMR remains a method of choice for the detection of wine chaptalization as it is the only approach which provides position-specific information on the origin of sugar in wine. However, the sample preparation step, which lacks major improvements since its conception, is strenuous and expensive, and suffers from drawbacks in terms of low sample throughput. Mainstream 1D and 2D NMR experiments provide a fast and affordable way to authenticate wine based on the geographical origin, vintage, and variety discrimination, and include a simple and non-destructive sample preparation step. With this approach, spectral data processing often represents a crucial step of the analysis. With properly performed NMR experiments good to excellent differentiation of wines from different vintages, regions, and varieties was achieved recently.

Fluorescence-based real time monitoring and diagnostics of recombinant Pichia pastoris cultivations in a bioreactor

This study describes the application of the multivariate curve resolution (MCR) analysis technique for real-time analysis of culture fluorescence during recombinant Pichia pastoris cultivation in a bioreactor. Fluorescence spectra were acquired with an on-line dual excitation wavelength fluorometer and then used to develop a real time MCR-based bioprocess monitoring and diagnostics tool. Initial bioreactor experiments using two similar recombinant antibody secreting P. pastoris cell lines showed significant differences in protein production. To distinguish between the contributions of operating conditions and the specific cell line's genetic composition to the observed differences in protein production, the bioreactor experiments were repeated and accompanied by real time MCR analysis. The tests demonstrated high sensitivity of MCR-derived "pure concentration" profiles to growth as well as to initial conditions, thus enabling real-time cultivation process trend diagnostics and fault detection. © 2018 Her Majesty the Queen in Right of Canada © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2761, 2019.

Viticultural practice and winemaking effects on metabolic profile of Negroamaro

Metabolic profiles of 32 Negroamaro red wines were analysed using (1)H NMR spectroscopy and multivariate statistical analyses (Principal Component Analysis, PCA, and Orthogonal Partial Least Square Discriminant Analysis, OPLS-DA). Among winemaking technologies three were compared: ultrasounds (U; 12 samples), cryomaceration using dry ice (C; 12 samples) and traditional (T; 8 samples). Moreover, each vinification technology was used for grapes grown by two different soil management practices, soil tillage (ST; 16 samples) and cover crop (CC; 16 samples), and by two different training systems, monolateral (M; 16 samples) and bilateral Guyot (B; 16 samples). All statistical models applied on NMR data revealed a good separation between ST (soil tillage) and CC (cover crop), showing a higher influence of the soil management practices compared to the winemaking technologies (ultrasound, cryomaceration and traditional). The differentiation among samples, due to soil management practices, was mainly caused by metabolites such as glycerol, 2,3-butanediol, malic acid, α/β-glucose and phenolic compounds, such as tyrosine and caffeic acid.

Effects of different vinification technologies on physical and chemical characteristics of Sauvignon blanc wines

In order to investigate the effects of cryomaceration and reductive vinification on chemical and physical indices and on antioxidant compounds of Sauvignon blanc wines, four wine-making procedures were applied: traditional white vinification, skin cryomaceration, vinification in a reductive environment, and a combination of the last two procedures. Significant differences were highlighted by both conventional analyses and NMR spectroscopy. The strongest changes were for organic acid concentrations (tartaric, in particular) and phenolic content. Cryomaceration caused a strong precipitation of tartaric acid, which may be desired if grapes have high acidity values. Cryomaceration protected those flavans reactive with vanillin from the action of oxidative enzymes. Vinification in a reductive environment, alone or combined with a cryomaceration step, gave wines with the highest solids content and caused a greater extraction of phenolic compounds from skins compared to traditional winemaking or cryomaceration alone, due to SO(2) solubilisation. Grape oenological expression can be strongly affected by the application of the investigated wine-making procedures.

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.

Detection of honey adulteration by sugar syrups using one-dimensional and two-dimensional high-resolution nuclear magnetic resonance

The importance of honey adulteration detection has recently increased owing to the limited production levels in recent years and the relative high price of honey; therefore, this illegal practice has become more and more attractive to producers. Hence, the need has arisen for more effective analytical methods aiming at detecting honey adulteration. The present research presents an effective method to detect adulteration in honey falsified by intentional addition of different concentrations of commercial sugar syrups, using one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) coupled with multivariate statistical analysis. Sixty-three authentic and 63 adulterated honey samples were analyzed. To prepare adulterated honeys, seven different sugar syrups normally used for nutrition of bees were used. The best discriminant model was obtained by 1D spectra, and leave-one-out cross-validation showed a predictive capacity of 95.2%. 2D NMR also furnished acceptable results (cross-validation correct classification 90.5%), although the (1)H NMR sequence is preferable because it is the simplest and fastest NMR technique.

Nuclear magnetic resonance and chemometrics to assess geographical origin and quality of traditional food products

In this globalization era, the opening of the markets has put at almost everybody's disposal a wide variety of foods, allowing everybody to taste food flavors and aromas from different nations. Notwithstanding this opportunity, countries try to preserve their markets by developing protection policies. A few countries have adopted different denominations to label their "typical food" products in order to give them additional value. Besides, the term "typical food" is widely thought of as something anchored to the local traditions, with geographical meaning and made with typical raw materials. Then a "typical food" starts to be considered "traditional" when it is made following specific and old recipes. As a matter of fact, these products acquire particular organoleptic characteristics that are not reproducible when produced in different places. In this review, NMR studies coupled to multivariate statistical analysis are presented with the aim of determining geographical origin and key quality characteristics.

Evidence of metabolic transformations of amino acids into higher alcohols through (13)C NMR studies of wine alcoholic fermentation

Because the metabolite transformations in wine fermentation processes play a crucial role in the organoleptic and hygienic quality of wines, the nuclear magnetic resonance (NMR) technique is presented as a significant tool to follow metabolic pathways. In this paper, we investigated the transformation of several amino acids into their corresponding higher alcohols during the alcoholic fermentation, showing that the amino acids are totally consumed in the first stages of the process.

Comparison of gas chromatography-coupled time-of-flight mass spectrometry and 1H nuclear magnetic resonance spectroscopy metabolite identification in white wines from a sensory study investigating wine body

Metabolite profiles of white wines, including Chardonnay, Pinot gris, Riesling, Sauvignon blanc, and Viognier varieties, were determined using both gas chromatography-coupled time-of-flight mass spectrometry (GC-TOF-MS) and proton nuclear magnetic resonance spectroscopy ((1)H NMR). A total of 108 metabolites were identified by GC-TOF-MS, and 51 metabolites were identified by (1)H NMR; the majority of metabolites identified include the most abundant compounds found in wine (ethanol, glycerol, sugars, organic acids, and amino acids). Compositional differences in these wines correlating to the wine sensory property "body", or viscous mouthfeel, as scored by a trained panel were identified using partial least-squares (PLS) regression. Independently calculated GC-TOF-MS and NMR-based PLS models demonstrate potential for predictive models to replace expensive, time-consuming sensory panels. At the modeling stage, correlations between the measured and predicted values have coefficients of determination of 0.83 and 0.75 for GC-TOF-MS and (1)H NMR, respectively. Additionally, the MS- and NMR-based models present new insights into the chemical basis for wine mouthfeel properties.

A thorough study on the use of quantitative 1H NMR in Rioja red wine fermentation processes

In this study, we focused our attention on monitoring the levels of important metabolites of wine during the alcoholic and malolactic fermentation processes by quantitative nuclear magnetic resonance (qNMR). Therefore, using (1)H NMR, the method allows the simultaneous quantification of ethanol, acetic, malic, lactic, and succinic acids, and the amino acids proline and alanine, besides the ratio proline/arginine through fermentation of must of grapes corresponding to the Tempranillo variety. Each (1)H NMR spectrum gives direct and visual information concerning these metabolites, and the effectiveness of each process was assessed and compared by carrying out analyses using infrared spectroscopy to ethanol and acetic acid. The quantitative data were explained with the aid of chemometric algorithms.

Classification of Italian honeys by 2D HR-NMR

The importance of honey has been recently increased because of its nutrient and therapeutic effects, but the adulteration of honey in terms of botanical origin has increased, too. The floral origin of honeys is usually determined using melisso-palynological analysis and organoleptic characteristics, but the application of these techniques requires some expertise. A number of papers have confirmed the possibility of characterizing honey samples by selected chemical parameters. In this study high-resolution nuclear magnetic resonance (HR-NMR) and multivariate statistical analysis methods were used to identify and classify honeys of five different floral sources. The 71 honey samples (robinia, chestnut, citrus, eucalyptus, polyfloral) were analyzed by HR-NMR using both 1H NMR and heteronuclear multiple bond correlation spectroscopy (HMBC). Spectral data were analyzed by application of unsupervised and supervised pattern recognition and multivariate statistical techniques such as principal component analysis (PCA) and general discriminant analysis (GDA). The use of 1H-(13)C HMBC coupled with appropriate statistical analysis seems to be an efficient technique for the classification of honeys.