Nuclear Magnetic Resonance Profiling of Wine Blends

Abstract

Nuclear magnetic resonance (NMR) profiling is used for characterization of monocultivar binary wine mixtures. Classification and quantification of the relative amount of wine in the mixture are made in two steps. First, each sample is classified as a mixture of a determined type by solving the appropriate classification problem using NMR profiles. The relative amount of the two corresponding monovarietal wines is then evaluated by multilinear regression of a selected set of NMR variables. Linear discriminant analysis (LDA), used in the classification step, gives a very good separation among the different mixture classes. On the other hand, a single layer artificial neural network, used to solve the multilinear problem, gives the relative amount of wine type in the mixture with a precision of about 10%.

NMR-based metabolomics in wine quality control and authentication

“…It was concluded that genetic differences in grapes are reflected in the composition of related wines which, in turn, can be discriminated by NMR-based metabolomics, and thus the study of single grape cultivars may prove useful in elucidating the genetic lineage of mixed grapevine cultivars. The analysis of wine blends obtained from binary mixtures of a wines using NMR spectroscopy in combination with linear classification models (LDA) and neural networks has also been reported [59].…”

Detection of irradiated beef by nuclear magnetic resonance lipid profiling combined with chemometric techniques

“…Recently ANNs have become the focus of interest in many disciplines including food science. Several applications of ANNs for classification, authentication and adulteration detection purposes of foods and drinks by pattern recognition of multielemental (Furia, Naccarato, Sindona, Stabile, & Tagarelli, 2011), chromatographic (Cordella, Militão, Clement, & Carrol-Bass, 2003), and spectroscopy analysis (Imparato et al, 2011) are available. In this study all the possible combinations of 3 inputs over a set of 54 variables, for a total of 24,804 networks, were tried.…”

“…NMR profiling has been successfully applied to the identification of botanical, zoological and geographical origin of different foods. This approach has been employed for the authentication, geographic origin and varietal traceability of virgin olive oil (Mannina, Patumi, Proietti, Bassi, & Segre, 2001;Sacchi, 2001) the discrimination of virgin olive oil from olive-pomace oil and refined olive oil (Zamora, Gomez, & Hidalgo, 2002), and in the characterization of monocultivar binary wine mixtures (Imparato, Di Paolo, Braca, & Lamanna, 2011). In food of animal origin, there is the possibility of using NMR spectra as a fingerprint in recognition of wild and farmed fish (Aursand & Alexon, 2001;Aursand, Mabon, & Martin, 2000), and in the detection of adulteration by undeclared mixing of offal to ground beef muscle (Al-Jowder et al, 2001).…”

NMR‐based metabolomics in wine science

“…6B). [8,10,15] Although many grape metabolites of amino acids, organic acids, and sugars also have been found to be associated with environmental factors of climate, vintage, and soil, [30,31] they would not be available for describing the [8,10,29] Lee et al [15] Wine Variety, region, vintage, winery G O O Anastasiadi et al [22] Wine/berry Variety, growing condition G O O Rochfort et al [35] Plus sensory evaluation Wine Wine quality G O O Skogerson et al [16] Plus sensory evaluation Wine Soil G O O Mazzei et al [54] Wine Variety, vintage G O O Ali et al [34] Plus sensory evaluation Wine Blend G O X Imparato et al [46] Berry Harvesting time, variety G O O Mulas et al [48] Ali et al [47] Leaf/berry/wine Disease, fungus infection G O O Lima et al [50] Ali et al [49] Figueiredo et al [51] Hong et al [52] Wine Fermentative time T O O López-Rituerto et al [43] Monitoring changes in several metabolites Wine Fermentative time T X X Avenoza et al [55] Monitoring changes in citrate and malate Wine Fermentative time, yeast and lactic acid bacteria strains G O O Son et al [9] Monitoring global changes and fermentative behavior…”

“…7). Furthermore, NMR-based metabolomics have successfully been applied for classifying wines according to blending ratios of grape varieties, [46] comprehensive monitoring of metabolic changes in berry during grape development, [47,48] understanding of the metabolic perturbation in grape diseases such as downy mildew and esca, [49][50][51] and investigating metabolic influence of Botrytis cinerea infection in Champagne base wine. [52] These studies on metabolic variations in grape berry and wine highlight strong dependence of both grape and wine metabolite on environmental factors, fermentative microorganisms, fungal infection of grape, and thus, potential influence of global metabolome on wine quality, which can easily be assessed by NMR-based metabolomic study.…”