Metabolomic Studies on Geographical Grapes and Their Wines Using¹H NMR Analysis Coupled with Multivariate Statistics

Abstract

Environmental vineyard conditions can affect the chemical composition or metabolites of grapes and their wines. Grapes grown in three different regions of South Korea were collected and separated into pulp, skin, and seed. The grapes were also vinified after crushing. (1)H NMR spectroscopy with pattern recognition (PR) methods was used to investigate the metabolic differences in pulp, skin, seed, and wines from the different regions. Discriminatory compounds among the grapes were Na, Ca, K, malate, citrate, threonine, alanine, proline, and trigonelline according to PR methods of principal component analysis (PCA) or partial least-squares discriminant analysis (PLS-DA). Grapes grown in regions with high sun exposure and low rainfall showed higher levels of sugar, proline, Na, and Ca together with lower levels of malate, citrate, alanine, threonine, and trigonelline than those grown in regions with relatively low sun exposure and high rainfall. Environmental effects were also observed in the complementary wines. This study demonstrates that (1)H NMR-based metabolomics coupled with multivariate statistical data sets can be useful for determining grape and wine quality.

Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate

“…Growing regions can be distinguished based on the abundance of several key fungal and bacterial taxa, defining potentially predictive regional features with obvious consequences for grapevine management and wine quality. The chemicosensory distinction of wines from different growing regions is well established (29)(30)(31)(32)(33), providing the conceptual basis of wine terroir, although the causative factors are elusive (9). Likewise, the formative influences of many key grape-derived microbiota on wine quality Significantly discriminant taxon nodes are colored and branch areas are shaded according to the highest-ranked variety for that taxon.…”

“…As the most dominant and discriminant taxa between regions and varieties have well-characterized impacts on grape and wine qual- ities, these differences may help explain regional patterns in wine chemicosensory properties (29)(30)(31)(32)(33). Whether these regionally differential microbiota actually modulate wine sensory qualities must be experimentally tested, as do all putative features of wine terroir.…”

NMR-based metabolomics in wine quality control and authentication

“…Muscat Bailey variety wines produced in three different regions in South Korea [17], German wines produced in different regions [55], and red and white wine varieties harvested in Apulia (southern Italy) and Slovenia [60] showed a clear differentiation according to the area of production using NMR-based metabolomics. Son et al [26] classified Cabernet Sauvignon wines harvested in California, France, and Australia using 1 H NMR spectroscopy and multivariate statistical analysis.…”

“…In fact, the whole NMR spectrum of a wine sample can be considered as a molecular fingerprint, and as such it can be used directly for comparison and identification purposes in metabolite fingerprinting of different wines. This chemical compositional/spectroscopic information constitutes the so-called wine metabolome, which is affected by a multitude of wine-making factors, including agronomic practices and pedoclimatic conditions [14], grape variety [15], fermentation practices [16], and geographical origin [17], and can be used for quality control and authentication purposes. For example, the ability to study geographical origin-related NMR metabolic effects is of extreme importance, since the high added value of wines is obtained from enforcing protected denomination of origin (PDO) and protected geographical indication (PGI) state regulations to control the appellation of wines [2,5].…”

An overview of the recent approaches to terroir functional modelling, footprinting and zoning

“…The first reaction involves the deamination of phenylalanine by the enzyme phenylalanine ammonia lyase (PAL) into cinnamic acid, thus diverting phenylalanine from the pathway that relates carbohydrates to the synthesis of proteins. Metabolomic studies have also been conducted through Proton nuclear magnetic resonance ( 1 H NMR) spectroscopy (Pereira et al, 2006;Son et al, 2009), which revealed that grapes grown in regions with high sun exposure and low rainfall showed higher levels of sugar, proline, Na and Ca together with lower levels of malate, citrate, alanine, threonine and trigonelline than those grown in regions with relatively low sun exposure and high rainfall (Son et al, 2009). The sensitivity of this method has allowed it to be successfully applied to classify wines according to their phenolic profile and allowed distinguishing between wines from different wineries of the same wine-producing zone and between different vintages for wines of the same variety in Greece (Anastasiadi et al, 2009) andSpain (López-Rituerto et al, 2012).…”