OENO IVAS 2019 banner
IVES 9 IVES Conference Series 9 OENO IVAS 9 OENO IVAS 2019 9 Analytical developments from grape to wine, spirits : omics, chemometrics approaches… 9 Integrated multiblock data analysis for improved understanding of grape maturity and vineyard site contributions to wine composition and sensory domains

Integrated multiblock data analysis for improved understanding of grape maturity and vineyard site contributions to wine composition and sensory domains

Abstract

Much research has sought to define the complex contribution of terroir (varieties x site x cultural practices) on wine composition. This investigation applied recent advances in chemometrics to determine relative contributions of vine growth, berry maturity and site mesoclimate to wine composition and sensory profiles of Shiraz and Cabernet Sauvignon for two vintages. 

Grape maturation was monitored using a berry sugar accumulation model and wines made from sequentially harvested grapes at three stages for each variety and vintage. Comprehensive targeted grape analysis of amino acids, carotenoids, sugars, organic acids, anthocyanins and volatile compounds were combined with targeted wine volatile and non-volatile chemical measures of composition and sensory descriptive analysis. Chemometric models of balanced sample sets derived from the pool samples were used in an ANOVA multiblock framework with orthogonal projection to latent structures (Boccard and Rudaz, 2016) to elucidate the relative importance of model design factors. 

Multiple data matrices derived from the experimental design factors are subtracted from the original data matrix to obtain pure effects and interaction submatrices with structured orthogonal data. A response matrix is derived from the positive eigenvalues associated with SVD of each effect matrix and residuals are then added to each submatrix prior to kernel OPLS. Model performance evaluated from residual structure ratio (RSR), goodness of fit (R2Y) and permutation testing identified the significant factors from each model. Projection of sample scores of significant factors against scores of the residual matrix is used to assess sample clusters with confidence intervals based on Hotelling T2. 

Loadings from significant experimental factors of each model were used for hierarchical cluster analysis (HCA) with Euclidean distance measures and Wards grouping criteria. Prior to HCA scores and loadings are rotated to consistent presentation of factor levels in model plots. A conservative interpretation of loadings heat maps was considered appropriate and a summary heat map for explanatory factors is presented that enable interpretation of the impact of cultivar, site (soil x mesoclimate), grape maturity and region on grape and wine composition. The integrated data driven approach used in this investigation may be of assistance for other investigators for omics based experiments.

Ref: Boccard, J. & Rudaz, S. 2016. Anal Chim Acta. 920:18-28.

DOI:

Publication date: June 19, 2020

Issue: OENO IVAS 2019

Type: Article

Authors

Leigh Schmidtke, Guillaume Antalick, Katja Suklje, John Blackman, Alain Deloire

National Wine and Grape Industry Centre, Charles Sturt University, Locked Bag 588 – Wagga Wagga – New South Wales 2678 – AUSTRALIA
Wine Research Centre, University of Nova Gorica, Vipavska, 5000 Nova Gorica, Slovenia
Agricultrual Institute of Solvenia, Lubljana, 1000, Slovenia
Montpellier SupAgro, Montpellier 34060,

Contact the author

Keywords

AMOPLS, sequential harvest, berry sugar accumulation, targeted metabolomics 

Tags

IVES Conference Series | OENO IVAS 2019

Citation

Related articles…

A preliminary study of clonal selection in cv. Viura in relation to varietal aroma profile

Viura is a synonym for Macabeo and currently it is the most widely planted white grape variety in D.O.Ca. Rioja, with 3,569 ha, representing 84% of the white grape cultivated area. It is a generous-yielding grape, presenting low values of titratable acidity and with large and compact clusters which makes it susceptible to Botrytis cinerea. Thus, this variety not always satisfies the wine grower’s prospects. Nowadays, the available plant material is scarce, moreover, it was selected on the basis of other quality criteria, not currently requested.

Barrels ad-hoc: Spanish oak wood classification by NIRs 

The wooden barrel is a key factor in enology, since wine chemical composition and sensory properties changes significantly in contact with the barrel[1]. Today’s highly competitive market constantly demands new differentiated products and wineries search innovations continuously.
Wood selection is crucial: barrels stability to keep constant their contribution and the result on products, and additional and differentiated wood contributions to impact their new products. Oak wood selection has traditionally been carried out using parameters such as specie, location and grain, however, it goes one step further nowadays. Large cooperage work with non-destructive techniques that allow classifying oak wood quickly and easily according to their organoleptic contribution[2].

Valorisation of integrated research on vineyard soils. Adaptation to the Val de Loire vineyard

La mise en valeur d’un terroir au travers du vin signifie dans un premier temps le respect du cahier des charges de l’A.O.C correspondante. Dans un second temps, elle sous-entend d’être à l’écoute des évolutions scientifiques, techniques et sociétales afin de satisfaire une production plus respectueuse de l’environnement et de la santé des hommes. Les recherches effectuées par l’Unité Vigne et Vin du centre INRA d’Angers ont débouché sur le concept d’UTB, Unité Terroir de Base (R.Morlat). UTB définit une aire de terrain ou le fonctionnement de la vigne est homogène en tous points.

A novel approach for the identification of new biomarkers of wine consumption in human urine using untargeted metabolomics

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.

Exploring multisensory interactions through the study of astringency diversity of mono-varietal Italian red wines

According to the OIV Focus 2017 estimating the vine varieties distribution in the world, Italy is the richest grape producing country in terms of varieties.